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INOM EXAMENSARBETE INDUSTRIELL EKONOMI,AVANCERAD NIVÅ, 30 HP
, STOCKHOLM SVERIGE 2020
Innovation Measurement as a Tool for Innovation CapabilityA Qualitative Case Study on the Role of Innovation Measurement within the Swedish Telecom Sector
MAJKEN DOMICELJ
KAROLINA STRÖMBERG
KTHSKOLAN FÖR INDUSTRIELL TEKNIK OCH MANAGEMENT
Innovation Measurement as a Tool for Innovation Capability
by
Majken Domicelj Karolina Strömberg
Master of Science Thesis TRITA-ITM-EX 2020:142 KTH Industrial Engineering and Management
Industrial Management SE-100 44 STOCKHOLM
Innovationsmätning som ett verktyg för innovationsförmåga
Majken Domicelj Karolina Strömberg
Examensarbete TRITA-ITM-EX 2020:142 KTH Industriell teknik och management
Industriell ekonomi och organisation SE-100 44 STOCKHOLM
Master of Science Thesis TRITA-ITM-EX 2020:142
Innovation Measurement as a Tool for
Innovation Capability
Majken Domicelj
Karolina Strömberg
Approved
2020-06-05
Examiner
Kristina Nyström
Supervisor
Kent Thorén
Commissioner
Confidential
Contact person
Confidential
Abstract
Innovation measurement is one of the most essential aspects in building innovation capability as it allows
organisations to capture their current innovation capabilities and understand where they need to direct their
efforts to improve. Further, measuring the innovation capability enables a data driven and insightful steering
management. To succeed, incumbent organisations need to understand the KSF for innovation capability
and internalise them.
The purpose of this study is to investigate how incumbent telecom firms can use innovation measurement
to improve their innovation capability. This was done through identifying KSF for innovation capability,
reviewing existing innovation measurement frameworks and then, compare and analyse the findings to
empirical data - from a case study at a major telecom operator.
This paper is of an interdisciplinary nature and combines the theories of innovation capability, service
innovation and innovation measurement. The methods used are qualitative, including a literature review, a
focus group and 19 semi-structured interviews. The thesis resulted in six KSF for innovation capability in
incumbent telecom firms, which was applied in an innovation measurement framework. The main
challenges associated with these KSF are also identified and concrete proposals, for improving the
innovation capability through using innovation measurement, are presented. Major contributions are of both
theoretical and empirical character.
The thesis contributes to the research field of how innovation capability can be measured and improved,
through using multidimensional metrics, in incumbent firms working with high-tech service innovation. It
also provides valuable empirical data around how innovation measurement can be interpreted and used, to
improve innovation capability in an industrial context.
Keywords: Innovation capability, innovation measurement, service innovation, telecommunications
industry
Examensarbete TRITA-ITM-EX 2020:142
Innovationsmätning som ett verktyg för
innovationsförmåga
Majken Domicelj
Karolina Strömberg
Godkänt
2020-06-05
Examinator
Kristina Nyström
Handledare
Kent Thorén
Uppdragsgivare
Konfidentiellt
Kontaktperson
Konfidentiellt
Sammanfattning
Innovationsmätning anses vara en av de viktigaste aspekterna för att bygga en stark innovationsförmåga
eftersom det ger en förståelse för den nuvarande innovationsförmågan och för hur organisationer kan
prioritera resurser och aktiviteter för att förbättra innovationsförmågan. För att lyckas behöver dessa företag
förstå vilka som är de avgörande faktorerna för innovationsförmåga och sedan internalisera dessa.
Syftet med studien är att förstå hur stora, etablerade telekombolag kan använda innovationsmätning för att
förbättra sin innovationsförmåga. Detta har gjorts genom att först identifiera de avgörande faktorerna för
innovationsförmåga, granska existerande ramverk för att mäta innovation. Sedan har detta jämförts med
undersökningsresultatet från den genomförda fallstudien på ett ledande, svenskt telekombolag. Studien är
av interdisciplinär natur och kombinerar teorier inom innovationsförmåga, tjänsteinnovation och
innovationsmätning.
Studien resulterade i sex avgörande faktorer för utveckling av innovationsförmåga i stora, etablerade företag
inom telekomsektorn. Dessa tillämpas sedan i ett ramverk för innovationsmätning. De huvudsakliga
utmaningarna kopplade till dessa faktorer har också identifierats och konkreta förslag för att förbättra
innovationsförmågan genom tillämpning av innovationsmätning presenteras.
Bidragen från denna studie är av både teoretisk och empirisk karaktär. Studien bidrar till forskningen kring
hur innovationsförmåga hos traditionella företag som arbetar med högteknologiska tjänster kan utvärderas
och förbättras genom att använda flerdimensionella mätvärden. Den bidrar även med viktiga empiriska data
kring hur innovationsmätning kan förstås och användas för att förbättra innovationsförmåga i en industriell
kontext.
Nyckelord: Innovationsförmåga, innovationsmätning, tjänsteinnovation, telekommunikation
1
Contents
List of Figures ................................................................................................................................................ i
List of Tables................................................................................................................................................. ii
1. Introduction .............................................................................................................................................. 1
1.1 Background .......................................................................................................................................... 1
1.2 Problem Formulation ........................................................................................................................... 3
1.3 Purpose and Research Question ........................................................................................................... 3
1.4 Expected Contributions ........................................................................................................................ 4
1.5 Sustainability Aspects .......................................................................................................................... 4
1.6 Delimitation ......................................................................................................................................... 5
1.7 Outline of the Thesis ............................................................................................................................ 5
2. Literature Review ..................................................................................................................................... 7
2.1 Service Innovation ............................................................................................................................... 7 2.1.1 Characteristics of Service .......................................................................................................................................................... 7 2.1.2 Service Dominant Logic ............................................................................................................................................................. 8 2.1.3 Research Streams within Service Innovation.................................................................................................................. 9 2.1.4 Service Management ................................................................................................................................................................... 9
2.2 Innovation Capability......................................................................................................................... 10 2.2.1 Dynamic Capabilities ................................................................................................................................................................ 10 2.2.2 Innovation Capability ............................................................................................................................................................... 12
2.3 Innovation Strategy ............................................................................................................................ 15 2.3.1 Service Innovation Strategy .................................................................................................................................................. 17 2.3.2 Innovation Portfolio ................................................................................................................................................................. 18 2.3.3 Agile Innovation Approach.................................................................................................................................................... 19 2.3.4 Time Horizons ............................................................................................................................................................................. 20
2.4 Cross-functional Collaboration .......................................................................................................... 21 2.4.1 Internal Collaborations ........................................................................................................................................................... 21 2.4.2 External Collaborations .......................................................................................................................................................... 23
2.5 Knowledge Management ................................................................................................................... 25
2.6 Innovation Measurement ................................................................................................................... 26 2.6.1 Management control systems .............................................................................................................................................. 26 2.6.2 Why measure innovation? ..................................................................................................................................................... 29 2.6.3 Perspectives on Innovation Measurement .................................................................................................................... 29 2.6.4 Measuring Innovation Capability ....................................................................................................................................... 30 2.6.5 Frameworks for Measuring Innovation Capability ................................................................................................... 32
3. Method..................................................................................................................................................... 36
3.1 Research Approach ............................................................................................................................ 36
3.2 Research Process ................................................................................................................................ 37
3.3 Data Collection .................................................................................................................................. 38 3.3.1 Literature Review ...................................................................................................................................................................... 38 3.3.2 Case Study...................................................................................................................................................................................... 39 3.3.3 Workshop ...................................................................................................................................................................................... 39
2
3.3.4 Interviews ...................................................................................................................................................................................... 39
3.4 Data Analysis ..................................................................................................................................... 40
3.5 Research Quality ................................................................................................................................ 41
3.6 Ethical Considerations ....................................................................................................................... 42
4. Industry Background ............................................................................................................................. 44
4.1 The Telecom Industry ........................................................................................................................ 44
4.2 The Case Company ............................................................................................................................ 45
5. Empirics .................................................................................................................................................. 47
5.1 Conceptual design: Framework selection .......................................................................................... 47 5.1.1 Overall Context and Challenges .......................................................................................................................................... 47 5.1.2 Framework selection................................................................................................................................................................ 48 5.1.3 Workshop ...................................................................................................................................................................................... 49
5.2 Case study: Exploring the innovation capability ............................................................................... 51 5.2.1 Circumstances in Business Environment ....................................................................................................................... 52 5.2.2 Strategy ........................................................................................................................................................................................... 53 5.2.3 Portfolio Management ............................................................................................................................................................. 55 5.3.4 Measurement ............................................................................................................................................................................... 56 5.2.5 Process ............................................................................................................................................................................................ 57 5.2.6 Communication ........................................................................................................................................................................... 62 5.2.7 Key Success Factors .................................................................................................................................................................. 64
6. Conclusion ............................................................................................................................................... 65 6.1 Synthesising the Key Success Factors .................................................................................................................................. 65 6.1.1 Measuring Innovation Capability ....................................................................................................................................... 66 6.1.2 Innovation Strategy .................................................................................................................................................................. 66 6.1.3 Decision-Making Process ....................................................................................................................................................... 68 6.1.4 Customer Orientation .............................................................................................................................................................. 69 6.1.5 Cross functional collaborations........................................................................................................................................... 69
Internal collaborations ................................................................................................................................................................. 70 External collaborations ................................................................................................................................................................ 70
6.1.6 Scaling up ....................................................................................................................................................................................... 71 6.1.8 Communication ........................................................................................................................................................................... 72
6.2 Service Innovation Capability Measurement ..................................................................................... 74 6.2.1 Innovation Strategy .................................................................................................................................................................. 74 6.2.2 Decision-Making Processes ................................................................................................................................................... 75 6.2.3 Customer Orientation .............................................................................................................................................................. 76 6.2.4 Cross Functional Collaboration ........................................................................................................................................... 77 6.2.5 Scaling up ....................................................................................................................................................................................... 77 6.2.6 Communication ........................................................................................................................................................................... 78 6.2.7 Verifying the Metrics ................................................................................................................................................................ 79 6.2.8 Synthesis of Innovation Measurement at Company X .............................................................................................. 81
7. Discussion ................................................................................................................................................ 83
7.1 Key Success Factors for Innovation Capability ................................................................................. 83
7.2 Implications for Practice .................................................................................................................... 83 7.2.1 Measurement Management and Control ........................................................................................................................ 84
7.3 Sustainable Development................................................................................................................... 84
3
7.4 Limitations ......................................................................................................................................... 85
7.5 Future work ........................................................................................................................................ 85
9. References ............................................................................................................................................... 87
Appendix I – Workshop Material ............................................................................................................... I
Appendix II – List of Interviewees............................................................................................................. II
i
List of Figures Figure 1. The research model of dynamic capabilities 12
Figure 2. A model of innovation capability 13
Figure 3. Information Flow in Hierarchical view of strategy and emergent view of strategy 16
Figure 4. The Innovation Ambition Matrix 17
Figure 5. The relationship between project portfolio success and business success 18
Figure 6. A model for collaboration for innovation 24
Figure 7. The key variables to analyse to control business strategy 26
Figure 8. Aspects impacting the Key Success Factors 28
Figure 9. The three major roles of innovation measurement 29
Figure 10. The 15 innovation capabilities practices presented 33
Figure 11. The basics of innovation capability measurement 33
Figure 12. The framework for measuring innovation capability 34
Figure 13. The framework for innovation capability 35
Figure 14. Systematic Combining 36
Figure 15. The research process and outline of the thesis. 37
Figure 16. The key actors in the telecommunications value chain 44
Figure 17. The digital ecosystem based on telecom services 45
Figure 18. An overview of the innovation teams in the case company. 46
Figure 19. An illustration of the adapted framework 49
ii
List of Tables Table 1. Summary of underlying dimensions of innovation capability. 14
Table 2. Basic dimensions of R&D performance analysis. 32
Table 3. Interview themes. 40
Table 4. Criteria for the innovation measurement framework. 48
Table 5. Criteria for selecting measurement frameworks. 49
Table 6. The topics covered in the interviews. 51
Table 7. The identified KSF for innovation capability for incumbent telecom firms. 64
Table 8. The identified KSF including subdimensions. 65
Table 9. Metrics related to innovation strategy. 75
Table 10. Metrics related to decision-making processes. 76
Table 11. Metrics related to customer orientation. 77
Table 12. Metrics related to cross-functional collaboration. 77
Table 13. Metrics related to scaling up. 78
Table 14. Suggested metrics on portfolio-level in the selected measurement framework. 80
Table 15. Suggested metrics on process-level in the selected measurement framework. 80
Table 16. Suggested metrics on portfolio-level in the selected measurement framework. 81
1
Acknowledgements The process of writing a thesis has been profoundly educational and enjoyable for us both. As the
final part of our education at KTH we are both glad that we chose a subject that we are passionate
about. While, the result is a product of our interest and efforts, it has also been highly dependent
on the support we have received from others.
First, we would like to express our gratitude to Company X, for the support and engagement
throughout this process and a special thank you to Johanna, who has gone above and beyond for
us to get as much insights as possible at Company X. We are also thankful to all interview
participants for your time and commitment. Lastly, we would like to extend our appreciation to our
supervisor at KTH, Kent Thorén, who has supported and provided us with valuable insights about
the industry, the research field and how to navigate through the thesis process.
1
1. Introduction This chapter aims to give an introduction to the paper and to provide the reader with an
understanding of the background. Further, the purpose and the problem formulation are defined
and presented together with the research questions. In addition, this chapter will specify the
scientific contributions this study is expected to produce and how it is positioned in relation to
previous research within the field, together with the delimitations of the study.
1.1 Background
Organisations in the 21st century are facing a fast-paced environment characterised by a high level
of change and uncertainty (Wiggins and Ruefli, 2005; Caylar & Menard, 2016). Global drivers
such as technological development, globalisation, digitalisation and sustainability are affecting
businesses on all levels, and require organisations to be adaptive and responsive towards external
changes (Caylar & Menard, 2016). Many industries are facing disruptions, which can be caused by
technological advancements, changed customer expectations, commoditization and new ways of
creating and delivering value (Melnyk, Stewart and Swink, 2004). Researchers and executives are
unanimously agreeing that innovation is one of the key factors for creating long-term, sustainable
competitive advantage (Markides, 1998; Mone, McKinley and Barker, 1998; Christensen, Raynor
and Van Bever, 2013; Ted and Bessant, 2013; Kuratko, Hornsby and Covin, 2014). Yet, in a
dynamic and fast-paced world, successful innovation and R&D activities are some of the main
challenges for many companies which struggle to navigate themselves towards a future strategic
position (Kuratko, Hornsby and Covin, 2014).
One category of organisations who tend to struggle with strategic innovation is incumbent firms in
highly technological (high-tech) industries - historically it has been proven difficult for large,
established firms to maintain a strong position in the current market, while simultaneously
transforming themselves toward a future market (Markides, 1998; Christensen, Raynor and Van
Bever, 2013; Mattes and Ohr, 2018). The history contains many examples of market-leading, great
companies who drastically failed due to their inability to meet the changing demands of their
markets (Hamel and Prahalad, 1994; Markides, 1998). The reasons as to why many organisations
fail to develop accurate innovation strategies are many - for example scarce resources, tight
financial goals and a lack of a holistic perspective (Mattes and Ohr, 2018). Regardless, there is no
doubt that innovation is essential for businesses’ long-term survival and growth (Mone, McKinley
and Barker, 1998, Christensen, Raynor and Van Bever, 2013, Ted and Bessant, 2013). Innovation
is considered a top priority amongst most executives and business leaders (Chan, 2008; Richtnér
et al., 2017) - according to a survey conducted by McKinsey & Company, 84 percent of the
respondent business leaders considered innovation as one of the most prioritised aspects of
successfully managing a business (Capozzi, Gregg and Howe, 2010). However, many innovation
projects fail (Schentler, Lindner and Gleich, 2010), and firms invest extensive resources into
innovation projects that do not result in new products or services at the market (Markides, 1998;
Richtnér et al. 2017).
Further, the global economy and market have previously been driven by manufacturing and
services has been separated from goods (Qiu, 2014). However, the fast development of IT, and
2
specifically ICT, has triggered a shift, where the economy is becoming more driven by services
(Rai and Sambamurthy, 2006; Barrett et al., 2015) and where emerging technologies create new
possibilities for new services (Fitzsimmons and Fitzsimmons, 2010). The increasing knowledge
and service intensity in many sectors have changed the value creating process to become even more
complex (Möller, Rajala and Westerlund, 2008), and service innovation will only become more
vital for firms to adopt into their business models (Lusch and Nambisan, 2015). However, in order
to meet the new customer expectations, it is essential both for academics and the industry to
understand service innovation (Spohrer and Maglio, 2008) and how to approach it (Möller, Rajala
and Westerlund, 2008). It is currently is a divided research field (Witell et al., 2016), and Ostrom
et al. (2010) defined service innovation as something which “creates value for customers,
employees, business owners, alliance partners, and communities through new and/or improved
service offerings, service processes, and service business models”. This paper will define service
innovation according to Ostrom et al.’s (2010) definition.
Moreover, innovation capability can be mentioned as “the ability to continuously transform
knowledge and ideas into new products, processes and systems for the benefit of the firm and its
stakeholders” by Lawson and Samson (2001, pp 384). According to research, one factor for long-
term success lies in the company’s ability to understand the dynamics of the capabilities, as well
as the company’s ability to acquire and incorporate these skills into the organisation (Calantone,
Cavusgil and Zhao, 2002; Saunila, Pekkola and Ukko, 2014). One important step in building strong
innovation capability in an organisation is to understand the key success factors that construct
innovation capability (Adams, Bessant and Phelps, 2006).
Innovation measurement aims to evaluate and visualise the innovation process which often is a
multidimensional and complex set of activities (Adams, Bessant and Phelps, 2006). Innovation
measurement can help firms to structure their innovation process in an optimal way and to assess
the organisation’s innovation capabilities, but it can also be used to gain insights around how they
are performing in terms of innovation relative to their competitors (Chan et al. 2008; Richtnér et
al. 2017; Brattström et al., 2018). However, measuring innovation can be challenging as innovation
processes often are complex and difficult to capture through metrics and, thus, require a high level
of understanding of the organisation, the market as well as the value creation process (Melnyk,
Stewart and Swink, 2004; Chan et al., 2008).
Further, the value created through innovation activities are not always as tangible as other
organisational activities such as sales and marketing, and therefore, innovation measuring can be
misleading if used in an inaccurate way (Ojanen and Vuola, 2005). Both researchers and
practitioners see innovation measurement as an integrated part in building strong innovation
capabilities, however; there are still both inconsistency in the findings regarding how it should be
designed and applied, as well conflicting views around what should actually be measured (Melnyk,
Stewart and Swink, 2004; Saunila, Pekkola and Ukko, 2014). Many organisations also experience
challenges around how to design, implement and evaluate innovation measurement systems and
there is a general lack of consensus and best practice (Melnyk, Stewart and Swink, 2004; Ojanen
and Vuola, 2005; Richtnér et al. 2017).
The telecom industry has transformed the way we communicate since the 1830s (Beers, 2019). For
example, the Internet and the mobile phone are innovations that changed our society to an
3
enormous degree (Bohlin et al., 2001). For the past 20 years, the telecom industry has been subject
to constant change, both due to technical development, as well as the integration and penetration
of other industries such as software, services and broadcasting (Bohlin et al, 2001). Since then, the
telecom industry has been undergoing major changes and is still highly transformative (EY, 2015;
PwC, 2019). The competitive landscape has changed, and telecom companies are now competing
against both the software industry as well as the content industry (PwC, 2019). Since connectivity
is becoming increasingly commoditized, telecom firms need to find new ways to create and deliver
value (Caylar & Menard, 2016). Research shows that there is still high potential for incumbent
telecom firms to create value for their customers, but the value creation process is changing in
several ways (Allee and Taug, 2006; Caylar & Menard, 2016). This require organisations to build
strong innovation capabilities, to respond to the changing market.
1.2 Problem Formulation
While innovation is critical for organisations’ long-term survival, profitability and growth
(Christensen, Raynor and Van Bever, 2013), many firms struggle to build accurate innovation
capabilities (Chan et al., 2008; Richtnér et al. 2017). Particularly established firms within highly
transformative, high-tech industries are struggling to develop the right skills to continuously renew
their value proposition in an adequate way. This is especially true for the telecom industry, which
for a long time have faced significant changes in the business environment (Allee and Taug, 2006;
Caylar & Menard, 2016). To differentiate themselves they need to provide complex and flexible
services to their customers (PwC, 2019). Innovation measurement is considered to be a cornerstone
in building strong innovation capabilities, as well as developing a responsive and efficient
innovation process. However, many organisations struggle to measure their innovation activities
effectively, especially within industries where the competitive landscape is changing (Mattes and
Ohr, 2018). Further, since service innovation is a diverse research field, the existing implications
regarding measuring service innovation (Edvardsson, Gustafsson, and Roos, 2005; Witell et al.,
2016) as well as innovation capability (Wang and Ahmed, 2004) are many times conflicting. It is,
therefore, crucial to understand the key success factors that construct innovation capability, connect
these to the innovation process and to identify appropriate metrics to visualise performance of
innovation (Melnyk, Stewart and Swink, 2004; Richtnér et al. 2017).
1.3 Purpose and Research Question
The purpose of this study is to identify the key success factors for incumbent telecom firms to
increase their innovation capability, and to assess how they can use innovation measurement to
improve this. The focal point will be to investigate the underlying dimensions for innovation
capability and analyse innovation measurement in relation to innovation capability. The aim is to
support incumbent firms within the telecom industry in visualising and improving their innovation
capability through implementing an innovation measurement framework. Hence, the research
questions that will be answered in this paper are as follows.
RQ1: What are the key success factors for innovation capability for incumbent telecom firms?
RQ2: How can innovation measurement be used to improve service innovation capability in
telecom firms?
4
1.4 Expected Contributions
This paper is expected to have both academic and practical contributions. Academically, it will add
on to the emerging field of research around innovation measurement. While numerous innovation
measurement frameworks and systems has been proposed by both researchers and practitioners,
many frameworks are yet to be evaluated and validated through empirical research. This paper will
contribute with empirical data through a case study in an industrial setting, namely a strategic
innovation group at an incumbent telecom firm in Sweden. More specifically, it will contribute to
the research field by exploring how innovation capability can be measured in incumbent firms that
are working with high-tech service innovation - since it appears to be a rather under researched
field. The paper aims to identify the most impactful dimensions of innovation capability as well as
the most suitable innovation measurement framework for evaluating and assess the innovation
capability at Company X. In addition, the study will provide an example of how it can be applied,
implemented and interpreted.
Practitioners can benefit from the findings in this paper as it offers insights about how incumbent
firms, within the telecom industry, can use innovation measurement to assess their innovation
capacity and, in turn, improve their innovation processes. This can contribute with both short term
and long-term value as well as operational efficiency. Innovation measurement has gained attention
amongst business leaders and executives, as innovation is increasingly important in the value
creation process. Further, the study will be design in such a way that it will be possible to draw
general conclusions on an industry level and will, therefore, contribute with unique and valuable
insights about high-tech industries.
The resulting framework is designed to be applicable for multiple industries and organisations.
However, the process of assessing and evaluating existing innovation measurement frameworks
was made from the perspective of the telecom industry, and the specific challenges associated with
that industry, which means that the selection process for another industry might have had a different
outcome.
In summary, this paper is expected to contribute with an interdisciplinary perspective to both the
academic field of innovation measurement as well as insights and knowledge on an industry level.
1.5 Sustainability Aspects
There are several implications that this paper will cover several sustainability aspects. The United
Nations sustainable development goals for 2030 cover areas such as quality education, clean water
and sanitation, affordable and clean energy and industry, innovation and infrastructure (United
Nations, 2015). These aims to improve both life quality for the world’s population, as well as
improve the environment and the biodiversity of the plant (United Nations, 2015). While this study
is not directly related to sustainable development, there are implications that the findings from this
study can be related to sustainable development. Many aspects of sustainability are related to
innovation and the development of new technologies (Weaver, 2000). This study aims to facilitate
organisations to improve their innovation processes and the outcome of their innovation efforts.
Through offering insights around how organisations in the telecom industry can develop their
5
innovations, this study could indirectly contribute to the sustainable development within several
areas.
The specific organisation which is studied in this paper are conducting innovation projects through
connectivity and IoT technologies within areas such as; infrastructure, automation of industrial
processes, digitalisation of education and healthcare, as well as water and sanitation. Given the
public utility that can be gained from these projects, this paper can help to facilitate sustainable
development through contributing with methods to improve the outcome of these processes.
1.6 Delimitation
Due to the delimitations of the thesis, the results and conclusions drawn from this study has some
inherent limitations. More specifically there are three areas of distinct delimitations. First, this
study was made on a limited period of approximately six months. Therefore, a qualitative study
was conducted to identify key success factors for measuring innovation capability, but no
quantitative data was collected to validate if the suggested metrics would have the desired impact.
Consequently, the actual impact of monitoring and measuring the innovation cannot be verified.
The study did not consider the economic or political situation in the analysis, factors which possibly
could affect the results.
Second, the thesis has geographical delimitations as it is oriented around the telecom industry on
the Swedish market, with its specific laws, regulations and interplay between actors. Due to the
market situation in Sweden, the results are expected to be relevant for countries with similar market
conditions, but the contextual delimitation needs to be considered when interpreting the results and
conclusions.
Last, this thesis focuses on the innovation capability related to radical innovations and does not
include the incremental innovation processes that takes place within the same organisation. The
distinction has been made in relation to the degree of newness of the innovation (to what extent the
product is new to the market and the customers) and to the time horizon around the innovation
(radical innovation is most often developed in relation to a more uncertain market with a longer
time horizon). As the processes of incremental and radical innovations can be inherently different
(Tidd and Bessant, 2013), the suggested innovation measurement metrics need to be assessed with
regards to the specific innovation process and type in question, when applied in practice.
1.7 Outline of the Thesis
To facilitate the understanding of the paper, the disposition of the thesis is presented below:
(1) Introduction: In this section, the reader is introduced to the context and main concept of
the paper. Further, this section will provide the reader with an understanding of the purpose,
contributions of the study and the sustainability implications, as well as the underlying
delimitations.
(2) Literature Review: Here, the most relevant theoretical concepts and literature is presented
and discussed. Theories and prevailing paradigms within the correlating research fields are
6
critically reviewed, compared and integrated, to form an understanding of the phenomenon
in relation to the specific research context.
(3) Industry Context: As the research is constituted in a specific context, the telecom industry,
a brief background to the industry and the industrial dynamics are presented, together with
(4) Method: The method adopted to carry out the research project is explained. The prevailing
research approach as well as an overview of the research process is presented and
motivated. Research quality and ethical considerations are also discussed in relation to the
methodology.
(5) Findings: In this chapter, the findings from the empirical data collection are presented. The
results are divided into three parts, in accordance to the process of the research. The first
part presents the empirical findings from the initial, exploratory interviews, the process of
selecting the measurement framework selection and the findings from the workshop. In the
second part, findings from the semi-structured interviews are presented, and the KSF for
innovation capability at the case company are identified. In the third part, specific metrics
are presented, based on the framework, the findings from part two and literature.
(6) Conclusion: Here, the findings from both literature and the empirical data collection are
analysed and discussed. The findings are discussed in relation to both the case company as
well as on a more general level. Some suggestions on future research is presented as well
as the limitations of the study.
(7) Discussion: Finally, the findings are concluded to answer to the research question and
summarise the main findings of the study.
7
2. Literature Review There is no doubt innovation is essential for businesses in the 21th century (Christensen, Raynor
and Van Bever, 2013; Tidd and Bessant, 2013; Kuratko, Hornsby and Covin, 2014). Innovation is
a vital part of building sustainable competitive advantage, especially in an environment which is
constantly changing at a high pace (Lawson and Samson, 2001). It has become increasingly harder
for organisations to maintain their competitive advantage over time, a phenomenon which has been
observed in a broad range of industries (Wiggins and Ruefli, 2005). High performing companies
distinguish themselves by maintaining a high level of innovation capability, introducing new
products to the market faster and with higher quality than their competitors, while operating more
efficiently (Lawson and Samson, 2001). They also manage to consistently add value to customer
and stakeholders through different kind of innovations - something that allows them to build a
strong and dynamic position on the future market (Lawson and Samson, 2001). Wiggins and Ruefli
(2005) introduced the concept of “hyper competition” which is drawing on the hypothesis that the
competition is constantly increasing, which forces companies to not only sustain, but also increase
their competitive advantage. However, innovation is an ambiguous term with many different
definitions, meanings and implications. To navigate in the field of innovation and to clarify how
this paper will approach innovation, some of the most common classifications will be presented
below. The purpose is to facilitate an understanding the most common types of classifications of
innovation, and to clarify there this paper position itself on the research field.
One of the most fundamental classifications of innovation is the distinction between incremental
and radical innovation. The idea of incremental and radical innovation is derived from the idea of
whether the innovation reinforces the capabilities within the organisation (incremental innovation)
or whether it forces the organisation to gain new skills and abilities (radical innovation) (Henderson
and Clark, 1990). Incremental and radical innovation has different implications for both the
organisation as well as the market - incremental innovation follows the established trajectory while
radical innovation often opens new market spaces (Christensen & Rosenbloom, 1995).
2.1 Service Innovation
Research on service innovation has historically been primarily focused on service firms and sectors
and such as hotels, hospitals and law firms among others (Jaw, Lo and Lin, 2010; Hogan et al.,
2011; Björk, 2014). Meanwhile, more firms have integrated service as a part of their existing value
proposition (Tidd and Hull, 2010; Qiu, 2014) and many high-tech companies are becoming service
organisations (Spohrer and Maglio, 2008), while others use servitization to improve their business
performance (Lee, Kao and Yang, 2014) or to gain competitive advantage (Baines et al., 2008).
This transition in the global business environment has also resulted in an increased interest among
researchers where service innovation (e.g. Vargo and Lusch, 2004; Miles 2010; Witell et al, 2016),
service science (e.g. Spohrer and Maglio, 2008; Miles, 2010), and service management (e.g.
Möller, Rajala and Westerlund, 2008) are examples of research fields which have emerged.
2.1.1 Characteristics of Service
Even though ‘Service’ as a research field has been covered by numerous researchers during the last
decades the area still lacks consensus around an exact definition of service and how to separate
services from goods (Vargo and Lusch 2004; Miles, 2010). Intangibility is a common characteristic
8
which signifies a service (Karmarkar and Pitbladdo, 1995; Gallouj and Weinstein, 1997; Miles,
2010). However, the distinction for services as something intangible has later been questioned since
software firms provide customers with products, which are also intangible (Vargo and Lusch 2004).
Further, services have also been characterised as highly variable and very few services are identical
to one another (Miles, 2010) - this characteristic has been termed ‘heterogeneity’ by some
researchers (e.g. Sampson and Froehle, 2009). The heterogeneity of services has historically been
a result of the different inputs to the services innovation process from the customer (Sampson 2001;
Sampson and Froehle, 2009). Services are, further, considered to be perishable since, in contrast to
goods, they cannot be stored (Trott, 2012). As a result, it is necessary for the service provider to
have the capacity to provide the service immediately but at the same time if the demand is too low,
it will be apparent immediately (Sampson and Froehle, 2009). Hence, planning activities as well
as managing demand is even more essential for service firms (Trott, 2012).
Inseparability is also a common characteristic for service (Sampson and Froehle, 2006; Jaw, Lo
and Lin, 2010). It means that services, compared to goods, are consumed at the same time as they
are being produced (Cowell, 1988). According to Sampson and Froehle (2006) this results in that
services cannot be produced before a demand exist which results in changed expectations on the
delivery and service. To separate how the service innovation is produced what service is produced
(i.e. the service product and the service process) is, therefore, difficult (Trott, 2012). As a result,
there is typically a high level of interaction between the customers and a service provider since the
customers are involved in the value creation process (Barras, 1990; Spohrer and Maglio, 2008;
Chase 2010; Miles, 2010). Spohrer et al. (2008) specifically defined service as ‘pay for
performance’ where the customers are a vital actor in the value creating process. Furthermore,
some researchers even define service as value co-creation (Möller et. al, 2008; Maglio and Spohrer,
2013), where value creation for a service is more complex than for goods due to more stakeholders
involved in the value creation process (Maglio and Spohrer, 2013). Chae (2012) stated that
considering that service is a co-creation by different actors and since their resources and contexts
vary - service is dynamic and always evolving.
2.1.2 Service Dominant Logic
There are numerous definitions and characteristics which researchers have used to capture the
essence of service. Due to the shift in many industries which are becoming more service centred
(Spohrer et al, 2008; Maglio and Spohrer, 2013) and previous definitions of service might not be
suitable anymore (Vargo and Lusch, 2004; Edvardsson, Gustafsson, and Roos, 2005; Barrett et al.,
2015). The Service dominant logic (SDL) emerged because of the changing business environment
with increased attention on service, and the controversial perspective created a large discussion
among researchers (e.g. Edvardsson, Gustafsson, and Roos, 2005; Miles, 2010; Barrett et al., 2015).
The SDL consider service as an integrated part of all economic exchanges and consider all services
as co-creations (Vargo and Lusch, 2004). From the SDL perspective, Vargo and Lusch (2004) also
gave a broader definition to service and defined it as “The application of specialized competences
(knowledge and skills) through deeds, processes, and performances for the benefit of another entity
or the entity itself “. In a later article, Vargo and Lusch (2008), declared that the essential difference
between the old perspective, referred to as the ‘Goods Dominant Logic’ (GDL), and SDL, is that
SDL consider service as a process and not only as an output.
9
2.1.3 Research Streams within Service Innovation
Service innovation has acknowledged by numerous researchers (e.g. Cowell, 1988; Spohrer and
Maglio, 2008; Jaw, Lo and Lin, 2010; Tidd and Hull, 2010; Ostrom et al. 2010; Edvardsson et.al,
2013). Service innovation, as ‘service’ and ‘innovation’, is a term that lacks consensus to its
meaning (Vargo and Lusch, 2004). Researchers have different opinions about the differences
between invention and innovation, where some researchers argue that an innovation is only the
outcome and others include the whole innovation process (Edvardsson, Gustafsson, and Roos,
2005). Miles (2010) identified that service innovation can both be regarded as a service product as
well as a service process (i.e. both as an output as well as a process), and how it is defined varies
within the research field. Further, it is also common that researchers fail to clearly define innovation
(Toivonen and Tuominen, 2009). Through an extensive systematic literature review where 1302
articles about service innovation were analysed, with the aim to define ‘service innovation’, Witell
et al. (2016) confirmed the divergence within the field. However, they also identified one
consensus: Service innovation is described as the creation of a new service and where the word
‘new’ could both refer to new to the world or new to a market (Witell et al., 2016).
2.1.4 Service Management
The specific characteristics of services innovation contributes to the emergence of both challenges
as well as opportunities. The intangible nature of innovation, further, complicates the process of
applying measurements, since the value of a service is determined by the customer’s perception
(Bessant and Tidd, 2007).
The high variability and almost uniqueness of services lead to a necessity to approach service
innovation in a more dynamic manner – compared to innovation of products or goods (Miles 2010,
Randhawa and Scerri, 2015). Moreover, the heterogeneous and complex nature of service offerings
also makes it more difficult to determine a suitable price level for the service (van Dinther et al.,
2011). Hence, service innovation activities need to be tailored for the specific conditions which are
affected by stakeholders, innovation type as well as technology (Möller et. al, 2008). The high
variability in service has been identified as one of the most challenging factors in service
management (Miles, 2010).
With embedded technology, firms can collect large amount of data on their customers’ behaviour
and automatically customize service offerings to their customers preferences (Kannan and Healey,
2011). Further, for industries that are experiencing fluctuating demand, the ability to automate parts
of the innovation process can be of great value to minimize miscalculations regarding capacity
(Sampson and Froehle, 2006). Sampson (2006) argued that a method to reduce the variability in
service innovation is to reduce the variation in the customer input. However, with the evolving
technology, customers also demand a higher level of flexibility (Boly et al., 2014).
Finally, scalability of an innovation is vital and necessary for real business impact (Mattes and Ohr,
2018). It is considered as one of the innovation process most challenging parts (Cooper, 1988;
Mattes and Ohr, 2018), and organisations that struggle to scale up their innovation projects also
tend to fail to generate profit from transformational products and services, and hence, risk to get
disrupted by competitors (Mattes and Ohr, 2018). Markets have different potentials and
preconditions which affect the ability for an innovation to be diffused and it might, therefore, need
10
to be altered to facilitate the local needs (Winter and Szulanski, 2001). However, the scaling
process of service innovation is considered even harder than for product innovation since services
is expected to be flexible and adapted for the specific customer (den Hertog, van der Aa and de
Jong, 2010). Documentation and spreading information, about the new service, to other units within
the organisation is imperative for large companies to succeed in the scale up process (den Hertog
and de Jong, 2007). It can be documentation about significant traits of the new service as well as
explaining how customers should be approached with the new service (den Hertog and de Jong,
2007). A common sign of a successful up-scaling process, in a large firm, is that the innovated
service tends to be replicated and diffused by other parts of the organisation (Winter and Szulanski,
2001). Winter and Szulanski (2001) also argue that knowledge transfer is essential for the internal
diffusion of the innovation since everyone working with the new offer need to comprehend the new
offer and use it for business purposes.
2.2 Innovation Capability
Building and retaining competitive advantage probably the most essential issues within strategic
management and due to the high level of uncertainty and change that most industries experience,
this topic has gained increased attention (Denford, 2013). There are, however, several perspectives
on competitive advantage and how it is created, which are derived from different viewpoints on
organisational theories (Breznik and Hisrich, 2014). Some of the most used frameworks are the
resource-based view (RBV) and the knowledge-based view (KBV). Simply put - the RBV is built
on the idea that the internal resources of an organisation are the key success factor for building
competitive advantage and that competitive advantage will be created if the resources are valuable,
rare and inimitable (Barney, 1991). The RBV framework is widely recognised but has also been
criticised from several researchers over time (Teece et al., 1997; Eisenhardt and Martin; 2000;
Priem and Butler, 2001). Further, the authors claim that the RBV is not useful for predicting future
competitive advantage, for several reasons. First, it lacks operational validity, which means that it
is hard for practitioners to convert the framework into actions in their organisations. Second, the
framework lacks measurement criteria, which makes it hard to evaluate the actual effect and
contribution. Third, Priem and Butler (2001) argue that the RBV is too static and that it treats
competitive advantage as “a black box” rather than as a dynamic concept.
2.2.1 Dynamic Capabilities
Teece et al. (1997) formally introduced the idea of dynamic capability with the same underlying,
fundamental question as Barney (1991) - how to create sustainable competitive advantage, and the
framework emerged from an “entrepreneurial”, Schumpeterian viewpoint. Thus, it recognises
innovation and destruction of competencies as major components in building competitive
advantage. However, Teece et al. (1997) see this framework as an extension, or a complement to
the RBV rather than an opposing concept. As the RBV has received increasing criticism for its lack
of transformational elements in relation to competitive advantage and internal resources, the
framework of dynamic capabilities constitutes the missing piece around transformational
mechanisms in organisations (Wang and Ahmed, 2007). Since then, the research around dynamic
capabilities have increased continuously and there are now a significant amount of papers and
studies (Barreto, 2009). However, Barreto (2009) also identified an absence of aggregated
consensus around concepts and definitions, in combination with contrasting viewpoints and
interpretations of results, which makes it hard to assess the overall validity and reliability.
11
Teece et al. (1997, p. 516) defined dynamic capability as “the firm’s ability to integrate, build, and
reconfigure internal and external competencies to address rapidly changing environments’’. The
concept of dynamic capabilities is, as the name indicates, focused on capabilities or abilities within
the organisation and, through that, puts strategic management in a central position (Teece et al.,
1997). In addition, Teece et al. (1997), emphasise the importance of understanding and recognising
the changing element in competitive advantage (in similarity with Priem and Butler (2001)). The
framework is built upon an interdisciplinary approach which combines and integrates skills from
several different organisational research areas, such as strategic management, human resources,
R&D, sales and marketing (Teece et al., 1997). Integrating, coordinating, building and reconfigure
resources and competencies are also a key concept within dynamic capabilities.
To create a better and more practical relationship between operational capabilities and dynamic
capabilities, Winter (2003) presented a capability hierarchy model. The zero level capabilities are
defined as “how we earn a living now” capabilities, that generate revenue and create value through
the current business model (Winter, 2003). Next in the hierarchy there are first order dynamic
capabilities which represent more incremental product development. Higher order capabilities are
the last step in the hierarchy and can be described as a structured approach to change management
and organisational learning. The hierarchical way of categorising capabilities has also been
mentioned by Zahra, Sapienza and Davidsson (2006) - they discuss substantive capabilities and
dynamic capabilities in a similar way. Overall, the research demonstrates a clear difference
between ordinary and dynamic abilities - dynamic capabilities are ability to change, modify and
renew ordinary capabilities (Winter, 2003).
Wang and Ahmed (2007) identified three main components of dynamic capabilities: adaptive
capabilities, absorptive capability and innovative capability, see Figure 1. These abilities constitute
the foundation of dynamic capabilities and play a vital part of a firm's capability development and
ultimately organisational performance (Wang and Ahmed, 2007). Adaptive capability describes
the ability to identify opportunities in new markets and to exploit these opportunities. Staber and
Sydow (2002) defined adaptive capability as the ability to find the balance between exploration
and exploitation and is closely connected to the distribution of a firm’s resources. The dynamic
element of adaptive capability lies into what extent the organisation can be flexible and change this
ratio over time (Wang and Ahmed, 2007). Absorptive capacity was originally defined by Cohen
and Levinthal (1990) - “the ability of a firm to recognise the value of new, external information,
assimilate it, and apply it to commercial ends… the ability to evaluate and utilise outside
knowledge is largely a function of the level of prior knowledge”. High absorptive capability is
illustrated by a high ability to learn from competitors and partners, exploit and use external
knowledge and to incorporate external information into the organisation. The last component,
innovative capability, will be presented and discussed in the following section.
12
Figure 1. The research model of dynamic capabilities presented by Wang and Ahmed (2007, pp. 39).
2.2.2 Innovation Capability
The last component of dynamic capabilities is the innovative capability. The word innovation
capacity is also used within the research to some extent, and is defined slightly different by some
researchers, but is most often used as synonyms. Innovation capability is an organisation’s ability
to conduct innovation in a successful way and several researcher claim that innovation capability
is perhaps the most crucial dimension to determine organisational performance, long term survival
and competitive advantage (Lawson and Samson, 2001; Calantone, Cavusgil and Zhao, 2002;
Wang and Ahmed, 2007). As determined previously, innovation is vital for sustaining competitive
advantage over time, especially in industries that experience large technological transitions and a
volatile external environment. Allee and Taug (2006) have identified innovation and creativity to
be the new driving forces of innovation capability, given the ongoing commoditization of
knowledge that is currently happening. It is therefore vital for organisations to make innovation an
integrated part of processes, cultures and structures, as it is crucial for long term value creation
(Allee and Taug, 2006). Innovation capability is therefore an essential matter for most
organisations and will be a central concept in this study.
Lawson and Samson (2001, p. 384) defined innovation capability as “ability to continuously
transform knowledge and ideas into new products, processes and systems for the benefit of the firm
and its stakeholders”. Another definition is by Wang and Ahmed (2007, p. 38) “The firm’s ability
to develop new products and/or markets, through aligning strategic innovative orientation with
innovative behaviours and processes”. There seems to be some consensus around the link between
innovation capability and innovation performance (Lawson and Samson, 2001; Wang and Ahmed,
2004; Calantone, Cavusgil and Zhao, 2002; Saunila and Ukko, 2012; Breznik and Hisrich, 2014).
There is, however, no unified definition of innovation capability - Wang and Ahmed (2004) tried
to conclude a general definition of innovation capability as they found the existing research to be
inconsistent and incoherent.
13
Innovation capability is a broad term and many researchers has tried to divide the concept into
different frameworks and underlying dimensions which together constitute an organisation’s
innovation capability. Some of the earlier frameworks on innovation capability is the
innovativeness construct - from which a firm’s innovation capability can be analysed and measured
(Wang and Ahmed, 2004). According to Wang and Ahmed (2004), dynamic capabilities and
especially innovative capabilities are embedded in organisational processes rather than stand-alone
processes within a company. Processes are often referring to a logical way of structuring activities
whereas capabilities are an intricate process which are integrated with other processes and systems.
Larson and Samson (2001) defined seven dimensions of innovation capability in an influential
framework, illustrated in the left box in Figure 2. Further, they have also identified a link, both
empirical and theoretical, between innovation capability and innovation performance, as well as
between innovation performance and overall organisational performance (Lawson and Samson,
2001). The framework is built upon the concept of mainstream and newstream, which was
originally presented by Kanter (1983). Research has shown that strong mainstream capabilities,
such as efficiency and quality in daily operations, can tend to hinder the development of strong
innovation capabilities. Therefore, this framework emphasises the concatenating link between a
firm's mainstream activities (operational, daily activities within current market) and the newstream
activities (the innovation activities, often in a future or new market space). Kanter (1983) claims
that mainstream activities should preferably be managed separately from innovation newstream,
but Lawson and Samson (2001) argue that they need to be managed interdependently, especially
in a fast-paced, transformational environment. In addition, Lawson and Samson (2001) discuss the
importance of “company-wide innovation capability”, which is explained as the integration of key
capabilities and skills to successfully create innovation. This is one of the functions of innovation
capabilities - coupling and synergise the two areas of operation.
Figure 2. A model of innovation capability by Lawson and Samson (2001, pp 388).
According to Saunila and Ukko (2012), most of the earlier definitions of innovation capability has
determined the concept as innovation capacity potential, which according to the authors is too
limited. In an extended definition, Saunila and Ukko (2012) have identified three main elements
which influence the innovation capability in an organisation. First, the innovation potential, which
are the factors within the current innovation capability. Second, the innovation processes are the
innovation activities and systems which allow the organisation to unlock their innovation potential.
Third, the result of the innovation activities, which is the end product, service or process created
14
by the organisation. This perspective, that there are innovation capability potential and released
innovation capability is also discussed by Frishammar et al. (2012). The potential and the released
capability are complementary, and both need to exist for a firm to be innovative and to build
competitive advantage (Frishammar et al., 2012). If a firm organise and manage the three
components of innovation capability, they have high probability of having successful innovation
processes (Saunila and Ukko, 2012).
In summary, innovation capability has emerged from the dynamic capabilities perspective and is
closely related with the concept, even if there are some ambiguity around exactly how they are
related. There is no doubt that innovation capability has become an important term while discussing
innovation in terms of strategic management (Boly et al., 2014). The prior research also give
consistent view of innovation capability as enabler and a measure of innovation performance,
which is why it is considered a relevant indicator when investigating and evaluating an
organisation’s innovation performance (Frishammar et al., 2012; Saunila and Ukko, 2012; Breznik
and Hisrich, 2014). Looking at what researchers are identifying as dimensions of innovation
capability, there are several overlapping ideas, and the most recurring dimension are summarised
in Table 1.
Table 1. Summary of underlying dimensions of innovation capability.
Dimension Mentioned by
Innovation strategy Lawson and Samson (2001); Adams, Bessant and Phelps (2006); Saunila and
Ukko (2012)
Organisational culture
Lawson and Samson (2001); Wang and Ahmed (2004); Adam, Bessant and Phelps
(2006); Skarzynski and Gibson (2008); Paalanen et al. (2009); Saunila and Ukko
(2012)
Knowledge management Lawson and Samson (2001); Adam, Bessant and Phelps (2006); Skarzynski and
Gibson (2008)
Communication (internal and
external)
Paalanen et al. 2009; Saunila and Ukko (2012)
Expertise/knowledge Lawson and Samson (2001); Skarzynski and Gibson (2008); Tura, Harmaakorpi
and Pekkola (2008); Saunila and Ukko (2012)
Creativity/innovativeness Lawson and Samson (2001); Wang and Ahmed (2004); Tura, Harmaakorpi and
Pekkola (2008); Paalanen et al. (2009); Saunila and Ukko (2012)
However, there are some areas which needs to be further developed for the concept to stay relevant.
First, Breznik and Hisrich (2014) highlighted the fact that the different research streams within the
dynamic capability field need to unify around notions, definitions and relationship between the
terms. Second, there are room for more interactive aspects of innovative capabilities. Lawson and
Samson (2001) argued that as the pace of digitalisation and technical change is increasing,
organisations will struggle to stay relevant on all fields. Therefore, they predicted a higher emphasis
on value networks and external relationships with customers, suppliers and other actors in the
ecosystem - something that needs to be captured in the term innovation capability for the concept
to stay relevant (Lawson and Samson, 2001).
15
2.3 Innovation Strategy
A strategy’s main functions is to align the organisation, define goals and objectives and ensure that
efforts are directed in the right way (Pisano, 2015). The strategy is one of the most central tools for
organisations to manage and adopt to uncertainties in the surrounding environment (Simons, 1995).
It is also a crucial element in positioning strategically for the future, and it is essential to determine
what your strategic intent is (Anthony et al., 2008). The effect of aligning the innovation strategy
with the business strategy has also been identified to be dependent on external factors which is why
it necessary for firms to understand the external environment before implementing a service
innovation strategy (Ryu, Lee and Choi, 2015). A business strategy includes two interdependent
parts; strategic mission and competitive strategy (Merchant and Van der Stede, 2005, pp.591). The
strategic mission can exist on a spectrum, from the “build mission” to the “harvest mission”.
Building is associated with a focus on growing sales and increase market shares (with the
willingness to sacrifice short-term profits), whereas the harvesting mission is focused on exploiting
the current business for maximising cash flows and short-term profits (Merchant and Van der
Stede, 2005).
The competitive strategy is telling how the company intend to build competitive advantage in
comparison to competitors. This can be done through a cost leadership strategy or through
differentiation strategy, meaning they are competing based on providing unique value from the
customers’ perspective. Historically, organisations had focused on one or the other, but in today’s
fast paced environment, most large organisations must balance both ends of the scales of strategic
mission and strategy, which require a high ability of ambidexterity (Mattes and Ohr, 2018).
However, this is inherently challenging for incumbent firms, for several reasons. For example, the
different strategies can rarely be realised within one organisational framework, and they often
require different competencies from the functional units such as sales and support (Mattes and Ohr,
2018). This tends to create reluctance towards the innovative and exploring parts of the
organisation (Mattes and Ohr, 2018).
There are two ways of viewing strategy within an organisation, the hierarchical view and the
emergent view (Simons, 1995), see Figure 3. In the hierarchical view the strategy is formulated
prior to implementation, the communication around the strategy is translated top to bottom, and
middle managers translate the strategy in their respective teams (Simons, 1995). These strategies
are then managed by control systems, which measure the outcome in relation to the intended
strategy. Conversely, in the emergent view of strategy, the underlying idea is that a strategy is
incremental, where formulation and implementation happen in an alternating, interdependent
process (Simons, 1995). In the same way as an incumbent firm must embrace the different parts of
strategic missions and competitive strategies, they also must let these views exist simultaneously
within the organisation, as they fill different purposes (Simons, 1995; Mattes and Ohr, 2018). The
exploiting, “building” mission is most often associated with innovation and development of new
products and services (Simons, 1995). Björk and Frishammar (2019) articulated that an innovation
strategy is about articulating the organisational goals in a clear and specific way as well as
identifying the necessary steps to reach the goals.
16
Figure 3. Information Flow in Hierarchical view of strategy compared to emergent view of strategy (Simons, 1995, pp 19-21).
Moreover, the innovation strategy needs to be tightly coupled with the overall business strategy
and ideally, these two enhance each other and increase the value produced by the organisation
(Pisano, 2015). Even though innovation is a top priority in most organisation, the absence of an
innovation strategy is common and an underlying reason to the low success rate of innovation
projects (Pisano, 2015). There is a close relationship between the innovation strategy and the firm’s
innovation performance (Lawson and Samson, 2001), and many issues around building innovation
capability is originated in the innovation strategy (Pisano, 2015). Aligning the current business
strategy and with the innovation strategy is equally important as difficult for incumbent firms, and
here, the innovation capability come into consideration (Lawson and Samson, 2001).
The innovation strategy thereby creates internal attention. Without a clearly articulated innovation
strategy, the attention is scattered (Lawson and Samson, 2001), which in turn affect the innovation
performance (Brattström et al., 2018). It will also make it harder to take strategically grounded
decisions regarding risk taking, choice of practice methods, and aligning different parts of the
organisation (Calantone, Cavusgil and Zhao, 2002). It can lead to random decisions based on
factors such as intuition or personal preference, rather than making informed choices based on the
strategy. As part of setting an adequate innovation strategy, setting the right ambition level is
crucial (Nagji and Tuff, 2012). Core innovation is mostly about optimising products within the
space the organisation already operates, usually associated with incremental, low risk innovation
(Nagji and Tuff, 2012). Adjacent innovation can have characteristics from both radical and
incremental innovation and tends to mean that the organisation is taking incrementally developed
offerings into market spaces where the organisation is unfamiliar (Nagji and Tuff, 2012). The
transformational innovation is the radical innovation projects that include developing new products
or services to new market spaces (Nagji and Tuff, 2012). The right level of ambition depends on
multiple factors and is very individual, there is no “one size fits all” (Mattes and Ohr, 2018). Nagji
and Tuff (2012) has created the “Innovation Ambition Matrix” which visualise the different areas
of innovation ambition, see Figure 4. The ambition level can be translated into what level of risk
the organisation is willing to take (Mattes and Ohr, 2018).
17
Figure 4. The Innovation Ambition Matrix (Nagji and Tuff, 2012, pp. 69).
2.3.1 Service Innovation Strategy
An innovation strategy is imperative for a firm’s service innovation as well as performance (Menor,
2015), especially to gain long term competitiveness (Björk and Frishammar, 2019). As previously
mentioned, service innovation differs in several ways from product innovation, therefore, how it
should also be approached differently (Ostrom et al. 2010). The increased interest in service
innovation has resulted in a substantial amount of research within the field (e.g. Menor and Roth,
2006; Möller et. al, 2008; Maglio and Spohrer, 2013). However, existing services innovation
strategies and methods are still considered to be insufficient by several researchers (e.g. Ostrom et
al. 2010; Edvardsson et.al, 2013; Menor, 2015).
Since service innovation, like other innovations, can vary from incremental to radical the most
suitable process for creating value when developing and delivering a service will, therefore, also
vary (Möller, Rajala and Westerlund, 2008). The approach will also be affected by the previously
mentioned factors included in the innovation ambition matrix, in Figure 4 (Nagji and Tuff, 2012).
In addition to this, Möller, Rajala and Westerlund (2008) emphasised the need to acknowledging
the customer involvement when selecting a service strategy. Edvardsson et al. (2013) argued that
co-creation of value is an important factor that influences the service innovation performance but
collecting data about customers in a deliberate way is the most crucial factor. Similarly, Barrett et
al. (2015) identified ICT as a cornerstone in the development of service innovation since it is an
enabling tool when exploring new ways to provide services (Barrett et al., 2015). Thus, due the
complexity within the research field, designing a service innovation strategy is not a simple task.
18
Edvardsson et.al (2013) identified the implementation of a service innovation strategy to be the
most critical factor to achieve a higher service innovation performance. Lightfoot and Gebauer
(2011) argued that by aligning the business strategy, innovation strategy and service innovation a
higher service innovation performance can be achieved. Further, Menor and Roth (2006) stated
that “an effective Service Innovation Strategy enables firms to effectively identify the
characteristics of a new service offering and deliver service while meeting customer expectations
and demands”. It is necessary to acknowledge service performance indicators, and it is further
crucial to understand the interdependence between the performance indicators. This is supported
by Menor and Roth (2006) as well as Björk and Frishammar (2019) who argue that an innovation
strategy is imperative to developing a measurement system for service innovation. However, it is
also a complex process to align the service innovation key success factors (KSF) with the service
strategy and it can easily be counterproductive if it is wrongfully implemented (Menor and Roth,
2006).
2.3.2 Innovation Portfolio
Some of the key purposes of implementing portfolio management is to improve project selection,
balance projects between portfolios to improve resource utilisation and value maximization
(Levine, 2005). While the innovation strategy is an essential part of building a strong innovation
capability and positioning the company for future growth, translating the strategy into practice is
just as important (Meifort, 2015). This is, however, proven to be difficult for many organisations -
Hrebiniak (2006) argue that the implementation phase is more problematic than the formulation of
the strategy for most firms. Historically, the research has focused mainly on how to manage
individual innovation projects, why the innovation project portfolio management (PPM) research
is still dispersed and divergent (Meifort, 2015). Innovation PPM is, however, a tool to implement
the business’ innovation strategy and through establishing an adequate strategic orientation, a
successful innovation project portfolio can be the link between strategy and business success
(Meskendahl, 2010). Meskendahl (2010) defined the relationship between project portfolio success
and business success based on a set of dimensions, see Figure 5.
Figure 5. The relationship between project portfolio success and business success (Meskendahl, 2010, pp. 811).
These dimensions contribute to the portfolio success for an organisation. The first dimension,
average single project success is related to project management practices, and degree of objective
fulfilment for the specific project (Meskendahl, 2010). The success of single project management
19
constitutes around 50 percent of the total portfolio success (Martinsuo and Lehtonen, 2007).
However, project portfolio as an organisational layer and management form is offering benefits
that goes beyond just the result of each individual project. Using the synergies between the projects
in the project portfolio is valuable from several perspective and can enhance the organisational
capability throughout different parts of the project management cycle (Meskendahl, 2010).
Increasing the strategic alignment between the projects and the business strategy is one of the
primary objectives with PPM (Stettina and Hörz, 2015). The portfolio management can improve
success rate and ensure that the right projects are pursued, due to an improved the strategic focus
(Cooper, 1988). However, research shows that many organisations tend to not emphasis the
strategic fit enough in the project selection phase (Levine, 2005; Jonas, Kock and Gemünden,
2013). However, even though a higher level of alignment can be achieved through PPM, there is
still limited research conducted within the area of PPM and strategic alignment (Meskendahl,
2010).
The fourth dimension is portfolio balance. It is important to reach a suitable portfolio balance for
the organisation to reach the business objectives, without being too exposed to risks (Mikkola,
2001). It also works to ensure a consistent generation of cash flow to maintain financial stability,
while also allowing the organisation to prepare for the future (Mikkola, 2001; Meskendahl, 2010)
The optimal balance includes several, company-specific dimensions, such as balance between
short- and long-term profit, risk level distribution and the time horizons associated with the projects
(Meskendahl, 2010). Finding this balance is closely related with the innovation strategy and the
innovation ambition - Nagji and Tuff (2012), the most successful innovators are the ones who have
a clearly determined balance between core, adjacent and transformational projects.
According to Jonas, Kock and Gemünden (2013), the portfolio success can be predicted based on
a concept called management quality. This is a three-dimensional concept: information quality,
allocation and collaboration within the portfolio (Jonas, Kock and Gemünden, 2013). Information
quality is related to the access of relevant and reliable information at the right time, while allocation
quality is the ability to distribute and manage resources effectively (Jonas, Kock and Gemünden,
2013). Lastly, cooperation quality is indicating how well the collaboration and information sharing
between projects is working (Jonas, Kock and Gemünden, 2013). If the quality of information is
high, the transparency can be improved as the decisions can be based on accurate information and
more easily shared and evaluated (Jonas, Kock and Gemünden, 2013). However, it is very common
that organisations manage projects by an ad hoc manner, with a low awareness of the contribution
to the portfolio balance (Nagji and Tuff, 2012). This can lead to weak or ambiguous decision
criteria for the projects, as well as a tendency to not kill projects in time (Cooper, 1988; Tidd and
Bessant, 2013). Is can also led to transparency issues, and tensions within the organisation (Jonas,
Kock and Gemünden, 2013).
2.3.3 Agile Innovation Approach
There are many different innovation processes, one of the most classic frameworks is ‘State-Gate
Model’ (Cooper, 1988), which has benefits such as a clearly defined structure for decision making
processes (Maylor, 2010) and documentation (Prencipe and Tell, 2001). However, the Stage-Gate
Model is a rigid and inflexible model, which results in complex decision-making processes and
drawn out innovation projects (Maylor, 2010). As a result, the ‘State Gate Model’ has been
20
challenged by agile and lean innovation processes, advocating for a more iterative approach to
innovation (Maylor, 2010; Stettina and Hörz, 2015). While agile project management has been is
well established in most companies working with software today, Stettina and Hörz (2015) argue
that also portfolios should be managed according to an agile work process. Through implementing
an agile approach to portfolio management, transparency, collaboration and strategic commitment
can be improved (Stettina and Hörz, 2015).
Two of the main drivers of agile development is customer-focus and simplicity (Margaria and
Steffen, 2018). Adopting an agile innovation can offer a solution on the complex decision-making
processes and the lack of customer orientation in the ‘State Gate Model’. This process is also
supposed to integrate a sustainable value creation from early in the process, with a multiple
stakeholder perspective (Highsmith, 2010). Creating and delivering value to the customers is
superior to aspects that are typically the focus in traditional project management, such as cost and
time management. While these aspects are, of course, relevant, they are secondary to the main goal
- value creation (Highsmith, 2010).
Highsmith (2010), also claim that an agile project needs be evaluated and measured in a different
way - with a higher focus on business objectives and innovation capabilities. It also emphasizes
the need for a “customer-developer”-partnership, where customers are involved to a high extent
throughout the innovation process and where all parts involved have responsibilities. In addition to
this, Mattes and Ohr (2018) argued that innovation projects should be evaluated early and
innovation projects, which do not create and provide enough value for the firm, should be killed.
Since cost efficiency is of increased interest, firms need to be able to cancel innovation projects in
a determined way. As a result, there will be resources and opportunities for other innovation
projects instead (Mattes and Ohr, 2018).
2.3.4 Time Horizons
Mosakowski and Earle (2000) stated that time is a factor which should be included in all firms’
strategies, and this has been confirmed by several researchers (Laverty, 1996; Flammer and Bansal,
2017). A firm’s time horizon has an immense impact on a firm’s business decisions, and it is
necessary to understand its impact on a firm’s performance (Flammer and Bansal, 2017). Short
term results are necessary for a firm's survival (Marginson, and McAulay, 2008), however, short
term goals might also have a negative impact of the long-term performance of a firm (Laverty,
1996; Brochet, Loumioti, and Serafeim, 2015). Thus, there is constant a trade-off between the
short-term and long-term performance of a firm (Laverty, 1996; Merchant and Van der Stede,
2013). Brochet, Loumioti, and Serafeim (2015) stated that this is apparent in many firms who tend
to disregard the future, and that behaviour has been identified as a reason to why many firms also
fail (Brochet, Loumioti, and Serafeim, 2015). The behaviour of prioritising the short-term results
to appease shareholders and other stakeholders is among researchers named short-termism
(Laverty, 1996; Marginson, and McAulay, 2008; Flammer and Bansal, 2017). Marginson, and
McAulay (2008) argued that short-termism at a company exists because managers are dependent
on capital markets, unbalanced performance measurements systems and norms within groups
among other things.
21
Laverty (1996) stated that it is extremely difficult for top management to get investors and
shareholders behind long-term investments that, in short sight, might reduce the profit. Since the
future is unknown it is a high risk for shareholders (Laverty, 1996) and especially if the reduced
profit is used for innovation, which is a considerable risk in many cases (O’Reilly and Tushman,
2011). However, firms with shareholders that have a longer time horizon tend to be more innovative
(Aghion, Van Reenen, and Zingales, 2010) and have a better performance (Tidd and Bessant,
2013). Hence, having a long-term perspective is valuable, and it is further argued that a long-term
horizon also forces a short-term horizon and, thus, improves benefits related to both horizons
(O’Reilly and Tushman, 2011).
Marginson, and McAulay (2008) suggested that to reach both short term necessities as well as long
term performance, groups should be mixed with people with both long-term as well as short-term
horizon. Meanwhile, Merchant and Van der Stede (2013) argued that by measuring future oriented
factors as well as non-financial factors, a more long-term horizon can be integrated into the firm’s
strategy. It can be measurement factors such as innovation accomplishments, market share
development and customer satisfaction, which will give an indication to what the future cash flow
will look like (Merchant and Van der Stede, 2013). Further Flammer and Bansal (2017) claimed
that by adopting long-term incentives, a firm might be able to rectify the short-term horizon. A
firm's dynamic capability might facilitate finding the balance between the long-term and short-term
horizon (O’Reilly and Tushman, 2011). O’Reilly and Tushman (2011), further argued that for the
combined strategy of both long-term and short-term horizon, it is necessary that the entire team is
committed to the strategy.
2.4 Cross-functional Collaboration
Cross functional collaborations refer to a collaboration with people with different knowledge and
competence who join forces and work together toward a common goal, which require expertise
from several disciplines (Kahn, 1996; Olson et al., 2001). In 2010, Tidd and Hull stated that service
innovation performance has shown to be higher in organization where the innovation activities are
performed by cross-functional teams and suppliers and customers are early involved in the
innovation process.
2.4.1 Internal Collaborations
Cross functional collaboration within a company is also referred to as interdepartmental
collaborations (Cuijpers, Guenter and Hussinger, 2011), which have strong similarities to the
research field of interdepartmental integration (Kahn, 1996). Many firms use cross functional teams
to gather people from different parts of the organisation as an attempt to also gather different
knowledge and perspectives, and as a result improve and increase the efficiency of the working
process (Lovelace, Shapiro and Weingart, 2001). There are several potential benefits from cross
functional collaborations such as improved communication, efficiency and product innovation
performance (Frishammar and Hörte, 2005).
Although, there are many potential benefits to cross functional collaborations, there are also
potential challenges which can emerge due to collaborations across internal functions (Griffin and
Hauser, 1996; Troy, Hirunyawipada and Paswan, 2008). Dougherty (1992) stated that, with
increased diversity in groups, varying perspectives about both strategy as well as the working
22
process might emerge. Further, without enough communication, cross functional projects tend to
be significantly less successful (Dougherty, 1992). Cross functional teams or collaborations, if not
executed proficiently, can result in less efficient decision-making arising conflicts about resources
and can sometimes result in increased costs (Troy, Hirunyawipada and Paswan, 2008).
Additionally, in cross functional collaborations, differing perspectives on time-horizon and low
tolerance for ambiguity can also create tensions as well as impair decision making in projects
(Griffin and Hauser, 1996). For example, Griffin and Hauser (1996) identified that people working
with R&D tend to have a longer time horizon whereas people from the marketing department have
a shorter time horizon. Thus, for a cross functional collaboration to be successful, it is essential that
there is a common goal, which all involved work towards and that the vision is shared among the
participants (Kahn and Mentzer, 1998). Further, to create the best preconditions for cross functional
collaborations, firms should ensure adequate communication and have leaders who efficiently
solve conflicts as well as potential miscommunications that might emerge (Lovelace, Shapiro and
Weingart, 2001). Further, complete support from top management is essential for cross functional
collaborations to work proficiently. (Troy, Hirunyawipada and Paswan, 2008).
Most literature on cross functional collaborations, regarding innovation, focuses on the potential
benefits for product innovation (e.g. Frishammar and Hörte, 2005; Dougherty, 1992; Troy,
Hirunyawipada and Paswan, 2008). However, a few researchers within the field of SDL and service
innovation, have described internal collaborations and cross functional collaborations as influential
factors for successful service innovation (Froehle and Roth, 2000; Ordanini and Parasuraman,
2010). Froehle and Roth (2000) mentioned that sharing knowledge and ideas across internal
functions should be encouraged for service innovation. Melton and Hartline (2012) further argued
for an indirect interdependency between cross functional teams and sales performance when
working with service innovation. However, the study also identified that in order for the cross
functional teams to have a positive effect on the sales of service innovation offers, the new service
need to show a clear increased value and have a quick adoption rate from customers (Melton and
Hartline (2012). Tidd and Bessant (2013, p.433) stated that: “Service delivery is improved by
customer focus and project management, and by knowledge sharing and collaboration in teams.
Time to market is reduced by knowledge sharing and collaboration, and customer focus and project
organization, but cross-functional teams can prolong the process. Costs are reduced by setting
standards for projects and products, and by involvement of customers and suppliers, but can be
increased by using cross-functional teams”.
Hence, cross functional collaboration is a complex matter which is dependent on several factors
and can both improve and hinder the service innovation process (Melton and Hartline, 2012). The
identified distance between functional departments was also acknowledged by Tidd and Bessant
(2013), who further stated that, integrating the innovation process and to include all necessary
functions early, is often used in service organisations, to increase communication and improve the
innovation projects who require that several units are involved.
Finally, to have many employees engaged in the innovation work is perceived as something
positive (Brattström et al., 2018). However, there also need to exist someone who has a holistic
perspective on the existing innovation activities, to avoid people or groups working in silos with
innovation (Deschamps and Nelson, 2015). According to Deschamps and Nelson, (2015), silos can
23
be prevented through different methods, for example a governance from the top management or a
cross functional team that works to increase the transparency of the innovation activities.
2.4.2 External Collaborations
A company can have external collaborations with firms from different sectors (Forrer, Kee and
Boyer, 2014), competitors, suppliers or customers, and that is generally regarded as a positive
influence on a firm's innovation performance (Un, Cuervo-Cazurra and Asakawa, 2010). External
collaborations, such as partnerships, have emerged as a response to increased competition in many
industries (Powell, 1987). It is a result of changes in the business environment where, for example,
the shortened life cycles for offers has increased the importance for firms to consider the dimension
of time, as well as enabling easy access to knowledge (Ditillo and Caglio, 2009). Collaborating
with external parties have been acknowledged as a method to gain knowledge, share risk, increase
business opportunities and can further be a method to improve the company reputation (Forrer,
Kee and Boyer, 2014).
Further, large incumbent firms tend to find it challenging to respond quickly to changed customer
requests due to its large size, which usually affects the amounts of governance as well as
documentation (Ditillo and Caglio, 2009). This was, further supported by Maylor, (2010) who
stated that, while thorough documentation can be beneficial in some situations, it also tends to
cause rigid and inflexible decision-making processes and the documentation can be overly time
consuming. Through collaborating with smaller firms, the incumbent firm can improve its response
time as well as the flexibility (Ditillo and Caglio, 2009), and the external collaboration can further
play a vital role to reduce the time to market (Wallin, and Von Krogh, 2010). The external
collaboration is usually beneficial for both parties because they get access to knowledge,
information, resources and markets (Un, Cuervo-Cazurra and Asakawa, 2010), which they
previously did not have access to (Tidd and Bessant, 2013).
External collaborations with business partners and customers have been identified as a factor which
can contribute to improved service innovation as well as value co-creation (Möller, Rajala and
Westerlund, 2008; Ordanini and Parasuraman, 2010; Witell et al., 2011; Hsieh and Hsieh, 2015).
Many innovation projects tend to be managed far away from the customer and end users, which is
problematic in complex and fast-paced environments with a high customer orientation (Maylor,
2010; Margaria and Steffen, 2018). Open innovation has become a popular phenomenon which
reduce the distance between the company and customers. It consists of exploiting external
resources and where co-creating value with external parties is one existing method to gain
competitive advantages (Wallin, and Von Krogh, 2010). Open innovation is usually an iterative
working process, and therefore, it has the additional potential to improve the product or service
quality (Wallin, and Von Krogh, 2010). To early include the customers in the innovation process
can, further, increase understanding of customer needs as well as market trends but can also
improve the customer satisfaction and customer relationship (Tidd and Bessant, 2013). Similarly,
Hsieh and Hsieh (2015) found a positive interrelationship between firms that have close
relationship with their customers and successful service innovation.
Although there are many potential benefits with external collaborations, there are challenges that
might emerge as well (Boudreau, 2010; Cuijpers, Guenter, Hussinger, 2011; Alexy, George and
24
Salter, 2013). The diverse, and sometimes conflicting, cultures, goals and perspectives is something
which might contribute to a difficulty during external collaborations (Boudreau, 2010).
Collaborations between firms can also be risky for a company, since valuable resources, which
provides competitive advantages, can be exposed (Dahlander and Gann, 2010; Alexy, George and
Salter, 2013). Further, external collaborations might lead to a decreased level of control and an
increased complexity within projects (Tidd and Bessant, 2013). Due to both the benefits and risks
of external collaborations, it is also argued that there need exist a balance between how much is
explored outside the firm and how much is exploited within the firm (Dahlander and Gann, 2010).
If you find the balance between exploiting and exploring you will have the best preconditions for
a long-term, sustainable business performance (Raisch et al., 2009).
Since external collaborations is a complex area, it might be beneficial to analyse why a
collaboration might be useful for a firm and what is the ambition and reason for the collaboration
(Tidd and Bessant, 2013). Relevant factors that should be taken into account during the shaping of
the collaboration is illustrated in Figure 6 below.
Figure 6. A model for collaboration for innovation (Tidd and Bessant, 2009, p.479).
To achieve the best conditions for collaborating externally, common rules need to be articulated,
goals need to be aligned, responsibilities need to be clearly stated (Bruce, Leverick and Littler,
1995). Further, people factors such as a high level of commitment, trust and communication are
identified as essential to a proficient collaboration and it is further important to have similarities in
the corporate culture (Bruce, Leverick and Littler, 1995). Kelly, Schaan, and Joncas (2002) argued
that the frequency of communication is an additional factor that impacts how successful
collaborations are.
25
2.5 Knowledge Management
A learning orientation is referring to organisations’ vision to learn and use knowledge to improve
competitive advantage (Tamer Cavusgil, Calantone and Zhao, 2003). Knowledge management is
an essential, yet challenging part for project-based organisations (PBO) - sharing knowledge
between projects is proven to be difficult (Pemsel and Wiewiora, 2013). The projects are often
managed independently, with no or little interaction between the projects and often without any
formal structures for knowledge sharing (Pemsel and Wiewiora, 2013). Many PBOs also tend to
prioritise other factors such as time management and delivery time over knowledge management
governance (Hobbs, Aubry and Thuillier, 2008). In a large and complex environment, innovation
projects are often going on for several years, which also makes knowledge sharing hard to condense
(Saunila and Ukko, 2012). Therefore, it can be beneficial to implement a knowledge management
system that create a continuous opportunity to gather and share knowledge both within the
organisation as well as between projects (Zika-Viktorsson, Sundström and Engwall, 2006). This
also allows the employees to reflect and discuss challenges and problems together with others, to
solve issues and improve the situation.
There are different ways to manage knowledge within PBOs and it depends on the type of the
organisation. PBOs that are of subsidiary character, which tend to have the challenges associated
with both line organisations and PBOs (Pemsel and Müller, 2012). According to Principe and Tell
(2001), there are different types of learning landscapes, which are associated with different types
of organisations. Knowledge-intensive organisations are often associated with a “people to
people”-communication, accomplished by a certain level of explicit knowledge sharing. Therefore,
there need to be a combination of formal knowledge management systems and establishing a
mutual knowledge sharing base for the people working in the projects, and the executives managing
the innovation portfolio and projects (Principe and Tell, 2001).
If the organisation has a project management office (PMO), that can be a natural place to centralise
the knowledge management (Hobbs, Aubry and Thuillier, 2008). As a PMO is functioning as
coordinating division across several dimensions within the organisation, it could implement a
structure for gathering insights and knowledge and distribute this to the different levels of the PBO.
However, research shows that both PMOs as an organisational entity as well as the managers within
the organisation often lack the right capabilities to organise and implement efficient knowledge
management structures (Hobbs, Aubry and Thuillier, 2008; Pemsel and Müller, 2012).
Knowledge management is closely related to the innovation capability within the organisation
(Tamer Cavusgil, Calantone and Zhao, 2003; Belkahla and Triki, 2011; Saunila and Ukko, 2012).
Companies that are committed to share knowledge and continuously learn are most likely to
develop a stronger innovation capability (Tamer Cavusgil, Calantone and Zhao, 2003). Calantone,
Cavusgil and Zhao (2002) have identified three ways that a strong orientation towards
organisational learning and knowledge management increases innovation capability:
(1) A strong orientation towards learning will most likely enact as an orientation towards
creating state-of-the-art solutions and new innovations.
(2) The organisation will be equipped with the right tools to identify and act on market
opportunities, and will, therefore, not miss new opportunities. The new products developed
26
will also have a stronger connection to customer needs, as the learning organisations will
have a better perception of their customers.
(3) As the organisation manage to be in tune with the market development, they are also
capable of understanding their competitors in an accurate way, which helps to strengthen
their own innovation capability.
Other researchers have also added the external knowledge perspective and put it in relation to
innovation capability. The ability to manage and share knowledge with partners, suppliers and
customers is closely related to internal knowledge management (Tamer Cavusgil, Calantone and
Zhao, 2003; Belkahla and Triki, 2011). Tamer Cavusgil, Calantone and Zhao (2003) found that
organisations that manage to transfer tacit knowledge between their suppliers and customers can
enhance their innovation capability.
2.6 Innovation Measurement
There is a growing body of literature on the subject innovation measurement (e.g. Adams, Bessant
and Phelps, 2006; Boly et al., 2014; Brattström et al., 2018). Given the strategic importance of
successful innovation (Chan et al., 2008), it is no surprise both researchers and business leaders are
interested in how innovation can be quantified and measured. Innovation measurement is, however,
a complex process without standardised solutions and predetermined pathways (Davila, Epstein
and Shelton, 2012; Richtnér et al., 2017). This chapter will explain management control systems,
why organisations should measure their innovation, provide a literature background and present
some of the most relevant frameworks for measuring innovation capability.
2.6.1 Management control systems
Management control systems (MCS) are a central mechanism for strategy implementation and their
effectiveness on the metrics’ correspondence with the strategy (Merchant and Van der Stede,
2012). According to Simons (1995), management control systems consists of four main parts, see
Figure 7.
Figure 7. The key variables to analyse to control business strategy (Simons, 1995, pp. 7).
27
MCS can be both diagnostic and interactive and the most suitable approach varies depending on
the internal environment and the aim for the control system (Widener, 2007). Diagnostic control is
usually used for data collection when previous performance levels are known, and the data can be
compared to that level (Simons, 1995). It is primarily used to evaluate already conducted activities,
and when the collected data can be easily collected regularly. When there exists uncertainty, i.e.
lack of information (Schrader, Riggs and Smith, 1993); the diagnostic control system is considered
beneficial (Simons, 1995). However, when there is ambiguity around the activities or measured
metrics, it is usually more beneficial to use interactive control. Schrader, Riggs and Smith (1993)
defined ambiguity as “lack of clarity”, where information might exist, but there is a lack of
understanding about the interrelationships between involved variables. The interactive control
system, compared to diagnostic, can provide rich information, meaning information sharing with
more physical and frequent interaction (Simons, 1995). Rich information is useful when the
ambiguity is high, and therefore often useful for interactive control systems (Rice, 1992). On the
other hand, the diagnostic control system provides lean information, for example numerical data,
which is more suitable for situations with uncertainty and not ambiguity. Additionally, whereas
diagnostic control system requires low engagement from managers, the interactive control system
depends on involving people from all levels, including managers. According to Simons (1995), the
interactive control system should be approached through face-to-face meetings, where the most
prioritised metrics or areas are discussed, analysed to create a plan to move forward. Hence,
depending on the MCS metrics, the most suitable control will differ (Widener, 2007).
Even if there has been a substantial development of research around how to measure, there are still
many organisations that struggle with measuring their innovation process (Chan et al., 2008). There
are room for improvement, both in the way innovation metrics are applied and the way they are
interpreted and used (Chan et al., 2008). Some of the most common mistakes are related to
improper selection of metrics; either over-measuring, only measuring an isolated part of the process
or relying on the metrics themselves to improve the innovation process rather than using it as a tool
to understand the process (Davila, Epstein and Shelton, 2012; Richtnér et al., 2017; Brattström et
al., 2018).
Key Success Factors
KSF are factors that must be achieved or fulfilled to reach the business objectives (Simons, 1995).
While there are several generic KSF, most of them will depend on the business strategy and the
business context and conditions - there are both industry specific KSF and organisation specific
KSF, see Figure X (Parmenter, 2015). An adequate number of KSF are between five to eight, where
some will be shared with other organisations in similar situations, and some will be specific for the
organisation (Parmenter, 2015).
28
Figure 8. Aspects impacting the Key Success Factors (Parmenter, 2015, pp. 167).
KSF can, according to Parmenter (2015), be the link between the strategy and the performance
measures, and it is necessary to identify the KSF to be able to get the metrics right. Through
identifying the specific KSF in relation to the firm specific strategy and preconditions, measures
can be established (Simons, 1995). This can be done through understanding what defines successful
performance in relation to the business strategy and objectives, which can then be translated into
performance measure (Simons, 1995). If an organisation has identified their KSF in a relevant way
and has based the performance measurement on these factors, they have created good opportunities
to monitor and understand the daily activities and understand the operations in relation to the
strategy (Parmenter, 2015).
A firm’s measured performance can be compared to specific targets, which address a level of
proficiency which the group or organisation aims to reach (Gray, Micheli and Pavlov, 2012). This
is usually closely connected to a diagnostic controlling system (Simons, 1995). For business units
that are oriented towards growth and creativity, measures that have a long-term perspective (e.g.
sales growth, market share development) have a positive impact. Meanwhile, the same metrics
have a negative impact for traditional business units that are managing existing parts of the business
(Merchant and Van der Stede, 2012). Likewise, the competitive strategy (discussed in section 2.3),
also needs to be reflected in appropriate metrics in the MCS.
Targets are usually constructed to foster a certain behaviour and can have a positive influence in
an organisation (Merchant and Van der Stede, 2012). However, improper implementation might
also result in unethical behaviour which further might result in the firm’s reputation is put at stake
(Latham, and Locke, 2006). For example, if targets are too high, they might result in the data being
manipulated to present an accepted level of performance (Locke, 2019). Hence it is essential that
a company’s targets foster the right behaviour and motivates people to work towards a common
goal (Gray, Micheli and Pavlov, 2012). Additionally, targets are central for continuous follow-up,
and it is important that the people that works towards the targets are involved in discussions where
the work related to the target is analysed (Gimbert, Bisbe, and Mendoza, 2010). Gimbert, Bisbe,
and Mendoza (2010) further argue that by discussing a firm’s activities in groups, regarding what
29
is measured, the organisation can improve learning and improve their strategy iteratively.
Moreover, measurement systems need to be dynamic and flexible to both internal and external
changes, such as organisational changes as well as changes on the business environment
(Franceschini, et al., 2007).
To synthesise, an innovation strategy is vital for a successful implementation of a measurement
system. However, the identification of KSF, related to the strategy, can provide insights regarding
essential business focus areas, and can facilitate constructing and selecting suitable metrics.
Moreover, the measurement system needs to be controlled and depending on the selected metrics,
the control systems could be either diagnostic or interactive. The nature of the metrics and control
system will influence the information gathered from the data collection but also how it should be
analysed and processed.
2.6.2 Why measure innovation?
According to Davila, Epstein and Shelton (2012), innovation measurement systems have three
major roles: plan, define and communicate strategy, monitor and evaluate performance, and learn
and identify new opportunities and threats, illustrated in Figure 9. According to Melnyk, Stewart
and Swink (2004), measures and metrics link together an organisation’s strategy, operations and
value creation.
Figure 9. The three major roles of innovation measurement (adapted from Davila, Epstein and Shelton, 2012).
2.6.3 Perspectives on Innovation Measurement
Even though it has been some discussions around whether innovation should be measured at all
(Ojanen and Vuola, 2005), according to Birchall et al., (2011), the value of measuring innovation
is confirmed by research. However, as innovation is an ambiguous and broad term, the research
around innovation measurement is naturally complex and multifaceted. This has led to a
fragmented and diverse body of knowledge around innovation measurement, including how
measurement systems should be implemented, what metrics provide the most insight and how the
data should be analysed (Boly et al., 2014; Richtnér et al., 2017).
As identified by Tidd (2001) as well as Brattström et al. (2018) there are two main research streams
within innovation measurement. The first stream emerged from the managerial accounting
30
perspective, which historically has not created measurement systems specifically for innovation,
rather than for accounting, finance and sales (Tidd, 2001). Davila, Foster and Oyon (2009) even
state the control systems within managerial accounting are designed to defeat innovation as it is
often a costly, high-risk and insufficient process. More recent research within this stream has
started to put more specific focus on innovation measurement (Brattström et al., 2018). Given that
this research stream has grown out of accounting, there is an emphasis on financial measures, such
as profitability, growth, market share and return on investment (ROI) (Tidd, 2001). Even if there
are some underlying problems coming from this perspective, it has contributed with insights around
how metrics can be incorporated in the operational part of the organisation and what implications
it has for the daily activities (Brattström et al., 2018).
The second research stream within innovation measurement has stemmed from the technology and
innovation management literature (Brattström et al., 2018). Given the background of this research
area, innovation has a more central position. However, there are still ambiguities and contradictions
within this field too (Tidd, 2001; Muller, Välikangas and Merlyn, 2005; Adams, Bessant and
Phelps, 2006). There are several different frameworks, however, the research area has struggled to
unify around any frameworks or methods (Tidd, 2001). This makes it hard to synthesize best
practices and common methods for measuring innovation, even though many aspects and
dimensions from different frameworks are overlapping (Tidd, 2001). If studies within managerial
accounting focus more on the financial aspects of innovation measurements, researchers within
this stream have acknowledged the need for using multiple measurements and combining
quantitative and qualitative metrics (Boly et al., 2014). Through combining these two categories of
metrics, organisation can better capture different aspects of their innovation process and gain a
deeper understanding of how they can improve (Chan et al., 2008). According to Brattström et al.
(2018), there has been an increased focus on contingency and alignment with both the innovation
strategy and the external conditions.
Brattström et al. (2018) build on to this perspective, and have as mentioned earlier, based their
research on the attention-based theory. The hypothesis is that innovation measurements create and
direct attention within an organisation, and that innovation measurement systems therefore be an
attention-focusing device. Depending on the level of ambiguity around the innovation, the different
sort of attention is preferred. If there is a low level of ambiguity, the attention needed can be more
direct and action oriented - helping managers to focus the attention on building a coherent and
efficient innovation process (Brattström et al., 2018). If the ambiguity is high, the attention needs
to be more focused on communication, understanding and coordinating - often members from
different parts of the organisation need to cooperate and communicate, in combination with support
from top management (Brattström et al., 2018).
2.6.4 Measuring Innovation Capability
Several different frameworks for measuring innovation can be found in the literature within
innovation measurement. Adams, Bessant and Phelps (2006) claim that there is no general best
practice available, much because the research itself is diverging in many areas. There are, however,
some recurring themes, dimensions and metrics which are more frequently used.
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Metrics
There are a range of different metrics within innovation measurement and according to Chan et al.
(2008), companies use an average of eight metrics for measuring innovation. The most basic
metrics are output and input metrics. Shapiro (2006) found that the most used metrics within
innovation measurement is “Percent of Revenue from New Products”. It is understandable that
organisations want to use this metric, but only looking at quantitative, output metrics such as
“Percent of Revenue from New Products” entails a risk of overlooking essential parts of the
innovation process (Shapiro, 2006). Davila, Epstein and Shelton (2012) have categorised
innovation metrics into leading, real-time and lagging metrics. Input metrics are examples of
leading metrics, as they indicate the resources available such as capital, time and personnel (Davila,
Epstein and Shelton, 2012). Process metrics are classified as real-time metrics as they illustrate the
translation between input and output. Output metrics are, thus, lagging metrics, which capture how
well the conversation from input through the process went. Chan et al. (2008) found that most
organisations use output metrics rather than input or process metrics and claim that it could be
beneficial to use a broader range of metrics. Further, it could be useful to include metrics that link
the innovation process to shareholder value more directly (Chan et al., 2008). Overall, Ojanen and
Vuola (2005) claim that one of the issues is an excessive focus on internal measurements, and that
the measurement tends to become both subjective and complicated.
Brattström et al. (2018) have introduced two new types of measurement types: directional
measurement and conversational measurements. As mentioned previously, it is built on the
attention-based theory and the two different measurement types support different types of attention,
depending on the ambiguity level of the innovation process. If the ambiguity level is low, the
purpose of innovation measurement is often to focus the attention on the innovation process. This
can be done through a few, specific metrics that help managers to prioritise different actions and
sort issues within the process. In general, directional measurements are more suitable for
incremental innovation, while conversational measurements are preferred for radical innovation.
Conversational metrics help managers to get a bigger perspective on the innovation process and to
identify patterns which could otherwise go under the radar. The issue translation is also a tool to
convert tacit knowledge into codified information. Organisations with a complex and ambiguous
innovation process often experience problems with communication, alignment of objectives and
coordinating activities across the organisation - and translation of knowledge can help to improve
this. (Brattström et al., 2018)
Measurement Dimensions
Several researchers have tried to summarise and conclude some consensus around innovation
measurement dimensions. Ojanen and Vuola (2005) presented a framework with the basic
dimensions for innovation performance analysis, where they try to answer questions to ensure that
the metrics are meaningful, see Table 2. These illustrate the most fundamental aspects of the
innovation process and through combining these, the organisation can get a better understanding
of the whole picture (Ojanen and Vuola, 2005; Chan et al., 2008). In addition, it is necessary to
understand the need for different measures for different part of the innovation process - as an
innovation project can last for several years, only measuring new products to market can be
misleading (Shapiro, 2006). In similarity with Ojanen and Vuola (2005), Boly (2014) also
identified different operational levels which can be measured: individual, project, portfolio, firm
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and global level. These all represent different subsystems which constitute the total innovation
management ecosystem.
Table 2. Basic dimensions of R&D performance analysis (Ojanen and Tuominen, 2002; EIRMA, 2004.
These categories are then further broken down to smaller measurement areas which can be captured
through specific metrics. They also broaden some of the terms, such as input and output, but also
add new dimensions such as portfolio management, knowledge management and
commercialisation, with the purpose to better capture the innovation capability process rather than
just the relation between input and output (Adams, Bessant and Phelps, 2006). Similarly, Muller,
Välikangas and Merlyn (2005) constructed a framework to help organisations adopt a holistic and
business-oriented perspective of their innovation process. They divided the metrics into a matrix
of three subgroups, inputs, processes and outputs, together with the three dominant views within
innovation measurement: the resource-based view, the dynamic capabilities-based view and the
leadership view (Muller, Välikangas and Merlyn, 2005).
2.6.5 Frameworks for Measuring Innovation Capability
There are, as mention, many different frameworks and methods for measuring innovation.
However, up until a few years ago there were few frameworks that have been designed to measure
innovation capability specifically (Boly et al., 2014). In this following section, three measurement
frameworks have been presented more thoroughly to present more detailed features and
characteristics of innovation capability measurement framework. The frameworks were selected
based on their compatibility with the study and the case company.
Framework A
Given that, the framework presented by Boly et al. (2014) measures innovation capability and is
built on the dimensions: innovation process, the practices and the results - which are categorised
as input, activity and output. The framework incorporates innovation capability as part of the
innovation process evaluation, which breaks down to 15 innovation capabilities practices which
can be evaluated, see Figure 10. The model focuses on a firm’s dynamic capabilities and absorptive
capacity to evaluate a firm’s innovation capability.
Through evaluating these 15 innovation management practices firms are classified on a scale
consisting of four classifications (Proactive, Preactive, Reactive and Passive). The results obtained
from using the measurement provide an analysis of a firm’s innovation process and it can help a
firm identify internal bottlenecks (Boly et al., 2014).
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Figure 10. The 15 innovation capabilities practices presented by Boly et at. (2014, p 613).
Framework B
Another framework that measures innovation capability is presented by Saunila and Ukko (2012).
They found five perspectives (financial, customer, processes, personnel, and innovation
performance) that visualise how innovation capability and business performance is connected
(Saunila and Ukko, 2012). They claim that innovation capability cannot be measured directly but
needs to be translated into metrics which represent the innovation capability. As mentioned in
section 3.2.2, Saunila and Ukko (2012) has made the division of innovation capability into
innovation potential, innovation processes and the results of the innovation activities. These are
illustrated in Figure 11.
Figure 11. The basics of innovation capability measurement (Saunila and Ukko, 2012, pp. 364).
This is then incorporated into a framework for measuring innovation capability in relation to
innovation performance and business performance, as it established a link between these three
areas. They have identified four areas of innovation performance, see Figure 12. The idea is that
the firm can measure the three areas of innovation capability through these perspectives. For
example, innovation capability potential is linked to personnel and processes, the innovation
capability process is linked to customers and financials, and the innovation results are linked to all
34
the aspects. The specific metrics and objectives are firm specific, but this gives an overall structure
on how to measure the different aspects of innovation capability. (Saunila and Ukko, 2012).
Figure 12. The framework for measuring innovation capability (Saunila and Ukko, 2012, pp. 366).
Framework C
Framework C presented by Björk and Frishammar (2019), is called “Innovationsstark” which is a
framework that categories metrics into three point of measurements: input, activities and outputs,
see Figure 13. The ’input’ consider the existing resources in terms of personnel, time and money,
but also qualitative factors such as organizational culture as well as employee motivation. The
‘input’ category is a tool to measure a firm’s innovation potential and is a future oriented
measurement. The ‘activities’ category is a real-time measurement, which is an analysis of the
firm’s present performance, and assist to direct or change ongoing activities as well as processes.
The measurements may be useful for a firm’s decision making. The ’output’ category provides
information regarding the generated results in the aspect of both qualitative and quantitative terms
but also created value (for customers, stakeholders and society). In the original measurement
framework, the three categories (inputs, activities and outputs) have four sub-categories: Portfolio,
Process, Project and Culture. (Björk and Frishammar, 2019).
The innovation portfolio provides a holistic perspective of a firm’s innovation projects they can be
categorised according to what markets they target, what product segment they belong to or what
technology it is built upon. The dimension of the innovation portfolio within the measurement
framework exists to give insights to how the portfolio should be balanced, and resources should be
allocated. Additionally, it can evaluate whether the projects are analysed in terms of risk level, size
of projects and innovation type among other things. The innovation process dimension evaluates
the innovation activities of a firm and might provide insights on efficiency, productivity, time
management and performance among other things. The insights should be compared to existing
goals and needs and continuously followed up on. Innovation projects are included in the
framework since innovations typically are created through projects and they, therefore, also need
to be evaluated. The measurements of a firm’s innovation projects are many times dependent on
the size of the firm and what market it targets. Finally, the culture dimension is only considered to
be an ‘input factor’ (and not an activity or output), since it created the preconditions for the
35
portfolios, processes and projects. Culture’s exact impact on innovation capability is still quite
ambiguous which is why it is also considered a novelty in the framework. (Björk and Frishammar,
2019)
Figure 13. The framework for innovation capability created by Björk and Frishammar (2019, pp. 74-75).
In this framework, both internal and external factors are taken into account. The internal activities
and performance are considered but also externalities in terms of customer relationships. It further
emphasises on the importance on following up continuously on the measurements to see the
progress. Finally, the framework is designed to be generic, which means that it can be adapted for
any firm. Since every firm’s strategies and goals differs, the measurements need be adapted to the
specific firm’s need. Therefore, the specific metrics should be chosen with the input of the firm
which are to be evaluated. (Björk and Frishammar, 2019.)
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3. Method Here, the methods for the study is presented and discussed. The research approach is presented,
followed by the research process and the data collection. The purpose is to provide a transparent
overview of how the study has been conducted. Lastly, the research quality and ethical
considerations of the study are discussed.
3.1 Research Approach
The aim is to explore how innovation measurement can be applied to evaluate and improve
innovation capability in a certain context (an incumbent telecom firm), and the analysis will be
made at an organisational and industrial level. Given the characteristics of the problem, the study
is centred around probing, investigating and understanding a qualitative problem, and the thesis is
based on two, open-ended research questions of explorative nature (Creswell, 2014). The study is
based on a pragmatic philosophy, which is based on the idea that it is possible, and often beneficial,
to not adopt one single perspective rather than to use and combine different perspectives (Saunders
et al., 2009). This goes well in line with the exploratory studies as they often require a flexible and
iterative approach throughout the process (Saunders et al., 2009).
Figure 14. Systematic Combining (Dubois and Gadde, 2002, pp. 555).
Further, the study has been conducted through an abductive research approach, which can be
described as a combination of the inductive and deductive approach, with an emphasis on the
inductive logic (Dubois and Gadde, 2002). According to Dubois and Gadde (2002) the overarching
goal with conducting research is to align theory with the empirical world, something that is
naturally incorporated in the systematic combination of theory, framework, case studies and the
empirical world, see Figure 14. Through systematically combining theory and empiricism in a
nonlinear process, theory and reality can be matched effectively throughout the process (Dubois
and Gadde, 2002).
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3.2 Research Process
The overall research process has followed the steps in Figure 15. The overall process was abductive
and used a systematic combination of literature and empirical data to build a solid understanding
of the research problem. In this section, the process of selecting the research area and formulating
the research question will be discussed, followed by the next steps in the process in section 3.3.
Figure 15. The research process and outline of the thesis.
Selecting the Research Area
The research area was chosen based on both personal interests, within the innovation research field,
and a request from Company X, who wanted to develop an innovation measurement system and a
method to monitor and evaluate their strengths and weaknesses regarding their innovation
activities. Thereafter, existing literature was examined to understand what had previously been
written within the area (Creswell, 2014), both from academics and practitioners. Weaknesses in
existing literature was identified as well as areas that had not yet been explored, which provided
insights to what this study could contribute with (Blomkvist and Hallin, 2015). Moreover, personal
strengths and previous experiences were also taken into consideration in the process of selecting a
38
suitable research area. The research area was also discussed with supervisors at KTH, as well as at
Company X, to generate new ideas and align the aim for the project. Hence, both rational and
creative thinking was used to select the research areas - and combining those two is argued to often
generate an interesting and value adding research area (Saunders et al., 2009).
Formulating Research Aim and Research Questions
This paper’s aim and research questions were generated in an iterative process which was not
finalised until the end of the project. The initial research questions were broader and more general,
since the answers which the result would provide were still unknown (Saunders et al., 2009). A
narrower research questions were constructed through reading literature and conducting interviews
at Company X, as well as with other industry experts. Due to the ambiguous nature of innovation,
and measurements of innovation (Adams et al., 2006), the iterative process of defining the research
questions is considered suitable to produce the final research questions (Blomkvist and Hallin,
2015).
To attain a relevant problematization, research questions and aim, the system perspective’s three
levels were taken into consideration (Blomkvist and Hallin, 2015). Hence, it was important that the
research scope covers the individual perspective, functional perspective and industrial perspective
(Blomkvist and Hallin, 2015). As a result, this paper will provide value both for co-workers as well
as the board at Company X but can also be generalizable enough to provide value for other
researchers and the telecom industry (Blomkvist and Hallin, 2015).
3.3 Data Collection
Data was collected through a literature review, interviews and a workshop, using a qualitative
method. The qualitative data collection method has some specific characteristics, which are typical
for qualitative studies. The first one is that the data is collected in a natural setting - the participants
in the research are studied in a specific context in which the problem is investigated (Creswell,
2014). The second one is that the researchers themselves are functioning as a key instrument in the
data collection process (Creswell, 2014). Lastly, the research has an emergent design, which means
that the process and the approach is emerging throughout the study (Creswell, 2014). When a study
is explorative and aims to investigate a complex problem in a dynamic environment, it is beneficial
to hold an emergent approach as the researchers learn more about the issue and take new
information in consideration along the way (Creswell, 2014). This was perceived as the most
natural and accurate way to approach the research, given the exploratory nature of the problem and
the wide, open-ended research question.
3.3.1 Literature Review
The main purpose with the literature review is to provide a deep understanding of the research areas
which are relevant to answer the research question (Saunders, 2009). An initial literature review
was conducted while forming the research problem - to facilitate an understanding of the area and
the existing body of knowledge. Once the problem formulation and the research question had
started to be defined, a more rigorous, critical review was conducted to investigate the most relevant
theories and frameworks within the field. The literature review included mainly primary literature,
but also secondary literature in form of reviews and summaries of certain theoretical fields. As the
39
research problem is situated in an industry specific context, primary, non-academic papers, such as
white papers and company reports, was included to understand the industry dynamics and trends.
The primary academic papers were collected from the following databases: IEEE Explore, JSTOR,
SAGE Research Methods Online, SpringerLink, ScienceDirect, Taylor & Francis Online, Web of
Science and Wiley Online Library.
One main purpose of the literature review was to identify the most relevant frameworks to measure
innovation capability. Due to the perishable nature of innovation as the theoretical area, the
frameworks included where not older than 10 years. To ensure that the most relevant literature and
frameworks was covered, continuous conversations with knowledgeable researchers and
supervisors was held. We also matched our framework selection towards summaries and overviews
from published reviews and journals.
3.3.2 Case Study
Several researchers have concluded that a case study can add context and empirical evidence to
theoretical frameworks. Case studies are regarded as an appropriate choice for studies that are
aiming to answer how and why questions, with a focus on a contemporary research area, in a setting
where the researchers cannot control behavioral events (Yin, 1994, pp 5-6). A case study allows
the researchers to collect large amounts of empirical data which can help to create a deeper
understanding of the problem (Yin, 1994, pp.8-9; Blomkvist and Hallin, 2015, pp.63-66). In
addition, a case study provides an opportunity to develop theory through integrating and
incorporating empirical data and insights into the theoretical field (Dubois and Gadde, 2002). Due
to the nature and aim of this study, a case study was considered a suitable choice as it will serve
the purpose of the study in the most appropriate way.
3.3.3 Workshop
One part of the initial empirical data collection was arranging a workshop with the members of the
group who are organising the innovation department on group level. The workshop was like a focus
group, which is a form of qualitative data collection method, where the researchers arrange a group
interview (Creswell, 2014). The workshop was arranged as a group interview face to face. The aim
was to discuss the current situation, obstacles in the innovation process and their perception of the
current innovation capability. This was done through a discussion based on the dimensions of the
chosen measurement framework for innovation capability. The topics and questions covered can
be found in Appendix X. The workshop was part of aligning the theoretical findings with the reality
and to ensure that theory matched the context. The workshop also provided a deeper understanding
of the problems and dynamics of the organisation, which could be translated to valuable insights
for the research project.
3.3.4 Interviews
During this research project, 19 interviews have been conducted, excluding the informal interviews
conducted at the initial stage. All interviews followed a non-standardised and semi-structured
strategy. They were all held electronically due to the outbreak of Covid-19, through internet
platforms such as Teams, Google Hangout and Zoom. The semi-structured way of leading the
interviews allowed a flexible and adaptable approach to the data collection and was considered
appropriate due to the exploratory characteristics of the study (Saunders et al., 2009, pp. 323).
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Table 3. Interview themes.
Introduction Introduction of the project
Introduction of the interviewee
Connection to innovation
Future Current trends within the telecom industry
Main challenges for Company X to face the changes within the industry
The competitive landscape and main competitors
Innovation process Description of the innovation process
Strength, weaknesses and obstacles related to the process
Current objectives and evaluation methods
Strategy Description of the innovation strategy, on team and organisation level
Visions, objectives and time horizons connected to the strategy
Level of alignment with strategy
Evaluation of alignment with strategy
Communication Perception of the brand amongst B2B customers
Challenges around strengthening the brand and communicating externally
Numbers and statistics that could facilitate the communication
The interview sample was based on an extensive mapping of the organisation, to identify the most
relevant individuals. The full sample can be found in Appendix II. The goal was to interview the
managers of each innovation team, to get insight into their operational work. Some higher-level
managers with close insight into the innovation strategy was also interviewed to get an
organisation-wide perspective. The so called “innovation ambassadors” in the organisation, who
are acting as representatives for the central innovation management team were also interviewed.
Lastly, two industry experts were interviewed to get an industry-level perspective, and to match
our findings from the internal interviews with an external perspective. The topics covered in the
interviews can be found in Table 3. As previously mentioned, semi-structured interviews allow
some flexibility in the topics, and not all topics were covered with all interviewees, depending on
the role and perspective of the interview. The interviews were scheduled for 60 minutes but there
were some slight variations (between 45 minutes to 75 minutes).
3.4 Data Analysis
The literature study was used to compile and identify existing key success factors (KSF) for
innovation capability and service innovation. It was further used to identify existing measurement
frameworks and, in combination with the gathered information during the informal interview,
41
suitable criteria for the framework could be identified. Thereafter, the most suitable framework
was selected, based on the identified criteria. Since the workshop was centred around the chosen
framework, through analysing the information gathered from the workshops, in combination with
the informal interviews, the themes for the interviews was selected.
After conducting the interviews, all interviews were transcribed and then coded. Coding is an
important data reduction technique, which helps the researchers to explore, analyse and interpret
the data (Cope, 2010). Through packaging and categorising the data, the chaotic and unstructured
raw data can be organised so that it can be used to compare and evaluate the collected data (Cope,
2010). The coding themes were based on the interview topics (presented in Table 4), and certain
underlying categories were identified within each topic, but also subjects that frequently emerged
such as ‘Measurement’, ‘Organisation and Culture’ and ‘Portfolio’. Developing the codes and
interpreting the results are an iterative process, which needs to be evolving through reading, coding,
reflection and writing (Flick, 2014). Overall, the data analysis is an iterative process, where
findings from the data collection is compared to the theoretical findings and processed continuously
(Saunders et al., 2009).
The empirical findings are presented in section 5.2 and due to the delimitation of this study, most
of the information regarding culture was excluded from the result section. After the interviews were
coded, the content was categorised, once again to identify generalisable themes and suitable metrics
for Company X, presented in Section 5.3. The data analysis method of first coding, analysing and
categorising in several steps is a recognised abductive approach when analysing data according to
methodology literature (Creswell, 2014). Thereafter, the result was compared to insights gathered
in lite literature review and presented in the discussion. The generalisable themes was, further,
acknowledged as this paper identified six KSF for innovation capability for incumbent telecom
firms.
3.5 Research Quality
Here, the reliability, validity and generalizability will be discussed, as they are the main aspects of
research quality (Saunders et al., 2009). Qualitative data collection methods, including interviews,
has limited reliability meaning that it might not be possible to replicate the procedure and get the
exact same results (Saunders et al. 2009). This is both the strength and the weakness with
qualitative, explorative research - it allows the researchers to explore a complex phenomenon in a
natural setting, but is also means that the results only mirror the reality at that specific time, and
there is no guarantee that the reality reflect an absolute truth (Saunders et al., 2009). However,
there is certain things researchers can consider increasing the reliability of the results as much as
possible. Creswell (2014) suggests that the process should be documented thoroughly, and that
communication between the researchers in the team is essential to ensure that the definitions are
consistent throughout the process. In this project, transcripts and were codes cross-checked, to
avoid mistakes and misconceptions.
Validity relates more to the accuracy of the findings, and how credible the results are (Creswell,
2014). The validity is affected by many different factors, such as how well the researchers manage
to access and interpret the interviewees knowledge, and bias from both the researchers and the
interviewees (Saunders et al., 2009). As the researchers are a key instrument in the data collection,
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they also carry a heavier responsibility in not affecting the results through biases (Creswell, 2014).
There is also an inherent level of subjectivity in the interviewees, and they can only express their
opinions and perceptions from their viewpoint. Hence, the results do not offer a definite truth,
rather than reflecting that person's understanding of the situation. However, there are methods to
improve the validity. Triangulation means that several independent sources has been used to
strengthen the findings (Creswell, 2014). This has been done both in terms of finding patterns and
similarities (as well as identifying paradoxes and dissimilarities) between interviewees, as well as
comparing the findings with literature and other documents and statistics. One example of this is
when the interviewees described the financial situation at the company, this was also checked in
public documents such as annual reviews and industry publications.
Last, the generalisability is an important part of conducting research, as it allows others to draw
upon the conclusions made in the study (Blomkvist and Hallin, 2015). Generalisability is also
called external validity, as it represents to which extent the findings are generalisable to the external
world (Saunders et al., 2009). Generally, qualitative studies, based on semi-structured interviews,
have a limited generalisability when it comes to statistical data since the data sample is too small.
It can, however, be useful for drawing qualitative conclusions about a phenomenon in a specific
context. This study investigates measuring innovation in relation to innovation capability at
incumbent firms within the telecom industry. Within the described context, the findings from this
study can be generalised, and given the correlations between theory and empirical data strengthen
this.
3.6 Ethical Considerations
The researchers have aimed to act in the accordance to ‘The European Code of Conduct for
Research Integrity’ (The All European Academies, 2017) which is founded on four principles of
ethics; reliability, honesty, respect and accountability. Through acting according to these four
principles, the study was conducted with an awareness about common ethical issues, resulting in
an increased credibility and authenticity for the study (Creswell, 2014).
During the selection of research area, it was imperative to identify a problem formulation which
provided insights to other researchers and practitioners, and not something only relevant for the
case company or the researchers (Creswell, 2014). Thus, through an extensive literature review,
relevant research areas were identified, where gaps and conflicting research fields also was
identified to ensure that the study could contribute to the existing body of knowledge.
When working with research participants (in this case the workshop group and interview
respondents) it was important to inform the participants about the purpose for the study (Saunders
et al., 2009). Therefore, in each interview, a short background as well as the purpose of the study
was presented. To further hinder the chance of the participants feeling deceived (Creswell, 2014),
all participants, internal as external, was informed that this project was conducted as a collaboration
with Company X, and that the researchers were master students at the Royal Institute of
Technology. Furthermore, all interviews were recorded, for the exclusive use of the researchers,
which was granted by all participants. To increase the transparency, the request about the interview
recording was made after the purpose of the study had been explained.
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Throughout the data collection and analysis, it was crucial to consider and protect the participants’
identity (Creswell, 2014). No raw data has, therefore, been shared to anyone apart from the
researchers (Saunders et al., 2009). Additionally, all interviewees were promised to remain
anonymous, each interviewee is therefore identified by an interview code, where their roles and
role descriptions have been further generalised for the participants to maintain anonymous. Further,
confidentiality was prioritised, since the research was conducted in collaboration with a firm
(Creswell, 2014). To ensure confidentiality, the researchers have signed an NDA to Company X,
and two employees at Company X have controlled that no confidential information have been
included in this paper. There are risks with promising confidentiality since it can constrain the
research (Creswell, 2014). Nevertheless, since the research aim was to identify industry wide
issues, sensitive business information was deemed as less relevant to include in the study.
Finally, to prevent a subjective presentation of the collected data, the ambition has been to present
the result with as unbiased language as possible and not include any personal reflections among
the empirical findings. However, none of the participants were native English speakers, thus the
presented findings might have been interpreted inaccurately, due to language barriers.
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4. Industry Background In this chapter, a brief introduction to the industry is presented. The purpose is to offer a
comprehensive background to the research context. Further is the case company introduced, to
provide an understanding of the case company’s position, and give some contextual details
associated with the research project. Due to confidential reasons, the company is not presented
with full name.
4.1 The Telecom Industry
The telecommunication industry has revolutionised how people communicate since the 1830’s and
has continuously expanded with inventions of new technologies such as the telephone, computer
and other mobile devices (Beers, 2019). Telecommunication enables remote communication
through phones and the internet with different technologies such as radio waves or cables (Beers,
2019). Globally, the sector had an estimated revenue of 1195 billion Euros in 2019, and the fastest
growing markets are Asia Pacific, North America and Europe (Statista, 2020). The telecom
industry in Sweden was highly regulated until the 1980’s, when the deregulation was initiated
(Bohlin et al, 2001). The industry was affected by the high level of regulations as well as a strong
vertical integration, meaning that there were a few, dominant actors on the market and little
competition between suppliers (Bohlin et al., 2001).
The Value Chain
The telecommunication industry has been changing at a rapid speed, where technology
development and innovation in combination with a deregulated market has led to changed customer
behaviours and new actors challenging existing players in the ecosystem (Beers, 2019). Some of
the main actors in the ecosystem are presented in Figure 16.
Figure 16. The key actors in the telecommunications value chain (adapted from Snir, 2011).
The equipment manufacturers manufacture and supplies the hardware and platforms to the
operators, who normally do not develop or manufacture any hardware. The operators enable the
telecommunication through the infrastructure and deliver connectivity. On top of the connectivity,
content and services can be delivered to the end users (often references to as On The Top, OTT),
who can be both private and business customers. An illustration of how this ecosystem works can
be found in Figure 17. The telecom industry is one of the industries that are most affected by the
ongoing digitalisation (EY, 2015; PwC, 2019). Given the disruptions in the industry, the traditional
telecommunication value chain has been transformed and extended due to the technical
development and changing customer behaviours (EY, 2015; Grineisen and Rehme, 2018).
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There has been a steady increase in OTT services, meanwhile the services have become
increasingly complex and integrated with digital ecosystem to a higher extent than before
(Grineisen and Rehme, 2018). Operators still have the largest part of the total revenue (55%),
however, the OTT players have gained 10% of the total revenue in just a few years - and their share
of the revenue is increasing (EY, 2015). Given that the traditional connectivity business has
stagnated in volume during the past 5 years (Almega, 2018), and are exposed to a very high level
of competition and price pressure, the many traditional telecom companies are worried about their
future position in the ecosystem (PwC, 2019). Telcos are competing more directly against both
software companies and OTT actors, which often operate with speed, agility and flexibility,
something that are challenging for the traditional telcos to meet (PwC, 2019).
Figure 17. The digital ecosystem based on telecom services (Grineisen and Rehme, 2018, pp. 313).
Grineisen and Rehme (2018) argues that there are two strategic ways that telcos can take. The first
option is the so called “bit pipe” which suggests that telcos place their focus only on connectivity
and try to gain competitive advantage through streamlining their operating and go for cost
leadership. The other option is for telcos to try to move up in the value chain. This could entail
increasing their value proposition by expanding the service portfolio, adding services on top of
their connectivity, as well as finding new ways of partnering with the players in the ecosystem
(Grineisen and Rehme, 2018).
4.2 The Case Company
As part of this thesis, a case study was conducted. The case company is a leading, Swedish telecom
operator. The case company is over 150 years old and has operations in 9 countries, including the
46
Nordic and Baltic region. Each country has its own organisation, with a certain level of autonomy.
There are some differences in the market position that the case company has across the different
regions. The core products are, however, the same: fixed networks, mobile communication,
roaming services and broadband technology. With the background and above-mentioned
challenges, with a commoditization of connectivity and increased competition from different types
of actors, innovation has an increasing role at the case company. To expand upstream in the value
chain is important to have a sustainable value proposition and to avoid being commoditized.
Through offering OTT services, which includes connectivity as part of the service, a larger part of
customer value creation is controlled and captures revenues, and the case company can take a
different role within the ecosystem.
The innovation work has recently gone through a centralisation process, with the aim to centralise
and optimise the innovation work conducted within the organisation. There is an internal incubator
division, which works both with small scale, radical innovation projects, as well as some
established innovation projects, that are under the upscaling process. In addition, there are also
innovation teams in most of the country organisations, working with various innovation projects.
These teams are, after the reorganisation, connected to the global innovation team, which belongs
to the group function, see Figure 18. The case study is done together with the global innovation
team, which is a relatively new group within the company. The team’s mission is to (1) create an
understanding of the different innovation teams and projects that are conducted within the different
country organisations and in the incubator unit, (2) create transparency within the organisation and
(3) through insights, optimise the innovation capability within the group. In this paper, the case
company will be referred to as Company X.
Figure 18. An overview of the innovation teams in the case company.
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5. Empirics In this chapter, the findings from the empirical data are presented. The results are divided into
three parts, in accordance to the process of the research. The first part presents the empirical
findings from the informal interviews, the process of selecting the measurement framework
selection as well as the findings from the workshop. In the second part, findings from the semi-
structured interviews are presented. In the third part, identified key success factors (KSF) are
presented as well as specific metrics presented, based on the framework, the findings from part
two and literature.
5.1 Conceptual design: Framework selection
This section presents the process of selecting a suitable measurement framework which was
achieved through synthesising knowledge gathered from the literature review but also through
conducting informal, unstructured interviews. Criteria for evaluating measurement frameworks
were selected and three chosen frameworks were evaluated to find the one most suitable for
Company X. This was followed by a workshop where more in-depth insights were gathered from
the perspective of the selected framework, in the aim to, further, focus the efforts.
5.1.1 Overall Context and Challenges
During the exploratory interviews, the need for a measurement system to visualise the innovation
work and to understand the current innovation capability was verified. It was also clear that the
company’s core business is highly profitable, however, as the industry is changing at a rapid pace,
there is a considerable level of ambiguity of the future business and positioning. Several of the
interviewees highlighted that the core product today for the telecom companies is undergoing
commoditization and, in some markets, has been exposed to a high level of price pressure. This
makes innovation strategically important to ensure that case company’s future position on the
market and identify new profit streams. Nonetheless, balancing between exploitation and
exploration (ambidexterity) is a common challenge for incumbent firms with a profitable core
business. There is an emphasis on exploiting the core business rather than on building the future
business. This is a common, but potentially problematic approach, given the rapidly transforming
competitive landscape. Therefore, it is not only relevant to measure the current innovation
capability but to also include how prepared Company X is for the future.
Further, all the interviewees consider the company’s size both as an advantage as well as a
challenge. The company can scale processes and offers and has access to resources for investing in
interesting projects. However, the large size of the organisation, in combination with the legacy
Company X has, as an old, incumbent firm, brings an inherent inertia. It is difficult to steer a large,
old company in an agile and transparent way, which is one of the challenges which Company X
faces.
A significant challenge mentioned several times during the informal interviews, is the structure of
the innovation units. Company X has innovation units in several countries and there has been a
lack of a enough overview on what innovation teams are working with and what phases the projects
are in. The aim is to attain a holistic and transparent view on the existing innovation projects and
optimise the resources invested. Through mapping the innovation teams and their projects, it was
48
identified that some teams are working with very similar projects, and that there many suboptimal
processes. This hinder full utilisation of the resources is costly for the organisation and most
probably leads to lower output.
The telecom industry, as many other industries, is becoming increasingly service oriented. Services
are more complex and require a higher level of flexibility, customers have new expectations and
the competitive landscape is also changing. It is harder than ever to predict the future, which is why
a high level of innovation capability and flexibility is more important than ever. When competition
is increasing and challenges every aspect of the business, incumbent firms need to be prepared to
fully utilise their strong position and financial muscles, while at the same time take a new role
within the ecosystem and find new ways of creating value. As a step in the direction of doing so,
understanding and improving innovation capability is crucial, as well as to engage the organisation
internally and communicate effectively with external stakeholders and customers.
5.1.2 Framework selection
As argued in the previous chapter, there are numerous methods to measure innovation capacity.
However, to answer the research questions for this paper, five criteria have been identified which
are presented in Table 4 below. .
Table 4. Criteria for the innovation measurement framework.
I. It should consider both the innovation input, output and the innovation process
II. It should consider both internal and external innovation activities
III. It should consider both the present time but also the future
IV. It should consider be adaptable to a large organisation
V. It should be adaptable to service innovation
Criteria I and II are based on assumed definition of service as well as important aspects of service
innovation and the S-D logic (Vargo and Lusch, 2004; 2008). The literature mentions the
importance of leading (input) and lagging (output) metrics, for a holistic perspective (Davila,
Epstein and Shelton, 2012). The challenge of withholding a holistic perspective of the process and
considering both leading and lagging metrics to include both present time and the future was
mentioned during the informal interviews and led to criteria III. Finally, criteria IV and V are based
on the characteristics of the case company, a large incumbent firm providing high-tech service.
Through a broad initial selection, covered in Chapter 3.3, innovation capability measurement
metrics and frameworks were screened (e. g. Adams, Bessant and Phelps, 2006; Saunila and Ukko,
2012; Boly, 2014). Finally, three frameworks (Framework A, B and C) were evaluated according
to the five criteria that are presented in Table 5. Framework C was the only framework that fulfilled
all criteria and therefore was considered most suitable.
Table 5. Criteria for selecting measurement frameworks.
Framework Authors Criteria I Criteria II Criteria III Criteria IV Criteria V
49
A Boly et al., 2004 Yes Yes Yes Yes No
B Saunila and Ukko,
2012
Yes Yes No Yes Yes
C Björk and
Frishammar, 2019
Yes Yes Yes Yes Yes
However, the measurement framework was altered for this project. Culture will not be considered
since the dimensions of portfolio, process and project was considered a higher priority to
investigate initially. The adjusted innovation capability measurement framework that will be used
is illustrated in Figure 19.
Figure 19. An illustration of the adapted framework made by Björk and Frishammar (2019, pp. 74-75).
5.1.3 Workshop
The workshop focused on the three dimensions of the chosen framework; portfolio, process and
project. The aim for the workshop was to align expectations of the innovation measurement
initiative and to gather important insights from the group members. They have deep insight into
both the organisation as well as objectives of the innovation activities. The group was divided into
two smaller groups to discuss questions related different dimensions. The questions discussed
during the workshop can be found in Appendix I and the following section is a compilation of what
was discussed and concluded.
Portfolio
Company X is in the initial stage of building an innovation portfolio, as a part of a larger initiative
to map and organise innovation work within the organisation. This means that information
50
regarding existing innovation projects is currently being collected from different units. The
organisation is aware about the need of having a structured portfolio to achieve transparency and
to utilise resources more efficiently.
Meanwhile, the selection process of innovation projects is currently highly affected by historical
status quo and a line organisation perspective. Innovation by nature means to do something new
and, thus, entails a higher risk than incremental product development projects. However, this is a
challenging act of balance, as incumbent organisation often has demanding financial goals to
deliver upon, and which often compromise the financial and organisational attention given to
innovation.
There is a shared understanding of the importance of having a central decision process, so that
projects are evaluated and selected through an objective process. In addition, there should be a clear
level of ambition regarding innovation funding and a clearly determined risk balance on a strategic
level. The workshop group believed that by having a few prioritised goals focused on innovation,
the portfolio could support a balance between short-term goals and long-term performance of
Company X.
Process
Due to the ongoing portfolio work, the innovation process is starting to become visible - however,
insights are still rather limited. There are some units within Company X that have requirements on
project speed and clear requirements for passing different stages of the innovation projects.
An issue that was brought up during the workshop was the challenge of scaling up innovation
projects. It is usually quite easy to get funding for small projects which only require small
investments for Company X. However, when innovation projects need larger investments, more
decision makers need to be involved and projects usually halts. Ambiguous requirements for being
granted an investment also enables a more subjective evaluation process and since it is not always
clear what information is needed to get a decision, many meetings end up without any decision at
all.
Another obstacle is the difficulty to convince decision makers to make decisions regarding
investment under uncertainty. While innovation have a large impact on companies and often have
a big potential, projects are, by nature, surrounded by uncertainties and hypotheses. Therefore, it
could be beneficial to have access to more data to support both specific projects, as well as prove
historical record of accomplishment of innovation capability, to gain trust and confidence.
Project
Innovation projects were regarded as quite well functioning and smooth in the different project
phases. The participants in the workshop considered that the challenges primarily emerge between
the project phases, when decisions are needed from a higher organisational level. This results in
projects often being paused and sometimes kept alive unnecessarily long and which is a cost for
Company X in terms of human and financial resources. It does not exist a specific innovation
budget today so to get funding for an innovation project, you need to request money from other
51
units’ budgets which sometimes is a challenge, the resources exist but there is no incentive to
allocate the resources.
According to the workshop group, almost all innovation projects are customer driven with
continuous feedback from the customers with a few exceptions. A recurrent issue for innovation
projects is that it is often hard to find a receiver and a seller for the new product or service, when
it is time to take the innovation to the market. The sales unit is interested in having maximum
revenue and it is, therefore, challenging for the people working with innovations to convince the
account managers to sell products that are not guaranteed to be profitable immediately. This is also
a factor which hinders the scale up process of the innovation project.
5.2 Case study: Exploring the innovation capability
This section aims to examine what the KSF for the case company are around building innovation
capability, which will answer RQ1 and feed into RQ2 and help us determine how innovation
measurement can be used to improve innovation capability. In this section, the main findings from
the interviews are presented, categorised into six subcategories. These categories basically follow
the themes from the interviews; however, some categories have been added as they emerged
throughout the data analysis. The selected metrics will later be presented and visualised as part of
the resulting framework.
Table 6. The topics covered in the interviews.
Topic Purpose
Future The future of the industry, the technical development and the trends are closely
connected to the strategy and to orient the innovation efforts in an adequate way.
Strategy The strategy of the company is the point of departure creating a measurement
instrument as the metrics should support the strategy.
Process To understand the variation in outcome of the innovation projects, it is necessary to
understand the processes and the obstacles within the processes.
Portfolio Portfolio management is an important part of managing the innovation of a
multinational company and is one of the dimensions of the framework.
Measurement The current way of measuring innovation gives insight about current practices and an
indication of what data is available.
Communication Part of the innovation measurement objectives is to improve the internal and external
communication.
The topics covered in the interviews are presented in Table 6. These topics were identified through
compiling the findings from the informal interviews, the workshop and from theory. The purpose
of the interviews was to get a deeper understanding of the challenges around strategy, processes
and purpose of the innovation work as well as obstacles within the teams. The obtained insights
were crucial for specifying the metrics for evaluation of innovation capability.
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5.2.1 Circumstances in Business Environment
The telecom industry has traditionally been (and is still) very profitable, telco companies’ core
product has profit margins that few other industries can compete with. However, while this is great
for business, it is also problematic, in several ways. First, this is not going to last forever. Several
interviewees, [I-02; I-14; I-15; E-02] mention that the core business, overall on an industry level,
is shrinking every year and the growth rates are expected to stagnate further. Even if it not a drastic
decrease yet, it is still something telco businesses need to plan for. During the interviews it was
consistently mentioned that not accounting for this is a huge risk for Company X. Further, the
traditional telco industry is saturated and is in the end of the technological life cycle, where there
are many new technologies and solutions with the potential to replace the established technology.
Several of the interviewees, [I-02; I-14; I-15; E-01; E-02], mentioned that not many new areas can
offer similar returns. But the overall decline risk makes looking at historical data a risk of putting
unrealistic expectations on the return on new investments in core business. As a result, investors
and decision makers might make inadequate assumptions.
As a result of the maturity level of the industry and the ongoing digitalisation, connectivity is
starting to become a utility, like electricity and water. The commoditization process is highly
recognised amongst the interviewees and is a big threat for the future of the industry.
“I don’t want to say learn from the mistakes but learn from the market dynamics that
we saw in other markets. We are all the time running the risk of entering something
that will commoditize our services. When we conduct interviews with our customers, a
lot of people already talk about us in the same way they talk about their electricity
providers, we are infrastructure providers and there is an intense battle on prices when
it comes to electricity. So, I would say that the biggest challenge is for us to not be
commoditized, so that our core products are still perceived as valuable.” - [I-12, 2020]
However, services delivered on top of connectivity are becoming more complex and integrated into
other ecosystems. This entails an increased emphasis on value added services, content, partnerships
and co-creation, and this is reshaping how operators are positioned and where in the value chain
they can participate. As the lines within the ecosystem as blurred, operators are figuring out what
role they can take. The same company can be both customer and partner, and this offer both great
opportunities as well as major, new challenges.
In addition, as a natural extension of this phenomena, the telco ecosystem is becoming increasingly
customer-centric on both B2B and B2C. Customer expectations are changing, and the customer
journey is more central than ever. One of the industry experts highlighted the growing customer
orientation and how it can be challenging for incumbent firms to handle the shift.
“One of the biggest challenges for many operators is to understand the shift, that it is
the customers that are in charge. It is the customer needs, interest and reality that set
the rules, rather than what the telecom operators often origin from - owning the
networks, dictating the offerings and services. Offering services and products from a
set list and say ‘Buy what you need but we will not do any alterations” - that type of
attitude need to change” - [E-01, 2020]
53
This was also mentioned by several of the internal respondents, [I-03; I-09; I-14], who had observed
smaller actors winning large orders from incumbent firms simply because they offer a better
customer experience and higher flexibility. As the services are becoming more software based and
digital, customers expect the same simplicity and flexibility from telcos as they get from ICT
companies (e. g. Google, Microsoft).
5.2.2 Strategy
Company X’s overall strategy is constituted on group level, and all units within the group should
be aligned with this strategy. The strategy is translated into team- or country-specific strategies,
where it can be moderately adapted to Company X’s position on the market in each country.
”The strategic focus is in protecting the core business, mostly. So, we are looking for
ways how to protect the basic everyday business that we do, how to enhance that, how
to leverage the assets what we acquired for running the major businesses.” - [I-08,
2020]
Apart from country units, there is a unit that is not directly linked to a specific market, who holds
an overall perspective and handles global operations. Their strategy is as well aligned with the
overall strategy but are later also translated to each teams’ role. However, a specific innovation
strategy is not as clearly defined.
The operating model is centred around the global organisation, which has a holistic perspective of
each country’s work. In the previous model, the countries were more autonomous, and this
centralised innovation model has created some friction within the company. Some argue that the
centralised innovation model creates a gap between the company and the country specific market
- since offers may be less adjusted for a specific market. Meanwhile, others argue that it is essential
that the company is managed and governed from a holistic perspective to ensure that all countries
provides the same experience to customers. Nonetheless, there is an awareness among most
respondents that it is hard to find a perfect balance. At Company X today, innovation occurs
currently both on a centralised level but also in each country. Regarding this, one respondent stated:
“As long as there exists a control and an awareness regarding what’s happening, so
we don’t launch two identical products under different names – nobody benefits from
that. But in general, I believe that it’s good that development and innovation occurs in
different places” - [I-06, 2020]
The need for a connection to local markets is further mentioned as relevant for Company X since
there could be a connection between global and local actors [I-02; I-05]. Regardless of where
innovation occurs, there seems to be a consensus about the need to improve transparency of
innovation activities.
Focus Areas
Company X has different focus areas indicating business segments that are targeted in its strategy
to improve core business. Most innovation projects are developed within these focus areas, apart
54
from the firm’s incubator in which new focus areas are tested and developed. However, it is still
essential that new focus areas are aligned with core business and strategy.
Another factor which greatly reflects the strategic direction of Company X is project size – all
projects need to be scalable. Several respondents, [I-02; I-03; I-05], mention that innovation
projects need to have the potential to reach a revenue at least 1% of the total revenue to be worth
pursuing. This further limit the scope for innovation projects that are considered interesting for the
company, and projects that are not related to the core business should not be driven.
Sustainable Development
Sustainable development is a highly prioritised area within Company X’s strategy where they have
ambitious goals for the entire organisation. Sustainability is further mentioned as a focus area for
innovation and is something that Company X encourage employees to be engaged in [I-04; I-17].
The size of Company X is viewed as something positive when it comes to the sustainability work
where one respondent mentioned:
“That is one of the best aspects of being part of a large organisation, that we actually
can make a difference. By changing how we work in regards to sustainable
development, we can make a real impact on the society.“ - [I-17, 2020]
Company X also have an ambition to improve public welfare through their business, [I-03], and
sustainable development in all three dimensions; social, economic and environmental is a crucial
part of that.
The Role of the Operator
Changing business environment and ambiguity about the future for telco actors have resulted in
many opinions regarding what role they should take in the future. A common opinion is that
Company X should focus on protecting their core business and develop products and services close
to the core. They should, further, be excellent on delivering network services. The importance of
core products is consensual among the respondents. However, some argue that this strategy might
be myopic, that Company X is holding on too tight to the core product and needs to be bolder in
the innovation work. Many ideas for radical innovation projects are not attempted for this reason,
and there is a low chance that such an innovation project would survive all decision phases.
“The interesting part of what we do in Company X is that, how do we innovate, close
enough to the core and still far away from the core enough to bridge new areas and
new revenues. I think that has been the main issue of everything that I’ve been working
with, within Company X and innovation is that: So much is interesting when you look
at technology and opportunities, but some of it is very difficult to connect to the core
and what we are doing.” - [I-15, 2020]
Others argues that the role of the operator will completely change. They believe that the
commoditization of connectivity services will force Company X to find new ways of creating
value. This could be done through taking a more consultative role, delivering more OTT services
and develop strong partnerships with other companies. It is mentioned that Company X have the
55
assets and skills to help other companies to evolve in their journey to become more autonomous
and digitalised. Therefore, they have the possibility to act as a strong and knowledgeable partner
rather than just a supplier of connectivity. In discussions with experts within the telecom-industry
[E-01], the orchestrating role is mentioned as a likely scenario for telco companies. This is also a
known possibility within Company X, where they are focusing more on customer-driven
innovations as well as performing consultative work for their customers as part of the sales process.
It is a method to create a stronger relationship with customers and build a stronger brand.
5.2.3 Portfolio Management
The portfolio initiative originates from an insufficient structure of different innovation projects in
different organisations and units. There are both groups and individuals who work with innovation
initiatives in silos and not within the management of the innovation governance, which is why it is
essential to have a portfolio perspective. The company has started to collect data on each unit’s
most promising, with the aim to increase transparency. The aim is for Company X to become more
efficient, do smarter investments and reduce costs. The portfolio as an organisational unit is
regarded as a positive initiative by most respondents, however, there is also an awareness that this
will also shed light on actual results and strategic relevance.
Evaluating the Portfolio and Risk Management
A structured selection process, where the innovation projects are evaluated in relation the
innovation strategy and the portfolio balance, does not yet exist. It was suggested during the
interviews that the core products and the adjacent products should be separated since they need to
be approached differently. One interviewee stated:
“We are very good at managing our core products. I think we should just continue as
we do, when it comes to every service that is correlated to our core product or
incremental improvements of our core products.” - [I-14, 2020]
There was an understanding among the respondents that Company X could become better at
spreading the risk among the innovation projects, with both high and low risk projects. One
respondent said:
“I believe that we can become better at saying ‘Now we have these high risk projects,
in order to manage them in a proficient way we should have x amount of low risk
projects’ in order to obtain a more even distribution” - [I-09, 2020]
Most interviewees consider most innovation projects at Company X to be fairly low risk. It is easier
to propose a low risk innovation project since high risk projects tend to be denied investments or
halt due to pending decisions. Within the established focus areas, there can be room for higher risk
projects, but they are always very calculated. One interviewee stated:
“We tend to think first safety of existing business instead of disrupting anything. It’s
the nature of operative business it’s to maintain the machine that gives quite a good
dividend, so there is a good reason to do that” - [I-08, 2020]
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Another interviewee commented:
“I mean they are businesspeople, they’re thinking about risks, investments and costs,
about complexity. Obviously in such an operation where we are measured by our result
day by day, low risk is easier and low investment are easier” - [I-09, 2020]
Since many decisions are made on case-by-case basis, and without a systematic way to innovate,
it is hard to create a holistic risk strategy and risk management.
5.3.4 Measurement
Overall, there is no established method for measuring and evaluating innovation on an
organisational level. Some teams have some metrics for their innovation processes, but the
measuring process is scattered and, in some teams, non-existing. However, there is a mutual
understanding of the value and need to establish an efficient and consistent measurement model to
evaluate the innovation capability across the organisation. It is also recognised as an important part
of managing innovation.
“For any organisation and business, the KPIs that are used also have support the new
business, otherwise they will never change people’s behaviours” - [E-01- 2020]
A measurement system, or index, can be an important tool to visualise if Company X improves
over time, or if their innovation capability declines. Almost all the respondents are very positive to
the initiative of implementing a common framework, with the purpose of mapping and
understanding the current innovation capability.
“Of course we would love to go into detail of actually understanding how much money
have we allocated in each stage, what we will get out of those projects, what outcomes
we are looking for, and then of course the speed and the different stages as well, but
we are not doing that at the moment” - [I-10, 2020]
At the company level there are well-established measurement systems measuring such as Net
Promoter Score (NPS) and Objectives and Key Results (OKR), that capture the collective
performance of the firm’s activity. However, these metrics are not specific enough to carve out a
uniform picture of the innovation capability within the organisation. The measurements will also
need to happen consistently over a longer period to enable collection of sufficient data quantities,
draw any long-term conclusions.
“When we implement a first version of this framework to start measuring relevant
KPIs, I think that we will start to create a better picture of whether our innovations fly
or not and based on that we can draw some further conclusions. To implement too
many metrics before we know the outcome is probably not the best way to do it. It is
better to start implementing the framework, and see what the result is and then we can
calibrate and see what we need to measure to become more efficient, work smarter and
get better results” - [I-16, 2020]
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Most managers interviewed say that they have the freedom to implement their own measurement
metrics. As a result, some have specific, quantitative metrics that they measure, others have more
qualitative evaluation processes, and some do not measure anything connected to innovation
specifically.
Additionally, the more complex an industrial ecosystem become, the more interdependent do the
actors get - the higher interdependency between the innovations. This increases the need for
customer and partner driven innovation, rather than innovating internally and then presenting a
finished product to the market. Therefore, measuring the ability to work customer driven and to
satisfy customer and partner expectations is an important dimension of innovation capability,
especially for an actor who are part of an intricate network. Several of the respondents [I-03; I-06;
I-10; I-17; E-02] mention the need to include a customer perspective in the framework to make it
a natural part of evaluating innovation capability. When discussing innovation measurement within
the telecom industry with an industry expert, she made the statement:
“I really believe that you have to talk to the customers. It might sound like a cliché,
and I am not talking about a standard survey, but to identify what customers are the
most important to us and to understand where we are not meeting their needs right
now. That could a big churn in a specific area, or a market analysis showing that the
competitors have a strong offering in that segment. Then you need to gather
information about that customers - it could be through in-depth interviews or other
types of qualitative data analysis to investigate their behaviours. [...] The question
needs to be: ‘What do we need to change to meet our customers’ needs now and, in the
future, and let that be the most important metrics’. It has to be customer driven.” - [E-
01, 2020]
5.2.5 Process
Several of the respondents [I-06; I-16; I-17] mentioned that Company X need to be more efficient
in many parts of the organisation, where efficient processes is one dimension. It was mentioned by
[I-16] that the inefficiency is a result of having high margins on the core business - the organisation
has not been forced to become lean and agile.
“We haven’t practices on how to deliver innovations fast, efficient and standardised -
with proficient evaluation metrics to make us more efficient until the next time.” - [I-
16, 2020]
There are several unofficial project management methods and the teams are free to work with
whatever method they prefer. The structure of the innovation process is, therefore, highly
dependent on who is responsible for the project. Hence, the experience of the quality and structure
of the innovation process depends on the projects that you have worked in and the opinions,
therefore, differs around the organisation.
Customer Orientation
A central dimension in innovation projects at Company X is early customer involvement. Customer
driven innovation has become more central to the entire organisation. Customers should always be
58
included in the early stages of the innovation projects to ensure that the innovation is relevant and
fill an actual customer need.
Customer insight is, according to several respondents, [I-03; I-08; I-09] vital to understand the
market better. However, some claim that Company X is still immature in terms of customer insight.
Company X possess large amount of data regarding their customers, but do not know how to use
it properly. The proficiency in using customer insights and working close with customers during
innovation projects also differs among the country organisations, but everyone is aware of the need
to improve within that area. I-03 further, emphasises the importance of combining the domains of
innovation, customers and business development. He stated:
“I believe that is smart to consolidate the three areas [innovation, customers and
business development] because it means that we can work with innovation, customers
and business development in relation to our strategic direction. It will be highly
beneficial because then you become more focused and there is a better chance to get a
higher return on what you do” - [I-03, 2020]
Financing and Decision-Making Processes
The decision-making process looks different depending on the scale of the project and what stage
the innovation project is in. In early stages of the innovation projects or if only small investments
are required, the decisions can usually be made within the team or specific unit. The criteria for
getting funding are more open and it is not always necessary to have “hard facts” to be granted an
investment. Decisions making about investments, during early stages of the innovation process, is
quite good and there is trust in decision makers and their ability to evaluate the project in a rational,
knowledgeable and fair manner.
However, when innovation projects need a larger investment, decisions are centralised. The
number of people in the organisation which are involved in the decision-making process also
increases as the innovation project grows. Therefore, the pace of the innovation projects usually
decreases and sometimes completely halt. The criteria for getting a larger investment are generally
the same for innovation projects as every other project within Company X. As a result, it is difficult
to get large investments since they usually entail a higher risk than other projects and, thus they are
not prioritised.
How well decision forums work is debated. Some argue that evaluation processes are fair, clear
and reasonable whereas others recognise it as subjective and not adapted for the purpose of
innovation projects. What is mentioned by several respondents, [I-02; I-13; I-14] is that projects
are often evaluated by the potential cash flow and monetary effect - something which cannot be
guaranteed for an innovation project. The differences in the decision forums for innovation
projects, depending on size, result in that it is usually possible to test the innovation on the market
but is rarely permitted to scale up. The innovation projects are often compared to other projects on
a case-by-case basis, therefore, one suggestion was to create a process with the aim to consider the
innovation projects, from a holistic perspective, with evaluation criteria that are more adjusted to
what can be expected of an innovation project.
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“To believe, in an early stage in an innovation project, that you know what the output
will be in the end, then you’re fooling yourself. Instead, an enabling work environment,
an open dialogue, and to be open for changes during the innovation project - It is
extremely important, otherwise it will fail” - [I-03, 2020]
A common phenomenon in the telco industry is that the short-term financial goals with quarterly
focus steer the organisation’s actions more than the long-term strategy. In Company X, this is
primarily experienced in the respective country organisations since they are pressured to deliver
financial results for the board and shareholders. As a result, the short-term goals are perceived as
more urgent and the innovation projects, that usually have a longer time horizon, are prioritised
lower.
“If we look at Company X stock market price today, the valued is based on the business
today, we are evaluated based on our day-to-day business […] I would like to see that
Company X’s value on the stock market is based on business potential and not only
the daily profits” - [I-02, 2020]
In other words, the decision-making process today is not adapted for innovation projects which is
challenging, especially for high risk innovation project. The innovation projects are compared and
evaluated to non-innovation projects, and this creates unrealistic expectations since innovation
projects have other preconditions. Seen from a long-term perspective, the organisation risks to
consistently discontinue innovation projects with potential due to unequal evaluation processes.
Early Evaluation and Cancelling Projects
It was mentioned by several respondents, [I-06; I-10; I-15], that Company X need to become better
at cancelling projects. Most people are aware of the importance of allowing innovation projects to
fail, some even considered it a positive thing to have an atmosphere which encourage innovation
projects to be shut down. One interviewee [I-03], mentioned that if 10% of the innovation projects
that are started ends up with a launched product or service, it can be considered a success. This is
something which is specifically significant for innovation projects, since they have high
uncertainties, and it should not be a general strategy for all projects.
“Not all innovation projects are meant to succeed and by cancelling projects, there
will be space and resources for new initiatives instead. [...] If you have a 100% hit rate
on your innovation projects, you are not innovating. Closing an innovation project - it
is not a failure, we tried, we learned a lot and we will use it somewhere else later. But
it takes courage to say, ‘I think we should cancel this project’, and you need to have a
culture that allows that.” - [I-06, 2020]
However, instead of cancelling projects early, projects tend to become longer than intended and
cost more than initially planned. Many innovation projects get complex and require larger
investments at an early stage. Several interviewees [I-06; I-05; I-15], suggested that a solution for
this is to focus more on early evaluation of innovation projects. By doing so, costs for projects
which later would be cancelled or paused due to predictable reasons such as no market fit or bad
timing could be mitigated. This could involve collecting data through testing the offering with
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customers or test the market response for an offering. This data might also later be useful in
decision forums when new investments are required. It is, therefore, beneficial to work with an
agile project management model since that enables continuous iteration, decision-making and
learning process. It might also reduce the complexity, which otherwise typically quickly increases
in the innovation projects.
Go to market
All products and services that are developed in innovation projects need to be handed over to each
country organisation, where the enterprise division is responsible for taking the offer to the market.
The ambition is usually to get all enterprise divisions, in each country, to sell the product or service.
To make the offer adaptable to different markets, the offering is returned to a central product
development unit where they decide how it should be packaged, delivered and how the business
model should be constructed among other things.
However, since the core products still generate good profit, it is perceived as difficult to make the
sales force discuss and sell new products and services. Several interviewees [I-01; I-02; I-03; I-08]
also mentioned that the sales process need to change - rather than selling the product, stories which
solve problems and improves the customers’ lives, should be sold. This require both a deeper
understanding of the customers’ business, but also a deeper understanding of the products and the
solutions. If this would be achieved, it could result in both higher customer satisfaction and a
stronger perception of the brand.
According to industry experts this is a common phenomenon when it comes to sales, not only in
the telco industry but in most industries. Sales teams are most often driven by revenue and as the
mainstream products and services are usually the ones which is most easy and profitable to sell, so
they are prioritised. Solving this issue might require structural changes which makes it more
profitable to sell new offerings. An external expert [E-01] mentioned that:
“The challenge will be to find a structure where it becomes profitable for an account
manager to also sell the new offer. That is only one example, not only the salespeople
need to be rewarded to sell the new (offering), a support function is also needed, who
need to be motivated to adopt, and that is typically financial or some other clear KPI.
It is at least as important to sell the new offers, even if it cannibalises on the old
business.” - [E-01, 2020]
However, the most difficult part is to find a balance, since the core products and services are still
carrying most of the revenue for companies. Hence, finding the balance between exploiting the
core business while also allowing exploration of new revenue streams is challenging for incumbent
firms. As a result, the innovation projects are highly dependent on the enterprise division, both in
terms of engagement but also technical competence. If you innovate within the existing focus areas,
where the enterprise department already are knowledgeable, the transition from the innovation
team to the enterprise division can be quite smooth. However, it is mentioned that:
“The tricky part is when new areas have been explored and innovated in. Then the
product does not have a natural receiver”. - [I-04, 2020]
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Several interviewees, [I-01; I-05; I-13] explained that they need convince the enterprise division,
or individual account managers, to take the offer to the market. The described transition from the
innovation project to sales is considered a large barrier. One interviewee stated:
“I think that the innovation and core business are still a bit far away from each other.
I think we miss an actual link between innovation practice and the results of innovation
practice, to the core business and the core organisation. We don’t have a natural link
as we speak”. - [I-15, 2020]
To improve this, some innovation projects have one project member who is responsible for taking
the offer to the customers and market. For some teams, who work primarily with customer driven
innovations, it is necessary to convince a business owner, who owns a customer for the project to
be assigned money. In other situations, they have started to work more in cross functional teams,
since innovation needs to be integrated in the whole organisation. Nonetheless, although Company
X is trying to mitigate the barriers, the challenge of taking the offer to the market is still
experienced.
Some innovation projects want to enter the market as soon as possible and to later adjust and
continue the development of the offer when the offer is on the market. However, one interviewee
commented that:
“I would say that all those sales channels are not very keen on selling things that are
not finished. Sales department require immediate revenue so if I have an innovation
project, it needs to be commercial, ready to launch right away. Otherwise they will not
use time for looking at it” - [I-15, 2020]
On the other hand, another interviewee, [I-16] argued that there is a difference between start-ups
and a company such as Company X, whose customers have certain expectations on quality and
functionality. As mentioned, when the offer needs to enter the market quickly, the product or
service many times must be released unfinished or as a prototype. How the market will react and
the potential impact a prototype release will have on Company X to release needs to be considered.
It is commented that it might be alright but there must be an awareness to how it affects Company
X.
“It is important to be able to have a short time-to-market, however; we also need to
maintain our reliability” - [I-02, 2020]
To choose between time to market and quality can be challenging since something usually needs
to be altered in the process to get the offer to the market more quickly. However, offers that emerge
from the innovation projects might not have a long lifecycle which makes ‘time to market’
essential. Therefore, there are people within Company X, that are looking for a solution to how a
parallel process can be constructed in order reduce the lead time and more easily test offers on the
market. It is mentioned [I-06] that it is important to work as fast as possible, but at the same time,
it should not affect the customers.
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The Scale-up and Cross Functional Collaboration
As the new services become increasingly complex and intertwined with other systems, platforms
and services, it becomes even more essential to have a well-managed ecosystem. This also applies
to the internal organisation. It is not so much about developing a product which is then delivered
to a product owner and a sales department - it is important to work across the whole organisation
from start, rather than to work in silos. It was discussed [I-02; I-16; I-17], that the existing
innovation process and structures need to be reconstructed for the process to become simpler and
more flexible. However, that will require an immense organisational change, which might be
necessary, but it will require time.
Scaling up the project is many times experienced as one of the most challenging part of the
innovation projects. This is a consequence of a slow decision-making process but also since all
other support-processes need to function when it is time for scaling. It is necessary that the product
or service can be sold, delivered, supported and it should all be done on a large scale. The linear
process which exists is described to inhibit and complicate the scaling process and makes it
challenging to scale up projects in a controlled, structured and sustainable way. Some innovation
projects are custom made for a specific customer and it is, therefore, both hard and expensive to
merge that offer into the established business.
5.2.6 Communication
Innovation is a key aspect in building a competitive advantage and a good position for the future.
Thus, building and communicating a brand around this is also of essential. Engaging the entire
organisation, by spreading insights about innovation projects and initiatives, is also important to
prevent people from working in silos. Hence, appropriate solutions for both internal and external
communication around innovation and building awareness around the brand is of necessary for
Company X [I-03; I-07].
Internal communication
Several interviewees [I-08; I-12; I-14; I-15] mentioned that they would appreciate to take part of
information about other countries’ innovation initiatives, and that is would be good to visualise
what is happening, numerically, in all parts of the company. This is already done to some extent,
and is a work in progress, however; all interviewees from Company X mentioned that they would
like clearer communication material and expressed that statistics and numerical information would
be helpful to get attention internally.
“I think it would be very relevant to visualise our own innovation capability to our
colleagues, so that we get everyone onboard” - [I-07, 2020]
Breaking up silos and creating strong cross-functional collaborations are important but challenging
dimensions when building a stronger innovation capability - especially given the size and
geographical diversity of Company X. Several interviewees [I-09; I-12; I-15] mention that great
improvement has been made during the past years but there are still improvements to be made.
Strengthening the internal communication is one factor to focus on to lower the barriers further.
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As a large portion of the innovation projects will fail, it can be challenging to motivate to the
shareholders to invest, when the existing business is still highly profitable. It is also challenging
since some innovation projects have a time horizon on several years, before they might become
profitable. However, since innovation is very crucial to ensure the future of Company X, they need
to establish efficient communication and stakeholder management. One of the external experts
discussed the integration of the innovation agenda into the main organisation at all levels.
“First of all, it is important to make it clear to everyone that innovation is the future
business of the company, in order to prevent that innovation will be regarded as an
item on a checklist - ‘When it is checked, we just continue as we always have’.
Regardless of how it is organised, whether it is in a separate unit or not, it needs to get
that recognition and understanding from the organisation. It should be communicated
by the executive board that the innovation is what we all will make money from in the
future. Therefore, every unit needs to be on board.” - [E-02, 2020]
External communication
The external communication can be used to create an understanding of how innovation contributes
to the business and, further, translate it into value for the shareholders. Company X has a lot of
legacy and is well-known for its core services but building an awareness around the innovation is
crucial. Company X needs to improve how they communicate their innovative activities and several
respondents [I-01; I-03; I-05; I-15] mentioned that customers are usually surprised when they are
informed about the innovation work Company X is pursuing. Similarly, [I-03] says that the market
surveys point in the same direction - as it gets harder to differentiate the brand based on price,
Company X should improve their innovation capability.
“I would say that (external communication) is extremely important and the feedback
we get from customers is very positive” - [I-04, 2020]
Overall, the external communication around innovation is a key component in attracting customers
and partners to obtain customer-driven innovation. It is ultimately about building a stronger brand
perception and control the values that are associated with Company X.
Knowledge Management
Apart from the potential business value, innovation projects can contribute with value that is non-
monetary - such as organisational learning and insights. However, it is useful to have a structured
process to codify and integrate that knowledge back into the organisation. As Company X is a
large, multinational company, building efficient learning processes and knowledge management is
an inherent challenge. There are forums within the organisation which aims to create community,
spread knowledge and share experiences, which most of the respondents experience as well-
functioning and positive. However, many interviewees [I-06; I-10; I-14] also feel like there could
be a better coherence between different teams and organisations, to favour organisational learning,
transparency and team spirit.
“Information sharing and tightening different parts of the organisation, when we are
geographically distanced in different countries is always something you can get better
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at, everyone included. I believe we need to work even more with forums and regular
meetings. [...] Spreading knowledge, experiences, insights and networks is so
important.” - [I-06, 2020]
5.2.7 Key Success Factors
Six KSF were identified after analysing, categorising and compiling the findings from interviews
with the respondents. These success factors, which all represent different areas, which all play a
crucial role in innovation capability, can be found in Table 7. The KSF are the synthesis of the
interviews and are part of the resulting framework.
Table 7. The identified KSF for innovation capability for incumbent telecom firms.
Key Success Factors
Innovation strategy
Decision making processes
Customer orientation
Cross-functional collaborations
Scaling up
Communication
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6. Conclusion
In this chapter, the conclusions from the thesis will be presented. The first section (6.1) aims to
answer RQ1, while 6.2 corresponds to RQ2. The first section is diving into the identified key success
factors (KSF) for innovation capability at the case company, where they are analysed and
compared to theory. In the second part of the chapter, the KSF are connected to suggested metrics.
6.1 Synthesising the Key Success Factors
The KSF was identified through the literature in combination from the empirical findings and can
be found in Table 8. In Table 1 the most commonly mentioned KSF to innovation capability are
presented. These laid the foundation for investigating the KSF for innovation capability at
Company X. Through incorporating theory and findings from the interviews, six KSF were
identified. These are further categorised into underlying dimensions which constitutes each key
success factor. These have, further, been categorised into sub-dimensions, also illustrated in Table
8.
Table 8. The identified KSF for innovation capability for incumbent telecom firms, including subdimensions.
Key success factors Underlying Dimensions
Innovation strategy
Portfolio Management
Strategic Alignment
Risk Management
Decision making processes
Time Horizons
Agile Processes
Customer orientation
Level of Flexibility
Customer Insights
Cross-functional collaborations
Internal Collaboration
Open Innovation and External Co-Creation
Scaling up
Financial Management
Market Dispersion
Communication
Internal Communication
External Communication
Knowledge Management
Establishing capabilities within these different dimensions, will lay the foundation for a strong
innovation capability. Each one of these dimensions have certain implications for the innovation
capability within a telecom firm and entail specific challenges. Overall, through comparing the six
KSF with the literature; strong correlations with acknowledged determinants for innovation
capability, specific dimensions within service innovation and characteristics of incumbent firms in
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highly transformational environments are identified. Further, according to the empiricism, these
dimensions have a high level of interdependence, and, thus, require a holistic approach.
6.1.1 Measuring Innovation Capability
To propose metrics for measuring innovation capability at the case company, the existing
frameworks for evaluation of innovation capability was screened and analysed, to assess which
framework was most suitable for the case company. The frameworks that were most suitable was
then analysed based on a set of criteria which were identified through discussions and informal
interviews with relevant persons at the case company and from the research field. The selected
framework, by Björk and Frishammar (2019), was the only framework which fulfilled all criteria.
It differentiated itself compared to the other evaluated frameworks by Boly et al. (2004) as well as
Saunila and Ukko (2012) by being adaptable to service innovation and taking present and future
into consideration. Further, the selected framework was also the most recent framework, published
in 2019, which was mainly considered as a strength, as it is a product of extensive research (Björk
and Frishammar, 2019). As innovation capability is a diverse field (Brattström et al., 2018), new
findings are revealed continuously, and this led to the conclusion that is was more suitable to use
a recently presented framework, which has compiled the most prominent research within this field.
Of course, it can also be considered a limitation to use a new framework that lack empirical
evidence, and the results from this paper will have to be validated further by similar studies. The
framework, which is based on a matrix structure, has four dimensions and three types of metrics.
The dimensions are portfolio, process, project and culture. Due to limited time and resources, the
cultural aspect was not included in the framework in this paper. However, this aspect can easily be
included at a later stage.
Based on the literature and research around innovation capabilities, the KSF to innovation
capability was identified as: innovation strategy, decision making processes, customer orientation,
cross-functional collaboration, scaling up and communication. These dimensions are based on the
findings from the literature, combined with the findings from the empirical data collection. It was
also observed that the dimensions had a high level of interdependency, which requires a holistic
perspective. However, no analysis of the internal relationship between these was made and the
dimensions were not weighted.
6.1.2 Innovation Strategy
The research on innovation capability generally agrees that innovation strategy is an essential part
prerequisite for innovation capability (e.g. Lawson and Samson, 2001; Wang and Ahmed, 2007;
Saunila and Ukko, 2012). However, lack of an innovation strategy is common which, according to
Pisano (2015), is one of the reasons why many organisations fail with innovation. This was partly
supported by the empirical data, as Company X had identified several focus areas, that are aligned
with the overall business strategy, but were also missing central parts of an innovation strategy.
For example, there is no explicitly stated innovation ambition, which, according to Nagji and Tuff
(2012), is a key part of the innovation strategy. The resources invested in innovation is not clearly
defined and monitored internally at Company X. The ambiguity around the innovation strategy as
well as the innovation ambition can, according to research, lead to a sub-optimised decision-
making process, as it is harder to take strategically grounded decisions (Calantone, Cavusgil and
Zhao, 2002). The lack of a predetermined risk level tends to lead to an overweight towards low
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risk, incremental innovation projects (Mattes and Ohr, 2018), something that was highly supported
by the empirical data - most of the interviewees expressed this as a concern. This is problematic,
as under-investing and focusing on innovation projects that are close to the core, is associated with
a huge business risk in the long-term perspective (Nagji and Tuff, 2012). This is especially true in
industries that are highly transformative and are approaching a trajectory shift, which is the case
for the telecom industry (Bohlin et al., 2001; PwC, 2019). It is also both common and especially
problematic for incumbent firms, as they tend to have longer transition times when it comes to
changing the core product (Christensen, Raynor and Van Bever, 2013; Mattes and Ohr, 2018).
Simons (1995) discussed how incumbent firms should view their strategy as an incremental,
emergent process, rather than a static document provided from top management. Therefore, the
strategy needs to incorporate feedback from members of the organisation, at all levels, but also
adapt according to the external environment (Simons, 1995). This implies that incumbent firms
should implement feedback loops from within the organisations. This is also associated with
knowledge management systems, which is discussed further down in section 6.3.8.
The project portfolio as an organisational entity is vastly recognised as a valuable tool to manage
PBOs (both standalone and subsidiary) and is discussed as a solution to many challenges associated
with innovation management (Meskendahl, 2010). For example, it can help to increase the
alignment between the organisational strategy and the innovation projects (Meskendahl, 2010;
Stettina and Hörz, 2015) as well as contribute to a create a balance in the distribution of projects
(Mikkola, 2001; Jonas, Kock and Gemünden, 2013). Both aspects are identified as key challenges
for Company X, which explains why portfolio management is a central dimension in the aim to
improve innovation capability. Portfolio is also one of the dimensions in the measurement
framework, which allow the organisation to aggregate valuable data and insights about the portfolio
level. This can, according to Jonas, Kock and Gemünden (2013), increase the possibilities to good
results as information quality is one of three dimensions which predicts portfolio success.
There are also structural benefits coming from the portfolio management, which could help to solve
some organisational challenges within Company X. At multinational, incumbent firms, silos and
lack of efficient communication channels are common problems (Deschamps and Nelson, 2015),
which are identified to a high degree at Company X. Through establishing an additional layer
within the organisation, who works across the entire organisation, with a clear purpose to manage
and improve the innovation project, management, they can tackle these issues more effectively
(Deschamps and Nelson, 2015). The way this unit is working resembles a lot with the research
around how a project management office is functioning. Project management offices can be a
natural place for knowledge management, and there is potential in developing this organisational
structure further. However, it is important to ensure that managers and key persons within the PMO,
have the right capabilities to organise and implement knowledge management systems (Hobbs,
Aubry and Thuillier, 2008). It is a common problem that PMO managers come from more
traditional project management, and they need to be trained to understand that a portfolio is not
just an upscaled project, it is a different form of organisational entity and need to be managed
through a different approach (Pellegrinelli et al., 2007). Thus, although it is in early stages,
Company X has started to take steps in the right direction.
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6.1.3 Decision-Making Process
To measure and evaluate innovation projects based on monetary values is common, meanwhile,
there are many who argue that it is not beneficial for the innovation performance (Shapiro, 2006;
Chan et al., 2008). This was also visible at Company X, where the decisions also many times are
significantly impacted by the short-term perspective, and the launched innovations are required to
be profitable instantly - which is why innovation projects are neglected. The literature acknowledge
these issues and argue that they primarily emerge due to a singular focus on the short-term horizon
(Merchant and Van der Stede, 2005), and similar to what is experienced at Company X, different
time horizons within a firm is also a common barrier (Griffin and Hauser, 1996). The literature
further states that common goals (Kahn and Mentzer, 1998), and clear communication (Lovelace,
Shapiro and Weingart, 2001) might mitigate the variety of time horizons.
However, due to the high ambiguity regarding the potential profit from innovation projects, it might
still be hard to convince units with short-term horizons to change their approach (Melton and
Hartline, 2012). Both researchers (Flammer and Bansal, 2017) and interviewed industry experts
noted that incentives might be necessary to motivate some parts of organisations to adapt to a long-
term horizon. At the same time, O’Reilly and Tushman (2011) argued that an improved dynamic
capability can improve the balance between short-term and long-term horizons. As an extension,
this suggests that an improved innovation capability can improve the balance of the time horizons.
Meanwhile, according to Merchant and Van der Stede (2013), a balance in time horizons can
improve the innovation capability, and this creates a paradoxical situation. Therefore, innovation
measurement might be a method to raise awareness to issues that might exists, and to motivate the
organisation to improve their innovation capability (Boly et al., 2014; Richtnér et al., 2017). Thus,
by making improvements on all the six identified KSF for innovation capability for a telecom firm,
the balance of long-term and short-term horizon can also be improved.
Another acknowledged issue during the interviews, was the amount of people involved in the
decision-making process, which is also mentioned in the literature as something that contributes to
slow and non-flexible decision-making processes (Maylor, 2010). Company X experienced that
innovation projects tended to become longer and more complex than necessary, and in some units,
more agile methods have been implemented to get around this problem. Agility is also mentioned
in the literature as a method to shift the focus to the innovation capability, increase the flexibility
as well as to improve customer satisfaction through the iterative process (Highsmith, 2010).
Stettina and Hörz (2015) also discusses agile portfolio management as a tool to increase
transparency and there, further, seems to be consensus both in the literature (Mattes and Ohr, 2018),
as well as at Company X that not all innovation projects are supposed to survive. Thus, it is
important not to let the costs for innovation projects become high in the early stages, and further,
as mentioned in the empirical findings, promote cancelling innovation project to leave room for
other innovation projects. However, this is not the case today at Company X, where the innovation
projects tend to become longer instead of being cancelled in early phases. Hence, a more extensive
application of agile working methods in the entire organisation, could be useful to save costs,
reduce the complexity and to early identify projects that should be cancelled (Margaria and Steffen,
2018).
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Therefore, to improve the innovation capability, it could be beneficial to include both time horizons
and promote more agile working methods in a measurement system, since they have the potential
to improve the innovation performance. Time dimension as a metric can be both a method to ensure
that the innovation metrics is aligned with the strategy, which is considered essential (Mosakowski
and Earle, 2000; Flammer and Bansal, 2017), it can further be a metric which through combining
it with other metrics can visualise the efficiency of the innovation activities within an organisation
(Shapiro, 2006; Boly et al., 2014).
6.1.4 Customer Orientation
Since Company X, the telecom operators, as well as companies in many other industries are
becoming service providers (Spohrer and Maglio, 2008; Tidd and Hull, 2010; Qiu, 2014), the
customer experience has become more relevant than before. To become proficient in creating
valuable customer experience, firms need methods to understand their customers (Tidd and
Bessant, 2013), customer insight is, thus, imperative to improve the service innovation performance
of a firm (Edvardsson et al., 2013). This was mentioned by Company X as an area which they have
become better at, but still could improve within. The relationship with customers can further be
improved through having a continuous communication (Kelly, Schaan, and Joncas, 2002).
Therefore, it might be beneficial to evaluate both customer satisfaction (Saunila and Ukko, 2012),
as well as to include a quantitative measure (Boly et al., 2014), such as the frequency of customer
validation.
Since the telecom operators is currently experiencing a shift where they previously developed
products with an inside-out approach, it might be useful to have metrics that are promoting
inclusion of customers and partners in the innovation process, as suggested in the literature on
service innovation (Tidd and Hull, 2010). However, the increased involvement of customers and
the increased requirement for flexibility is also considered to be a liability to Company X. The
large organisational structure, and its existing processes, is dependent on standardisation to scale
current offers but the need for flexibility are further mentioned by an interviewed industry expert,
as well as in the literature (Miles, 2010; Randhawa and Scerri, 2015), as a general challenge for
incumbent operators. There are doubts about whether the existing organisational structure have the
capability to meet these new requirements on flexibility. At Company X, as well as many other
incumbent firms, a reconstruction of how products and services are produced might be necessary,
since incumbents tend to be much slower and less flexible than the market requires (Caylar &
Menard, 2016). However, organisational change is usually a long process (Pathak, 2010), and what
Company X can improve until then, is their dynamic capability (Teece, 2007). Since the dynamic
capability will enable firms to adjust, integrate and renew competencies within a firm (Winter,
2003), they might improve the preconditions to face the increasingly changing environment with
higher expectations on flexibility. To optimise a firm’s dynamic capabilities, it will be necessary
to improve the innovation capability but also the adaptive and absorptive capabilities (Wang and
Ahmed, 2007).
6.1.5 Cross functional collaborations
Collaborations can help companies to improve their innovation capability (Saunila and Ukko,
2012), and at Company X, non-functioning collaborations had a seemingly large impact on some
historic innovation activities.
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Internal collaborations
Internal collaboration can result in an improved efficiency and innovation performance
(Frishammar and Hörte, 2005). However, this is only possible if there exist common goals, strategy
and clear communication (Dougherty, 1992). As mentioned in 6.3, collaborating units and people
may work under different time horizons. For example; at Company X it appears difficult to
motivate the sales organisation to embrace new innovations that are not closely related to the
existing focus areas. Melton and Hartline (2012) identified that for service innovation to be
beneficial for a sales organisation, it needs to have a quick adoption rate and be familiar to the
customers. Thus, it might not be wrong that the sales organisation is focused on the identified focus
areas within Company X. However, since it is necessary to have both a short-term and long-term
perspective (Laverty, 1996), the earlier mentioned incentive for the sales organisation, might be a
way to increase the interest for promoting new offers (Flammer and Bansal, 2017).
Further, to present data which prove external interest, such as customer verifications or market
response, might additionally increase the interest for the innovation units’ projects (Brattström et
al., 2018). Another approach, which Company X used in some innovation units, is to assign an
internal project member as a business owner, who is responsible for taking the innovation to the
market. This is another example of a cross-functional collaboration, in which the sales process is
integrated with the innovation process - which has been identified as a strategy that is adopted
particularly in-service organisations (Tidd and Bessant, 2013). The disconnect between R&D and
the business units is common and acknowledged problem in the literature (Tidd and Bessant, 2013).
Cross functional teams and integrating the business owner in the innovation process are, thus,
methods to reduce the distance between the functions.
Measuring the innovation capability is not only used to directly increase the innovation
performance but also to increase the engagement internally (Brattström et al., 2018), which was
mentioned as desirable during the workshops as well as the interviews. Moreover, measurements
can also be used to visualise the innovation activities within the firm and improve the internal
collaborations, which further can improve the innovation capability even more (Froehle and Roth,
2000).
External collaborations
As mentioned in section 6.4, including the customers in the innovation process has become more
relevant (Möller et. al, 2008; Maglio and Spohrer, 2013). Since service is co-creation of value,
according to the S-D logic (Vargo and Lusch, 2004), it is more important to integrate the entire
supply chain from suppliers to customers in the value creation process (Tidd and Hull, 2010).
Additionally, collaborating through partnerships has also become more popular to gain knowledge
and resources quickly, as well as to reach new markets, to gain competitive advantages (Ditillo and
Caglio, 2009; Tidd and Bessant, 2013). It was further mentioned that a large firm, such as Company
X, can be a valuable partner due to their extensive resources - and Company X is interested in
increasing their number of partners. However, due to the risks and challenges that might emerge
through collaborations (Alexy, George and Salter, 2013), it might be useful for firms, such as
Company X, to also analyse their potential customers and partners based on compatibility and
alignment of objectives (Boudreau, 2010; Tidd and Bessant, 2013)
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Another key trend, is that the span of the life cycle for new products and services, has become
shorter (Ditillo and Caglio, 2009), which was also acknowledged by Company X. For large
companies, time-to-market is usually long due to slow and complex processes (Ditillo and Caglio,
2009; Tidd and Bessant (2013). Thus, it can be valuable to use collaborations and open innovation
to shorten the lead time as well as to reduce risks (Gnyawali and Park, 2011). Additionally, large
incumbent companies tend to be defensive of their brand, and the value of quality and customer
experience (Ditillo and Caglio, 2009), and this was mentioned by Company X to why they should
not deliver half-finished products. Open innovation can, therefore, be a valuable path, to more
quickly produce a qualitative offer with a shorter time-to-market (Wallin, and Von Krogh, 2010).
At Company X, the awareness of the value of customer orientation is rather high and during the
interviews, it was mentioned that they should take a more consultative role instead of focusing on
their own offers, to integrate themselves into their customers’ eco systems and innovate together.
However, the literature states that a strategy like that can also be risky, since that might leave
Company X too exposed or too dependent on other firms’ resources (Boudreau, 2010). Therefore,
Company X might want to evaluate how much they should to exploit versus explore, to achieve
the best level of adaptive capability (Staber and Sydow, 2002).
6.1.6 Scaling up
Scaling up is one of the most difficult parts of the innovation process, both according to literature
and the empirical data (Cooper, 1988; Mattes and Ohr, 2018). At Company X, this is associated
with improper financing, due to unrealistic profitability expectations and a low understanding of
the prerequisite support from the rest of the organisation. The importance of earmarking money for
innovation projects is mentioned as one of the key actions for avoiding ambiguity around financing.
Another challenge mentioned by several interviewees, which is also highlighted by Mattes and Ohr
(2018), is the unfortunate situation that occur when innovation managers need to fight for funding
from other business units, which are often running under a tight budget themselves.
According to Chan et al. (2008) it can be beneficial to use metrics that are connected to shareholder
value, as this highlights the quantitative contribution to the organisation, and visualise the
investments made as well as the return on investments. As the scale up process is problematic, but
highly critical for creating business impact and generating a substantial return on the investment,
it also makes sense to connect financial metrics with metrics that illustrate how the distribution of
projects are going. Further, as there is a strong connection between innovation capability and firm
performance (Wang and Ahmed, 2007), there should be a positive correlation between an increased
innovation capability and the financial performance, at least in the longer perspective.
Lastly, as Winter and Szulanski (2001) mentioned, the diffusion of a product is also a sign of a
functioning scaling up process for an innovation. Spreading an innovation to different markets is
essential for creating substantial, long-term value (Mattes and Ohr, 2018). However, for large
multinational firms, the conditions on the markets can be different depending on the country, which
was commented during an interview. To understand the overall potential for an innovation and to
determine the right timing is thus, much more complex.
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6.1.8 Communication
Communication is considered to a main aspect of innovation measurement from both literature and
the empirical data collection. Communication is indirectly covered in the metrics presented but are
not measured directly.
Internal
One of the benefits from innovation measurement is to improve the internal communication within
an organisation (Brattström et al., 2018). Additionally, one of the major objectives with the current
centralisation of the innovation organisation is to increase transparency and engagement internally.
Measuring innovation and gathering data connected to the innovation capability, can be a good
step in the right direction, as several of the interviewees expressed a wish to get more insight into
other parts of the innovation organisation, especially the ones that are not located in the main
market (Sweden). Further, silos and overlapping work, can be avoided through efficient
communication, which historically has been an issue.
Brattström et al. (2018) discussed the attention-based view in relation to innovation within
organisations and argue that measuring innovation can function as an attention focusing device.
They claim that attention goes to matters that are urgent, rather than important, which is why it can
be useful to implement innovation measurement to steer the attention. Company X has a high level
of ambiguity in their innovation, with multiple stakeholders and objectives as well as managers
who need to prioritise between short- and long-term outcomes. For high ambiguity, it is
recommended to focus on conversational metrics (characterised by multiple, ambiguous metrics),
which are initiated to create an internal focus on the innovation metrics data and to visualise the
innovation projects and identify patterns and issues (Brattström et al., 2018). Interactive control
systems are useful for conversational metrics, since they provide rich information and can help
companies to re-interpret their environment (Simons, 1995). Company X, which is a part of a
transformative industry, needs to continuously interpret and reinterpret their environment since it
is constantly changing. The ability to understand of the changes and current state of the external
environment is also necessary to attain both adaptive and absorptive capability in a transformative
industry (Wang and Ahmed, 2007).
External
Many incumbents’ firms have a short-term financial perspective (Laverty, 1996; Brochet,
Loumioti, and Serafeim, 2015), which can hinder innovation within an organisation (Mattes and
Ohr, 2018) and is a reason to why firms fail (Brochet, Loumioti, and Serafeim, 2015). It is very
difficult for managers within an organisation to get investors and shareholders to promote projects
that might mean reduced profits (Laverty, 1996). While this is true, and is supported by the
empirical data, shareholders should also consider the opportunity cost from a long-term
perspective. One of the industry experts mentioned under-investing as one of the major challenges
for telecom firms during this time. Competition is increasing at a high pace (PwC, 2019), and
preparing for the future is more urgent than ever. Innovation measurement can help to demonstrate
how innovation is contributing to the firm, both from a financial perspective as well as from a brand
perception perspective.
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As the lines within the ecosystem are increasingly blurred, and cross functional collaborations is
becoming an central part of building innovation capability (Ordanini and Parasuraman, 2010), the
brand perception towards customers and external partners is essential. For an incumbent firm with
heavy legacy, that can be challenging, but establishing an efficient communication around
innovation capability and ongoing innovation initiatives can be one way of doing so. Brattström et
al. (2018) discussed innovation measurement as an attention-focusing device from an internal
perspective, but it could also have the potential to gain attention from customer, partners,
shareholders and external decision-makers as well. Several interviewees mention the need of telling
a story around the innovations and the new offerings. Rather than just highlighting the technical
benefits, it is important to put into the customers’ context and incorporating it into the customers’
story.
Knowledge management
Knowledge management is one of the cornerstones in building a strong innovation capability
(Calantone, Cavusgil and Zhao, 2002; Adams, Bessant and Phelps, 2006; Tamer Cavusgil,
Calantone and Zhao, 2003; Belkahla and Triki, 2011; Saunila and Ukko, 2012). It is generally seen
as a success factor for developing dynamic capabilities within an organisation, but is, considered
to be especially challenging to PBOs (Pemsel and Wiewiora, 2013). Looking at the case company,
several of the employees mentioned that they want to share and get access to knowledge within the
organisation, but there is a lack of both formal and informal structures for sharing knowledge - a
common phenomenon according to Pemsel and Wiewiora (2013). Some country organisations have
well-functioning forums for sharing knowledge, which is very appreciated according the
interviewees, as it offers a space for reflection and discussion across teams. Some of the
interviewees mention that they keep the level of documentation low, as they want to keep the
process simple and flexible. While this is understandable, it could still be beneficial to implement
some sort of structure around knowledge management.
As Company X is a multinational, large corporation, with highly technological and complex
innovation projects, they could benefit from develop a knowledge management system that include
both informal and formal knowledge management systems. This can both improve the individual
performance as well as increase the organisational learning. Through implementing these systems,
they are also more likely to exploit synergies between projects in a better way, as they establish
better communication channels. Implementing conversational types of metrics (discussed in
section 6.8.1), also functions as an issue translation tool, converting tacit knowledge into explicit
information. In organisations with a high level of ambiguity, there are often issues related to
communication and aligning the organisation - and converting knowledge can be beneficial to
create clarity and alignment (Brattström et al., 2018).
The organisational, as well as industrial, challenge of scaling up innovations could be improved by
improving the knowledge management, since scaling up requires knowledge transfer (Winter and
Szulanski, 2001). For a large corporate firm, this means that other units, need to comprehend and
apply new information which, at Company X, is not as well functioning as it could be. Hence,
through focusing on improving the communication quality, knowledge management and
knowledge transfer - better preconditions for scaling up could be obtained. Knowledge
management systems need to be designed with respect to the learning landscape within the
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organisation. Organisations that are knowledge intensive tend to be leaning on “people to people”-
communication, and even if a certain level of explicit knowledge sharing is needed, it is also
important to establish knowledge sharing mechanisms (Principe and Tell, 2001). According to
Principe and Tell (2001), those mechanisms should be more informal and allow sharing of tacit
knowledge between team members as well across teams and business units.
6.2 Service Innovation Capability Measurement
In this section, RQ2 is answered. Integration of literature and empirical findings resulted in the six
presented KSF for innovation capability. A set of metrics, based on the identified KSF and
according to the accepted framework, is presented in the following section. Each metric is designed
to:
1. Fill a specific purpose for improving the innovation capability
2. Together with the whole framework build a comprehensive picture of the innovation
capability and the innovation performance underpinning this.
Further, to visualize how the metrics relates to the frameworks, the metrics are categorised
according to the two dimensions of the framework. The first dimension is the level of assessment
within the organisation: portfolio, process and project. The second dimension is the point of
measurement: input, activity and output. To verify the KSF and suggested metrics, the metrics will
be presented in the framework at the end of this section.
6.2.1 Innovation Strategy
Since an adequate innovation strategy is essential to successful innovation operations as well as
building innovation capability (Richtnér et al., 2017). Measuring the portfolios alignment with the
innovation strategy is a necessary dimension to create a sustainable measurement framework and
to developing a coherent vision of the purpose of innovation as well as the future position
(Brattström et al., 2018). A balanced and sustainable innovation portfolio thus connects the
innovation strategy with the innovation projects, and to links operational activities with the strategy
(Meskendahl, 2010).
Risk management is an essential to determine how much risk the organisation should take and how
the different types of risks should be balanced (Brattström et al., 2018). There is an intricate
connection between the innovation ambition and the risk balance, expressed by the innovation
strategy in the innovation portfolio, which is reflected in Metric 1.2 and 1.3. The desired risk
balance needs to be determined at the strategy level and be used while evaluating both the portfolio
composition as well as individual projects. Metric 1.2 is measuring what is dedicated on strategic
level to each risk level (core, adjacent and transformation) and Metric 1.3 is measuring the
corresponding activities. The metrics complement each other and are designed to give a
multidimensional perspective on the innovation activities to later understand potential levels for
targets. It is also possible to follow up and monitor the interplay between input and activity.
Similarly, Metric 2.3 also assists in project level decision making by visualising the current state
of a projects. An understanding of the current situation and what stages the active projects are at,
helps taking informed decisions about new projects, resource allocation and other project related
issues.
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The last Metric, 3.8, captures the achievement of the ambitious sustainability goals that is in
Company X’s overall strategy. Since the innovation projects are necessary for sustainability work
(Weaver, 2000), it is, essential to ensure their alignment with these goals. Therefore, Metric 3.8
aims to show how all projects support the sustainability goals in some aspects.
Table 9. Metrics related to innovation strategy.
Metric Dimension Category
1.2 Percent of total investments in innovation dedicated to
core/adjacent/transformational
Portfolio Input
1.3 Percent of ongoing projects of core/adjacent/transformational nature? Portfolio Activity
2.3 Number and percent of projects in different stages of the innovation
process?
Process Activity
3.8 How has the project supported our Sustainability Goals? Project Output
6.2.2 Decision-Making Processes
One clear challenge that arose when doing the empirical data collection was the time management
especially connected to decision making processes. There are clear connections between the quality
of information and the ability to make adequate decisions within a reasonable timeframe (Jonas,
Kock and Gemünden, 2013; Stettina and Hörz, 2015). So, providing accurate data and information
can facilitate an easier decision-making process, a better selection process, and increase the
portfolio success rate (Jonas, Kock and Gemünden, 2013). Moreover, differing time horizons
within the organisation was commented as an issue at Company X, therefore, data collection can
provide increased insight, and be used to align different perspectives (Stettina and Hörz, 2015).
Both Metric 2.2 and 3.5 aims to give an indication of how well the time plan has been followed
and if there have been any large delays connected to the process or the projects. Through mapping
which projects that tend to be delayed, it is possible to see if there are any patterns in which projects
are awaiting decisions or get stuck in queues. According to several respondents, the high-risk
projects tend to get stuck in long complex decision processes and with more demanding stakeholder
management whereas low-risk projects are often able to run according to plan. The collected
information could be useful information in discussions about portfolio management and risk
management. Last, Metric 3.3 is useful for determining how projects are affected by external
factors, and to what extent it is causing delays. Further, through combining Metric 3.3 with other
metrics, efficiency of projects can be visualised which also can facilitate information needed for
decision making.
Several interviewees expressed the necessity of cancelling projects in time, which is related to the
ability to take informed and active decisions. Some even mentioned that it should be perceived as
positive to cancel a certain percentage of the innovation projects - as that is a natural part of the
innovation process. Now, Company X has limited insight into the extent to which they are
cancelling innovation projects. So, through Metric 1.6, data around the how many projects are
cancelled in relation to the total amount will be provided, which can give a useful indication about
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to what extent projects are “allowed to fail”. Focusing on the percent of cancelled projects can
further provide information about the degree of active decisions making.
Overall, an interactive working process was mentioned as a method to improve the decision-
making process as well as the agility for some groups. It was further mentioned as something which
can enable the project group to learn and iterate during the project. Therefore, to continuously
evaluate the innovation activities can both improve the final product as well as facilitate learning
(Davila, Epstein and Shelton, 2012).
Table 10. Metrics related to decision-making processes.
Metric Dimension Category
1.6 Percent of projects cancelled? Portfolio Output
2.2 Total number of projects running according to plan in relation to total number
of projects? (Percent)
Process Activity
3.3 Percent of total time the project has been paused? Project Activity
3.5 How many weeks has the project been active this far? Project Activity
6.2.3 Customer Orientation
Customer-orientation is becoming increasingly essential to remain relevant on the market,
something that both literature and the empirical data collection supports (Grineisen and Rehme,
2018; PwC, 2019). There is also a clear link between high customer satisfaction and the innovation
capability (Saunila and Ukko, 2012). Through the empirical data collection, it became clear that
this was recognised as important but also perceived as a challenge for the organisation. Due to the
nature of the telecom industry and the characteristics of Company X, a high-level customer-
orientation has not been naturally achieved. However, as the market situation and the customer
expectations are changing, being redirected towards understanding and meeting customer needs
rather than just delivering a product or service.
All the customer focused metrics are designed to ensure that the customer perspective is central in
the development of new projects and that they are aligned with real customer needs. Metric 1.7 is
an output metric, meaning it is lagging, and gives an indication of the degree the projects are
fulfilling customer expectations. Metric 2.1 captures to what extent external partners are included
in the idea creation process.
Finally, Metric 3.4 aims to identify to what extent customers are included in the testing process, as
testing with customers before launching should increase customer satisfaction and contribute with
valuable customer insights. Additionally, measuring efficiency in relation to time might result in
reduced quality (Latham, and Locke, 2006), therefore, since quality is essential for Company X,
Metric 3.4 can increase the focus on quality in innovation projects. To summarize, the metrics and
ambition to increase the customer orientation consists of improving the customer insights and the
flexibility of the organisation.
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Table 11. Metrics related to customer orientation.
Metric Dimension Category
1.7 Total customer satisfaction with new products or services due to innovation? Portfolio Output
2.1 To what extent have we created ideas with external partners (e.g. customers)?
(Percent of total amount of projects)
Process Input
3.4 Number of tests with customer until now? Project Activity
6.2.4 Cross Functional Collaboration
Open innovation and customer-centred innovation are two of the major trends within innovation
management today (Maglio and Spohrer, 2013), and should be considered while developing new
projects (Tidd and Hull, 2010). If a team has developed several projects without including external
partners, it can be useful to follow up on, to understand why and to investigate the outcome of these
projects. Cross functional collaborations have become increasingly valuable for many firms,
including Company X, and both internal and external collaborations should be encouraged to
improve the innovation capability (Saunila and Ukko, 2012).
The necessity for innovating with customers and partners is something that was emphasized by
Company X, nonetheless, it is also mentioned that they still need to become better at it. Metric 3.1
might, therefore, visualise if there are any patterns to when the customers or partners are involved
or not. At the same time as it is essential that Company X collaborates externally, it also involves
risks and challenges (Alexy, George and Salter, 2013). Thus, to mitigate risks and understand the
customer better, Metric 3.2 was deemed suitable (Tidd and Bessant, 2013).
To link the issue with transferring innovation into the core organisation and to find an internal
receiver, Metric 3.6 is formulated to ensure that there is responsible for taking the innovation to
the market within the projects. At Company X, this often requires cross functional collaborations
to function, however, it works differently in different units. How the project manager chooses to
go with that, if they assign an internal business owner, within the project, or include someone from
the main sales organisation is, therefore, not determined. Nonetheless it is imperative to think one
step further, beyond the initial phase at an early stage (Mattes and Ohr, 2018,) and to measure the
ability to do so can help to strengthen this skill.
Table 12. Metrics related to cross-functional collaboration.
Metric Dimension Category
3.1 Are there customers or partners closely connected to the project? Project Input
3.2 Is customer analysis and verification made throughout the project? Project Input
3.6 At this stage, has the project a business owner? Project Activity
6.2.5 Scaling up
To include financial metrics, have several purposes. Firstly, it gives a quantitative visualisation of
the investments in innovation, which in turn gives a picture of the available resources. Metric 1.1
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gives an indication of the total investment made in innovation in relation to the total revenue, to
put the quantitative number in relation to the organisational revenue. Secondly, financial metrics
connect amount dedicated to means available, which is one of the ultimate goals of building
innovation capability - to improve the financial performance of the firm (Wang and Ahmed, 2007).
According to Chan et al. (2008) it is useful to link innovation measurement to shareholder value,
as it tends to increase the attention given to innovation as well as the willingness to invest. Metric
1.5 is aiming to visualise how much new products or services has contributed in terms of sales in
relation to the total sale. Metric 2.4 is complementing 1.5 as it indicates how many products or
services that has been launched that year. It is, however, important to be aware of how to define
‘sales from new products or services’, as it could be a potential source of misinterpretation. Here,
it is defined as products launched within the past year, but the time frame is not obvious. As it
might take some time before new products gain significant market shares, that might not happen
within the first year. Lastly, Metric 3.7 captures the goal fulfilment of the projects, which is a
simple metric, but still valuable. The goals do not have to be purely financial however, it can be
beneficial to have some goals linked to aspects such as organisational learning.
The ability to scale up the innovation projects is associated with creating business impact and
delivering long-term value (Mattes and Ohr, 2018). It is proven to be difficult for incumbent firms
to find good processes for scaling up their innovation projects, and one of the underlying reasons
is that the link between the innovation departments and the core organisation is underdeveloped
(Mattes and Ohr, 2018). For a multinational organisation, the ability to scale up innovations and to
transfer them to all markets is recognised as essential by Company X, but also as a major challenge.
Winter and Szulanski (2001) claim that the ability to diffuse innovative products and services to
other parts of the organisation is a sign of a successful scale up processes. Given this, metric 1.4 is
useful to visualise how the ability to transfer projects between markets, on a portfolio level, and
indicate how well the scale up process is working.
Table 13. Metrics related to scaling up.
Metric Dimension Category
1.1 Percent of the revenue invested in innovation Portfolio Input
1.4 How many offers have been transferred to other markets? Portfolio Activity
1.5 Sales from new products or services (launched less than 3 years ago) in
relation to the total sales during past 3 years?
Portfolio Output
2.4 Number of products or services launched on the market during the past 12
months?
Process Output
3.7 How has the project reached its goals? Project Output
6.2.6 Communication
There are several implications connected to communication in relation to innovation capability and
has, therefore, been identified as a key success factor to innovation capability. The factor
communication has, as mentioned, the underlying dimensions internal communication, external
communication and knowledge management. However, no specific metrics have been assigned to
this key success factor since the results from the measurement are often used to improve
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communication (Froehle and Roth, 2000; Brattström et al., 2018), which also can be a useful tool
for Company X. The communication is measured indirectly in the framework, by the customer
orientation metrics, as those require a high level of communication.
Control systems are also closely related to communication since, depending on the selected metrics,
the control system will provide different types of information and the most suitable communication
forums will differ (Simons, 1995). Therefore, it is important for Company X to select the most
suitable control system for each metric. The metrics with low ambiguity will benefit from having
lean information, where it is not necessary to have high interaction between the people sharing
information. Meanwhile, the metrics with high ambiguity need to have rich information, and thus
the analysis of the measurement will benefits from having face-to-face communication. Through
rich information exchange for the metrics with high ambiguity, Company X will be able to both
understand their external environment as well as understand the interdependence of internal factors
that affects their measurements and metrics.
Further, it is important for Company X to use the gathered data to improve knowledge management
and to give feedback to the organisation based on the findings from the data. A high ability to
manage and share knowledge is associated with innovation capability (Tamer Cavusgil, Calantone
and Zhao, 2003; Lin, 2007). Many project-based functions and organisations struggle with
establishing efficient knowledge management processes (Pemsel and Wiewiora, 2013). Within
Company X, there is an awareness around the benefits of knowledge sharing and some units are
working with formal or informal methods to share knowledge. However, there is also room for
establishing more structured systems for governing and managing knowledge. The reasons as to
why incumbent firms struggle with knowledge sharing can be low interaction between independent
projects, silos between units and lack of formal knowledge governing systems (Zika-Viktorsson,
Sundström and Engwall, 2006, Pemsel and Wiewiora, 2013). Increased transparency due to the
collection, monitoring and visualisation of data might, therefore, reduce silos and increase
interaction.
Another interesting aspect of knowledge management is the possibility to use portfolios and project
management offices as knowledge governing units within an organisation (Pemsel and Wiewiora,
2013). In the ongoing centralisation within Company X, the overarching business innovation unit
has initiated portfolio management, and are arranging regular meetings to increase communication
and information sharing within the organisation. This is one of the most important aspects to predict
portfolio success according to Jonas, Kock and Gemünden (2013), who have identified both quality
of information and cooperation quality as major indicator on the success of the portfolio.
6.2.7 Verifying the Metrics
Throughout this chapter, 19 metrics that are connected to the identified KSF have been suggested.
According to the authors of the framework, every cell in the framework (illustrated in Figure 19
should have at least one metric. This will provide a holistic evaluation of the innovation capability.
To verify that the suggested metrics are enough to evaluate a telecom firms’ innovation capability,
the metrics are presented below in three tables, for each level of assessment (i.e. portfolio, process
and project).
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Table 14. Suggested metrics on portfolio-level in the selected measurement framework.
1. Portfolio
Input
1.1 Percent of the revenue invested in innovation the past fiscal year
1.2 Percent of total investments dedicated to (core/adjacent/transformational)
Activity
1.3 Percent of ongoing projects of core/adjacent/transformational nature?
1.4 How many offers have been transferred to other markets?
Output
1.5 Sales from new products or services (launched less than 3 years ago) in relation to the total sales in
the organisation during past 3 years?
1.6 Percent of projects cancelled?
1.7 Total customer satisfaction with new products or services due to innovation?
Table 14 illustrates the metrics on portfolio level. Since all the three points of measurements (input,
activity and output) have designated metrics it can be considered as sufficient. The portfolio-
metrics are corresponding to the key success factors: innovation strategy, decision making
processes, customer orientation and scaling up.
Table 15. Suggested metrics on process-level in the selected measurement framework.
2. Process
Input
2.1 To what extent have we created ideas with external partners (e.g. customers)? (Percent of total
amount of projects)
Activity
2.2 Total number of projects running according to plan in relation to total number of projects?
(Percent)
2.3 Number and percent of projects in different stages of the innovation process?
Output
2.4 Number of products or services launched on the market during this fiscal year?
Table 15 illustrates the metrics on process level. There are metrics for input, activity and output
and thus the process level, for measuring the innovation capability, presented in this thesis, can be
regarded as acceptable. The process metrics are a result of the key success factors: innovation
strategy, decision making processes, customer orientation and scaling up.
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Table 16. Suggested metrics on portfolio-level in the selected measurement framework.
3. Project
Input
3.1 Are there customers or partners closely connected to the project?
3.2 Is customer analysis and verification made throughout the project?
Activity
3.3 Percent of total time the project has been paused?
3.4 Number of tests with customer until now?
3.5 How many weeks have the project been active this far?
3.6 At this stage, has the project a business owner?
Output
3.7 How has the project reached its goals?
3.8 How has the project supported our sustainability goals?
Finally, Table 16 illustrates the metrics on project level where all three points of measurements
also have appointed metrics. The project-metrics is related to the key success factors: innovation
strategy, decision making processes, customer orientation, cross functional collaborations and
scaling up.
Since metrics are appointed to all parts of the selected framework, the suggested measurements can
be enough to evaluate and improve the innovation capability for Company X. The key success
factors with most assigned metrics are; Innovation Strategy, scaling up and decision-making
processes and has, through empirical findings and literature, been considered as the most crucial
factors to measure. The key success factor Communication is not included in the metrics since it is
indirectly connected to the other key success factors, however, since it is an essential part after the
data collection, to spread information and improve organisational learning, which further can
improve the innovation capability (Tamer Cavusgil, Calantone and Zhao, 2003)
6.2.8 Synthesis of Innovation Measurement at Company X
This section aimed at answering RQ2. To answer this question, the findings from section 6.1 was
used to provide a theoretical foundation for investigating innovation measurement. According to
research, innovation measurement can provide a powerful tool to monitor, evaluate and visualise
innovation capability. Key success factors, as well as metrics, are company specific, and the
suggested metrics enables a holistic perspective of the innovation capability at Company X.
However, they might not be useful for all companies. Nonetheless, innovation strategy, decision
making processes and scaling up have been considered the most central key success factors, and
might, therefore, be applicable to more firms with similar preconditions as Company X.
First, measuring innovation can be a first step to attain a holistic perspective of the innovation
activities. This can later be used to take conscious decisions, that are aligned with the strategy and
founded of actual data. It can further be used to understand which targets that are important to
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improve and streamline the innovation activities. The compiled data can serve as decision support
when updating or developing the innovation strategy.
Second, innovation measurement can be used to increase the communication, both internally as
well as externally, and increase the transparency within a firm. Internally, through minimizing
overlapping work and increase the knowledge management, the innovation capability can be
improved. Implementing an innovation measurement system can also increase the attention to the
innovation activities, which later can improve the conditions for decision-making processes and
internal collaborations. Externally, communicating insights gathered from innovation
measurement can facilitate the management of the expectations from shareholders - from requiring
instant profitability to valuing a firm’s future potential.
Third, through continuously and consistently monitor, measure and evaluate the innovation
activities over a longer time, previously unmonitored patterns might be identified which later can
be utilised or improved. Selecting a suitable control system will be crucial to gain as much
knowledge and benefits as possible from the innovation measurement, and the metrics will
determine which system is the most suitable. Hence improving the innovation measurement can
assist in building long-term innovation capability and through that improving the future strategic
position.
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7. Discussion The purpose of this thesis is to evaluate the key success factors for innovation capability at
incumbent firms within the telecom sector. The thesis consists of a literature review and a case
study divided into three parts. The first part aimed to identify the most suitable framework for
assessing the innovation capability at Company X, and the second part evaluated the current
situation at the company based on the key success factors for innovation capability. The third part
proposed a set of metrics based on the framework and the current situation at the case company.
This section provides an analysis and discussion of the main findings, from both literature as well
as the empirical case study.
7.1 Key Success Factors for Innovation Capability
The purpose of this thesis is to evaluate what the KSF for innovation capability are for an incumbent
telecom firm and investigate how innovation measurement can be used to improve innovation
capability. The thesis consists of a literature review and a case study, divided into three parts. The
first part aimed to identify the most suitable framework for assessing innovation capability at
Company X, whereas the second part evaluated the current situation at Company X, regarding their
innovation capability and proposed six KSF for innovation capability for Company X. The third
part presented a set of metrics, based on the framework, the KSF and the current situation at the
case company. The full set of proposed metrics can be found in Table 14, 15 and 16. These metrics
are structured according to the theoretical framework and the identified KSF, based on the approach
suggested by the framework, as well as from the literature. The goal is to capture the most critical
aspects of innovation capability and to visualise the current state through the composition of
metrics.
The findings from this thesis suggests that measuring innovation capability, through the process of
first identifying KSF, and thereafter metrics, can be a valuable tool for incumbent telecom firms to
improve their innovation performance. The selected framework is suitable for large incumbent
firms working with high-tech service, and might, therefore, be useful for firms for similar firms.
The identified KSF for the case company in relation to innovation capability are: innovation
strategy, decision making processes, scaling up, xx, xx. Given that the KSF are identified both in
the literature as well as through the empirical findings as essential for innovation capability, there
are reason to believe that some of them are generalizable for other companies in similar situations.
Through the innovation capability measurement, firms can increase their insight and awareness to
the innovation activities which can improve internal engagement, brand perception and change the
expectations from stakeholders. This suggests that communication regarding a firm’s innovation
capability can increase the firm’s control of their future position.
7.2 Implications for Practice
Establishing an innovation capability measurement framework should be an iterative, long-term
and continuous process, which needs time and effort to generate results (Richtnér et al., 2017;
Brattström et al., 2018). It is not a quick fix solution, rather than it is an instrument which can be
part of a bigger solution. Innovation strategy should be dynamic and needs to be continuously
84
updated to stay aligned with the external environment and internal business changes (Franceschini,
et al., 2007). Hence, the metrics also need to be development iteratively.
7.2.1 Measurement Management and Control
The most common traps when measuring innovation capability are to overestimate the
measurement instrument itself (and not seeing it as part of a bigger control solution), to use too
many or too few metrics or only measure parts but not the whole (Richtnér et al., 2017). These are
all relevant aspects to incorporate into the control design process. The frameworks can help to
create a holistic perspective of the innovation capability from several dimensions and perspectives,
but as the metrics will be developed and changed, the holistic perspective needs to be considered.
It is also essential to be realistic with the number of metrics used - over measuring is not going to
improve the results, instead it can complicate the interpretation and analysis of the results. Further,
Richtnér et al. (2017) have also warned about internal politics as a critical factor in the innovation
measuring process and raise the concern of overlooking the impact of politics. They suggest a
cross-functional approach to innovation measurement, where teams across the whole value chain
are included to mitigate internal resistance. It is also helpful to invest some time in getting everyone
onboard with the measurement process, so that everyone understands the purpose and the
objectives. As internal politics was mentioned as an obstructing factor at Company X, these aspects
will most likely be relevant considerations to take into the future.
Although it is essential to select adequate metrics when measuring innovation capability, a control
systems is also needed, to ensure that outcome from the measurement is aligned with the innovation
strategy (Simons, 1995). For firms that lack an innovation strategy, the desired outcome might not
be clearly stated, such as Company X. Therefore, the metrics considered as critical for the firm
which have a high level of ambiguity an interactive control system should be used where the
metrics are discussed by managers and employees from all levels, preferably in a face-to-face
meeting (Simons, 1995). Through discussing specific metrics, insights about the specific metric
can be gained, but it can further provide knowledge for how to adjust the innovation strategy
(Parmenter, 2015).
7.3 Sustainable Development
Sustainable development is considered as a central factor for firms to include in their business
model, since stakeholders and the society expect that firms should to take responsibility and work
toward UN’s sustainable development goals (Lowitt, 2013). Further, being prominent within
sustainability is considered a competitive advantage, which also motives many companies to
actively work towards sustainable development (Lowitt, 2013). Company X, and other large
incumbent telco firms, have the potential to make considerable impacts in terms of their
sustainability work, since they tend to work in large scales. As mentioned in section 1.5, innovation
and sustainable development is closely related (Weaver, 2000) and through identifying the KSF
for how incumbent telecom companies can improve their innovation capability, this paper might
be able to improve Company X and other firms’ sustainability work. Furthermore, through
identifying challenges related to the innovation process, an awareness of areas which need to be
further investigated or improved, such as promoting a more long-term time-horizon, might also, in
the long-term, benefit sustainable development.
85
Due to the close connection between innovation and sustainability, as well as the fact that
sustainability is supposed to permeate everything that Company X do - one of the suggested metrics
is also focused on the firm’s sustainable development goals (metric 3.8). Since measurements can
be used to increase attention and engagement (Richtnér et al., 2017) and the suggested metric is a
lagging metric (Davila, Epstein and Shelton, 2012), which, thus, evaluates how well the strategy
has been aligned with the innovation activities (Franceschini, et al., 2007; Brattström et al., 2018).
7.4 Limitations
This study has several limitations that needs to be considered when interpreting the findings. First,
there are a certain level of ambiguity around the field of innovation capability, which makes it
difficult to compare studies and findings. Since innovation capability is different in each
organisation and as this study has only focused on one case company, there is a risk that some of
the identified issues are specific to Company X. However, by including external industry experts
as participants in the study, as well as to thoroughly compare the findings with the existing
literature, the reliability of the findings might have been improved. Furthermore, most of the
interviewees from Company X work primarily with innovation, thus, the results might be coloured
by their perspective. To include more people from other areas might have provided a broader and
more generalised picture of the operations.
Additionally, the body of knowledge regarding innovation, service innovation as well as innovation
measurements are growing steadily, with new theories entering constantly, and there are many
conflicting opinions. This study is based on the assumed definitions of innovation capability and
service innovation, and through reading an extensive amount of literature, assumptions have been
made to narrow the scope. With that said, some research might have been missed, which could
have led to wrongfully made assumptions.
7.5 Future work
This thesis has contributed to the diverse and conflicting research fields within innovation
capability, service innovation and innovation measurement. The findings are built upon the Service
Dominant Logic, the concept of innovation capability, as part of dynamic capability, and it, further,
explores Björk and Frishammar’s (2019) framework for measuring innovation capability. Through
collecting empirical data from a Swedish incumbent telecom firm, the study consolidates the
research areas, to provide specific KSF for innovation capability for incumbent telecom firms. A
previously, not thoroughly explored research area.
While the field of innovation measurement is emerging and the body of knowledge around this
field is increasing continuously, there are still many opportunities to be explored. We propose that
future studies focus on complementing the theoretical research with case studies on how innovation
capability can be measured and, through that, improved. From an industrial viewpoint, it would
also be beneficial to investigate how innovation capability can be used as a competitive advantage
in a fast-paced transformative industry with new players entering the market.
Another angle that has been re-occurring throughout the project and could be interesting for future
work is the cultural aspect. It is identified as a dimension of innovation capability by several
86
researchers (Lawson and Samson, 2001; Skarzynski and Gibson, 2008; Paalanen et al., 2009,
Saunila and Ukko, 2012). Further, it was also highlighted as an important factor that affect the
organisation to a high extent. However, culture was not included in this project, mainly due to time
and resource limitations. Measuring culture and environmental aspects connected to innovation
capability would most likely be of a different nature and require a higher level of qualitative
estimation and evaluations. Further, as described in Section 2.2.2 innovation capability is a part of
the dynamic capability, according to Wang and Ahmed’s (2007) framework. Therefore, evaluating
a large telecom operator regarding their entire dynamic capability (i.e. innovation capability,
adaptive capability and absorptive capability) could further improve their chance be successful in
the long-term perspective and be profitable in a rapidly changing business environment.
87
9. References Adams, R., Bessant, J. and Phelps, R. (2006). Innovation management measurement: A review. International Journal
of Management Reviews, 8(1), pp.21-47.
Aghion, P., Van Reenen, J. and Zingales, L. (2010). Innovation and Institutional Ownership. SSRN Electronic Journal.
Alexy, O., George, G., and Salter, A. (2013). Cui bono? The selective revealing of knowledge and its implications for
innovative activity. Academy of Management Review 38 (2): 270–91.
Allee, V. and Taug, J. (2006). Collaboration, innovation, and value creation in a global telecom. The Learning
Organization, 13(6), pp.569-578.
Almega. (2018). IT- Och Telekombranschens Utveckling - Almega. [online] Available at:
<https://www.almega.se/statistik/it-och-telekombranschen/> [Accessed 12 April 2020].
Anthony, S., Sinfield, J., Johnson, M. and Altman, E. (2008). The Innovator's Guide To Growth. Boston, Mass.:
Harvard Business Press.
Baines, T., Lightfoot, H., Benedettini, O. and Kay, J. (2008). The servitization of manufacturing 'A review of literature
and reflection on future challenges'. Journal of Manufacturing Technology Management, 20(5), pp.547-567.
Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), pp.99-120.
Barras, R. (1990). “Interactive Innovation in Financial and Business Services: The Vanguard of the Service
Revolution,” Research Policy (19), pp. 215-237.
Barreto, I. (2009). Dynamic Capabilities: A Review of Past Research and an Agenda for the Future. Journal of
Management, 36(1), pp.256-280.
Barrett, M., Davidson, E., Prabhu, J. and Vargo, S. (2015). Service Innovation in the Digital Age: Key Contributions
and Future Directions. MIS Quarterly, 39(1), pp.135-154.
Beers, B. (2019). What Is The Telecommunications Sector?. [online] Investopedia. Available at:
<https://www.investopedia.com/ask/answers/070815/what-telecommunications-sector.asp> [Accessed 12
April 2020].
Belkahla, W. and Triki, A. (2011). Customer knowledge enabled innovation capability: proposing a measurement
scale. Journal of Knowledge Management, 15(4), pp.648-674.
Bessant, J. and Tidd, J. (eds). (2007) Innovation and entrepreneurship. John Wiley, West Sussex, England
Birchall, D., Chanaron, J., Tovstiga, G. and Hillenbrand, C. (2011). Innovation performance measurement: current
practices, issues and management challenges. International Journal of Technology Management, 56(1), pp.1-
19.
Björk, J. and Frishammar, J. (2019). Innovationsstark. 1st ed. Laholm:
https://innovationsstark.se/innovationsstark.pdf.
Björk, P. (2014). The DNA of Tourism Service Innovation: A Quadruple Helix Approach. Journal of the Knowledge
Economy, 5(1), pp.181-202.
Blomkvist, P. and Hallin, A. (2015). Methods for engineering students: Degree projects using the 4-phase Model. 1st
ed. Lund: Studentlitteratur AB.
Bohlin, E., Brousseau, E., and Hulten, S. (2001). Innovation in the telecommunications industry. Economics of
Innovation & New Technology. 10. 73-87.
Boly, V., Morel, L., Assielou, N. and Camargo, M. (2014). Evaluating innovative processes in french firms:
Methodological proposition for firm innovation capacity evaluation. Research Policy, 43(3), pp.608-622.
Boudreau, K. (2010). Open Platform Strategies and Innovation: Granting Access vs. Devolving Control. Management
Science, 56(10), pp.1849-1872.
Brattström, A., Frishammar, J., Richtnér, A. and Pflueger, D. (2018). Can innovation be measured? A framework of
how measurement of innovation engages attention in firms. Journal of Engineering and Technology
Management, 48, pp.64-75.
Breznik, L. and D. Hisrich, R. (2014). Dynamic capabilities vs. innovation capability: are they related?. Journal of
Small Business and Enterprise Development, 21(3), pp.368-384.
Brochet, F., Loumioti, M. and Serafeim, G. (2015). Speaking of the short-term: disclosure horizon and managerial
myopia. Review of Accounting Studies, 20(3), pp.1122-1163.
Bruce, M., Leverick, F. and Littler, D. (1995). Complexities of collaborative product development. Technovation,
15(9), pp.535-552.
Calantone, R., Cavusgil, S. and Zhao, Y. (2002). Learning orientation, firm innovation capability, and firm
performance. Industrial Marketing Management, 31(6), pp.515-524.
Capozzi, Gregg and Howe. (2010). McKinsey Global Survey “Innovation and commercialization”.
88
Caylar, P. L., Menard A. (2016). How telecom companies can win the digital revolution. The McKinsey Quarterly.
Chae, B. (2012). An evolutionary framework for service innovation: Insights of complexity theory for service science.
International Journal of Production Economics, 135(2), pp.813-822.
Chan, V., Musso C., Shankar, V. (2008). Assessing Innovation Metrics: McKinsey Global Survey Results. The
McKinsey Quarterly.
Chase R. (2010). Revisiting “Where Does the Customer Fit in a Service Operation?”, in Maglio P.P. et al (ed),
Handbook of Service Science. Springer Science, Business Media, LLC pp. 11-18
Christensen, C., & Rosenbloom, R.S. (1995) Explaining the attacker's advantage: Technological paradigms,
organizational dynamics, and the value network. Research Policy, 24(2), p. 233-257.
Christensen, C., Raynor, M. and Van Bever, D. (2013). The innovator's solution, revised and expanded. Harvard
Business School Publ.
Cohen, W. and Levinthal, D. (1990). Absorptive Capacity: A New Perspective on Learning and Innovation.
Administrative Science Quarterly, 35(1), p.128.
Coombs, R., & Miles, I. (2000). Innovation, measurement and services: The new problematique. In J. S. Metcalfe, &
I. Miles (Eds.), Innovation systems in the service economy (pp. 85–103)
Cooper, R. (1988). The new product process: a decision guide for management. Journal of Marketing Mangement,
3(3). 238-255.
Cooper, R. (2013). Where Are All the Breakthrough New Products?: Using Portfolio Management to Boost Innovation.
Research-Technology Management, 56(5), pp.25-33.
Cope, M. (2010). Coding qualitative data. Qualitative Research Methods in Human Geography. 223-233.
Cowell, D. (1988). New service development. Journal of Marketing Management, 3(3), pp.296-312.
Creswell, J. W. (2014), Research design: Qualitative, quantitative, and mixed methods approaches, Sage publications.
Cuijpers, M., Guenter, H. and Hussinger, K. (2011). Costs and benefits of inter-departmental innovation collaboration.
Research Policy, 40(4), pp.565-575.
Dahlander, L. and Gann, D. (2010). How open is innovation?. Research Policy, 39(6), pp.699-709.
Davila, A., Foster, G. and Oyon, D. (2009). Accounting and Control, Entrepreneurship and Innovation: Venturing into
New Research Opportunities. European Accounting Review, 18(2), pp.281-311.
Davila, T., Epstein, M. and Shelton, R. (2012). Making innovation work. 2nd ed. Upper Saddle River, N.J.: FT Press.
den Hertog, P. and De Jong, G. (2007). Randstad’s business model of innovation: Results from an exploratory study
in the temporary staffing industry. Innovation, 9(3-4), pp.351-364.
den Hertog, P., van der Aa, W. and de Jong, M. (2010). Capabilities for managing service innovation: towards a
conceptual framework. Journal of Service Management, 21(4), pp.490-514.
Denford, J. (2013). Building knowledge: developing a knowledge‐based dynamic capabilities typology. Journal of
Knowledge Management, 17(2), pp.175-194.
Deschamps, J. and Nelson, B. (2015). Recognizing The Imperatives For An Effective Governance System. Innovation
Governance, pp.299-319.
Ditillo, A. and Caglio, A. (2009). Controlling Collaboration Between Firms. Burlington: Elsevier Science.
Djellal, F., Gallouj, F. and Miles, I. (2013). Two decades of research on innovation in services: Which place for public
services?. Structural Change and Economic Dynamics, 27, pp.98-117.
Dougherty, D. (1992). Interpretive Barriers to Successful Product Innovation in Large Firms. Organization Science,
3(2), pp.179-202.
Dubois, A. and Gadde, L. (2002). Systematic combining: an abductive approach to case research. Journal of Business
Research, 55(7), pp.553-560.
Edison, H., bin Ali, N. and Torkar, R. (2013). Towards innovation measurement in the software industry. Journal of
Systems and Software, 86(5), pp.1390-1407.
Edvardsson, B., Gustafsson, A. and Roos, I. (2005). Service portraits in service research: a critical review. International
Journal of Service Industry Management, 16(1), pp.107-121.
Edvardsson, B., Meiren, T., Schäfer, A. and Witell, L. (2013). Having a strategy for new service development – does
it really matter?. Journal of Service Management, 24(1), pp.25-44.
Eisenhardt, K. and Martin, J. (2000). Dynamic capabilities: what are they? Strategic Management Journal, 21(10-11),
pp.1105-1121.
Ferreira, J., Raposo, M. and Fernandes, C. (2013). Does innovativeness of knowledge-intensive business services differ
from other industries? 33(7–8), pp. 734–748.
Fitzsimmons, J. A., & Fitzsimmons, M. (2010). Service management: Operations, strategy, and information technology
(7th ed.) New York: McGraw Hill.
89
Flammer, C. and Bansal, P. (2017). Does a long-term orientation create value? Evidence from a regression
discontinuity. Strategic Management Journal, 38(9), pp.1827-1847.
Flick, U. (2014). The SAGE Handbook of Qualitative Data Analysis.
Forrer, J., Kee, J. and Boyer, E. n.d. Governing Cross-Sector Collaboration. San Francisco CA Jossey Bass.
Franceschini, F., Galetto, M., Maisano, D. and Neely, A. (2007). Designing Performance Measurement Systems.
Springer, Berlin, Heidelberg.
Frishammar, J. and Hörte, S-Å. (2005). Managing External Information in Manufacturing Firms: The Impact on
Innovation Performance*. Journal of Product Innovation Management, 22(3), pp.251-266.
Frishammar, J., Kurkkio, M., Abrahamsson, L. and Lichtenthaler, U. (2012). Antecedents and Consequences of Firms’
Process Innovation Capability: A Literature Review and a Conceptual Framework. IEEE Transactions on
Engineering Management, 59(4), pp.519-529.
Froehle, C. and Roth, A. (2009). A Resource-Process Framework of New Service Development. Production and
Operations Management, 16(2), pp.169-188
Företagskällan. (2016). Avregleringen Av Telemarknaderna - Företagskällan. [online] Available at:
<https://www.foretagskallan.se/foretagskallan-nyheter/lektionsmaterial/avregleringen-av-telemarknaderna/>
[Accessed 10 May 2020].
Gadrey, J., Gallouj, F. and Weinstein, O. (1995). New modes of innovation. International Journal of Service Industry
Management, 6(3), pp.4-16.
Gallouj, F. and Weinstein, O. (1997). Innovation in services. Research Policy, 26(4-5), pp.537-556.
Gatignon, H., Tushman, M., Smith, W. and Anderson, P. (2002). A Structural Approach to Assessing Innovation:
Construct Development of Innovation Locus, Type, and Characteristics. Management Science, 48(9),
pp.1103-1122.
Geissdoerfer, M., Bocken, N. and Hultink, E. (2016). Design thinking to enhance the sustainable business modelling
process – A workshop based on a value mapping process. Journal of Cleaner Production, 135, pp.1218-1232.
Gimbert, X., Bisbe, J. and Mendoza, X. (2010). The Role of Performance Measurement Systems in Strategy
Formulation Processes. Long Range Planning, 43(4), pp.477-497.
Gnyawali, D. and Park, B. (2011). Co-opetition between giants: Collaboration with competitors for technological
innovation. Research Policy, 40(5), pp.650-663.
Gray, D., Micheli, P. and Pavlov, A. (2012). Measurement Madness.
Griffin, A. and Hauser, J. (1996). Integrating R&D and Marketing: A Review and Analysis of the Literature. Journal
of Product Innovation Management, 13(3), pp.191-215.
Grineisen, J. and Rehme, G. (2018). Evolution Path: The Telco-centric Digital Ecosystem. Management for
Professionals, pp.309-318.
Grönroos, C. (2008). Service logic revisited: who creates value? And who co‐creates?. European Business Review,
20(4), pp.298-314.
Hamel, G. and Prahalad, C. (1994). Competing for the Future. Harvard Business Review, (July-August 1994), pp.122-
128.
Henderson, R., & Clark, K. (1990). Architectural Innovation: The Reconfiguration of Existing Product Technologies
and the Failure of Established Firms. Administrative Science Quarterly, 35(1), 9-30. doi:10.2307/2393549
Hietanen, J., Andéhn, M. and Bradshaw, A. (2018). Against the implicit politics of service-dominant logic. Marketing
Theory, 18(1), pp.101-119.
Highsmith, J. (2010). Agile Project Management. 2nd ed. Upper Saddle River, N.J.: Addison-Wesley.
Hobbs, B., & Aubry M. (2008). "An Empirically Grounded Search for a Typology of Project Management Offices.".
in Project Management Journal, 39, pp. S69-S82.
Hogan, S., Soutar, G., McColl-Kennedy, J. and Sweeney, J. (2011). Reconceptualizing professional service firm
innovation capability: Scale development. Industrial Marketing Management, 40(8), pp.1264-1273.
Hrebiniak, L. (2006). Obstacles to Effective Strategy Implementation. Organizational Dynamics, 35(1), pp.12-31.
Hsieh, J. and Hsieh, Y. (2015). Dialogic co-creation and service innovation performance in high-tech companies.
Journal of Business Research, 68(11), pp.2266-2271.
Jaw, C., Lo, J. and Lin, Y. (2010). The determinants of new service development: Service characteristics, market
orientation, and actualizing innovation effort. Technovation, 30(4), pp.265-277.
Jonas, D., Kock, A. and Gemünden H. (2013). "Predicting Project Portfolio Success by Measuring Management
Quality—A Longitudinal Study.". in IEEE Transactions on Engineering Management, 60,pp. 215-226.
Kahn, K. and Mentzer, J. (1998). Marketing’s Integration with Other Departments. Journal of Business Research,
42(1), pp.53-62.
90
Kahn, K. (1996). Interdepartmental Integration: A Definition with Implications for Product Development Performance.
Journal of Product Innovation Management, 13(2), pp.137-151.
Kannan P.K., Healey J. (2011). Service Customization Research: A Review and Future Directions. In: Demirkan H.,
Spohrer J., Krishna V. (eds) The Science of Service Systems. Service Science: Research and Innovations in
the Service Economy. Springer, Boston, MA
Kanter, R.M. (1983). The Change Masters. New York: Simon & Schuster
Karmarkar, U., R. Pitbladdo. (1995). Service markets and competition. Journal of Operations Management 12(3/4)
397–411
Kaur, K., Jajoo, A. and Manisha. (2015). Applying Agile Methodologies in Industry Projects: Benefits and Challenges.
2015 International Conference on Computing Communication Control and Automation.
Kelly, M., Schaan, J. and Joncas, H. (2002). Managing alliance relationships: Key challenges in the early stages of
collaboration. R and D Management, 32(1), pp.11-22.
Kuratko, D., Hornsby, J. and Covin, J. (2014). Diagnosing a firm's internal environment for corporate entrepreneurship.
Business Horizons, 57(1), pp.37-47.
Latham, G. and Locke, E. (2006). Enhancing the Benefits and Overcoming the Pitfalls of Goal Setting. Organizational
Dynamics, 35(4), pp.332-340.
Laverty, K. (1996). Economic "Short-Termism": The Debate, the Unresolved Issues, and the Implications for
Management Practice and Research. The Academy of Management Review, 21(3), p.825.
Lawson, B. and Samson, D. (2001). Developing Innovation Capability In Organisations: A Dynamic Capabilities
Approach. International Journal of Innovation Management, 05(03), pp.377-400.
Lee, J., Kao, H. and Yang, S. (2014). Service Innovation and Smart Analytics for Industry 4.0 and Big Data
Environment. Procedia CIRP, 16, pp.3-8.
Levine, H. (2005). Project portfolio management. San Francisco, CA, Jossey-Bass Inc.
Lightfoot, H. and Gebauer, H. (2011). Exploring the alignment between service strategy and service innovation.
Journal of Service Management, 22(5), pp.664-683.
Locke, E. (2019). Some observations about goals, money and cheating in business. Organizational Dynamics, 48(4),
pp 1-5
Lovelace, K., Shapiro, D. and Weingart, L. (2001). Maximizing Cross-Functional New Product Teams' Innovativeness
And Constraint Adherence: A Conflict Communications Perspective. Academy of Management Journal,
44(4), pp.779-793.
Lowitt, E. (2013). The Future Of Value How Sustainability Creates Value Through Competitive Differentiation. San
Francisco, Calif.: Jossey-Bass.
Lumpkin, G. and Brigham, K. (2011). Long-Term Orientation and Intertemporal Choice in Family Firms.
Entrepreneurship Theory and Practice, 35(6), pp.1149-1169.
Lusch, R. and Nambisan, S. (2015). Service Innovation: A Service-Dominant Logic Perspective. MIS Quarterly, 39(1),
pp.155-175.
Maglio, P. and Spohrer, J. (2013). A service science perspective on business model innovation. Industrial Marketing
Management, 42(5), pp.665-670.
Malerba, F. (2005). Innovation and the evolution of industries. Journal of Evolutionary Economics, 16(1-2), pp.3-23.
Margaria, T. and Steffen, B. (2018). Simplicity as a Driver for Agile Innovation. Software Technology: 10 Years of
Innovation in IEEE Computer, pp.17-34.
Marginson, D. and McAulay, L. (2008). Exploring the debate on short-termism: a theoretical and empirical analysis.
Strategic Management Journal, 29(3), pp.273-292.
Markides, C. (1998). Strategic Innovation in Established Companies. Sloan Management Review, 39(3).
Martinsuo, M. and Lehtonen, P. (2007). Role of Single‐Project Management in Achieving Portfolio Management
Efficiency. International Journal of Project Management, 25, 56–65.
Mattes, F. and Ohr, R. (2018). Scaling-Up Corporate Startups. 1st ed. Independently published.
Meifort, A. (2015). Innovation Portfolio Management: A Synthesis and Research Agenda. Creativity and Innovation
Management, 25(2), pp.251-269.
Melnyk, S., Stewart, D. and Swink, M. (2004). Metrics and performance measurement in operations management:
dealing with the metrics maze. Journal of Operations Management, 22(3), pp.209-218.
Melton, H. and Hartline, M. (2012). Employee Collaboration, Learning Orientation, and New Service Development
Performance. Journal of Service Research, 16(1), pp.67-81.
Menor, L. and Roth, A. (2006). New service development competence in retail banking: Construct development and
measurement validation. Journal of Operations Management, 25(4), pp.825-846.
91
Menor, L.J. (2015). ’Illuminating the Service Provider’s Strategic Mandate on Realizing Apt Quality and Value
Through Service Innovation’ In in Agarwal, R. et al. (eds.), The Handbook of Service Innovation, Springer-
Verlag London, pp. 27-51
Merchant, K. and Van der Stede, W. (2012). Management Control Systems. 3rd ed. Harlow, England: Financial Times
Prentice Hall.
Meskendahl, S. (2010). The influence of business strategy on project portfolio management and its success — A
conceptual framework. International Journal of Project Management, 28(8), pp.807-817.
Michel, S., Brown, S. and Gallan, A. (2007). An expanded and strategic view of discontinuous innovations: deploying
a service-dominant logic. Journal of the Academy of Marketing Science, 36(1), pp.54-66.
Mikkola, J. (2001). Portfolio management of R&D projects: implications for innovation management. Technovation,
21(7), pp.423-435.
Miles, I. (2010). Handbook of service science, Service Innovation. New York: Springer, pp.511-533.
Möller, K., Rajala, R. and Westerlund, M. (2008). Service Innovation Myopia? A New Recipe for Client-Provider
Value Creation. California Management Review, 50(3), pp.31-48.
Mone, M., McKinley, W. and Barker, V. (1998). Organizational Decline and Innovation: A Contingency Framework.
The Academy of Management Review, 23(1), pp.115-132.
Mosakowski, E. and Earley, P. (2000). A Selective Review of Time Assumptions in Strategy Research. The Academy
of Management Review, 25(4), p.796.
Muller, A., Välikangas, L. and Merlyn, P. (2005). Metrics for innovation: guidelines for developing a customized suite
of innovation metrics. Strategy & Leadership, 33(1), pp.37-45.
Nagji, B. and Tuff, G. (2012). Managing Your Innovation Portfolio. Harvard Business Review.
O'Reilly, C. and Tushman, M. (2011). Organizational Ambidexterity in Action: How Managers Explore and Exploit.
California Management Review, 53(4), pp.5-22.
Ocasio, W. (1997). Towards an Attention-Based View of the Firm. Strat. Mgmt. J., 18: 187-206.
Ojanen, V. and Vuola, O. (2005). Coping with the multiple dimensions of R&D performance analysis. Int. J. Technol.
Manag. 33, pp.279-290.
Olson, E., Walker, O., Ruekerf, R. and Bonnerd, J. (2001). Patterns of cooperation during new product development
among marketing, operations and R&D: Implications for project performance. Journal of Product Innovation
Management, 18(4), pp.258-271.
Ordanini, A. and Parasuraman, A. (2010). Service Innovation Viewed Through a Service-Dominant Logic Lens: A
Conceptual Framework and Empirical Analysis. Journal of Service Research, 14(1), pp.3-23.
Ostrom, A., Bitner, M., Brown, S., Burkhard, K., Goul, M., Smith-Daniels, V., Demirkan, H. and Rabinovich, E.
(2010). Moving Forward and Making a Difference: Research Priorities for the Science of Service. Journal of
Service Research, 13(1), pp.4-36.
Paalanen, A., Kujansivu, P. and Parjanen, S. (2009). “Measuring the effects of an innovation-focused intervention”,
Proceedings of the XX ISPIM Future of Innovation Conference in Vienna, 21-24 June.
Parmenter, D. (2015). Key Performance Indicators: Developing, Implementing, And Using Winning Kpis. 3rd ed.
Hoboken, New Jersey: John Wiley & Sons, Inc.
Pathak, H. (2010). Organizational Change. Pearson India.
Pellegrinelli, S., Partington, D., Hemingway, C., Mohdzain Z., and Shah M. (2007). "The importance of context in
programme management: An empirical review of programme practices.". in International Journal of Project
Management, 25, pp. 41-55.
Pemsel, S. and Wiewiora, A. (2013). Project management office a knowledge broker in project-based organisations.
International Journal of Project Management, 31(1), pp.31-42.
Pemsel, S. and Müller R. (2012). "The governance of knowledge in project-based organizations.". in International
Journal of Project Management, 30, pp. 865–876.
Pisano, G. (2015). You Need an Innovation Strategy. Harvard Business Review, pp.44-54.
Powell, W. W. (1987). Hybrid organizational arrangements: new form or transitional development? California
Management Review, Fall.
Priem, R. and Butler, J. (2001). Is the Resource-Based "View" a Useful Perspective for Strategic Management
Research? The Academy of Management Review, 26(1), p.22.
PwC. (2019). A Pragmatic Approach For Telcos To Utilise Agile As A Transformation Accelerator. [online]
PwC. Available at: <https://www.pwc.se/sv/branscher/telekom/telekomoperatorer.html> [Accessed 14 April
2020].
Qiu, R. (2014). Service science. Hoboken, New Jersey: Wiley.
92
Rai, A. and Sambamurthy, V. (2006). Editorial Notes—The Growth of Interest in Services Management: Opportunities
for Information Systems Scholars. Information Systems Research, 17(4), pp.327-331.
Raisch, S., Birkinshaw, J., Probst, G. and Tushman, M. (2009). Organizational Ambidexterity: Balancing Exploitation
and Exploration for Sustained Performance. Organization Science, 20(4), pp.685-695.
Randhawa, K. and Scerri, M. (2015). ‘Service Innovation: A Review of the Literature’ in in Agarwal, R. et al. (eds.),
The Handbook of Service Innovation, Springer-Verlag London, pp. 27-51
Rice, R. (1992). Task Analyzability, Use of New Media, and Effectiveness: A Multi-Site Exploration of Media
Richness. Organization Science, 3(4), pp.475-500.
Richtnér, A., Brattström, A., Frishammar, J., Björk, J. and Magnusson, M. (2017). Creating Better Innovation
Measurement Practices. MITSloan Management Review, 59(1), pp.45-54.
Rohrbeck, R., E. Kum, M., Jissink, T. and V. Gordon, A. (2018). How Leading Firms Build a Superior Position in
Markets of the Future. Corporate Foresight Benchmarking Report. Aarhus Universitet.
Ryu, H., Lee, J. and Choi, B. (2015). Alignment Between Service Innovation Strategy and Business Strategy and Its
Effect on Firm Performance: An Empirical Investigation. IEEE Transactions on Engineering Management,
62(1), pp.100-113.
Sampson, S. and Froehle, C. (2006). Foundations and Implications of a Proposed Unified Services Theory. Production
and Operations Management, 15(2), pp.329-343.
Sasser, W.E., Olsen, R.P. and Wyckoff, D.D. (1978). Management of service operations, Allyn and Bacon, Boston,
MA
Saunila, M. and Ukko, J. (2012). A conceptual framework for the measurement of innovation capability and its effects.
Baltic Journal of Management, 7(4), pp.355-375.
Saunila, M., Pekkola, S. and Ukko, J. (2014). The relationship between innovation capability and performance.
International Journal of Productivity and Performance Management, 63(2), pp.234-249.
Schentler, P., Lindner, F. and Gleich, R. (2010). Innovation Performance Measurement. Innovation and International
Corporate Growth, pp.299-317.
Schrader, S., Riggs, W. and Smith, R. (1993). Choice over uncertainty and ambiguity in technical problem solving.
Journal of Engineering and Technology Management, 10(1-2), pp.73-99.
Schumpeter, J. A. (1934). Theory of economic development. Cambridge, MA: Harvard University Press.
Scott, D., Eyring M. and Gibson, L. (2006). Mapping Your Innovation Strategy. Harvard Business Review, pp.44-54.’
Sekaran, U. (2005). Research methods for business– a skill building approach, Fourth edition, John Wiley & Sons,
New York.
Shapiro, A. (2006). Measuring Innovation: Beyond Revenue from New Products. Research-Technology Management,
49(6), pp.42-51.
Simons, R. (1995). Levers of control. Boston, Mass.: Harvard Business School Press.
Skarzynski, P. and Gibson, R. (2008). Innovation to the Core: A Blueprint for Transforming the Way Your Company
Innovates, Harvard Business School Press, Boston, MA.
Snir, Y. (2011). The Telecom Value Chain. [online] ECI's Official Blog. Available at:
<https://blog.ecitele.com/the-telecom-value-chain> [Accessed 12 April 2020].
Spohrer, J. and Maglio, P. (2008). The Emergence of Service Science: Toward Systematic Service Innovations to
Accelerate Co-Creation of Value. Production and Operations Management, 17(3), pp.238-246.
Staber, U. and Sydow, J. (2002). Organizational adaptive capacity: a structuration perspective. Journal of Management
Inquiry, 11, 408–424.
Statista. (2020). Global Telecommunications Industry Revenue By Region 2012-2019 | Statista. [online]
Available at: <https://www.statista.com/statistics/268636/telecommunications-services-revenue-since-2005-
by-region/> [Accessed 12 April 2020].
Stettina, C. and Hörz, J. (2015). "Agile portfolio management: An empirical perspective on the practice in use.". in
International Journal of Project Management, 33, pp. 140-152.
Straub, A. (2011). Maintenance contractors acting as service innovators. Construction Innovation, 11(2), pp.179-189.
Tamer Cavusgil, S., Calantone, R. and Zhao, Y. (2003). Tacit knowledge transfer and firm innovation capability.
Journal of Business & Industrial Marketing, 18(1), pp.6-21.
Teece, D. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise
performance. Strategic Management Journal, 28(13), pp.1319-1350.
Teece, D., Pisano, G. and Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management
Journal, 18(7), pp.509-533.
93
The All European Academies. (2017). The European Code of Conduct for Research Integrity. ALLEA - All European
Academies.
Tidd, J. (2001). Innovation management in context: environment, organization and performance. International Journal
of Management Reviews, 3(3), pp.169-183.
Tidd, J. and Bessant, J. (2013). Managing Innovation: Integrating Technological, Market and Organizational Change.
5th ed. Chichester: Wiley.
Tidd, J. and F.M. Hull. (2003). Service innovation: Organizational responses to technological opportunities and market
imperatives. London: Imperial College Press.
Tidd, J. and F.M. Hull. (2010). ’Managing Service Innovation’ In Salvendy, G. and Karwowski, W. (eds) Introduction
to service engineering. Hoboken, N.J.: John Wiley & Sons. pp.576-601
Toivonen, M. and Tuominen, T. (2009). Emergence of innovations in services. The Service Industries Journal, 29(7),
pp.887-902.
Trott, P. (2012). Innovation management and new product development, 5th edn. Pearson, Education, Essex, England
Troy, L., Hirunyawipada, T. and Paswan, A. (2008). Cross-Functional Integration and New Product Success: An
Empirical Investigation of the Findings. Journal of Marketing, 72(6), pp.132-146
Tura, T., Harmaakorpi, V. and Pekkola, S. (2008). Breaking inside the black box: towards a dynamic evaluation
framework for regional innovative capability. Science and Public Policy, 35(10), pp.733-744.
Un, C., Cuervo-Cazurra, A. and Asakawa, K. (2010). R&D Collaborations and Product Innovation*. Journal of
Product Innovation Management, 27(5), pp.673-689.
United Nations (2015). Sustainable Development Goals.:. Sustainable Development Knowledge Platform. [online]
Available at: https://sustainabledevelopment.un.org/?menu=1300 [Accessed 2 Mar. 2020].
van Dinther C., Blau B. and Conte T., Weinhardt C. (2011). Designing Auctions for Coordination in Service Networks.
In: Demirkan H., Spohrer J., Krishna V. (eds) The Science of Service Systems. Service Science: Research
and Innovations in the Service Economy. Springer, Boston, MA
Vargo, S. and Lusch, R. (2004). Evolving to a New Dominant Logic for Marketing. Journal of Marketing, 68(1), pp.1-
17.
Vargo, S. and Lusch, R. (2008). From goods to service(s): Divergences and convergences of logics. Industrial
Marketing Management, 37(3), pp.254-259.
Wallin, M. and Von Krogh, G. (2010). Organizing for Open Innovation: Organizational Dynamics, 39(2), pp.145-154.
Wang, C. and Ahmed, P. (2004). The development and validation of the organisational innovativeness construct using
confirmatory factor analysis. European Journal of Innovation Management, 7(4), pp.303-313.
Wang, C. and Ahmed, P. (2007). Dynamic capabilities: A review and research agenda. International Journal of
Management Reviews, 9(1), pp.31-51.
Weaver, P. (2000). Sustainable Technology Development. International Journal of Sustainability in Higher Education,
1(3), pp.305-308.
Widener, S. (2007). An empirical analysis of the levers of control framework. Accounting, Organizations and Society,
32(7-8), pp.757-788.
Wiggins, R. and Ruefli, T. (2005). Schumpeter's ghost: Is hypercompetition making the best of times shorter? Strategic
Management Journal, 26(10), pp.887-911.
Winter, S. (2003). Understanding dynamic capabilities. Strategic Management Journal, 24(10), pp.991-995.
Winter, S. and Szulanski, G. (2001). Replication as Strategy. Organization Science, 12(6), pp.730-743
Witell, L., Snyder, H., Gustafsson, A., Fombelle, P. and Kristensson, P. (2016). Defining service innovation: A review
and synthesis. Journal of Business Research, 69(8), pp.2863-2872.
Yin, R. (1994). Case Study Research: Design and Methods. 2nd ed. Thousand Oaks: Sage Publications.
Zahra, S., Sapienza, H. and Davidsson, P. (2006). Entrepreneurship and Dynamic Capabilities: A Review, Model and
Research Agenda*. Journal of Management Studies, 43(4), pp.917-955.
Zika-Viktorsson, A., Sundström P., & Engwall P. (2006). "Project overload: An exploratory study of work and
management in multi-project settings.". in International Journal of Project Management, 24, pp. 385-394.
Zollo, M. and Winter, S. (2002). Deliberate Learning and the Evolution of Dynamic Capabilities. Organization
Science, 13(3), pp.339-351.
I
Appendix I – Workshop Material Source: Björk and Frishammar, 2019.
Dimension Questions
Portfolio
To what extent are we making conscious and strategic choices to balance the portfolio, in the
resource allocation to the different areas, technologies and projects we want to accomplish?
To what extent are we aware of, and evaluate the balance between high and low risk project,
large and small projects, and radical and incremental innovation projects, as well as the
distribution between different technical areas?
Process
What requirements is there today, on the speed of the innovation process? How would you like
it to be?
How are you working with distribution of resources to the innovation process? How do you
think it should be?
What output measurements are used to evaluate the innovation process? How do you think it
should be?
Do you currently have a process that is functioning according to how it should be, in your
opinion? Are there aspects that you already know you need to improve to avoid inactive
projects?
Project
Are projects sometimes paused, and do you know the reason as to why that might happen?
Do we have enough slack available for unpredicted events, in the innovations projects that we
run? Do we have the ability to quickly start new projects when the opportunity is given?
Are there mechanisms to ensure external feedback on the projects progress integrated in the
projects?
What is the most important aspect in our projects: time, cost or quality?
II
Appendix II – List of Interviewees
Interviewee
code Profile of interviewee
Focus
perspective Date Channel
Length
[min]
I-01 Senior Vice President of the Global Operations. Strategic 27.03.20 Video 60
I-02 Executive of the Global Innovation Department. Strategic 26.03.20 Video 60
I-03 Director over country-specific innovation
department.
Strategic
Operational 26.03.20 Video 75
I-04 Head of a technical, country-specific innovation
department.
Operational
Process 26.03.20 Video 60
I-05 Manager within the global incubator
department.
Strategic
Operational 26.03.20 Video 60
I-06 Head of operational excellence in the global
incubator department.
Operational
Process 31.03.20 Video 75
I-07
Manager within communication. Communication 26.03.20 Video 75
I-08
Director over a larger, country-specific
innovation initiative, and innovation
ambassador.
Operational 03.04.20 Video 60
I-09 Commercial manager over a country-specific
innovation department.
Commercial
Operational 30.03.20 Video 60
I-10 Manager for a country-specific innovation
department, focusing on partnerships. Commercial 02.04.20 Video 60
I-11 Sales director for a country-specific
organisation.
External
Commercial 30.03.20 Video 45
I-12 Manager of a country-specific innovation
department and innovation ambassador. Operational 06.04.20 Video 60
I-13
Senior manager for a country-specific
innovation department and innovation
ambassador.
Operational 03.04.20 Video 45
I-14 Manager within a country-specific innovation
and business development.
Strategic
Operational 30.03.20 Video 60
I-15 Senior project manager within country-specific
innovation projects and innovation ambassador. Operational 01.04.20 Video 60
I-16 Business Architect within decision-making
processes. Process 16.04.20 Video 45
I-17 Business and Corporate Developer Strategic
Industrial 17.04.20 Video 45
E-01 External industry expert. Strategic 14.04.20 Video 60
III
Industrial
E-02 External industry expert. Strategic
Industrial 08.04.20 Video 45
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