Patterns of Data-Infused Business Model Innovation

1 Karlsruhe Service Research Institute www.ksri.kit.edu

KSRI – Karlsruhe Service Research Institute

www.kit.eduKIT – The Research University in the Helmhotz Association

Patterns of Data-Infused Business Model Innovation@ IEEE Conference on Business Informatics (CBI), Paris, 2016

Ronny Schüritz, Prof. Dr. Gerhard SatzgerKarlsruhe Service Research Institute (KSRI), Karlsruhe Institute of Technology (KIT)


There is a growing amount of data and a lack of research in the area of data-driven business models

Out of over 600 Chief Operating Officers,

32% have already adopted advanced analytics and modelling tools

63% plan to invest in it within the next 2-5 years

The academic focus has been largely on technical questions round the collection, storage and mining of big data.

Estimate of worldwide data by 2020

0

10000

20000

30000

40000

2005 2010 2012 2015 2020Datavolume in exabyte

Source: V. Turner, J. Gantz, D. Reinsel, and S. Minton, “The digital universe of opportunities: Rich data and the increasing value of the internet of things.” IDC, 2014.IBM, “Redefining Ecosystems,” Somers, NY, 2016.L. Kart, N. Heudecker, and F. Buytendijk, “Survey Analysis : Big Data Adoption in 2013 Shows Substance Behind the Hype.” Gartner, 2013.

30. Aug 2016 Ronny Schüritz - Patterns of Data-Infused Business Model Innovation


It is often claimed that data and analytics bring to bear entirely new “data-based” or “data-driven” business models

Hartmann et al. (2014) analyzed a series of start-ups and categorized them

Chen et al. (2011) illustrates two kinds of service oriented paradigm: Data-as-a-Service (DaaS) and Analytics-as-a-Service (AaaS


Source: P. M. Hartmann, M. Zaki, N. Feldmann, and P. A. Neely, “Big Data for Big Business? A Taxonomy of Data-Driven Business Models Used by Start-Up Firms,” 2014.Y. Chen, J. Kreulen, M. Campbell, and C. Abrams, “Analytics ecosystem transformation: A force for business model innovation,” Proc. - 2011 Annu. SRII Glob. Conf. SRII 2011, pp. 11–20, 2011.


Taking a simple model we evalute how the business model ofincumbents is impacted by data and analytics

Value Proposition

Value Creation

Value Capturing

Based on a conceptual analysis and an evaluation of 115 business models

How does the exploitation of data with analytics affect the business model of an incumbent?

What can be offered to other parties?

How are resources orchestrated to deliver a defined value proposition?

How is the value proposition turned into (monetary) remuneration for the company?



§ EXAMPLE: Saarstahl

§ suffered form a scrape rate of ~32% of the produced steel which is detected after production process

§ now a network of sensors is used to analyze the material during production

§ analysis of data enables the recognition of defect in material in real-time

Pattern 1: Data-infused value creation

§ Data and analytics are used to optimize the way the company operates and creates value

§ Aims at higher efficiency within the company

§ Changes do not affect the customer directly

Value Proposition

Value Creation

Value Capturing



§ Example: Stables online-store§ identifies customers’ location through IP-address§ individual prices based on factors such as:

§ average customer income in that area§ distance to the closest rival “brick-and-mortar” store§ A study unveiled price variation of up to 166% due to geographic

location1

Pattern 2: Data-infused value capturing

§ Data and analytics are used to impact the way business models capture value by creating a better understanding of the customer§ discovery and application of usage

patterns from web data § automated insights into their customer

needs§ make conclusions about the customer’s

individual willingness to pay

Value Proposition

Value Creation

Value Capturing

1 Mikians et al. (2012): Detecting price and search discrimination on the internet, in: Proc. o.t. 11th ACM Workshop on Hot Topics in Networks, pp. 79-84.



§ Example: Rolls Royce

§ Already offering performance-based contracts instead of “simply” selling jet engines to customers (“power-by-the-hour”)

§ Additionally, they collect engine data from a variety of integrated sensors

§ With software VisiumFUEL customers of Rolls Royce can monitor the aircraft’s fuel consumption and identify opportunities for efficiency improvements

Pattern 3: Data-infused value proposition via creation

§ Innovating existing value proposition by offering additional value through data and analytics

§ No changes in value capturing

§ Additional value is contributing to differentiation or strengthening long term loyalty

Value Proposition

Value Creation

Value Capturing



§ Example: Daimler Fleet Board

§ offers a fleet operation service across all industries

§ in cooperation with an insurance company, data and analytics are used to additionally offer highly individualized and flexible price models:

§ they track the driver behavior as well as the intensity of vehicle usage

§ based on this data the insurance premium is calculated on an individual monthly basis

Pattern 4: Data-infused value proposition via capturing

§ Data and analytics change the way value is capture and by that add value in the value proposition

§ The way value is created in their core business model is not impacted

Value Proposition

Value Creation

Value Capturing



Pattern 5: New business models

§ Some companies are able to utilze the full potential of data and analytics for their business model

§ infusing the entire business model eventually creates a completely new, “data-driven” or “data-based” business model

Value Proposition

Value Creation

Value Capturing

§ Example: Verizon Wireless

§ As the biggest mobile phone operator in the US they collect the individual whereabouts of their customers through their regular service

§ They enrich this data with demographic information (e.g. age, gender)

§ Then offer “Precision Market Insights”, a service for businesses, point-of-interest operators, cities, fairs, etc. that helps to gain a better understanding of the customer segments and customer flows



Data-infusion is a continuum and in practice still lacks to createvalue for customers via a data-infused value proposition

Data-infusion is not a binary criterion

Data-infusion cannot onlyused forinternal optimization



Thank you!

Ronny Schüritz

[email protected]://de.linkedin.com/in/ronnyschueritz
