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Recent developments in society and business have triggered the emergence of new forms of organizations, beyond the traditional hierarchical form. A study of contemporary literature and industry practices reveals the following distinct forms: hierarchical, ambidextrous, collaborative, learning and emergent. Simultaneously, embedded within organizations are different types of social networks. Our research indicates classifications of social networks along three key dimensions - the type of response generated by these networks (customized response, modular response and routine response), the centrality of the networks (ego-centric, socio-centric and open networks) and the network architecture (centralized networks, request-based networks, hub-swarms and swarms).This paper examines the relevance of social network types to organizational forms. We have designed a survey instrument based on the Analytic Hierarchy Process to solicit opinions of experts in the above areas. Preliminary results of this initial survey clearly indicate that specific combinations of social network types are found in particular organization forms. Potential applications of this study towards organizational design and transformation are also explored in the paper.
Citation preview
Organizational Forms and Social Network Types –
A Framework for Analysis
Navneet Bhushan, Karthikeyan Iyer
[email protected], [email protected]
Crafitti Consulting Private Limited, Bangalore, India
http://www.crafitti.com
(This paper was communicated to the Social Network Analysis Conference 2008 hosted by Tata
Institute of Social Sciences, Mumbai on Dec 26-27, 2008)
Abstract
Recent developments in society and business have triggered the emergence of new
forms of organizations, beyond the traditional hierarchical form. A study of
contemporary literature and industry practices reveals the following distinct forms:
hierarchical, ambidextrous, collaborative, learning and emergent. Simultaneously,
embedded within organizations are different types of social networks. Our research
indicates classifications of social networks along three key dimensions - the type of
response generated by these networks (customized response, modular response and
routine response), the centrality of the networks (ego-centric, socio-centric and
open networks) and the network architecture (centralized networks, request-based
networks, hub-swarms and swarms).This paper examines the relevance of social
network types to organizational forms. We have designed a survey instrument based
on the Analytic Hierarchy Process to solicit opinions of experts in the above areas.
Preliminary results of this initial survey clearly indicate that specific combinations
of social network types are found in particular organization forms. Potential
applications of this study towards organizational design and transformation are also
explored in the paper.
Introduction
The changing shape and form of organizations is a topic of considerable interest in recent times.
The reasons for the changes are multi-fold. Some argue that these changes have been
necessitated by the phenomenon of hyper-competition [1] that characterizes the nature of
disorder, stress and unpredictability that is confronting modern organizations. This phenomenon
is seen to arisen from the shift in economic growth cycles from the post-war economy to the new
economy based on technological drivers of information, communication and technology [2].
Along similar lines, others have pointed out that modern organizations are driven by
discontinuity rather than continuation and stabilization [3].
Along with competitive drivers, changes to organization form and shape have also been
influenced by social factors – primarily the organizational culture and climate, with its emphasis
on attitudes, values, feelings and social processes [5]. Organizational culture and climate are
greatly influenced by the leadership of the organization. At the same time they also get impacted
by prevalent cultures and climate in other organizations as well as by overall trends in social
culture.
Irrespective of the specific factors driving organizational change, it is clear that in the recent
past, new organizational forms have emerged. These new forms offer insights for organizational
design and change and are being seen as key drivers for innovation and growth.
Recent renewed interest in social network theory is a result of the new evidence that the way
large group of people behave collectively is not in a hierarchical structured manner as desired by
the proponents of hierarchical organization designers. In fact, the natural way we behave is more
close to a messy world of networks of complex connections. The new studies have shown variety
of social structures and processes that govern overall behavior of a group of population. These
social processes lead to different type of emergent properties that cannot be easily established by
studying only local individual interactions. This is in fact the hallmark of complex systems [26]
These two interesting trends of emerging new organization forms and various social network
structures – intuitively seem to be linked in some form. To study these relationships we have
used a framework based on the methodology of Analytic Hierarchy Process (AHP) [24, 25]. This
paper describes the framework and the initial results obtained so far. The paper is organized in
following sections – Section 2 gives a brief overview of emerging new organization forms and
also gives our understanding and for the purpose of this study our classification of the new
organization forms. In Section 3, an overview of various social network types and basis of these
different types are described. It also describes our understanding and classification of social
network types. Section 4, describes the methodology based on the AHP. Section 5 describes the
framework derived from the analysis of results obtained in the previous section. The paper ends
with Section 6 where potential applications of the framework are discussed and future steps are
identified.
2 New Forms of Organizations
Several new organizations forms have been proposed and discussed in literature [2]; while these
forms (clubbed together) offer a stark contrast to the regular hierarchical organizational form,
there are a few distinct types of new organizational forms that have been the subject of much
interest and study. Broadly, these may be classified as:
a) Ambidextrous Organization
b) Collaborative Organization
c) Learning Organization
d) Emergent Organization
2.1 Ambidextrous Organization
Ambidextrous organizations look at simultaneous exploration and exploitation as a means to
sustained performance and growth.
In order to successfully compete, they pursue a portfolio of innovations including:
a) Incremental Innovations: Small improvements in existing products or operations
b) Architectural innovations: Technology or process changes to fundamentally change a
component or element of business
c) Discontinuous innovations: Radical advances that may significantly alter the basis for
competition in an industry
For ambidexterity, the creation of project teams that are structurally independent units, each
having its own processes, structures and cultures, but integrated into the existing management
hierarchy i.e. connected at the top, has been recommended [8].
2.2 Collaborative Organization
These organizations look at collaboration as the means to achieve organizational goals. There is
great emphasis on team-based structures. Information pathways and flows between teams
(horizontally, vertically, internal, external) are widened and the boundaries and intersections are
exploited for value creation and innovation.
Three levels of collaborative work systems have been defined [7], each level increasing the
organization‟s capacity to serve its customers, employees and owners with an increase in
investment and results moving from left to right:
a) Traditional Teams
b) Team-based organizations
c) Collaborative Organizations
2.3 Learning Organization
These organizations focus on experimentation and learning as the key goals to be pursued. There
is a clear orientation towards the pursuit of perfection at all levels [14]. Knowledge (and thereby
change) is expected to be continuously created. “To create new knowledge means quite literally
to re-create the company and everyone in it in a nonstop process of personal and organizational
self-renewal. In the knowledge-creating company, inventing new knowledge is not a specialized
activity – the province of the R&D department or marketing or strategic planning. It is a way of
behaving, indeed a way of being, in which everyone is a knowledge worker – that is to say, an
entrepreneur.”[11]
Learning organizations use the following building blocks [13] to institutionalize learning:
a) A supportive learning environment
b) Concrete learning processes and practices
c) Leadership behavior that reinforces learning
Learning organizations tend to focus on systemic problem-solving as the means to competitive
excellence [10]. Learning and knowledge are transparently shared with the environment as a
long-term strategy for sustained growth and innovation [12].
2.4 Emergent Organization
Emergent organizations follow living system principles with focus on evolution. Boundaries are
ephemeral and created and destroyed as relevant. The organization is extremely receptive to
change and thrives on adapting to and creating change.
Emergent organizations are characterized by extra-ordinary decentralization [15]. They have also
therefore been described as open or boundary-less organizations or structures. The behavior of
emergent organizations is seen to bear similarities with swarm behavior seen in the natural
world, e.g. the intelligence embedded in the behavior of swarms of ants [16].
Much of recent evolution of social networks as a consequence of the growth in size, utility and
connectivity of the internet is being studied from the perspective of learning and application to
organizations. For instance, the development of user communities or information communities
has opened up multiple avenues for new businesses and business models (EBay, Google Ads).
Organizations have looked at emergent strategies to identify new products or services through
lead user innovations [17]. There are also interesting explorations of how a relatively small
number of key opinion influencers in social networks can determine the overall outcome or
direction of change for that network [18].
Table 1 summarizes the key differences between the five organization forms.
Table 1: Key Differences between Organizational Forms
Organization
Form
Hierarchical Ambidextrous Collaborative Learning Emergent
Key function Efficient
allocation of
resources
Balance growth
and efficiency
Information
flow, 1+1 > 2
Continuous
improvement
Evolution
Flow Uni-
directional,
top-down
Conditional Multi-
directional,
peer-to-peer
Cyclic, Directed
towards ideality
Natural, not
consciously
directed
Evolution Standard Tree The banyan tree Cross- Continuous Living system
hierarchy model Pollination
improvement,
pursuit of
perfection
principles
Knowledge Assumed to be
codified,
known
Some
knowledge
codified, some
to be obtained
Potential to be
maximized
through sharing
Knowledge to be
improved and
increased
continuously
Created as
needed
Interdependence Clear, closed
boundaries
Modular
architecture,
Clear, closed
boundaries
Fuzzy
boundaries
Clear but open
boundaries
Boundary-less
Detection of and
Response to
change
Central
detection and
intelligence,
command-
control, crisp
response,
detection and
response slow
for large org.,
fast for small
organizations
Multiple
antennae ready
for feedback,
multiple
intelligence
centres, crisp
response
Fuzzy,
democratic
response, some
change
absorbed, some
adapted,
detection and
response slow
but holistic
Clear yet
decentralized
detection and
response,
response strategic
Decentralized,
adaptive
response
3 Types of Social Networks
The informal connections formed in a large population leads to emergent structures that
sociologists term the formation of social networks. The social network theory has remained more
of a curiosity rather than a serious field to pursue, despite the work of Milgram [28], Granovetter
[27] and tipping point framework offered by Gladwell [18]. Recently, however, the work by
Duncan Watts [26] has brought the social network theory to the forefront. The need was also felt
as the world has become more connected and hence more networked. The organization structures
of the past are transforming naturally into different forms or structures that resemble more of the
networked form rather the hierarchical one.
Since then various researchers have studied the social networks and tried to distinguish between
various types of social networks based on desired response, centrality of the network and the
architecture of the network. In [23], networks in 60 different industries have been studied and
classified into three archetypes according to the response delivered by the Network. We
summarize these three types of social networks in Table 2 along three main parameters – the
types of problems and solutions encountered by the networks, the value delivered and illustrative
industries where these are likely to be found.
Table 2: Social Network Archetypes
Type --> Customized Response Modular Response Routine Response
Problems and Solutions Ambiguous Known components – but
combination or sequence
not known
Well-defined and
predictable
Value Quickly framing and
solving a problem in an
innovative way
Delivering a unique
response depending upon
the constellation of
expertise required by the
problem
Efficient and consistent
response to a set of
established problems
Examples New product dev,
investment banks, Strategy
consulting
Surgical teams, Law firms,
B2B sales
Call centers, insurance
claims processes
According to [21], social scientists have studied three types of networks – the ego centric, socio-
centric and open networks. The characteristics of the three types are shown in Table 3.
Table 3: Social Scientists Classification of Social Networks
Ego-Centric Networks Socio-Centric Networks Open-System Networks
Networks that are connected with a
single node or individual
Boundaries of the network are clear;
Networks in a Box
Boundaries are not necessarily clear
Example, My good friends, All
companies doing business with ABC
Example, students in a class,
employees of an organization
Example, network of elite class,
connections between corporations
Lists alone are insufficient – info
about connections also is required
Most studied in terms of fine points
of network structure
Most interesting and most difficult
to study
The shift to network form of organizations has become so prevalent that even the historically
most hierarchical form of human organization, i.e., military structures, are now beginning to
explore the network form of organizations to take care of increasingly complex situations and
foes that these forces are asked to tackle. The Network Centric Warfare as the field is now called
is a new form of military strategy, technologies, organization and doctrines that requires more
holistic explorations and understanding. The trend towards network form is clearly evident. In
[22], authors describe different forms of network centric warfare architectures that are possible.
Table 4 list down these architectures – which varies from centralized, where a central hub
controls the network, to a loosely coupled network structure where the elements or nodes come
together to solve a problem and then go back or move to next problem – through the process of
swarming.
Table 4: Taxonomy of Network Centric Warfare Architectures
Architecture Characteristics
A. Centralized One central high value Hub – other low value nodes networked and controlled
by Hub
B. Hub-Request “Type E” Request based plus one or more central high value hubs
C. Hub-Swarm “Type G” Swarming plus one of more central high value hubs
D. Joint Mixture of other six types (Type A, Type B, Type C, Type E, Type F and Type
G)
E. Request-Based Nodes of same value, but with different specialized capabilities. Request for
service between nodes of different kinds
F. Mixed Mixture of “Request-Based” and “Swarming”
F1: Limited Types Small number of node types (includes the case of separate sensor, engagement,
and C2 grids”
F2: Commonality Nodes are different, but have significant commonality
G. Swarming Nodes identical or nearly so
G1: Emergent Swarming Nodes follow simple rules, like insects
G2: Situationally Aware
Swarming
Nodes share information to build up Situational Awareness picture
G2(a): Orchestrated One node is a temporary “leader”
G2(b): Hierarchical Nodes are arranged in a Hierarchy
G2(c): Distributed No Leader or Hierarchy
The above discussion points to three key dimensions in which social networks have been studied
or classified in the literature. The three key dimensions are - (1) The type of response that these
networks generate i.e., what kind of output the networks can generate (three different type of
responses are Customised Response, Modular Response and Routine Response, (2) Second
dimension is the centrality of the networks - in this dimension also there are three types - Ego-
centric (individuals at the center with their network), Socio-Centric Networks where boundaries
of the network are clear and finally Open Networks where boundaries are not necessarily clear,
(3) Third dimension is the network architecture - where we have four options Centralized
networks, Request based networks, Hub swarms and Swarms. Combining these three dimensions
one can in principle get 3x3x4 = 36 different Network types. However we have selected finally 5
different types of Social Networks as described below.
Customized Response Open Swarms (CROSs): These types of social networks usually do not
have any clear boundaries (they are open). They have nearly identical nodes in terms of their
capabilities and authority. These nodes come together to respond to problems through a process
of creating shared awareness, quickly formulating the problems and solving problems by
leveraging each other's capabilities collectively. After problems are responded to they go to next
problems or keep on building their capabilities. These networks typically create customized
responses to unstructured problems.
Modular Response Socio-Centric Request-Based (MRSR): These types of social networks
have clear boundaries and typically generate solutions through a combination or re-sequencing of
components of the over-all solutions. They work in an environment when components of the
problems and solutions are known but constructing the solution requires combination of
components in a non-trivial way. Further the nodes of these networks have same value but
different capabilities and they respond to the problems by requesting each other to provide their
unique capabilities to solve problems through modularized responses.
Routine Response Ego-Centric Centralized (RECC): These types of social networks create
routine responses to structured problems. There is typically a centralized hub of high value
which has low value nodes connected. The centralized hubs of different sub-nets have their own
ego-centric networks based on the network of the leader of the hub. However the low value
nodes of a subnet do not connect to low-value nodes of other subnets.
Customized Response Socio-Centric Hub-Swarm (CuSHuS): These types of social networks
have one or more high value hubs besides large number of nearly equal value nodes. These
nearly equal value nodes swarm together for solving an unstructured problem with the high value
hubs. Each subnet may have its own high value hub and many equal value nodes that can create
shared picture of the problems which gets picked and responded to through swarming in a
slightly controlled manner.
Customized Response Open Request-Based (CROR): These types of social networks do not
have clear boundaries. However, customized response is created through a request based
mechanism.
The question we are exploring here is – which of these social network types are most likely to be
found in which type of organization forms as defined in Section 2. This mapping is of interest for
variety of purposes, and a framework to study this mapping may be useful. We describe the
methodology of developing such a framework using the technique of Analytic Hierarchy Process
(AHP) in Section 4.
4 Methodology
Let us formulate the problem. The question we need to answer is the following,
In each of the organization forms that we have defined in Section 2 – Hierarchical,
Ambidextrous, Collaborative, Learning and Emergent, what are the relative chances of finding
each of the social network types that we have defined in Section 3 – Customized Response Open
Swarms (CROSs), Modular Response Socio-Centric Request-Based (MRSR), Routine Response
Ego-Centric Centralized (RECC), Customized Response Socio-Centric Hub-Swarm (CuSHuS),
and Customized Response Open Request-Based (CROR).
Possible ways in which this question can be answered is – (a) to have direct measurement in real
life organization forms, (b) to make a mathematical model and solve it (c) to simulate the
organization forms and let the social networks emerge (d) to ask the experts and to use the
consensus of experts to reach to a high level mapping of social network types to organization
forms. The first three methods as of now have found to be infeasible hence we chose the opinion
of experts as a surrogate for actual measurement. For this purpose we have used the methodology
of Analytic Hierarchy Process (AHP). Before we define the methodology and results, in Section
4.1 we give a brief overview of AHP.
4.1 Analytic Hierarchy Process (AHP) – An Overview
AHP [24, 25] provides a means of decomposing the problem into a hierarchy of sub-problems
which can more easily be comprehended and subjectively evaluated. The subjective evaluations
are converted into numerical values and processed to evaluate each alternative on a numerical
scale. The detailed methodology of AHP can be explained in following steps:
Problem is decomposed into a hierarchy of categories and parameters.
Opinion is collected from experts corresponding to the hierarchic structure, in pair wise
comparison of alternatives on a qualitative scale. Expert can rate the comparison as equal,
marginally strong, strong, very strong, and extremely strong. The comparisons are made
for each criterion and converted into quantitative numbers on a 9 point scale.
The pair wise comparisons of various criteria generated at step 2 are organized into a
square matrix. The diagonal elements of the matrix are 1. The criteria in the ith
row is
better than criteria in the jth
column if the value of element (i,j) is more than 1; otherwise
criteria in jth
column is better than criteria in ith
row. The (j,i) element of the matrix is
reciprocal of (i,j) element.
The principal eigen value and the corresponding right eigen vector of the comparison
matrix gives the relative importance of various criteria being compared. The elements of
the normalized eigen vector are termed weights with respect to the criteria or sub criteria.
The consistency of the matrix is then evaluated. Comparisons made by this method are
subjective and AHP tolerates inconsistency through the amount of redundancy in the
approach. If this consistency index fails to reach a required level then answers to
comparisons may be re-examined. The consistency index, CI is calculated as
CI = (max – n)/ (n-1) (1)
Where, max is the maximum eigen value of the judgment matrix and n is the order of the
matrix. This CI is compared to that of a random matrix, RI. The ratio derived, (CI /RI) is
termed the consistency ratio (CR). It is suggested that the value of CR should be less that
0.1 [24, 25].
The ratings of each alternative is multiplied by the weights of the sub-criteria and aggregated to
get local ratings with respect to each criterion. The local ratings are then multiplied by weights of
the criteria and aggregated to get global ratings.
4.2 Derivation of Ratings from Expert Opinions
The social network ratings are derived from a process of consensus creation in inputs from
multiple experts. These experts have been involved in studying various organization forms and
also experienced in multiple social networks. However, there are variations in their views on
relative probability of the social network types. We present below the process of creating
consensus.
In the initial setting, 5 experts were chosen. These experts were given the background of the
model and information on organization forms and social network types. The experts were asked
to fill in the relative importance of each social network type for every organization form in pair
wise qualitative comparisons as shown in Fig. 1.
Fig 1. Pair wise comparisons from experts
Consistency Ratio of each matrix by each expert is checked and in kept below 0.1 as
recommended by the methodology. The final output using the AHP process from each of the
experts is given in the figures below.
As one can see from the above table, the experts differ from each other and there is no
consensus. The methodology calls for taking the normalized geometric mean as a basis for
consensus of experts. The Table below gives the geometric mean of the inputs from experts
using AHP.
The geometric means are normalized to get the final consensus rating of all the five experts. The
final consensus ratings are given below. The green marks are the top ranking social network
types that the experts feel will be found in specific organization forms. The orange marks are the
second ranked social network type that the experts feel will be found in the specific organization
forms. And finally the blue marks are the third ranked social network type that the experts
believe will be found in the specific organization forms.
4.3 The Results
The results obtained as shown in the Table above are represented as radar plots where each spoke
of the radar indicates one of the five social network types. The mapping of social network types
to each of the organization forms is explained below:
a) Hierarchical organization
forms are likely to have Routine
Response Ego-Centric
Centralized type (47.5%). as
well as Modular Response
Socio-Centric Request Based
type (30.9%) of social
networks.
b) In Ambidextrous organization
form, experts believe the Modular
Response Socio-centric Request-
based social network will be most
prevalent form (43.5%). It is
interesting to note that Customized
Response Socio-Centric Hub-
Swarm comes out to be distant second (21.4%) closely followed by Routine-response
Ego-centric Centralized (16.5%).
c) In the case of Collaborative
organization form, the Customized
Response Socio-centric Hub-
Swarm social network type wins
with 42.5%, distantly followed by
Customized response open swarms
(18.7%) and Customized response
open request based (18.5%) social
network types.
d) In the Learning organization form,
Customized Response Socio-Centric
Hub-Swarm wins with 43.7%
followed by Customized Response
Open Request-based with 24.9%
and Customized Response Open
Swarms with 17.2%.
e) In the Emergent organization form
Customized Response Open Swarms
with 45.4% wins followed by
Customized Response Open Request-
based with 24.9% and Customized
Response Socio-Centric Hub-Swarm
with 16.9%.
The consolidated picture that emerges when we combine all the five charts is shown in the figure
below.
While experts have differed with each other on several counts, it is interesting to note that the top
three social networks identified as most likely to be found in a particular form of organization are
consistent. This implies that the experts are differing in the degree to which a social network type
is likely to be found in a particular form of organization but are fairly in agreement on the types
of social networks that are likely to be found. Furthermore, the top 3 social network types for any
particular organizational form cover more than 75% of the relative weights. In combination,
these two results signify that there are clear associations or mapping between organizational
forms and social network types. As we move from hierarchical to emergent forms, there is
unambiguous change in the mappings to social network types.
5 The Framework for Analysis
5.1 Patterns in most likely combinations
Using the topmost relevant social network types in combination, it is possible to find the aspects
of social networks that are potentially critical to a particular organizational form.
a) Hierarchical form
This form is characterized by the absence of customized response and open type of social
networks. However, within the other forms there seems to be scope for freedom and
movement (routine and modular response, ego-centric and socio-centric, centralized and
request-based).
b) Ambidextrous form
This form is characterized by socio-centric and ego-centric social networks to some
extent (open type of social networks may make ambidexterity difficult). There is
considerable freedom with respect to all the other types of social networks. All types of
responses are valid, but there is movement away from routine responses and towards
customized responses. Similarly, all architectures are possible but there seems to be
movement away from centralized and towards hub-swarm type of architecture.
c) Learning form and Collaborative form
At the outset, experts seem to be associating the same combinations of social networks to
both these forms. Therefore, both of them are essentially characterized by customized-
response type of social networks. A deeper look however, reveals some interesting
differences. Learning organizations seem to have a preference towards request-based
architectures, while collaborative organizations are equally likely to involve swarm as
well as request-based architectures. In both learning as well as collaborative forms, there
seems to be a movement towards open social networks.
d) Emergent form
This form is characterized by customized-response open swarm types of social
networks. Request-based architecture may exist in some cases.
5.2 The existence of evolution paths
If one were to look at gradual change in the compositions of social network types in an
organization (this may happen by design or by accident in the real world) i.e. the second most
likely social network type gradually becomes more prevalent, and some previously non-existent
type of social network structure gets introduced), there seem to be clear evolution paths as
showed in the following figure:
a) Hierarchical organizations are most likely to evolve into ambidextrous organizations, if a
hub-swarm architecture gets introduced, as is necessary for exploratory capability.
b) Ambidextrous organizations may evolve into either learning or collaborative
organizations, if the social network is opened up beyond socio-centric networks. What
would trigger a specific movement towards learning or collaboration as the primary form
is difficult to assess. It seems that, if there is movement away from the swarm
architecture towards request-based architectures, learning-based approach may form the
primary focus, with collaboration as one of the means to achieve learning. On the other
hand, if swarm-based architectures continue to remain, it is likely that collaboration
becomes the primary driver, and learning is one of the many things achieved through
collaboration.
c) Collaborative organizations are more likely to morph into emergent forms, once the
transition from socio-centric hub-swarms to open swarms is complete. By the same
token, emergent organizations may revert to more controlled collaborative behavior if
there is a need for socio-centric networks to assume greater importance.
d) Learning organizations can gradually move towards more emergent forms once the
transition from socio-centric to open social networks is complete and request-based
architecture are supplemented with swarm-based architectures. In essence, this implies
the addition of the capability to learn from external, random, decentralized events in
addition to process driven learning.
6 Applications and future steps
There are several potential applications of this framework from an organizational design
perspective.
Firstly, this framework can help organizations start thinking about what is their current
form or type of organization and what do they want to be in the future. Simultaneously,
organizations can start observing the types of social networks that are prevalent.
Sometimes it may be difficult for organizations to determine their exact form; there may
be evidence to suggest that more than one form fits the bill. In such cases, the prevalent
types of social networks can offer a clue towards the essential form of the organization.
Once organizations are clear about “which form seems to fit best” and “what types of
social networks are prevalent”, they can use the framework to figure the path of evolution
they would like to take and correspondingly the changes to the organizational social
networks that they need to make. The framework gives clear guidelines to the types of
capabilities that need to be added and movements that need to be made in order to move
towards organizational forms more suitable to growth and innovation, based on the
organizational context.
Often, organizations struggle to extract the best out of their people because organizational
processes are not in sync with the way people work and interact on the ground. This
framework can be used by organizational leadership to redefine their understanding of the
form of their organization to synchronize with the nature of social networks prevalent.
The framework lends itself well to incremental application as well as part-application
(application to parts of the organization without affecting other parts); it does not require
whole-sale changes to the organizational design.
Most importantly, the framework is sufficiently flexible and open to fine-tuning and
modification by incorporating opinions of further more experts in the field. It is an
evolving framework and can be continually (or periodically) updated and used as a
strategic tool for organizational design feeding into organizational growth and
innovation.
While this is a preliminary framework that incorporates the opinions of a fairly small number of
experts (5 in number), the results are sufficiently interesting for us to pursue this research in
greater detail. The next steps are to broaden this research by getting opinions from a larger
community of experts and then (or simultaneously) apply the framework in live organizational
contexts. We also anticipate the need for mechanisms to objectively detect the types of social
networks prevalent in organizations as well as to identify portions of organizations most
receptive to the types of changes articulated in this paper.
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