Social Network Types And Organizational Forms - A Framework For Analysis

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

Hierarchical

Ambidextrous

Collaborative

Learning

Emergent

Efficient

Balance growth

Information

Continuous

Evolution

allocation of

and efficiency

flow, 1+1 > 2

improvement

Conditional

Multi-

Cyclic, Directed

Natural, not

directional,

directional,

towards ideality

consciously

top-down

peer-to-peer

Form  Key function

resources Flow

Evolution

Uni-

Standard Tree

The banyan tree

Cross-

directed Continuous

Living system

hierarchy

model

Pollination

improvement,

principles

pursuit of perfection Knowledge

Assumed to be

Some

Potential to be

Knowledge to be

Created as

codified,

knowledge

maximized

improved and

needed

known

codified, some

through sharing

increased

to be obtained Interdependence

continuously

Clear, closed

Modular

Fuzzy

Clear but open

boundaries

architecture,

boundaries

boundaries

Boundary-less

Clear, closed boundaries Detection of and

Central

Multiple

Fuzzy,

Clear yet

Decentralized,

Response to

detection and

antennae ready

democratic

decentralized

adaptive

change

intelligence,

for feedback,

response, some

detection and

response

command-

multiple

change

response,

control, crisp

intelligence

absorbed, some

response strategic

response,

centres, crisp

adapted,

detection and

response

detection and

response slow

response slow

for large org.,

but holistic

fast for small organizations

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

Well-defined

combination or sequence

predictable

and

not known Value

Quickly

framing

and

Delivering

a

unique

Efficient

and

solving a problem in an

response depending upon

response

to

innovative way

the

established problems

constellation

of

consistent a

set

of

expertise required by the problem Examples

New

product

dev,

investment banks, Strategy

Surgical teams, Law firms,

Call

centers,

B2B sales

claims processes

insurance

consulting

According to [21], social scientists have studied three types of networks – the ego centric, sociocentric 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

Boundaries of the network are clear;

Boundaries are not necessarily clear

single node or individual

Networks in a Box

Example, My good friends, All

Example,

companies doing business with ABC

employees of an organization

connections between corporations

Lists alone are insufficient – info

Most studied in terms of fine points

Most interesting and most difficult

about connections also is required

of network structure

to study

students

in

a

class,

Example, network of elite class,

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 A. Centralized

Characteristics 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.

Mixture of “Request-Based” and “Swarming”

Mixed F1: Limited Types

Small number of node types (includes the case of separate sensor, engagement, and C2 grids”

F2: Commonality G. Swarming

Nodes are different, but have significant commonality Nodes identical or nearly so

G1: Emergent Swarming

Nodes follow simple rules, like insects

G2: Situationally Aware

Nodes share information to build up Situational Awareness picture

Swarming 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 - Egocentric (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. Analytic Hierarchy Process (AHP) – An Overview

4.1

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 Requestbased 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 Requestbased 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 customizedresponse 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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