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Social Network Analysis and Knowledge Management

KM 631April 28, 2007

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Outline

• Overview of SNA and it's relation to KM• Broad applications of SNA • Application of SNA to KM• SNA basics using Kite diagram• Class examples - UCLA and Mgt 631• Going beyond structure - Study of Trust

at HP• Personality and social networks

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Definitions

• Knowledge Management: the range of practices used by organizations to identify, create, represent and distribute knowledge for reuse, awareness, and learning across the organizations.

• Social Network Analysis: The mapping and measuring of relationships and flows of information between people, organizations, computers, or other information or knowledge processing entities. – Nodes are people and groups; links show relationships or

flows between the nodes

4Source: Krebs & Associates

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7http://www.orgnet.com/booknet.html

Revealing Book Networks

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Political Books and Polarized Readers?

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World Trade

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SNA of the 9-11 Terrorist Network

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Social Network Theoryis related to…

• Social capital• Network effect• Diffusion of innovations• Complexity theory (butterfly effect, swarm

theory)• Small world phenomenon, six degrees of

separation• Online social networks (Facebook, Linked-In)

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Networks Are Critical to Innovation Diffusion

Time

Percent ofAdopters

20% early adopters

later adopters

Rogers, E. (1995). The Diffusion of Innovations. New York: The Free Press

“critical mass”

Successful innovation

Unsuccessful innovation - “island of innovation” - diffuse or die phenomenon

100%

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Diffusion Using Opinion Leaders

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IT-Enabled Networking

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Using E-Mail to Identify Optimal Paths

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Broader Applications of SNA

• Reveal how infections spread among patients and staff in a hospital

• Accelerate diffusion by identifying opinion leaders

• Improve the innovation of a group of scientists and researchers

• Find emergent leaders in fast growing company

• Map executive's personal network based on email flows

• Analyze book selling patterns to position a new book

• Analyze terrorist networks

• Map interactions amongst blogs on various topics

• Map communities of expertise in various medical fields

• Examine a network of farm animals to analyze how disease spreads from one cow to another

• Map network of Jazz musicians based on musical styles and CD sales

• Discover emergent communities of interest amongst faculty at various universities

• Discern useful patterns in click streams on the WWW

Source: http://www.orgnet.com/sna.html

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Application of SNA to People and Organizations

Career Planning How do people find jobs?

Mergers and Acquisitions

Is the cross-border M&A working?

Business Process Re-engineering

Where are the organizational disconnects?Where are the bottlenecks?

Human Resources

Are any groups isolated? (e.g., young engineers)Are diversity efforts working?

Organizational Design

How should the office be laid out?

Knowledge Management

How do innovations spread?Who are the resident Subject Matter Experts?

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Your Network Structure Matters

• Social networks that are large, diverse, rich in weak ties and “structural holes” lead to a range of positive outcomes including:– Access to novel sources of information (Granovetter,

1973)– Fruitful inventions and career advancement (Burt, 1992)– Discovery of new jobs (Granovetter, 1993)

• Social networks that are small, dense, rich with strong ties leads to:– Increased accessibility (Baker, 1993)– Help with resource mobilization (Obstfeld, 2005)– Protection in times of danger or uncertainty (1992)

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Three Common Organizational Communication Networks and How They

Rate on Effectiveness Criteria

depends

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The Kite Diagram

Who is most “central”?Most “between”?Most “close”?

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Centrality Measures• Local Centrality (Degree): The number of links an actor has with

other actors.

• A potential sign of power

• High in-degree can be a sign of prominence or prestige

• High out-degree can be a sign of influence

• Betweeness: The degree to which an actor is situated between two groups, and is a necessary route between those groups.

• Actors with high betweeness have the potential to have a major influence

• They can be mediators/brokers, gatekeepers, bottlenecks, or obstacles to communication

• They are especially valuable when the link two diverse groups

• Global Centrality (Closeness): the average distance between an actor and all other actors in a network.

• Most likely to be “in the know” about what is happening

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Adjacency Matrix for Kite Diagram

  AndreBeve

rly Ed GarthFer

nando Carol DianeHeather Ike Jane

Andre   1     1 1 1      

Beverly 1   1 1     1      

Ed   1   1     1      

Garth   1 1   1   1 1    

Fernando 1     1   1 1 1    

Carol 1       1   1      

Diane 1 1 1 1 1 1        

Heather       1 1       1  

Ike               1   1

Jane                 1  

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Three Ways to Gather Data

• Closed Network (Positional) Approach– Researcher studies connections

between closed, known network

• Ego (Reputational) Approach– Researcher studies those named on

ego’s list

• Snowball Method– Researcher asks ego to nominate others

and follows chain

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Six Varieties of Knowledge Networks

• Work Network– With whom do you exchange information as part of your daily work

routines?

• Social Network– With whom do you “check in” inside and outside the office to find out

what is going on?

• Innovation Network– With whom do you collaborate or kick around new ideas?

• Expert Knowledge Network– Whom do you turn to for expertise or advice about the enterprise?

• Career Guidance or Strategic Network– Whom do you go to for advice about your future?

• Learning Network– Whom do you work with to improve existing processes or methods?

Source: http://www.well.com/~art/s+b42002cm.html

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UCLA ELP Class Social Network

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UCLA ELP Class Social NetworkNode Size = Centrality

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UCLA ELP Class Social NetworkNode Size = Betweeness

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UCLA ELP Class Expert Network

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UCLA ELP Class Expert NetworkNode Size = Centrality

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UCLA ELP Class Expert NetworkNode Size = Betweeness

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KM 631 “Acquaintance” Network

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KM 631 “School” Network

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KM 631 “Social” Network

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KM 631 “Acquaintance” Network – Reciprocal Ties

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KM 631 “School” Network – Reciprocal Ties

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KM 631 “Social” Network – Reciprocal Ties

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KM 631 Class “Social” NetworkNode Size = Centrality

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What’s the Moral of the Story?

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Categories of Network Properties

Relational (qualitative) •Strength of ties•Accessibility•Likeability/”fun”•Reputation•Expected reciprocity? •Competing unit?•Dependence•Trust

Structural (quantitative)•Size•Density•Diversity•Structural Holes•Isolates/Cliques•Centrality•Betweeness•Closeness

Individual (qualitative)•Personality (e.g., Big 5, self-monitoring)•Emotional intelligence•Intentionality•Past experience

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Maximizing Network Support and Productivity

1. How valuable is the information I receive from this person?2. How well does this person collaborate with me to solve problems and make

decisions?3. How aware is this person of my skills?4. How accessible is this person to me?5. How “engaged” is this person with me?6. How safe is it to communicate with this person?7. What is the level of quality of conversation with this person?8. To what degree is my productivity improved by this person?9. How much power and influence does this person have?10. How much do I like this person?11. To what degree does this person support the achievement of my career

goals?12. To what degree does this person support the achievement of my personal

goals?13. To what degree does this person energize (or exhaust) me?14. To what degree do I trust this person?

Source: Robert Cross & Andrew Parker (2004), The Hidden Power of Social Networks: How Work Really Gets Done in Organizations. Harvard Business School Press.

• Evaluate each person in your network• Be evaluated by each person in your network!• Best conducted as 360 by 3rd party, NOT managers

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Trust Is…

• one’s willingness to become vulnerable to another party in order to achieve some expected gain even when one is unable to control or monitor the other party (Mayer et al., 1995).

• the “essential lubricant,” that enables cooperation and social exchange (Cohen and Prusak, 2001:28, Barber, 1983; Hardin, 1996; Luhmann, 1979).

• At least minimum levels of trust are required for individuals to activate and use the contacts in their networks (Rousseau et al., 1998)

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Components of Trust

• Competence: Being an expert in the subject matter I seek

• Benevolence: Having my best interests at heart

• Integrity: Ethical behavior or alignment with my value system

Source: Mayer, R., Davis, J. and Schoorman, F. (1995). An integrative model of organizational trust. Academy of Management Review, July, Vol. 20, No. 3, pp. 709-734

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HP Study• Sample: 50 senior leaders at HP (SVPs, VPs, Directors, GMs) yielding

data on 661 contacts• Who do you go to for:

– Actionable advice: Suggestions or recommendations to help you succeed

– Political help: Assistance with thinking strategically– Emotional support: A sympathetic ear– Raw information: Facts, figures, date and numbers that help you

get work done• Please rate this person in terms of:

– Competence– Benevolence– Integrity

• How big a difference has this person’s advice made to your success?

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Whom Would You Choose To Work With?

Source: Casciaro, T & Lobo, S. (2005). Competent Jerks, Lovable Fools and the Formation of Social Networks. HBR

Faced with the need to accomplish a task at work, what sort of person would you pick to help you? Studies showed that most people would choose a “lovable fool” over a “competent jerk”.

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Type of Support

Competence Benevolence Integrity

Seek actionable advice .197** .209** .198**

Seek emotional support -.009 .369** .243**

Seek political or strategic assistance

.126** .108* .114**

Seek raw information -.086* -.144** -.136**

Correlations Between Element of Trust and Type of Support Sought

N = 660 contacts from 50 executives

46Note: C, B, I dichotomized into L+M = L, H=H

Variations of Trust and Difference Made in Career Success

Avg Diff Made

0

0.5

1

1.5

2

2.5

L L H H H H

L L L H L H

L H L L H H

44 52 63 62 166 256

Avg Diff Made

CompetenceBenevolenceIntegrityN

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Big Five Personality Traits

• Extroversion (warmth, gregariousness, assertiveness, activity, excitement-seeking, positive emotions)

• Agreeableness (trust, straightforwardness, altruism, compliance, modesty, tender-mindedness)

• Conscientiousness (competence, order, dutifulness, achievement-striving, self-discipline, deliberation)

• Neuroticism (anxiety, anger, depression, self-consciousness, impulsiveness, vulnerability)

• Openness to Experience (fantasy, aesthetics, feelings, actions, ideas, values)

Source: Costa & McCrae, 1992, NEO PI-R Professional Manual

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Individual Attribute

NetworkSize

Strength of

Ties

Trust Density Diversity

Extroversion + + + +

Agreeableness +

Conscientiousness

+

Neuroticism -

Openness to Experience

+ -- +

NetworkingIntentionality

+ + +

Correlations Between Personality Traits and Social Network Structure