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Social Networks at Work
Patti AnklamLeveraging Context, Knowledge, and NetworksHutchinson [email protected]
How work really gets done.
©2002 Patti Anklam
Six degrees of separation
Concepts in (Social) Networks
Small worlds..who you know has a great
deal to do with what you come to know
©2002 Patti Anklam
Social Capital
Customer
StructuralHuman
Social
Social capital consists of the sum of active and
potential resources that are available through the network of relationships that exist
… and is fundamental to the creation of intellectual capital
New knowledge comes through combination and exchange
©2002 Patti Anklam
Social Network Analysis (SNA)
Social Network Analysis is focused on uncovering the actual network of relationships
The success or failure of organizations may depend on managing the context of these networks.
Analysis can produce understanding as well as action.
©2002 Patti Anklam
Who analyzes networks?
The study of networks is an essential element in the research on complex adaptive systems, as applied to:
The Internet Power grids Molecular biology
Application of and research in social network analysis is broad and diverse:
Social sciences Economics Epidemiology Homeland defense (terrorist networks) Management science
©2002 Patti Anklam
Typical Questions in an SNA Analysis
How frequently you receive information from others that you need to do your job
How well you know the knowledge and skills of others Your level of confidence that if you ask this person for help
they will actively engage in problem solving with you How much more effective you could be if you could
communicate more with other individuals
Survey includes the capture of key demographic information, including group or subgroup, level in hierarchy, geographical
or physical location, tenure, and so on.
©2002 Patti Anklam
Output Provides Insight into Different Aspects
©2002 Patti Anklam
SNA Leads to Meaningful Questions
Formal Structure Informal Structure
Ashok
Jennifer
Brenda
M ohan
W endy
Rudy
T om
Ben
Vijay
Pete
M avis
Aaron
M avis
Jeff
Ross
Nancy
Cathy
Sarah
Paul
©2002 Patti Anklam
Cross-Business Information Flow
= President
= Operations= Product Line A
= Small Accounts= Product Line B= Product Line C= HR/Finance= Large Accounts
I frequently or very frequently receive information from this person that I need to do my job.
Network Measures
Density = 17%Cohesion = 2.3Centrality = 9
Central People NS (21)DH (19)
©2002 Patti Anklam
Quantitative Measures
Density – percentage of ties that exist out of the total possible
Distance – the “degrees of separation” Cohesion – the average distance Centrality – extent to which the network relies on
only a few key individuals Central individuals – those who are in the key
networking roles
©2002 Patti Anklam
Quantitative Analysis Provides Management Insight
SmA Ops PL A PL B PL C LgA10 5 8 8 9 10
Small Accounts 72% 2% 11% 0% 2% 5%Operations 4% 85% 10% 5% 7% 12%Product Line A 8% 3% 77% 0% 1% 4%Product Line B 0% 13% 2% 73% 0% 17%Product Line C 2% 16% 1% 3% 54% 17%Large Accounts 2% 18% 5% 16% 12% 73%
Density. Data provides the percentage of information-getting relationships that exist out of the possible number that could exist. It is not a goal to have 100%, but to target the junctures where improved collaboration could have a business benefit.
©2002 Patti Anklam
Comparative Metrics Provide Benchmarks/Best Practices
# of people Cohesion Distance Centrality DegreeExecutive Team 9 46% 1.4 33.0% 3.7Executive Team Extended 54 22% 2 23.0% 12Human Resources 24 17% 1.8 36.0% 4Innovation Group 19 26% 2 49.0% 4.6Product Line C 9 54% 1.4 37.5% 4.3Product Line A 8 78% 1.1 10.0% 5.4Small Accounts 10 72% 1.3 31% 6.5Engineering Group 19 32% 1.8 31.0% 5.4Product Line B 8 80% 1.2 26% 5.4Large Accounts 11 74% 1.3 29% 7.3
Information Network
©2002 Patti Anklam
SNA Moves People to Action
Provides concrete and actionable view of flows and relationships: Makes concrete how work is happening in comparison to the formal structure. Makes visible the aspects of a group that we can work with.
Qualitative and Quantitative aspects: Graphics are very meaningful to people. Data enable metrics, provide meaningful information when there are very large
numbers of people The combination “cracks the code” of delivering this type of diagnostic data to
managers Proven uses in:
Planning for reorganization (or post-reorganization) Identifying key people prior to mergers or acquisitions Succession planning and retention Knowledge creation and sharing Improving organizational effectiveness
©2002 Patti Anklam
SNA Identifies the Unofficial Organizational Roles
Central connector Boundary spanner Information broker Peripheral specialist
…always provides insights and at least one surprise!
From Harvard Business Review June 2002, “People Who Make Organizations Go – Or Stop
©2002 Patti Anklam
Using the Results of SNA
Organizational Leadership work Restructuring and process redesign Staffing and role development
Categories of Interventions
Developing Networks Tools and technologies (expertise locators,
discussion forums, and so on) Collaborative knowledge exchange and
getting acquainted sessions
Individual action Personal and public Personal and private
©2002 Patti Anklam
Applications for Social Network Analysis
Inform the planning of workflow software and collaboration systems
Support critical junctures in networks that cross boundaries Identify people in key knowledge roles
Aid in planning for succession and retention Reward invisible work
Understand integration before or after re-organization, merger, or acquisition
Establish team context before a major project Identify lead users for change management programs
©2002 Patti Anklam
Process of SNA Project
1. Obtain management sponsorship2. Choose the network and participants3. Prepare the network (set expectations)4. Design and distribute survey5. Analyze and prepare data6. Interview central people to validate the context7. Present results8. Generate action plan9. Follow up
©2002 Patti Anklam
Critical Success Factors
Management commitment Focus on exchanges that create and sustain work Identification of all key people in network Obtaining sufficient context to present the results
objectively Sensitivity to individuals’ concerns about how the
data will be used
©2002 Patti Anklam
Six Myths about Informal Networks*
To build better networks, we have to communicate more Everybody should be connected to everybody else We can’t do much to aid informal networks How people fit in is a matter of personality (which can’t be
changed) Central people who have become bottlenecks should make
themselves more accessible I already know what is going on in my network
*Rob Cross, Nitin Nohria, and Andrew Parker, MIT Sloan Management Review, Spring 2002
©2002 Patti Anklam
More Information
Patti AnklamHutchinson [email protected] (978)456-4175
Seth EarleyEarley & [email protected] (781)444-0287
Acknowledgment. This work in social network analysis was bootstrapped through participation in research with the Institute for Knowledge-Enabled Organizations (IKO). Rob Cross and Andrew Parker, researchers, provided “above and beyond” support for key projects as well as solo projects during my learning process.