Social Networks at Work

Patti AnklamLeveraging Context, Knowledge, and NetworksHutchinson Associatespatti@byeday.net

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 Associatespatti@byeday.net (978)456-4175

Seth EarleyEarley & Associatesearley@searley.com (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.