Network Analysis (SNA/ONA) Methods for Assessment & Measurement

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Many nonprofits and foundations have been using social network analysis (SNA) and organizational network analysis (ONA) techniques in program assessment, planning, and measurement. This webinar will review a number of techniques that are being used and the ways that the results of network analysis are informing and supporting the ways that nonprofits are leveraging networks to achieve greater good by creating, facilitating, and weaving networks.

transcript

Using Network Analysis toAssess and Measure Networks

January 14, 2012Patti Anklam With June Holley and Claire Reinelt

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Webinar Goals

Share current thinking about how network analysis is used in designing and evaluating nonprofit programs

Provide examples of network analysis used in assessment and measurement contexts

Stimulate thinking about correlating network analysis with measurement and evaluation outputs and outcomes

Network Thinking & Non-Profits

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The Evolution of Network Thinking

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What is Network Analysis?

• Social network analysis (SNA) is a collection of techniques, tools, and methods to map and measure the relationships among people and organizations

• Organizational network analysis (ONA) often refers to the use of SNA methods in the context of organization dynamics and development

• In practice, we use these tools to map connections among people and ideas, issues, and other entities as well as the social and organizational connections

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Network Analysis: The Method in a Nutshell

Step Activities/ToolsDesign Identify boundaries

Clarify and design questionsCollect Data Surveys

InterviewsFacebook, LinkedInEmail logs

Analyze data to generate maps and metrics

(Netdraw/UCINET, NodeXL, Gephi … many others)

Review data Validate; look for questionsPrepare evaluation Match network results with context

and storiesMove into action Weaving & other interventions

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Survey Example

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Survey Example – Demographic Component

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Survey Example – Affiliation Component

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Survey Example – Network Questions

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Network Questions Probe Relationships

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Analyses Outputs: Map Patterns

Multi-Hub Hub and Spoke

Stove-piped (Siloed) Core/Periphery

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Quick View: What an Analysis Can Tell

• Overall very well connected• One region distinctly

clustered with fewconnects to otherregions

• Staff are highlycentral

• Identification ofkey connectors

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Reasons for a Network Analysis: Examples

1. Assessment, Planning, & Weaving

2. Measure changes over time3. Sense-making & story-

finding4. Positioning and working with

individuals in the network

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Assessment, Planning, & Weaving

• Assess the network’s capacity for collaboration, information transfer, innovation

• Identify key individuals• Establish goals for enhancing connectivity• Create an action plan

Strategic Purpose

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Assessment: Capacity for Collaboration

Source: Transcending Boundaries: Strengthening Impact. The Full Potential of a Justice Network (Research & Network-Building Project Report, April 2011, Criminal Justice Funders Network). Courtesy of June Holley.

When funders indicate with whom they would like to work in the near future, the network becomes more robust.Funders are saying they want to work more together.

Current Funder Interaction Network Future Funder Interaction Network

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Assessment: Affiliation Network

• Identify potential relationships among people based on shared events, meetings, ideas, or areas of expertise

• Nonprofits use this to see which organizations “attach” to different ideas

• Forms the basis for network weaving

Strategic Purpose

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Drill Down Into Affiliation Network

• Identify people with common interest – basis for building communities of practice

• See which people share interest in multiple issues or topics

• A way for the network to reveal itself and have rich conversations

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Measuring Changes Over Time

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Very Well

Well

Somewhat

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Maps copyright © 2012 New Directions CollaborativeSource: Boston Green & Healthy Building Network, Beth Tener and Al Nierenberg, January 2008

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2007

Boston Green & Healthy Building Network

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• Look at the whole network and its components:– Overall cohesion– Degrees of separation

• Good for comparing groups within networks or for comparing changes in a network over time

Analyses Outputs: Metrics

• Look at positions of individuals in the network:– # of connections– Favorability of position

• Good for identifying people who are well positioned to influence the network or to move information around

Individual position metricsOverall network metrics

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How the Metrics Enhance the Maps

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2011Year # Density Avg # ties

2009 55 2.2% 1.2

2010 90 2.7% 2.4

2011 85 5.3% 4.5

2012 82 8% 6.88

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2012

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Sense-Making & Emergence

• Barr Foundation Fellows Program– See changes over time, but really to see how the network has supported

emergence – Work to shift Barr staff from the center

Pat Brandes

Source: Networking a City, Marianne Hughes & Didi Goldenhar, Stanford Social Innovation Review, Summer 2012

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Sense-Making: New School Development in Boston

• An intentional network may have no other purpose than to enable emergence

• Maps that show the evolving relationships within a network help to identify powerful network stories

“This person has helped me accomplish work-related tasks.”

Source: Networking a City, Stanford Social Innovation Review, Summer 2012

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Positioning: The Individual View 4Node Betweenness Indegree OutDegree

62 792.67 26 3080 660.48 17 3264 530.61 20 3323 333.36 20 1471 321.42 21 2056 316.42 20 18

• Centrality metrics identify people with the most ties (in-degree and out-degree)

• Those positioned to move information around in the network or be in the know (betweenness)

• Can identify people to lead task teams, to provide resources to, or to train as weavers

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Tracking Individuals’ ChangesI learned something from this person that made me a better leader. – 2009

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Tracking Individuals’ ChangesI learned something from this person that made me a better leader. – 2011

Network Analysis & Measuring Outcomes

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Summary – What We Know

• Measure the cohesion of the network overall:– High-level structure (stove-piped, core/periphery, highly clustered)– Average degree of separation– Average number of connections each person has

• Identify individuals by their centrality to the network:– Core or periphery? How do you bring people in from the outside?– Broker? Connector? Facilitator? Bottleneck?– Number and diversity of connections

• See changes over time

What We Can Measure and Show in an Analysis:

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Things We Can Do With What We Know

Ways to change patterns in networks

Practices from the KM/OD Repertoire

Weaving. Create intentional connections

Convene. Make introductions through meetings and webinars, face-to-face events

Increase the flow of knowledge Establish collaborative workspaces, install instant messaging systems, make existing knowledge bases more accessible and usable; implement social software or social network software

Create awareness Provide expertise directories

Connect disconnected clusters Weave: establish knowledge brokering roles; expand communication channels

Create more trusted relationships Assign people to work on projects together

Alter the behavior of individual nodes Create awareness of the impact of an individual’s place in a network; foster network literacy

Increase diversity Add nodes; connect and create networks; encourage people to bring knowledge in from their networks in the world

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Measurement Challenges

• Maps area snapshot in time• Targets and thresholds

– How much cohesion is “enough?” Is there a point at which increasing the number of ties makes the network less efficient?

– Is it reasonable to set a target for the cohesion metric?

• Tying Network Metrics to Outcomes– We have to think of the metrics as

indicators and as correlates of other survey questions Source: Dave Snowden, Cynefin Advanced Practitioner’s Course December 2012

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Questions?

Question

• patti@pattianklam.comhttp://www.pattianklam.com

•claire@leadershiplearning.orghttp://www.leadershiplearning.org/

•June@networkweaving.comhttp://www.networkweaving.com

Thank you.