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Network analysis methods for assessment & measurement


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Presentation slides for a webinar produced by the Leadership Learning Community. Full audio is available on their site, at …

Presentation slides for a webinar produced by the Leadership Learning Community. Full audio is available on their site, at

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  • 1. Network Analysis Methods forAssessment & Measurement January 14, 2012 Patti Anklam With June Holley and Claire Reinelt
  • 2. 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 2
  • 3. Network Thinking & Non-Profits
  • 4. The Evolution of Network Thinking 4
  • 5. 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 5
  • 6. Network Analysis: The Method in a Nutshell Step Activities/Tools Design Identify boundaries Clarify and design questions Collect Data Surveys Interviews Facebook, LinkedIn Email logs Analyze data to generate (Netdraw/UCINET, NodeXL, Gephi … maps and metrics many others) Review data Validate; look for questions Prepare evaluation Match network results with context and stories Move into action Weaving & other interventions 6
  • 7. Survey Example 7
  • 8. Survey Example – Demographic Component 8
  • 9. Survey Example – Affiliation Component 9
  • 10. Survey Example – Network Questions 10
  • 11. Network Questions Probe Relationships 11
  • 12. Analyses Outputs: Map PatternsMulti-Hub Hub and SpokeStove-piped (Siloed) Core/Periphery 12
  • 13. Quick View: What an Analysis Can Tell• Overall very well connected• One region distinctly clustered with few connects to other regions• Staff are highly central• Identification of key connectors 13
  • 14. Reasons for a Network Analysis: Examples1. Assessment, Planning, & Weaving2. Measure changes over time3. Sense-making & story- finding4. Positioning and working with individuals in the network 14
  • 15. Assessment, Planning, & WeavingStrategic Purpose• Assess the network’s capacity for collaboration, information transfer, innovation• Identify key individuals• Establish goals for enhancing connectivity• Create an action plan 15
  • 16. Assessment: Capacity for Collaboration Current Funder Interaction Network Future Funder Interaction Network 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.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. 16
  • 17. Assessment: Affiliation NetworkStrategic Purpose• 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 17
  • 18. 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 18
  • 19. Measuring Changes Over Time Very Well Boston Green & Healthy Building Network Well Somewhat 2005 2007 24 9 32 1 24 9 32 1 31 3 31 18 7 3 18 6 7 6 25 25 33 28 4 33 28 4 26 26 8 29 17 8 29 2 17 2 11 12 11 12 23 16 27 23 16 27 10 19 10 19 21 21 15 15 13 13 34 14 34 14 30 30 5 20 22 5 20 22Source: Boston Green & Healthy Building Network, Beth Tener and Al Nierenberg, January 2008 Maps copyright © 2012 New Directions Collaborative 19
  • 20. Analyses Outputs: MetricsOverall network metrics Individual position metrics• Look at the whole network • Look at positions of and its components: individuals in the network: – Overall cohesion – # of connections – Degrees of separation – Favorability of position• Good for comparing • Good for identifying groups within networks or people who are well for comparing changes in a positioned to influence the network over time network or to move information around 20
  • 21. How the Metrics Enhance the Maps 2011Year # Density Avg # ties2009 55 2.2% 1.22010 90 2.7% 2.42011 85 5.3% 4.52012 82 8% 6.88 2010 2009 2012 21
  • 22. 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 BrandesSource: Networking a City, Marianne Hughes & Didi Goldenhar, Stanford Social Innovation Review, Summer 2012 22
  • 23. Sense-Making: New School Development in Boston • An intentional network may “This person has helped me accomplish work-related tasks.” have no other purpose than to enable emergence • Maps that show the evolving relationships within a network help to identify powerful network storiesSource: Networking a City, Stanford Social Innovation Review, Summer 2012 23
  • 24. Positioning: The Individual View Node Betweenness Indegree OutDegree 62 792.67 26 30 80 660.48 17 32• Centrality metrics 64 23 530.61 333.36 20 20 33 14 identify people with 71 321.42 21 20 56 316.42 20 18 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 24
  • 25. Tracking Individuals’ ChangesI learned something from this person that made me a better leader. – 2009 2005 2007 2008 2009 2010 25
  • 26. Tracking Individuals’ ChangesI learned something from this person that made me a better leader. – 2011 26
  • 27. Network Analysis & Measuring Outcomes
  • 28. Summary – What We KnowWhat We Can Measure and Show in an Analysis:• 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 28
  • 29. Things We Can Do With What We KnowWays to change patterns in Practices from the KM/OD Repertoire networksWeaving. Create intentional Convene. Make introductions through meetings and webinars, face-to- connections face eventsIncrease 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 softwareCreate awareness Provide expertise directoriesConnect disconnected clusters Weave: establish knowledge brokering roles; expand communication channelsCreate more trusted relationships Assign people to work on projects togetherAlter the behavior of individual nodes Create awareness of the impact of an individual’s place in a network; foster network literacyIncrease diversity Add nodes; connect and create networks; encourage people to bring knowledge in from their networks in the world 29
  • 30. 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 Source: Dave Snowden, Cynefin Advanced Practitioner’s Course December 2012 other survey questions 30
  • 31. Questions? 31
  • 32. • • • http://www.networkweaving.comThank you.Question