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Social Networking Analysis: uncovering the secrets of information flow for our information architecture Maria Horrigan Principal Consultant #OZIA09  #SNA
Information and knowledge Human absorptive capacity Growth Time Cohen & Levinthal 1989 A world of rapidly growing knowledge ….
....that is increasingly connected ..and just a click away local networks old colleagues colleagues at other offices new friends family local colleagues old friends virtual communities old classmates
Understanding Modern Users  Modern wants, needs, online behaviours, attitudes, expectations, and motivations: Increasingly complex and faceted Information needs: More and more complex Increasingly difficult to document Context of use: Complex dynamics, influencers and influences
Context of the Case: Large scale project in government No idea what the end solution would be like Lots of information, but in people’s heads Multiple stakeholders across multiple silos Information flows between individuals and groups not well known External industry pressure for project to occur How could we leverage the network for the benefit of the project?
The Six Degrees of Separation
Social Networking Analysis (SNA) Helped us explore questions such as: How does information flow into the network? Where does the information flow? Who is involved and why? What are they saying? What do they know? How do they interact? Strength of relationships & interactions ? Are there emergent sub-groups?
What we did Adopted an agile approach Broke down huge project puzzle into smaller business issues to solve Had multiple streams of activities (IA had visualisation of all the different parts of the puzzle) Used SNA in each stream to uncover the information needs of the users Used “skinny” documentationto convey to stakeholders the key features of the system, its processes and the flow of information
Informal organisation Formal Organisation Uncovered organisational networks  Teigland et al. 2005
Centrality : revealing network structure  Very centralized network - one or a few very central ‘nodes’. If removed, network quickly fragments and fails   Less centralized network - resilient. Many nodes can fail yet allow remaining nodes to still reach each other  Boundary Spanners - connect their group to others. Innovators as have access to ideas and information in other clusters  Periphery of a network -may connect to networks not currently mapped. Important sources of fresh information
SNA – Revealing Network Centrality http://en.wikipedia.org/wiki/Social_network_analysis_software
What we found: Degree of Centrality Hub has most connections – authority gained It not the “more connections the better”, but where they lead to… ..and how they connect the otherwise unconnected
What we found: Betweeness Centrality  Great influence over what flows (and does not) “location location location” Broker role between    Industry and Organisation
 What we found: Closeness Centrality  Shortest path to all others – gives quick access Excellent position to monitor info flows Best visibility of what is happening in the network
Formalvs Informal Info Flow
Formal  vsInformal Info Flow
User Profiles within the Organisation Boundary Spanner Potential blocker Influencer Key User Project Champion Gatekeeper Key source Key User Key decision maker Trusted advisor Periphery Key User
Access to more Knowledge and Info … but of course this is just a subsection of the networked organisation Map shows 1st & 2nd degree relationships  Actors on the periphery of the  network had access to many other networks within the organisation
Leveraged Centrality Understood who might be “blockers” or “gatekeepers”  of information and content Found people to go to in order to elicit information   Minimised re-work & unnecessary consultation – meeting fatigue Quickly identified who might know the answer, communicate with them, understand their lessons learned, improve likely success  Knew who and how to communicate key messages  through use of targeted IA tools
Captured SNA in personas Started off with ‘skinny’ view of users gained thru workshops Added to personas as info uncovered thru SNA  Built up personas as we went in our agile project iterations, rather than all-at-once
From skinny to zen personas As our project knowledge evolved, we added to our understanding of users: Their information preferences Their expectations Their capabilities Their information needs Their social network profiles (Forrester’s Technographics) Documented as ‘ZenAgile’ personas
Added style preferences to personas ,[object Object]
 Animated
 Creative
 Outgoing
 Goal oriented
 Assertive
 Task & information focusedT Talkers D Drivers task people S Supporters C Controllers ,[object Object]
 Information & task focus
 Detail orientated
  Cautious & risk averse
  People oriented
 Team players

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Social network analysis: uncovering the secrets of information flow for our information architecture

  • 1. Social Networking Analysis: uncovering the secrets of information flow for our information architecture Maria Horrigan Principal Consultant #OZIA09 #SNA
  • 2. Information and knowledge Human absorptive capacity Growth Time Cohen & Levinthal 1989 A world of rapidly growing knowledge ….
  • 3. ....that is increasingly connected ..and just a click away local networks old colleagues colleagues at other offices new friends family local colleagues old friends virtual communities old classmates
  • 4. Understanding Modern Users Modern wants, needs, online behaviours, attitudes, expectations, and motivations: Increasingly complex and faceted Information needs: More and more complex Increasingly difficult to document Context of use: Complex dynamics, influencers and influences
  • 5. Context of the Case: Large scale project in government No idea what the end solution would be like Lots of information, but in people’s heads Multiple stakeholders across multiple silos Information flows between individuals and groups not well known External industry pressure for project to occur How could we leverage the network for the benefit of the project?
  • 6. The Six Degrees of Separation
  • 7. Social Networking Analysis (SNA) Helped us explore questions such as: How does information flow into the network? Where does the information flow? Who is involved and why? What are they saying? What do they know? How do they interact? Strength of relationships & interactions ? Are there emergent sub-groups?
  • 8. What we did Adopted an agile approach Broke down huge project puzzle into smaller business issues to solve Had multiple streams of activities (IA had visualisation of all the different parts of the puzzle) Used SNA in each stream to uncover the information needs of the users Used “skinny” documentationto convey to stakeholders the key features of the system, its processes and the flow of information
  • 9. Informal organisation Formal Organisation Uncovered organisational networks Teigland et al. 2005
  • 10. Centrality : revealing network structure Very centralized network - one or a few very central ‘nodes’. If removed, network quickly fragments and fails Less centralized network - resilient. Many nodes can fail yet allow remaining nodes to still reach each other Boundary Spanners - connect their group to others. Innovators as have access to ideas and information in other clusters Periphery of a network -may connect to networks not currently mapped. Important sources of fresh information
  • 11. SNA – Revealing Network Centrality http://en.wikipedia.org/wiki/Social_network_analysis_software
  • 12. What we found: Degree of Centrality Hub has most connections – authority gained It not the “more connections the better”, but where they lead to… ..and how they connect the otherwise unconnected
  • 13. What we found: Betweeness Centrality Great influence over what flows (and does not) “location location location” Broker role between Industry and Organisation
  • 14. What we found: Closeness Centrality Shortest path to all others – gives quick access Excellent position to monitor info flows Best visibility of what is happening in the network
  • 16. Formal vsInformal Info Flow
  • 17. User Profiles within the Organisation Boundary Spanner Potential blocker Influencer Key User Project Champion Gatekeeper Key source Key User Key decision maker Trusted advisor Periphery Key User
  • 18. Access to more Knowledge and Info … but of course this is just a subsection of the networked organisation Map shows 1st & 2nd degree relationships Actors on the periphery of the network had access to many other networks within the organisation
  • 19. Leveraged Centrality Understood who might be “blockers” or “gatekeepers” of information and content Found people to go to in order to elicit information Minimised re-work & unnecessary consultation – meeting fatigue Quickly identified who might know the answer, communicate with them, understand their lessons learned, improve likely success Knew who and how to communicate key messages through use of targeted IA tools
  • 20. Captured SNA in personas Started off with ‘skinny’ view of users gained thru workshops Added to personas as info uncovered thru SNA Built up personas as we went in our agile project iterations, rather than all-at-once
  • 21. From skinny to zen personas As our project knowledge evolved, we added to our understanding of users: Their information preferences Their expectations Their capabilities Their information needs Their social network profiles (Forrester’s Technographics) Documented as ‘ZenAgile’ personas
  • 22.
  • 28.
  • 29. Information & task focus
  • 31. Cautious & risk averse
  • 32. People oriented
  • 35.
  • 36. Activity Write 5 words or phrases that relate to the words: Beach and Ocean Place a V, an A, or a K against each: V=visual (Something ‘seen’ or had visual stimulation) e.g. See the blue sky, see children playing in the water A=Auditory (A ‘sound’ memory or related to a sound e.g. Hear the waves against the shore K=Kinaesthetic(Has a ‘doing’ memory & you thought of yourself feeling the emotion) e.g. Feel the sun and the sand, the taste of salt
  • 37.
  • 40.
  • 42.
  • 44.
  • 45. The result: ZenAgile Personas! Social Technographics Centrality Communication preferences
  • 46. What did I learn? Found out who knows what and how the info flowed through the organisation Personas good way to help convey and shape understanding of user’s info needs Agile approach - build on “skinny” profile & flesh out personas as the project proceeds Involving the right people with the right info can mean the difference between success & failure
  • 48. IA & Six Degrees of Separation You may only be one or two degrees away from some who know the info you need Information networks can be connected and lessons learnt and reuse made possible
  • 49. Applying SNA and Communications Makes sure you understand the user dynamics with the organisation Choose the right channel based on users style and preferences Build personas as you uncover more about the users Makes sure your IA artefacts match these preferences
  • 50. ”No one knows everything, everyone knows something, all knowledge resides in humanity ” Networks Lévy 1997
  • 51. FinMaria Horrigan www.slideshare.com/murph www.barocks.com Zenagile.wordpress.com @miahorri #OZIA09 , #SNA Email : maria.murphs@gmail.com