Interventional            Researcher NetworkingVIVO Conference 2011 – Jeff Horon, Tony Tsai, Jennifer Hill
Science of Team Science Conference                                     Jeff Horon
Agenda Why interventional networking? How it works What to do  (within your own organization or study)                    ...
Why networking at all?To bridge informational and social gaps, e.g.:  A    [isn‟t aware of]   B  C    [is aware of]     D ...
Why bridge information gaps?To benefit from direct awareness effects A    [is aware of]    B                              ...
Why bridge information gaps?To benefit from information broker effects A    [expresses a need to]   B                     ...
Why bridge information gaps?To benefit from information broker effects A                B        [connects]               ...
Imagine a network where… Everyone knows 1 in 20 colleagues (5%)                                     Jeff Horon
Imagine a network where… Everyone knows 1 in 10 colleagues (10%)                                     Jeff Horon
Imagine a network where… Everyone knows 1 in 5 colleagues (20%)                                     Jeff Horon
Why interventional networking?To counter researcher objections, e.g.Objection: “I already know everyone working in my fiel...
Why interventional networking?Evidence: University of Michigan Disease Target Sponsored Project Network                   ...
Why interventional networking?Evidence: University of Michigan Disease Target Sponsored Project Network          Core grou...
Why interventional networking?Evidence: University of Michigan Researchers working with a family of anatomical conceptsSen...
Why interventional networking?Another common objection:Objection: “I only need a new collaborator every couple years and I...
Recall                  In order to be helpful,                    B had to be aware of                    C by the time A...
Why interventional networking?Researchers don‟t know everyone working in their fieldResearchers can help themselves and ot...
Why interventional networking?Simply making the data available isn‟t enough  because researchers use defective  networking...
Why interventional networking?But what about people you don‟t know?                                        Jeff Horon
Variation to introduce: Intervention!                       Norms that lead to                         defective strategie...
How interventional networking works Objectively detect people working in a  field Use data to drive better-than-chance  in...
Objective detectionTry to capture all relevant researchers,  based upon sponsored project,  publication, or other data    ...
Objective detectionObjective detection helps deal with defective networking strategiesTip: Don‟t disregard personal knowle...
Drive better-than-chance interactions Use data-driven approach to determine: For awareness interactions, Who should meet w...
Drive better-than-chance interactions What will create better-than-chance  interactions is situation specific, but  reason...
Case Study: Launching an Institute  For a launch day event we strategized how to:         -Match research interests, proje...
Case Study: Launching an Institute  Data Sources:       ?     Registration Survey             Co-Authorship               ...
Case Study: Launching an Institute Matching was based upon the registration  survey…                               and mat...
Case Study: Launching an Institute Matches were prohibited if individuals had  previously co-authored or participated on a...
Case Study: Launching an Institute Individuals received „Netflix-style‟   recommendations:              Attendee, you     ...
Case Study: Launching an Institute We also arranged the seating chart to  maximize the chances strong matches  would inter...
Case Study: Launching an Institute And mapped attendees according to  conceptual interest ( )                             ...
Case Study: Launching an Institute Preliminary feedback “I know most of the people on the list, but then again, I should k...
Case Study: Launching an Institute Outcomes We have our first set of „Who did we try to  introduce to who?‟ data! Ongoing ...
Case Study: Launching an Institute Next time, instead of:   A     [go find]   B   We would try:   C [knows] A & B; C [go i...
Variation to introduce: Intervention!                       Norms that lead to                         defective strategie...
Q&AJeff Horon – j.horon (at) elsevier.com – http://jeffhoron.com           Jennifer Hill – jenchill (at) umich.edu
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Interventional Researcher Networking

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Interventional Researcher Networking

  1. 1. Interventional Researcher NetworkingVIVO Conference 2011 – Jeff Horon, Tony Tsai, Jennifer Hill
  2. 2. Science of Team Science Conference Jeff Horon
  3. 3. Agenda Why interventional networking? How it works What to do (within your own organization or study) Jeff Horon
  4. 4. Why networking at all?To bridge informational and social gaps, e.g.: A [isn‟t aware of] B C [is aware of] D [but wouldn‟t collaborate with D yet] Jeff Horon
  5. 5. Why bridge information gaps?To benefit from direct awareness effects A [is aware of] B Jeff Horon
  6. 6. Why bridge information gaps?To benefit from information broker effects A [expresses a need to] B [is aware of] C Jeff Horon
  7. 7. Why bridge information gaps?To benefit from information broker effects A B [connects] C Jeff Horon
  8. 8. Imagine a network where… Everyone knows 1 in 20 colleagues (5%) Jeff Horon
  9. 9. Imagine a network where… Everyone knows 1 in 10 colleagues (10%) Jeff Horon
  10. 10. Imagine a network where… Everyone knows 1 in 5 colleagues (20%) Jeff Horon
  11. 11. Why interventional networking?To counter researcher objections, e.g.Objection: “I already know everyone working in my field”Reality: Never the case in my experience! Jeff Horon
  12. 12. Why interventional networking?Evidence: University of Michigan Disease Target Sponsored Project Network Jeff Horon
  13. 13. Why interventional networking?Evidence: University of Michigan Disease Target Sponsored Project Network Core group members were unaware of non- core-group researchers Jeff Horon
  14. 14. Why interventional networking?Evidence: University of Michigan Researchers working with a family of anatomical conceptsSenior researcher listed 40 colleagues by nameSearch found ~1,500 on campus working with relevant concepts, hundreds as an area of focus Jeff Horon
  15. 15. Why interventional networking?Another common objection:Objection: “I only need a new collaborator every couple years and I only look for them when I need them”Reality: This is in-the-moment thinking. Knowledge before-the-fact can be helpful, for direct connections or to help one connect others. Also, don‟t forget about serendipitous interactions. Jeff Horon
  16. 16. Recall In order to be helpful, B had to be aware of C by the time A expressed a need A B [connects] C Jeff Horon
  17. 17. Why interventional networking?Researchers don‟t know everyone working in their fieldResearchers can help themselves and others through networking before there is an explicit needBut belief in these objections is pervasive and could undermine adoption of researcher networking tools Jeff Horon
  18. 18. Why interventional networking?Simply making the data available isn‟t enough because researchers use defective networking strategiesTypical defective networking strategy: “Who should I invite to an event?” (conference, poster session, etc.) -My department -Maybe that other department -People I‟ve worked with in the past -Other people I know of Jeff Horon
  19. 19. Why interventional networking?But what about people you don‟t know? Jeff Horon
  20. 20. Variation to introduce: Intervention! Norms that lead to defective strategies Research networking tools should ease interventional networking Jeff Horon
  21. 21. How interventional networking works Objectively detect people working in a field Use data to drive better-than-chance interactions Jeff Horon
  22. 22. Objective detectionTry to capture all relevant researchers, based upon sponsored project, publication, or other data Jeff Horon
  23. 23. Objective detectionObjective detection helps deal with defective networking strategiesTip: Don‟t disregard personal knowledge. Use it to check your results. Jeff Horon
  24. 24. Drive better-than-chance interactions Use data-driven approach to determine: For awareness interactions, Who should meet who? (and why?) Who among that group doesn‟t know who else? For strengthening existing connections, Who knows who and to what degree? Among the weaker connections, which could be strengthened? (and why?) Jeff Horon
  25. 25. Drive better-than-chance interactions What will create better-than-chance interactions is situation specific, but reasonable expectations are that they will occur when researchers: -don‟t know each other well -have some common interest(s) -stand to mutually benefit Jeff Horon
  26. 26. Case Study: Launching an Institute For a launch day event we strategized how to: -Match research interests, project needs, opinions -Shuffle existing working relationships, rank, etc. Social interaction models for different events throughout the day using a variety of survey, publication, sponsored project, HR, and other data Senior Faculty Junior Faculty‘Pitch’ Group Mentoring Mixed Equals Jeff Horon
  27. 27. Case Study: Launching an Institute Data Sources: ? Registration Survey Co-Authorship (Source: Scival Experts) Project Co-Participation (Source: Internal Awards Data) Jeff Horon
  28. 28. Case Study: Launching an Institute Matching was based upon the registration survey… and matched individuals with strong common interests and ? having reciprocal method „have expertise‟ / „need expertise‟ relationships Jeff Horon
  29. 29. Case Study: Launching an Institute Matches were prohibited if individuals had previously co-authored or participated on a sponsored project Jeff Horon
  30. 30. Case Study: Launching an Institute Individuals received „Netflix-style‟ recommendations: Attendee, you should meet… (why) (why) (why) Jeff Horon
  31. 31. Case Study: Launching an Institute We also arranged the seating chart to maximize the chances strong matches would interact Jeff Horon
  32. 32. Case Study: Launching an Institute And mapped attendees according to conceptual interest ( ) Jeff Horon
  33. 33. Case Study: Launching an Institute Preliminary feedback “I know most of the people on the list, but then again, I should know them. Anyway, there‟s no way the system would know that given that we haven‟t published together.” “I didn‟t know that she had the same interest in this topic.” “I like my table assignments. There were a few people I didn‟t know as well as a few that I knew from a long time ago that I could reconnect with.” “I‟ve never heard of these people on my list. I‟ll see if I can bump into them somehow.” “I‟ve met two people on my list. I‟ve finished my assignment for the day.” “I guess I don‟t get one of the cool folders [with recommendations]” (from a late registrant who missed the data cut-off for matching) Jeff Horon
  34. 34. Case Study: Launching an Institute Outcomes We have our first set of „Who did we try to introduce to who?‟ data! Ongoing analysis has been handed off to a research group Other groups have expressed strong interest Jeff Horon
  35. 35. Case Study: Launching an Institute Next time, instead of: A [go find] B We would try: C [knows] A & B; C [go introduce] A & B Jeff Horon
  36. 36. Variation to introduce: Intervention! Norms that lead to defective strategies Research networking tools should ease interventional networking Jeff Horon
  37. 37. Q&AJeff Horon – j.horon (at) elsevier.com – http://jeffhoron.com Jennifer Hill – jenchill (at) umich.edu

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