Orchestrating Ecosystem Transformation with Data-Driven Network Visualizations

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Innovation Ecosystems refer to the inter-organizational, political, economic, environmental, and technological systems through which a milieu conducive to business growth is catalyzed, sustained, and supported. The orchestration of relationships through which talent, information and financial resources flow is a critical capability for regional transformation. Using data-driven visualizations of relationships for co-creation, examples from Norway, Europe and Austin are described in the context of technology-based wealth creation.

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Orchestrating Ecosystem Transformation with Data-Driven Network Visualizations

  1. 1. Orchestra)ng    Ecosystem  Transforma)ons    with    Data-­‐driven  Network  Visualiza)ons  Martha  G  Russell  h-p://mediax.stanford.edu  Neil  Rubens,  Jukka  Huhtamäki,  Kaisa  SBll,  Camilla  Yu,  Rahul  Basole      
  2. 2. Ecosystem  
  3. 3. InnovaBon  Ecosystems  Innova)on  Ecosystems  refer  to  the  inter-­‐organizaBonal,  poliBcal,  economic,  environmental,  and  technological  systems  through  which  a  milieu  conducive  to  business  growth  is  catalyzed,  sustained,  and  supported.    Heterogeneous  and  conBnuously  evolving  set  of  firms  that  are  interconnected  through  a  complex,  global  network  of  relaBonships.  [Basole  et  al.,  2012    A  dynamic  innovaBon  ecosystem  is  characterized  by  a  conBnual  realignment  of  synergisBc  relaBonships  that  promote  growth  of  the  system.    In  agile  responsiveness  to  changing  internal  and  external  forces,  knowledge,  capital  and  other  vital  resources  flow  through  these  relaBonships.    Martha G. Russell, Kaisa Still, Jukka Huhtamaki, and Neil Rubens, “Transforming innovation ecosystems through shared visionand network orchestration,” Triple Helix IX Conference, Stanford University, July 13, 2011.
  4. 4. InnovaBon  Ecosystems  Approach  •  Networked  systems  perspecBve  to  examine  why,  when,  and  how  interfirm  networks  and  alliances  form  and  change  (Gula)  et  al.,  2000)  •  Co-­‐crea)on  creates  value  (Ramaswamy  &  Guillart,  2004)  •  Value  creaBon  requires  orchestra)on  among  firms  across  segments  (Basole  &  Karla,  2012;  Dhanaraj  &  Parkhe,  2006)  •  Responsiveness  to  changing  internal  and  external  forces  (Rubens  et  al.,  2011)  •  Shared  Vision  guides  and  accelerates  transformaBon  (Russell  et  al.,  2011)  
  5. 5. DistanceOldNew
  6. 6. The Way We USED to Think About Organizations New  OrganizaBonal  Chart  Based  on  RelaBonships  Relationship-Focused Co-Creation InfrastructureStakeholder  Infrastructure  =  RelaBonships  (Companies  are  interlocked  through  key  people  –  informa8on  flow,  norms,  mental  models.(Davis,1996)  
  7. 7. New Data & New ToolsAccessing Data Streams about Innovation   Building a Dataset on InnovationCrystallisation Through Visualisation The  Card-­‐Mackinlay-­‐Shneiderman  visualisaBon  reference  model:(Card  et  al.,  1999;  Miksch,  2005)  !"#$%&()*+%,"-)*%./0*1)2*31$%4"-"/*31%51*+6$)$%,)1)10%7)$8*+)2*31% 5(39"%:1;"++)0"1("%</)9*;"%=*;*%!"##$%&()*+,-%Accuracy  of  Wikipedia  (Giles,  2005)    
  8. 8. STEP  1  Boundary  SpecificaBon  STEP  2  Metrics  IdenBficaBon  STEP  3  ComputaBon,  Analysis  &  VisualizaBon  STEP  4  Sense  Making  &  Storytelling  DATA                determines  feeds  Deals  &  Alliances  Execu)ves  &  Funding  Public  Opinion  &  Discourse  IEN  NL  SDC  Iden8fy,  extract,  and  curate  InnovaBon  Ecosystem  Network    Data-­‐driven  VisualizaBons  Basole,  Russell,  Huhtamäki,  SBll  and  Rubens,  “Understanding  Mobile  Ecosystem  Dynamics:  A  Data-­‐Driven  Approach,”  Submi-ed  to  JIT  March  2013.  
  9. 9. The  new  maps  may  be  based  on  the  connecBons  through  relaBonships  -­‐    rather  than  on  distance.    §  Ecosystem  PerspecBve  §  RelaBonship  based    §  Links  form  networks  §  Resource  flows  =  knowledge,  capital,  talent  §  Network  orchestraBon    
  10. 10. h-p://www.slowtrav.com/blog/chiocciola/Geirangerlord.jpg  
  11. 11. Norwegian  Tech-­‐based  Companies  Their  Branch  Offices  and  Their  Financial  Orgs  Links  show  relaBonships  Example  view  to  IEN  dataset  in  Gephi.  Companies  are  selected  with  keyword  search  “Norway  +  Norwegian;”  the  funding  organizaBons  associated  with  those  companies  are  added    Nodes  represent  companies  and  their  investors;  edges  indicate  resource  flows.    The  network  layout  is  created  with  Yifan  Hu  MulBlevel  algorithm  and  nodes  are  inflated  according  to  their  indegree,  i.e.  the  number  of  the  connected  investors.    
  12. 12. Advisors & Angels Expand AccessInvestors  leverage  co-­‐creaBon  opportuniBes  with  investments  in  mulBple  companies.  Intl  companies  not  shown.    Companies  leverage  value  co-­‐creaBon  opportuniBes  through  relaBonships  with  mulBple  investors.  Some  investors  are  internaBonal.    Timeline  analysis  of  investment  events  reveals  pa-erns  of  co-­‐investment  –  an  indicaBon  of  intenBon  to  co-­‐create  value  and,  perhaps,  sBmulus  programs.  IEN  Dataset,  July  2010  
  13. 13. Sørlandet is world leading in offshore oil drillingtechnologyTorger Rev, Innovation Ecosystems Summit, Stanford University, July 11, 2011
  14. 14. ShippingbrokersEffectiveports andterminalsAdvancedship equip-mentMaritimeR&DSpecializedship yardsMaritimeeducationShipdesignMaritimeITShipmanagementMarine  insurance  Shipping  finance  Advanced  fisheries  Environmental  standards  MariBme  policies  Offshore  oil  and  gas  industry  LogisBcs  systems  MariBme  lawyers  Ship  classificaBon  services  SHIPPING  Mari)me:    From  ship  tonnage  to  mari)me  technology  and  finance  Torger Rev, Innovation Ecosystems Summit, Stanford University, July 11, 2011
  15. 15. SHIPPING  Torger Rev, Innovation Ecosystems Summit, Stanford University, July 11, 2011Mari)me:    From  ship  tonnage  to  mari)me  technology  and  finance  
  16. 16. Insights  About  Norway  •  Dual  offices:  regional  and  Oslo  •  In  sectors  we  studied  –  Business  locaBons  parallel  technical  university  programs    –  Investor  relaBonships  have  strong  local  links    •  Some  invesBng  organizaBons  are  governmental  programs  •  Expands  to  Oslo  when  offices  are  in  Oslo  •  InternaBonal  relaBonships  linked  to  small  set  of  personal  relaBonships  at  execuBve  level  –  InternaBonal  investors  drawn  through  execuBve  relaBonships  •  RelaBonships  through  execs  at  Google  and  AOL  provide  channels  for  global  network  expansion  
  17. 17. CapDigital  -­‐  Regional  Sector  Catalyst  Vision  To  catalyze  the  new  digital  infrastructure  in  France  with  global  connecBons  To  create  an  ecosystem  to  facilitate  the  relaBonship  between  France  and  global  market  Enable  Paris  to  become  global  region  of  the  market  for  digital  services        How  do  you  spend  money  locally  to  enhance  global  parBcipaBon  in  a  way  that  returns  the  benefit  back  home?  • CapDigital  members:  –  Small  startups  –  Large  companies  –  Support  programs  28  
  18. 18. Parisian  InnovaBon  Ecosystem  CapDigital  –  France  -­‐  Global  Pale  Red:  French  company  Dark  Red:  CapDigital  member    Light  Green:  Foreign  Venture/  firm  Dark  Green:  French  venture  firm    Blue:  Foreign  company  From  IEN  Dataset  2010  Selected  Paris  companies  Linked  people  &  venture/financing  enBBes  Linked  companies,  people  &  v/f  enBBes    1  degree    2  degree  29  Preliminary  and  proprietary  for  CapDigital  Permission  required  for  sharing  ©  2010  InnovaBon  Ecosystems  Network  InnovaBon  Ecosystems  Network  
  19. 19. Network  Graph  Parisian  InnovaBon  Ecosystem  Pale  Red:  French  company  Dark  Red:  CapDigital  member    Light  Green:  Foreign  Venture/  firm  Dark  Green:  French  venture  firm    Blue:  Foreign  company  From  IEN  Dataset  2010  Selected  Paris  companies  Linked  people  &  venture/financing  enBBes  Linked  companies,  people  &  v/f  enBBes    1  degree    2  degree  30  Preliminary  and  proprietary  for  CapDigital  Permission  required  for  sharing  ©  2010  InnovaBon  Ecosystems  Network  InnovaBon  Ecosystems  Network  
  20. 20. CapDigital  Program    OpportuniBes  Pale Red: French companyDark Red: CapDigital memberLight Green: Foreign Venture/ firmDark Green: French venture firmBlue: Foreign companyZone  2:  VC  Community  Zone  3:  New  CapDigital  Members  Zone  4  of  Parisian  Two-­‐Level  InnovaBon  Ecosystem  From  IEN  Dataset  2010  Selected  Paris  companies  Linked  people  &  venture/financing  enBBes  Linked  companies,  people  &  v/f  enBBes    1  degree    2  degree  
  21. 21. Analysis  of  EIT  ICT  Labs:  Trento  included  as  the  sixth  node,  more  ciBes  connected  to  colocaBon  centers,  updated  data  and  transformaBon  in  place    SBll,  Huhtamäki,  Russell,  Rubens  (2012).  Transforming  Innova8on  Ecosystems  Through  Network  Orchestra8on:  Case  EIT  ICT  Labs  
  22. 22. Adding  San  Francisco  Bay  Area  as  “the  seventh  EIT  ICT  Labs  node”  for  contrast,  interconnecBons,  comparison  and  benchmark  SBll,  Huhtamäki,  Russell,  Rubens  (2012).  Transforming  Innova8on  Ecosystems  Through  Network  Orchestra8on:  Case  EIT  ICT  Labs  
  23. 23. AusBn  Ecosystem    Enterprises,  Deals  &  Alliances  678  companies  and  498  interconnecBons  
  24. 24. Aus)n’s  Young  Growth  Companies  Primary  Office  in  Aus)n  Investors    AusBn  Ventures    Silverton  Partners    DFJ  Mercury    Ba-ery-­‐  Ventures    Floodgate    S3  Ventures    New  Enterprise  Associates    Rho  Capital  Ventures    Texas  Emerging  Technology  Fund    Interwest  Partners    Companies  =  801  Investors  –  286  Leadership  Indiv’s  =  1355    Key  Individuals    Joshua-­‐  Baer    Kevin-­‐  Cunningham    John  Hime    Kip  Mcclanahan    Bill  Boebel    Larry  Warnock    Robert  Reeves    Jason  Calacanis    Mike  Maples    Ron  Conway    Companies  DaBcal    Homeaway    Sailpoint-­‐technologies    Mass-­‐relevance    Digby    B-­‐side    Bazaarvoice    Wp-­‐engine    Convio-­‐2    Gowalla    Actacell    IEN  Dataset,  March,  2013  
  25. 25. Aus)n’s  Young  Growth  Companies    Primary  Office  in  Aus)n  Zone  3  Zone  1  Zone  2  
  26. 26. Zone 1: Multiple Connections & InvestorsDaticalATI company. Datical received seed fund of $660K in July last year. It hasdiversified investors, including Austin Ventures.Funding                              TOTAL    $660K  Seed,  7/12  AusBn  Ventures  Mohr  Davidow  Ventures  Mercury  Fund  John  Hime  Robert  Reeves  Daniel  Nelson  Leadership                              Daniel  Nelson  CEO,  Cofounder  Pete  Pickerill  VP  Products,  Cofounder  Robert  Reeves  CTO,  Cofounder  
  27. 27. John Hime is on the board of both Affinegy (ATI alumus company) and Datical(current ATI company). Datical has had several venture investments; Affinegyhas had none yet. Relationship may create bridge to investment.ZONE 1: Emerging Network
  28. 28. Ordoro - ATI AlumusA current ATI company isconnected with an ATI alumuscompany through Central TexasAngel Network.Contribution of ATI, such asintroducing the companiesXERIS develops patient-friendly injectables basedon its XeriJect™ andXeriSol™ formulation anddelivery platforms.Ordoro provides a web appfor small and medium-sizede-commerce retailers tomanage their orders,inventory and suppliers.XERIS - Current ATIZONE 2: Potential Network
  29. 29. Inxero, a current ATIcompanyZONE 3: Need Network
  30. 30. Aus)n’s  Young  Growth  Companies    Primary  Office  in  Aus)n  Zone  3  Zone  1  Zone  2  
  31. 31. AusBn  Start-­‐ups,  Founders  and  Angels  IEN  Dataset,  March,  2013  692  companies  3500+  investors  $79K  average  investment    
  32. 32. Colleges/Universi)es  =    200+  University  of  Texas,  AusBn    Stanford  University    Massachuse-s  InsBtute  of  Technology    University  of  California,  Berkeley  Georgia  InsBtute  of  Technology    University  of  Michigan    Harvard  University  Purdue  University    University  of  Colorado,  Boulder    University  of  Chicago    Loca)ons  =  200+  San  Francisco  New  York,  NY  Los  Angeles  Houston  Palo  Alto    Dallas  London    Boston  Chicago  Silicon  Valley    Sectors/Markets  =  374  Social  media    Mobile  SaaS  e-­‐commerce  Digital  media    Social  commerce  Consumer  internet    Marketplaces  Small  and  medium  businesses  EducaBon    Companies  =  2000+  Latakoo    Bazaarvoice  Infochimps    SalesVu  OwnLocal    Predictable  Data    Mass  Relevance    ForcasBx  SQMOS  Vivogig      Network  of  AusBn  Start-­‐ups,    Founders  &  Angels   IEN  Dataset,  March,  2013  
  33. 33. Actors &EventsImpactover timeCoalitionsShared  Vision  TransformaBon  Measure & TrackInteract &FeedbackCo-CreateValueMeasuring Impact of Transformative Coalitionsin Innovation EcosystemsMartha G. Russell, Kaisa Still, Jukka Huhtamaki, and Neil Rubens, “Transforming innovation ecosystems through shared visionand network orchestration,” Triple Helix IX Conference, Stanford University, July 13, 2011.
  34. 34. IC2  Fellows’  Co-­‐authorships  
  35. 35. THE  GOAL  OF  CREATIVE  COLLABORATIONS  IS  TO  DO  SOMETHING  TOGETHER  THAT  NEITHER  COULD  DO  INDEPENDENTLY    PATE  IN  IC2  IITIATIVE    JOIN  THE  EFFORT  AND  HELP  US  MAP  IT    IC2-­‐IEN  WORKING  SESSION  –  JUNE  3-­‐4,  2013  FUTUR  EST  EN  SEINE,  PARIS,  JUNE  12-­‐13,  2013  INTERNATIONAL  SOCIETY  OF  PROFESSIONAL  INNOVATION  MANAGERS  –  JUNE  16-­‐19,  HELSINKI    
  36. 36. 53Skill  of  the  Future  =    Network  OrchestraBon  
  37. 37. •  Thank  you          •  Martha  Russell  •  InnovaBon-­‐ecosystems.org  •  marthar@stanford.edu  

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