Data-Driven Analysis of
Co-Creation in Innovation Ecosystems
 Jukka Huhtamäki, Martha G Russell, Neil Rubens and Kaisa Still
         EBRF 2010, September 15-16, Nokia, Finland

           www.innovation-ecosystems.org
Innovation Ecosystems & Value Co-Creation
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.

Value is co-created for the innovation ecosystem through events, impacts and
coalitions/networks that emerge from a shared vision of the desired transformations.
Data-driven metrics measure, track and visualise the transformation, empowering
interaction with feedback for the shared vision.

                  Innovation Ecosystems Transformation Framework




                              www.innovation-ecosystems.org
Research Problem/Questions

 Theme: How can data-driven visual social network analysis
 provide insights on innovation ecosystems?

 We look for insights that can be used to:
 • Communicate complexity to co-create vision
 • Identify and empower influential individuals for critical actions
 • Connect components to catalyze the evolution of the ecosystem
 • Develop and implement programs (meetings, funding, initiatives) to foster
   co-creator networks
 • Measure and transform an innovation ecosystem

 This study: How do co-creator networks enable local/regional
 ROI on innovation investments made for globalization?

 Work in progress!
 www.innovation-ecosystems.org
Infrastructure for Resource Flows
                         - - - Relationships
 The Way We USED to Think About Organizations      New Organizational Chart Based on Relationships




 Relationship-Focused Co-Creation Infrastructure
                                                                 (Companies are interlocked through
                                                                 key people – information flow, norms,
                                                                 mental models.(Davis,1996)


                                                                 (Visual) Social Network Analysis
                                                                 “. . . allows investigators to gain new
                                                                 insights into the patterning of social
                                                                 connections, and it helps investigators
                                                                 to communicate their results to others.“
                                                                 (Freeman, 2009)
Data for Visualisation & Knowledge Crystallisation




 Accessing Data Streams about Innovation   Building a Dataset on Innovation




  Crystallisation Through Visualisation                The Card-Mackinlay-Shneiderman visualisation
                                                       reference model:(Card et al., 1999; Miksch, 2005)
Investments as Value Co-Creation
Companies leverage value co-creation
opportunities through relationships with
multiple investors. Some investors are
international.

Investors leverage co-creation
opportunities with investments in multiple
companies. Intl companies not shown.

Timeline analysis of investment events
reveals patterns of co-investment – an
indication of intention to co-create value.




                                              Example view to IEN dataset in Gephi.
                                              Companies are selected with keyword
                                              search “Finland + Finnish;” the funding
                                              organizations associated with those
                                              companies are added Nodes represent
                                              companies and their investors; edges
                                              indicate resource flows. The network
                                              layout is created with Yifan Hu
                                              Multilevel algorithm and nodes are
                                              inflated according to their indegree, i.e.
                                              the number of the connected investors.
Investments As Value Co-Creation




                      Degree distribution




Example view to IEN dataset in NodeXL. Nodes represent companies and their investors; companies are selected with
keyword search “Finland + Finnish”. Nodes are inflated according to their indegree, i.e. the number of investors of a
company. Finnish Industry Investment is the main investor with outdegree 17 (betweenness centrality 1965).
Employee Mobility As Value Co-Creation




 Example view to IEN dataset for keyword search “Tampere”. Nodes represent companies and their previous and current
 employees. The network layout is created with Fruchterman Reingold algorithm and nodes are inflated according to
 their outdegree. Protocols for anonymity are evolving.
Towards Actionable Co-Creation Insights
Relationship interlocks structure         We apply these methods and tools to
resource flows for co-creation.           better understand how local/regional
                                          investments made for globalization can
                                          return benefits to the local region.
Openly accessible data provides
directional results. Data can be
federated to co-create datasets.
                                                   Make complex relationships known for
                                                         sharing and co-creation
Visual network analysis
 • Reveals co-creation relationships
    • People, companies, funding
 • Reveals patterns of co-creation
   • Existing edges and potential links
• Provides analytical opportunities
   • Augment dataset with data from
     multiple sources, if needed
• Communicates complex
  relationships to diverse groups
                                                Johari Window, Joseph Luft and Harry Ingham, 1955
Discussion & Takeaways


Knowledge crystallisation provides co-creation feedback loop: also support for
interventions, action research, policy analysis.

Visualisations reveal multidimensional complexities.

SNA metrics highlight patterns of ecosystem relationships.

Technically, our framework for tracking, processing and visualising data enables
the parallel uses of various state of the art analysis tools.

Data sources abound; can be federated for co-creation of analytical & actionable
insights. Collaborations are welcome.

Discovering the story behind numbers and their visualisations requires context,
perspective, interaction and iteration!

www.innovation-ecosystems.org
Appendix
IEN Work in Progress
Regional case studies are underway:
•Cap Digital, Paris
•Birmingham Science Park Aston
•New York City Media Labs
•Norwegian Regional Development

Future presentations

September 18-19, 2010, Beijing, China, “Innovation Ecosystems: New Insights with Network
Approach”, Beijing First Global World City Conference, September 18-19, 2010, Beijing, China.

October 5, 2010, Oslo, Norway, “Innovation Ecosystems in Traditional and Changing Cultures:
Examples from Minnesota and Silicon Valley”, Norwegian Information Technology Forum October 5,
2010, Oslo, Norway.

October 22, 2010, Madrid, Spain, “Using Social Media to Leverage Triple Helix Insights in
Innovation Ecosystems,” Workshop at Triple Helix Conference VIII, October 12, 2010, Madrid, Spain.

November 7-10, 2010, Austin, TX, “Using Data-Driven Social Network Analysis for Insights on
Innovation and Change,” INFORMS, Austin, TX.

November 14 – 17, 2010, Sacramento, CA, “Social Media Conversations and Value Networks in
the Green-tech Innovation Ecosystem,” 2010 Behavior, Energy and Climate Change Conference.

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Innovation ecosystems value co-creation

  • 1. Data-Driven Analysis of Co-Creation in Innovation Ecosystems Jukka Huhtamäki, Martha G Russell, Neil Rubens and Kaisa Still EBRF 2010, September 15-16, Nokia, Finland www.innovation-ecosystems.org
  • 2. Innovation Ecosystems & Value Co-Creation 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. Value is co-created for the innovation ecosystem through events, impacts and coalitions/networks that emerge from a shared vision of the desired transformations. Data-driven metrics measure, track and visualise the transformation, empowering interaction with feedback for the shared vision. Innovation Ecosystems Transformation Framework www.innovation-ecosystems.org
  • 3. Research Problem/Questions Theme: How can data-driven visual social network analysis provide insights on innovation ecosystems? We look for insights that can be used to: • Communicate complexity to co-create vision • Identify and empower influential individuals for critical actions • Connect components to catalyze the evolution of the ecosystem • Develop and implement programs (meetings, funding, initiatives) to foster co-creator networks • Measure and transform an innovation ecosystem This study: How do co-creator networks enable local/regional ROI on innovation investments made for globalization? Work in progress! www.innovation-ecosystems.org
  • 4. Infrastructure for Resource Flows - - - Relationships The Way We USED to Think About Organizations New Organizational Chart Based on Relationships Relationship-Focused Co-Creation Infrastructure (Companies are interlocked through key people – information flow, norms, mental models.(Davis,1996) (Visual) Social Network Analysis “. . . allows investigators to gain new insights into the patterning of social connections, and it helps investigators to communicate their results to others.“ (Freeman, 2009)
  • 5. Data for Visualisation & Knowledge Crystallisation Accessing Data Streams about Innovation Building a Dataset on Innovation Crystallisation Through Visualisation The Card-Mackinlay-Shneiderman visualisation reference model:(Card et al., 1999; Miksch, 2005)
  • 6. Investments as Value Co-Creation Companies leverage value co-creation opportunities through relationships with multiple investors. Some investors are international. Investors leverage co-creation opportunities with investments in multiple companies. Intl companies not shown. Timeline analysis of investment events reveals patterns of co-investment – an indication of intention to co-create value. Example view to IEN dataset in Gephi. Companies are selected with keyword search “Finland + Finnish;” the funding organizations associated with those companies are added Nodes represent companies and their investors; edges indicate resource flows. The network layout is created with Yifan Hu Multilevel algorithm and nodes are inflated according to their indegree, i.e. the number of the connected investors.
  • 7. Investments As Value Co-Creation Degree distribution Example view to IEN dataset in NodeXL. Nodes represent companies and their investors; companies are selected with keyword search “Finland + Finnish”. Nodes are inflated according to their indegree, i.e. the number of investors of a company. Finnish Industry Investment is the main investor with outdegree 17 (betweenness centrality 1965).
  • 8. Employee Mobility As Value Co-Creation Example view to IEN dataset for keyword search “Tampere”. Nodes represent companies and their previous and current employees. The network layout is created with Fruchterman Reingold algorithm and nodes are inflated according to their outdegree. Protocols for anonymity are evolving.
  • 9. Towards Actionable Co-Creation Insights Relationship interlocks structure We apply these methods and tools to resource flows for co-creation. better understand how local/regional investments made for globalization can return benefits to the local region. Openly accessible data provides directional results. Data can be federated to co-create datasets. Make complex relationships known for sharing and co-creation Visual network analysis • Reveals co-creation relationships • People, companies, funding • Reveals patterns of co-creation • Existing edges and potential links • Provides analytical opportunities • Augment dataset with data from multiple sources, if needed • Communicates complex relationships to diverse groups Johari Window, Joseph Luft and Harry Ingham, 1955
  • 10. Discussion & Takeaways Knowledge crystallisation provides co-creation feedback loop: also support for interventions, action research, policy analysis. Visualisations reveal multidimensional complexities. SNA metrics highlight patterns of ecosystem relationships. Technically, our framework for tracking, processing and visualising data enables the parallel uses of various state of the art analysis tools. Data sources abound; can be federated for co-creation of analytical & actionable insights. Collaborations are welcome. Discovering the story behind numbers and their visualisations requires context, perspective, interaction and iteration! www.innovation-ecosystems.org
  • 11. Appendix IEN Work in Progress Regional case studies are underway: •Cap Digital, Paris •Birmingham Science Park Aston •New York City Media Labs •Norwegian Regional Development Future presentations September 18-19, 2010, Beijing, China, “Innovation Ecosystems: New Insights with Network Approach”, Beijing First Global World City Conference, September 18-19, 2010, Beijing, China. October 5, 2010, Oslo, Norway, “Innovation Ecosystems in Traditional and Changing Cultures: Examples from Minnesota and Silicon Valley”, Norwegian Information Technology Forum October 5, 2010, Oslo, Norway. October 22, 2010, Madrid, Spain, “Using Social Media to Leverage Triple Helix Insights in Innovation Ecosystems,” Workshop at Triple Helix Conference VIII, October 12, 2010, Madrid, Spain. November 7-10, 2010, Austin, TX, “Using Data-Driven Social Network Analysis for Insights on Innovation and Change,” INFORMS, Austin, TX. November 14 – 17, 2010, Sacramento, CA, “Social Media Conversations and Value Networks in the Green-tech Innovation Ecosystem,” 2010 Behavior, Energy and Climate Change Conference.