Data-Driven Analysis of Co-Creation in Innovation EcosystemsJukka Huhtamäki, Martha G Russell, Neil Rubens and Kaisa StillEBRF 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
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 YifanHu Multilevel algorithm and nodes are inflated according to their indegree, i.e. the number of the connected investors. ILLUSTRATIVE
Investments As Value Co-Creation ILLUSTRATIVE 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 ILLUSTRATIVE Example view to IEN dataset for keyword search “Tampere”. Nodes represent companies and their previous and current employees. The network layout is created with FruchtermanReingold algorithm and nodes are inflated according to their outdegree. Protocols for anonymity are evolving.
Towards Actionable Co-Creation Insights Relationship interlocks structure resource flows for co-creation. Openly accessible data provides directional results. Data can be federated to co-create datasets. Visual network analysis
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
We apply these methods and tools to better understand how local/regional investments made for globalization can return benefits to the local region. Make complex relationships known for sharing and co-creation 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
AppendixIEN 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.