Silicon Valley vs. Europe Using data-driven network visualisations Dr. Antonio Hyder Director of Research

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Silicon Valley vs. Europe Using data-driven network visualisations Dr. Antonio Hyder Director of Research

Relationship networks remarkably affect the potential success in the markets Term ‘Ecosystem’ addresses complexities of networks of relationships Term ‘Orchestration’ refers to the capability to purposefully build and manage inter-firm innovation networks

1. Interventions can be orchestrated to facilitate transformation of innovation ecosystems 2. This study uses a big data-driven, relationship-based and network centric approach to operationalise an innovation ecosystems framework. 3. Network visualisations show how connections at level of individual nodes and links can have effects that ripple through an ecosystem as a whole 4. Coordinated and continuously improved use of visual and quantitative social network analysis, special characteristics, significant actors and connections in the innovation ecosystem can be revealed

Innovation ecosystem: Entities consisting of organisations and connections between them. They create extraordinary creativity and output on a sustanable basis (Hwang & Horowitt, 2012) and also consist of interdependent firms that form symbiotic relationships to create and deliver products and services (Basole and Rouse, 2008).

Innovation ecosystem: Innovation ecosystems are a network of relationships through which information, talent and financial resources flow through systems, creating sustained value co-creation including human networks and firm-level networks as well as the “inter-organizational, political, economic, environmental and technological systems of innovation through which a milieu conducive to business growth is catalysed, sustained and supported” (Russell et al., 2011)

Network Orchestration (1/2) Increasingly, networks are intentionally ‘orchestrated’ or ‘engineered’ by an organisational actor who recruits network members and shapes their interactions, corresponding to phases of innovation ecosystem building and management (Ritala et al., 2013) The impacts of such orchestration have been shown to be pervasive, robust and long-lived (Paquin & Howard-Grenville, 2013). To connect and manage competences across a broad network of relationships is one of the most important meta-capabilities for a networked world (Ritala et al., 2009). There have been many programmes of government interventions to create and support networks (Cunningham & Ramlogan, 2012).

Network Orchestration (2/2): Fully explores the processes in innovation ecosystems that are enacted through time and how nested network structure shapes the process. Relationships and interactions should be continuously examined. Network orchestrators are urged to engage in sense-making for external audiences who have little or no prior understanding of the transformation activity & its ‘rightness’ (Möller and Rajala, 2007).

Innovation ecosystems transformation framework

Data-driven network visualisations: They offer a powerful approach to providing evidence-based information when talking about ecosystems, their structures, actors and interactions. The visualisations can reflect the structure of an innovation ecosystem at a single point in time and they can also show the evolution of an ecosystem’s actors and their relationships over time (Basole et al., 2012).

EIT ICT Labs data collection EIT is a Knowledge and Innovation Community (KIC) EIT ICT Labs sample is drawn by selecting all the companies that have their primary office in one of the six co-location cities of EIT ICT Labs: Berlin, Eindhoven, Helsinki, Paris, Stockholm and Trento.

Red: Companies Blue: Key individuals Blue links: From individuals to companies Green: Financial firms Green links: From investors to companies Gray links: from EIT ICT Labs co-locations to companies

Blue: Key individualsGreen: Financial Firms Blue links: Individuals to CompaniesGreen links: Investors to Companies Red: CompaniesGray links: EIT ICT Labs co-location to companies

Blue: Key individualsGreen: Financial Firms Blue links: Individuals to CompaniesGreen links: Investors to Companies Red: CompaniesGray links: EIT ICT Labs co-location to companies

San Francisco considered as a 7 th EIT ICT labs city for the same year 2013

Red: Companies Blue: Key individuals Blue links: From individuals to companies Green: Financial firms Green links: From investors to companies Gray links: from EIT ICT Labs co-locations to companies

Conclusion: 1. Data-driven network visualisations offer a powerful approach for providing evidence- based information when talking about ecosystems, their structures, key actors and interactions, revealing their context and the potential for novel structures and relationships. 2. Data-driven visualisations can support the development of insights needed to orchestrate transformations of ecosystems, recognising that activities orchestrated through individual actors of a network impact the whole network with the potential to leverage innovation.

Conclusion: 3. Network orchestrators should simultaneously: A. Facilitate the network B. Enable the individual actors and their activities.

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Silicon Valley vs. Europe Using data-driven network visualisations Dr. Antonio Hyder Director of Research

References: International Journal of Technology Management, Vol. 66, Nos. 2/3, 2014 p.243 Insights for orchestrating innovation ecosystems: the case of EIT ICT Labs and data-driven network visualisations Contact me: LinkedIn: Antonio Hyder Twitter: Antonio Hyder