Visualizing an Open Innovation Platform: The structure and dynamics of Demola :: MindTrek 2013

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Visualizing an Open Innovation Platform: The structure and dynamics of Demola Huhtamäki, Luotonen, Kairamo, Still, Russell TUT // New Factory // VTT // Stanford Academic MindTrek 2013: "Making Sense of Converging Media”

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Visualizing an Open Innovation Platform: The structure and dynamics of Demola Jukka Huhtamäki, Ville Luotonen, Ville Kairamo, Kaisa Still and Martha G. Russell Presentation at Academic MindTrek 2013

Transcript of Visualizing an Open Innovation Platform: The structure and dynamics of Demola :: MindTrek 2013

Page 1: Visualizing an Open Innovation Platform: The structure and dynamics of Demola :: MindTrek 2013

Visualizing an Open Innovation Platform: The structure and

dynamics of Demola

Huhtamäki, Luotonen, Kairamo, Still, RussellTUT // New Factory // VTT // Stanford

Academic MindTrek 2013:"Making Sense of Converging Media”

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In this presentation

• Case context description: what is Demola?

• Challenges in measuring Demola & open innovation

• Use case examples

• Method: data-driven network animation

• Results

• Discussion

• Critique

• Wrap up and future work

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What is Demola?

• Open innovation platform & ecosystem engager established in 2008 in Tampere

• By 2013, 86 companies and 1200 students from 3 universities have participated in 250+ projects

• The Demola network is expanding internationally

• This study focuses in Demola Tampere

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Open innovation platform & ecosystem engager established in 2008 in Tampere

By 2013, 86 companies and 1200 students from 3 universities have participated in 250+ projects

The Demola network is expanding internationally; this study focuses in Demola Tampere

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Challenges in measuring Demola

…and open innovation in general:

• Tradition: A linear view on innovation;

• Measuring inputs (money) and outputs (patents, products, new companies);

• Survey-based methods, aggregate measures

How does one measure the performance of an ecosystem engager?

Still, K., Huhtamäki, J., Russell, M. & Rubens, N. 2012. Paradigm shift in innovation indicators—from analog to digital. Proceedings of the 5th ISPIM Innovation Forum, 9-12 December, Seoul, Korea.

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Use case examples

Who wants to measure?

Why do they want to measure? What will the do with the measurement insights?

Policy makers Interested in the impact that Demola has had to the surrounding ecosystem

Evaluate the utility of the platform for future investments and the applicability of the approach

Company representatives

Utility of Demola engament Decide whether to engage or not; Select an approach suitable for their portfolio

Demola operators Activity in general; Companies with changing (increasing/decreasing) Demola engagement; Ecosystem Structure

General Demola introductions, marketing & sales; Demola key area development

University students Reviewing opportunities that participating in a Demola project would open

Decide whether to participate or not

University decision-makers

Impact, new developments in the ecosystem

Add initiatives for students to get involved

International actors Impact, engagement, transformation To evaluate the utility of the process for deciding the applicability of the approach

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Method: data-driven network analysis (& action research)

(Hansen et al., 2009)

Project Detail Example

Project Id Project 115

Name Koukkuniemi 2020

Started 2010-05-04

Ended 2010-10-31

Status Completed

Collaboration Partner City of Tampere

Type of Partner Public

Project Domain Non-profit

Location Tampere

Key Areas well-being, knowledge management, regional studies

Project Team Members uta, uta, tut, tut

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Result 1: Project network

Nodes represent projects and companies

Company nodes are light green; other colors indicate cluster membership

Node size shows its betweenness value

Force-driven layout

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Result 2: Project domain network

Nodes represent project domains

Nodes are connected through domain co-occurence

Colors show cluster membership

Node size shows its betweenness

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Result 3: Project sphere animation

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Discussion

• Technical challenges exist when using internally collected data for network visualization and animation

• Visualization development challenges data-collection procedures and can add value to existing data

• Demola operators find value particularly in the animation of the project sphere; international collaborators have also expressed an interest in them

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Critique

• Method?

• Results?

• Validation?

• NAV model vs. visual analytics

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Acknowledgements & thank you

Time for your comments and questions.

Jukka Huhtamäki <jukka.huhtamaki @tut.fi>

Ville Luotonen

Ville Kairamo

Kaisa Still

Martha G. Russell

Acknowledgements Ville Ilkkala, Meanfish Ltd, supported animation development. Heikki Ilvespakka took care of exporting the data from the Demola platform