From Skunk Works to Enterprise Open Innovation

by Klaus-Peter Speidel

Deploying Open Innovation Inside the Enterprise

From Skunk Works to Enterprise Open Innovationby Klaus-Peter Speidel and Michael Bonner

The brightest ideas often come from unexpected sources. This is why Open Innovation (OI) works. When companies go outside their own R&D departments to tap the knowledge of thousands of independent inventors, university researchers and other knowledge holders, good things happen: OI helps organizations overcome group-think, encourages lateral thinking and promotes collaboration across different fields.

Let’s go back to the initial definition of Open Innovation by Henry Chesbrough. He defined Open Innovation as the systematic facilitation of the inflow and outflow of ideas beyond the borders of the enterprise. In other words, Open Innovation is about making borders permeable: Chesbrough’s famous drawing of an innovation funnel with holes through which ideas and solutions flow in and out made this very clear.

Now, the borders that isolate organizations from the “outside world” are not the only ones. There are multiple borders that isolate different divisions within an organization from each other. Whether hierarchical, functional, or cultural, they all have one thing in common: they prevent knowledge from flowing where and when it is needed.

Making these internal borders systematically permeable through Open Innovation could thus be a worthy endeavor. Let’s call this Enterprise Open Innovation (EOI).

Using EOI to shoot holes in Silos

As early as 1991, the US National Academy of Engineering reported that “case after case shows the superiority of cross-functional teams for speed” and recommended the Skunk Works technique, whereby companies build dedicated cross-functional innovation teams to work on specific projects. The value of this kind of cross-functional collaboration for innovation lead many companies to create dedicated cross-functional innovation teams that cut across knowledge silos. But this approach is more like sticking a needle through the wall of a silo, rather than actually making it sustainably permeable. More specifically, though, there are a important limitations to this approach, which EOI might overcome.

From Skunk Works to EOI

  1. A Skunk Works team is always built with a specific purpose in mind (a “mission”). Determining purpose remains totally centralized. There is thus no natural way in which topics can “emerge” based on observations (let alone interactions) of employees.
  2. Team members are chosen based on management’s assessment of which people are suitable for the “task-force.” There is no framework for accepting contributions from sources that are external to this team.
  3. Skunk Works doesn’t help finding solutions from unexpected sources.

EOI could address all these problems. Semantic and AI expert identification technologies that give companies access to solutions outside the corporation and allow widespread access to challenges already exist. These same tools could be deployed within the enterprise and facilitate enterprise-wide collaboration. The advantage of partially automatizing expert-identification both internally and externally is that it eliminates the preconceptions of human experts which can bias team-building within the framework of Skunk Works. The openness of the system allows interest-based participation of all employees and helps identify unforeseen contributors, thereby facilitating the emergence of new kinds of solutions, which typically come from unexpected sources.

Why isn’t EOI a more widespread practice yet?

There are both cultural and technical reasons (and the list could be longer).

Culture

  1. The “silo’d” structure of organization which EOI is supposed to overcome: most employees’ job descriptions (and daily tasks) don’t naturally call for the kind of cross-functional collaboration which is essential for innovation.
  2. Individual resistance to sharing. People sometimes feel that their position will be threatened if they share information. But in an open network where sharing is a natural practice, and yields recognition, these fears can be overcome.

Technology

  1. Lack of the kind of social networking technologies and methods that allow many people to organize collaboration across locations and functions based on common interest in topics and challenges in a natural and organic way
  2. Absence of advanced semantic technologies for expert identification. The use of these tools boosts contribution by allowing to reach out actively to clearly identified topic experts as well as unobvious contributors

You do not need elaborate techniques to demonstrate the existence of knowledge silos in order to pull them down and create transparent social networks. It’s about people connecting not about connecting people. Methods and tools that are developed in the framework of the social semantic web allow them to do this based on what they want to accomplish and the needs they identify. Michael Bonner and I also wrote an EOI primer on hypios Thinking.

Feedback welcome!

A Guide to Open Innovation and Crowdsourcing

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Michael BonnerMichael Richard Jackson Bonner works for Allan Bonner Communications Management Inc. He is in charge of Solver relations at hypios, an open problem-solving company based in Paris. Michael holds an MPhil from the University of Oxford, and is currently reading for a doctorate in Oriental Studies. His website is www.jacksonbonner.com.

Klaus-Peter SpeidelKlaus-Peter Speidel is the VP of Communications at hypios, which provides enterprises with open innovation ecosystems.

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  1. Hi, I’m interested by Open Innovation and Rapid Innovation: https://nbry.wordpress.com/2011/01/22/when-open-innovation-meets-rapid-innovation/

    I would like to know more about Hypios and EOI approach. Can we get in touch? @nicobry on Twitter

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