A New Paradigm for Innovation
Describe and Search
by Klaus-Peter Speidel
Within the problem solving aspect of innovation there is a paradigm shift on the horizon. The old paradigm is DAT (Define and Try). This refers to the traditional approach of relying on strictly internal research and development solutions, where researchers and engineers quickly define their problem and then try to figure out a solution themselves and with their closer team-members. We think this approach is inherently less efficient than what can be called DAS (Describe and Search). Here’s why:
A typical roadblock for problem solving is lack of information. There are two ways to obtain information: producing it or finding it. That you lack a piece of information doesn’t imply that it doesn’t exist and has to be produced. In most cases, a lack of information is in fact a lack of access. In many cases we’ve assimilated this reality, as when we run a web-search to figure out the answer to a question.
For challenging Research and Development (R&D) problems, it is more difficult to obtain solution-information. However, the fact that it’s harder to find doesn’t mean that nobody has the relevant solution-information and that it’s best for the problem-owner (the person “having” the problem) to go into a resource-consuming information-production mode in order to solve it, for example by conducting experiments in the lab. Given the likely existence of the solution somewhere, this would be grossly inefficient. And yet, it happens a lot all the same.
Systematic patent and publication research is a first step to avoid reinventing the wheel. But the fact that it doesn’t work, doesn’t mean there’s no solution. In many cases, solutions are, what you could call “embodied” in a strong sense: there is no searchable trace of the solution’s existence (no publications or patents), however somebody knows how to get to the solution relatively fast if only you get your problem in front of them. Finding those people has become much easier with growth of the social internet.
How do you find the right person to solve your problem?
There are listing-and-community-approaches (broadcasting problems to a large enough community or acquiring lists of experts), solver-and-expert-identification technologies, and mixed approaches that combine advanced solver-and-expert-identification technologies with listings and community building like hypios. These services make it much easier to get your problem in front of the right solver, and as the tools progress, Describe-And-Search (DAS) becomes more and more attractive.
It’s important to understand that we are not talking about replacing all internal (or closed) problem solving by external (or open) problem solving, but about making it part of the standard procedures for all complex R&D challenges to search for existing solutions (inside and outside) and expert Solvers before going into solving mode yourself.
I recently spoke with a rep from a large innovation consulting agency who works a lot with SMEs. He told me that most of the 1500 specialist R&D intensive firms they were working with accepted as a proof of the non-existence of a solution that a large multinational company asks them to develop this solution, i.e. they assume that the large multinational company must have done the solution search before asking them to develop it. But this is wrong. We’ve had several cases where large multinational companies posted problems on hypios and got multiple workable solutions (that had pre-existed) in a matter of months.
Why has DAT been predominant (An Error Theory)?
So why do many companies still lack a culture of solution search?
There are certainly multiple reasons for this.
The first reason is that in an environment where research meant closed research, companies didn’t need rigorous ways to distinguish between mildly confidential and non-confidential problems (only what was highly confidential had to be clear). So people are insecure about what problems they can share with potential external solvers (even anonymously). The second reason is probably that finding experts or solutions used to be much more difficult until very recently, especially for non-academic experts, who don’t publish. It’s only recently, that tools like hypios’ have been developed, and make expert-search widely available, quick and efficient.
Before deciding to launch the BioMass Challenge, DownEast had worked with different consultants for about two years and had not been able to find a satisfactory solution.
For the challenge, hypios’ Solver Surfer technology analyzed several millions of websites, identifying several thousand potential experts, hundreds of which reviewed the problem, which lead to a first round of solutions, ten of which are now under close scrutiny.
The little scheme above shows the rationale for DAT goes down as the tools for Solution Search progress, and the companies that are able to integrate these tools in their innovation processes quickly will find faster, and cheaper ways to innovate.
This article is related to a far more extensive publication entitled “Overcoming Cognitive and Cultural Resistances in Open Problem-Solving” that is going to be published in A Guide to Open Innovation and Crowdsourcing (edited by Paul Sloane) along with chapters from Braden Kelley and others.
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Klaus-Peter Speidel is the VP of Communications at hypios, which provides enterprises with open innovation ecosystems.
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I enjoyed reading your article and wanted to bring you up-to-speed with a new program at the Industrial Research Institute (IRI). We have 200 well know industrial and U.S. Federal Laboratories all pursuing best practices and shared learning in the management of R&D, new technology and innovation. Our new IRI “Community Forum” is a great example of DAS where members use a “list and community approach” that gets their problems in front of thousands of “right solvers.” Innovation and all its related topics are always on the minds of R&D intensive organizations. Questions like; “What is your experience with Open Innovation firms?” “What metrics do you use for open innovation?” “How do you transition innovation from the labs to business units?” “What are effective enterprise-wide metrics for return on innovation?” These are actual examples of questions our members are asking and getting amazing responses.
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Really nice article.. Great too see