> Loud and Clear: Broadcasting & the Limits of "Open Innovation" in Problem Solving

> Harvard professor Karim R. Lakhani is often cited for his work on open innovation. In fact, Lakhani's landmark study, entitled “The Value of Openness in Scientific Problem Solving”, focuses on “broadcast searches”. He concludes that the right solutions for a problem often come from the periphery of a field. People at the periphery, or “outsiders”, are not just people outside of the lab or the company, but outsiders to the problem's field. (The study was based on an extensive pool of scientific problems in industries ranging from chemistry to agriculture). A broadcast search, as Lakhani defines it, involves disseminating a problem in such a way that it reaches these outsiders. According to Lakhani, people situated at disciplinary crossroads are best able to see the connections between solutions in one area and their potential cross-applications to problems in another. Even though this might not be true for every problem, in cases where experts in a field find it hard to work out a solution themselves, they should probably try to ask people from outside their field. Most of the executives who have decided that their companies should use hypios.com to broadcast their problems have experienced the impact of fresh perspectives from outside their field and see hypios as a way to systematize this effort. hypios works hard to make sure they have a solver base able to meet these expectations: “We try to get highly qualified solvers from various sectors and actively push problems to them that are outside of their declared field of expertise”, says Benjamin Roth, Chief Technical Officer.

While broadcasting is often used interchangeably with “open innovation”, this has led to some lack of clarity about the role of outsiders in problem solving situations. Open innovation is often incorrectly thought of in terms of the open source model. In open source production, broadcasting plays a role insofar as there is no assumption about where the best solution can come from. The similarity ends there, however, since, in the case of open source production, the solution, like the original problem, is then broadcast again, restarting the process. But this symmetrical dissemination of problem and solution is not practical for most situations, since the problems are often discrete and one-off (once solved, the information is integrated into a company's normal production process) and the solutions destined to be proprietary.

If open innovation as broadcasting requires only that a problem reach those outsiders most likely to have a pre-existing solution, what are the optimal conditions for broadcasting? Broadcasting, as a concept taken from radio and television, suggests two phases: emission and reception. Disseminating a problem to reach outsiders must involve formalizing a problem using the least amount of “insider” language as possible. This increases the chances that “outsiders” will be able to recognize that they have the solution sought. Still, it's not enough to simply put the problem out there, any more than random placement of an advertisement will help it reach its target audience. What's required, as the advertising parallel suggests, is that it reaches the outsiders you seek.

It seems then, that optimal “emission” conditions require that problems can be effectively “pushed” to solvers, even if, as is often the case, the solver doesn't know himself that he is capable of solving it. It might take somebody capable of suggesting the right problems to solvers. Imagine a situation where a bio-chemist has a data imaging tool that could be re-purposed to solve a problem in geology, but does not recognize this directly. Obviously, the geology section of a website like hypios is not where she would most naturally look for problems to solve. If the problem could be presented to her, however, based on a complex analysis of her qualifications and solving-history, she might realize that she has that ability.