An recent article from the Economist made me think about how companies could learn from the distributed innovation of open source to find the great ideas within.

The article is about InnoCentive, which helps connect problems with solutions:

Innocentive is based on a simple idea: if a firm cannot solve a problem on its own, why not use the reach of the internet to see if someone else can come up with the answer? Companies, which InnoCentive calls “seekers”, post their challenges on the firm’s website. “Solvers”, who number almost 180,000, compete to win cash “prizes” offered by the seekers. Around 900 challenges have been posted so far by some 150 firms including big multinationals such as Procter & Gamble and Dow Chemicals.


More than 400 have been solved. InnoCentive reckons the approach can work for innovations in all sorts of fields, from chemistry to business processes and even economic development. It has formed a partnership with the Rockefeller Foundation, a charity, to help solve problems posted by non-profits working in poor countries, with some initial success.

InnoCentive is now looking inwards with a new service called Innocentive @Work which “replicates the solver network inside a firm”:

Challenges are first offered to “seeker” companies’ own employees. Only if they cannot help is the outside network brought into play. “Companies often don’t know how much they already know,” says Dwayne Spradlin, InnoCentive’s chief. An early challenge at one firm was to find a source of some data, which, it turned out, had already been acquired by another division.

This is particularly interesting given that InnoCentive began in 2000 as e.Lilly, a place for pharmaceutical giant Eli Lilly to put out the problems it was failing to solve internally.

Right under their noses

The fact that InnoCentive is successfully being used to solve problems shows the power of setting up a structured framework for innovation. Why is this important? Let’s take a look at the open source software community and ask this: how can thousands of individual coders collaborate on something as huge as Linux or Android?

A large part is the framework in which contributors operate. Much of the coding that needs to be done is well defined and there is a solid framework for executing the solutions. Want to fix a bug? Go into the source code repository, download the project, work on your bit, test it and then upload it for community approval. All your contributions are tracked, and you can see who’s working on what and resolve conflicts. Because of this, a lone coder can quickly change just a single line of code (that’s what most do), while at the same time huge companies can put thousands of their people to task (for example, IBM has contributed 6.3% of Linux, and Sun is mostly responsible for Java).

What would happen if the strengths of this model were applied to business problems, which are a whole lot fuzzier? By what framework could a salesperson easily fix a bug in a large marketing campaign? Or an engineer contribute to an ethnographic study for a new vacuum cleaner? To be fair, programming has the particular advantage of being a granular, text based medium, but tools like Innocentive@Work could make problems visible within an organisation and give solutions a place to go (and the solvers to be rewarded).

InnoCentive is not the only service to link problems and solvers. In the same space are Hypios, InnovationXchange, NineSigma and Tekscout in US, PRESANS in France, Innoget in Spain, and Fellowforce. Moreover, this approach is not only for research and development in the traditional sense: just look at the success of Threadless in generating t-shirt designs, for science or the several dozen sites like TopCoder and ODesk which allow you to outsource self contained business problems, from coding to marketing.

As web based applications, these companies are essentially a testing ground for highly automated processes which allow people to contribute innovative solutions (or even just good work). Organisations should therefore keep a close on eye on the fittest of these services to see exactly what they do to make it easy to specify problems, maintain relationships with solvers and to communicate clearly.

Too often, innovation is forced to squeeze through bureaucracy. Implemented correctly, such automated frameworks could make it look a lot more meritocratic.

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