A map of open innovation tools

Open Innovation (OI) has made tremendous progress, both in theory and practice, since its major principles were articulated by Henry Chesbrough in a seminal 2003 book. Today, much better than in 2003, we understand OI’s value proposition, its governance and management, and the corporate culture supporting its implementation.

However, I feel that there is a topic that for all these years, hasn’t received attention commensurable with its importance. This topic is OI tools. As far as I know, a 2013 study by Chesbrough and Sabine Brunswicker remains the only publication presenting a systematic list of OI practices used by American and European companies. (I’d be very grateful to anyone pointing me to additional published data on the topic.)

Chesbrough and Brunswicker classified OI tools based on two parameters: the knowledge flow direction (inbound vs. outbound) and knowledge flow financial nature (pecuniary vs. non-pecuniary). Although I agree that the first parameter is of strategic significance, I don’t consider the second one being important from the operational point of view.

In contrast to Chesbrough and Brunswicker, I propose to classify OI tools based on the identity of OI partner(s). This leads to the creation of two major buckets of OI tools: co-creation and crowdsourcing.

Co-creation. When firms co-innovate (co-create) with their customers, suppliers, and academic and business partners, they deal with defined partners, the partners whose identity is known to them. (Which, of course, doesn’t preclude all engaged parties from signing legally binding NDAs.) Firms deal with defined partners, too, when they form joint ventures or get engaged in inbound and/or outbound licensing.

Crowdsourcing. In contrast to co-creation, crowdsourcing implies undefined partners (“an undefined, generally large group of people,” as worded by Jeff Howe in 2006), the members of a crowd whose identity is unknown to the firm, at least initially.

The presence of a large number of partners–and the need to ensure that they all act independently of each other to make crowdsourcing campaigns effective–dictates the use of online methods of aggregating the incoming knowledge. This is another difference from co-creation that still largely relies on face-to-face interactions. The need of dealing with complete “strangers” also forces firms to pay careful attention to confidentiality and IP rights (the exception to this being when firms are using internal crowdsourcing).

The main specific crowdsourcing practices include innovation contents (challenges), external innovation portals, and using open innovation intermediaries, such as InnoCentive, NineSigma, or HeroX.

Startups. Formally speaking, engaging startups falls into the co-creation category as it involves dealing with defined partners. However, I prefer to keep this tool separate because of the acute interest it attracts in business literature and because engaging startups helps firms address technical and business problems that are different from those tackled by “pure” co-creation. (I’ll come back to this point in a separate post.)

Launching corporate venture funds and setting up accelerators/incubators are two major forms firms use to engage startups.

Webscouting. I define webscouting as collecting knowledge and insight by targeted browsing of online content. What makes webscouting similar to crowdsourcing is that both deal with undefined, unknown open innovation partners. What sets webscouting apart from both crowdsourcing and co-creation is the one-way (passive) mode of interaction between the partners: firms collect knowledge from the content creators without providing them with feedback. (In contrast, crowdsourcing and co-creation both imply the two-way mode of interaction between the partners, either online or in person.)

There are two specific practices in the webscouting basket. The first is netnography (a hybrid of “internet” and “ethnography”): gathering insight (needs and wants) of existing and prospective customers by following their conversations and/or observing their behavior online. The other is the social media solution scouting, a practice very similar to–and in some cases overlapping with–netnography: searching already existing (i.e. generated by consumers) solutions to the firm’s problems. (Here, I leave aside potential ethical issues and IP complications that could result from using this tool.)

Lead Users. The last element of my map, lead users, lies at the intersection between co-creation and crowdsourcing. On the one hand, engaging lead users in the development of new products and services represents co-creation in its classic form. On the other, the large number of engaged lead users justifies the employment of online tools, as in the case of crowdsourcing, rather than face-to-face interactions. The Audi Virtual Lab, a project that involved 7,000+ customers in the co-development of the Audi in-car multimedia system, is a great example of an advanced lead user application.

Obviously, any map makes sense only if it helps reach the desired destination. Can my map help apply different innovation tools to specific problems? I’ll talk about it in my next post.

Image credit: Nadjib BR on Unsplash

About Eugene Ivanov

Eugene Ivanov is the Founder of (WoC)2, an innovation consultancy that helps organizations extract maximum value from the wisdom of crowds by coordinated use of internal and external crowdsourcing.
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1 Response to A map of open innovation tools

  1. Pingback: Opening open innovation toolbox |

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