Editor's Note:   The following post was published on the Forbes.com website on May 6, 2012. It is re-posted here with permission.

About a year ago I was asked to participate in a roundtable discussion on innovation at the University of Virginia.  The participants were senior innovation executives from companies such as Bank of America, Corning, Northrup Grumman, and AT&T, among others. One of the topics we discussed was “open innovation”, beginning with the typical references to Henry Chesbrough and his work on the topic. We spoke about technology licensing, intellectual property, joint ventures, and the challenge of managing this type of innovation.  Within a few minutes, however, something interesting happened.  A few of the participants challenged the group’s singular focus on the business models and mechanisms that are often associated with open innovation a-la Chesbrough. They spoke about innovation projects in their organizations that were certainly “open,” but not focused on licensing, joint ventures, or other issues typically considered under the realm of open innovation. That session led me to realize that there is some confusion regarding open innovation, or at least there is a need to cast a wider net around what open innovation is all about.

To understand why open innovation has become so popular over the past few decades, it helps to remember what the typical or routine R&D and commercialization process looks like in most organizations. The caricature is one of scientists in white lab coats developing technologies (“R”) and business people developing (“D”) and commercializing (“C”) those technologies.  In fact, an entire cottage industry has developed around helping organizations manage typical innovation processes, most notably using the Stage-Gate system, or some variant thereof.

The typical R&D and commercialization process opens the door to a few big problems.  It is unlikely that the best (or even very good) ideas are all located in one organization and, even with an idea in hand, should one organization really manage all of the technical and markets risks associated with commercializing technologies?  That’s where open innovation comes in.  Chesbrough defines open innovation as, “A paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market as the firms look to advance their technology.” The prevailing thought is that open innovation allows organizations to simultaneously expand their breadth of ideas, opportunities, and know-how while minimizing the technical and market risks associated with innovation.  Open innovation appears to come with little downside.

If we expand the interpretation of open innovation just a bit to include other innovation processes that are executed with organizations or individuals outside the typical boundaries of the R&D organizations, we find that most organizations have probably already engaged in open innovation in one form or another.  A broader interpretation highlights lots of links to other “non-routine” innovation processes that look and sound a lot like open innovation. Many of these processes are currently used by organizations to execute innovation initiatives, but it’s hard to argue that these are typical or routine R&D processes:

• User innovation and lead user methodologies.  User innovation defines the business model at companies such as Threadless.  This company asks designers to design t-shirts that they would buy, gets opinions about which designs are the best, then manufactures the t-shirts and sells them to the same community that designed them.  Can we really say that it is typical for the firm to almost completely rely on users to design the product that they will purchase?

• Innovation ecosystems and platform innovation models: the innovation that takes place through Apple’s application marketplace for the iPhone and iPad are good examples.  Clearly Apple conceived and developed the platform, but it would be hard to say that the devices would be as valuable as they are without the network of developers creating new applications.  Same holds for Google and the Android platform.  This type of “innovation ecosystem” is at the core of most ideas about how our economy needs to position itself for the next 50 years of growth.

• Co-development and other short-term non-equity alliances.  This is one that most firms are definitely already engaged in.  While not a new business model, co-development is certainly “open”, and is fraught with different risks compared to typical (internal) innovation projects. Most of the risk has to do with coordinating ideas and people from two or more big (often bureaucratic) organizations.

• Innovation contests and innovation tournaments: consider the innovation contests staged through organizations such as Innocentive, the X-Prize Foundation, or 99designs.com. These contests clearly involve innovative work, and by definition are open systems, but they are anything but routine.  Actually, a discussion about open innovation should probably have started with the concepts of tournaments or contests.  These were around long before open innovation as defined by Chesbrough (one of the earliest innovation contests was initiated by the Longitude Act, passed in 1714 by the British Parliament, which established a prize for anyone that found a practical method for determining a ship’s longitude.) For a nice review and discussion on innovation contests, see Tina Rosenberg’s recent opinion piece in the New York Times.  For a detailed look at the history and current thoughts on this topic, take a look at the book by Christian Terwiesch and Karl Ulrich.

• Crowdsourcing and prediction markets (a.k.a. the wisdom of crowds).  Crowdsourcing is a great way to access a wide range of ideas that are candidates for development.  Proctor and Gamble’s “connect and develop” process, which allows anyone in the world to submit proposals for new product ideas, is a good example of crowdsourcing in innovation.  Of course, input from external communities is exactly what makes prediction markets such as the Iowa Electronic Market work.  While prediction markets were originally conceived for events such as elections and other non-innovation related work, there are a number of firms that have started using prediction markets to manage different stages of the innovation process.

But how should these different modes of open innovation be used to deliver new products, services, and processes?  Some of the links above outline strategies for managing these forms of open innovation, and in the weeks that follow we’ll highlight others.  In the mean time, I look forward to your comments and discussion.

 - Raul Chao is on the faculty of the Darden School of Business at the University of Virginia.