Message from the editor

Chip Kelly is the head coach of the University of Oregon Ducks football team, which came close to winning the Bowl Championship Series (BCS) championship game in January, losing to Auburn University by 5 points. Playing for the national championship was something Oregon had never done before. Kelly first gained national attention in 2009 with an upset of the then No. 5 ranked University of Southern California Trojans. That season he was the first Pacific-10 rookie coach ever to win an outright conference championship. Oregon also became the first Pacific-10 team to win a conference title by two games since the University of Washington accomplished the feat in 1991. How did Kelly deliver such amazing results in his first two years as head coach?

He innovated. It’s as simple as that. He saw problems others didn’t and developed solutions others ignored.

Football coaches have recruited and developed players, and they have designed and run plays predicated on one core principle—if we are bigger, stronger, and faster, we’ll win.

If you were in Kelly’s situation, heading a program that had never even played for the national title, your success rate recruiting the biggest, strongest, and fastest players would be low. And as a result, your talent won’t stack up, especially if your plays are designed to succeed on the basis of your players being big, strong, and fast. What’s a coach of an up-and-coming program to do?

Redefine the problem. And by doing so redefine the solution—in terms of recruiting, player development, and play design and execution. That’s exactly what Kelly did.

It turns out that big, strong, and fast are not the only attributes that can contribute to success in football, something that should have been obvious if coaches considered factors that lead to success in other sports. Another attribute is endurance. In basketball, soccer (football outside the US), and swimming, teams that have better endurance outperform their opponents as the event wears on. John Wooden (famous University of California, Los Angeles [UCLA] basketball coach) ran practices so fast they were more aerobic than actual games, so players always had a little more energy at the end of games than their opponents. By selecting and developing talent for endurance, then designing game execution strategies that position endurance as the key determinant of who wins, Kelly saw an opportunity to optimize in ways that other, more well-known colleges were not.

That’s exactly what he’s done. He recruits players less for their size and strength and more for their speed and endurance. His practices are run at a pace that makes game action appear slower, builds cardiovascular capacity, and is more likely to take weight off than put it on players’ bodies. This approach translates directly into game strategy. Other teams typically take 34 seconds between the end of one offensive play and the start of the next; Oregon cuts that down to 23 seconds, leaving less time for opponents to catch their breath. The result? Oregon outscored opponents by a massive 115 points in the fourth quarter in 2010.

The point isn’t that Chip Kelly innovated or that he is a football genius (even if he is). The thinking process that led to the innovation is the point. By redefining (abstracting) the problem, he was able to look outside the known best practices of his own sport, identify patterns of success not practiced in his sport, and create a version of that pattern of success in football.

In this issue of the Technology Forecast, we ask and answer the question, “is innovation the result of inscrutable, opaque genius, or can innovation be treated as an end-to-end process subject to performance optimization by adopting proven methods?”

We find that the time is now ripe for organizations to develop, manage, and continually improve an end-to-end process, supported by technology, in which innovations are more likely to be discovered, better assessed, and better converted into profits in what can become an idea-to-cash process. The key area for technology support is the systematization of problem solving, which is at the heart of how innovation happens and progresses.

The first article, “Can innovation be disciplined without killing it?,” on page 06 examines the importance of problem solving in the end-to-end innovation process. The article highlights approaches that systematize problem solving so that more participants can contribute to problem solving, rather than just those in research and development (R&D) or product development functions. The article also lays out the key stages in the end-to-end process as ideas move from discovery to incubation to acceleration to scaling.

“Powering the innovation life cycle” on page 26 examines the software available to organize and discipline the innovation process. Idea management systems digitize the notion of an idea and organize innovation activities around the movement from ideas to cash. Solution identification approaches such as TRIZ provide methods to systematize problem solving and allow software support by treating innovation as another case of knowledge engineering, access, and distribution. Both approaches increase participation and transparency in the innovation processes.

“The strategic CIO’s new role in innovation” on page 44 offers insight into how CIOs can use the IT infrastructure to support more disciplined idea-to-cash processes. Implementing and supporting end-to-end processes has long been part of the CIO’s charter. To drive innovation, CIOs can contribute in two distinct areas. First, they can help drive the creation of the end-to-end innovation process. Second, they can put together and implement the technology on which the enterprise executes much of the innovation process.

These articles are supported by in-depth interviews with executives and thought leaders at companies on the leading edge of innovation management:

  • Jon Bidwell and Patrick Sullivan of Chubb share their journey of innovation from ideas to marketable products and how information technology is enabling the process.
  • Bill Hessler describes multiple cases of innovative problem solving using structured methods from his experiences at multiple engineering corporations.
  • Matthew Greeley of Brightidea details how idea management systems and their openness and social software features create opportunities for IT to support innovation processes.
  • James Todhunter of Invention Machine shares how systematic methods for problem solving and knowledge management can help enterprises sustain innovation.
  • Paul McCusker of AES describes an example of innovation at AES and how that is seeding a platform for innovation across all AES facilities.

Please visit to find these articles and other issues of the Technology Forecast. If you would like to receive future issues of the Technology Forecast as a PDF attachment in your e–mail box, you can sign up at

We welcome your feedback and your ideas for future research and analysis topics to cover.