Through the blog Tomorrow’s Trends i came across Scott Berkun’s blog and the interesting post Why research labs fail at innovation. It turns out that Scott have released a book on the subject “The Myths of Innovation” which I haven’t read.
In the post he structures his findings this way:
- [Generating ideas is] certainly hard work but it’s the easier part – it’s getting new ideas into products and out to customers that’s crazy hard
- R&D groups and product teams have conflicts & resentment on philosophical, goal and ego grounds and until those issues are confronted little else matters: great ideas will go nowhere
- The problem is that R&D ego would see this role as a concession to product team “superiority”, which is why to my knowledge its never been done
- [The ...] VP-centric model encourage researchers to treat line level product managers and programmers as dead men walking, instead of as collaborators, prototype testers, or (gasp) peers in developing new ideas
- Innovation is a social process that smart motivated people want to participate in – if you propagate the belief that only special people in special roles can do it, something is broken
- In the end every failed R&D effort has a Product VP who was unwilling to take the risk, either for good reasons (the ideas were not worthy) or bad (they didn’t believe or didn’t have the the courage)
Interesting list but I have noticed something along a different line: the nature and level of knowledge around X apparently hinders a person or a group from being innovative around X.
One theory is that the more you know about an issue the more your concepts and associations are locked into place and the less innovative you are. Frans Johansson’s book The Medici Effect suggests to an explanation to this by studying the cross sections where two or more knowledge areas meet i e where the participants have to question their carefully developed knowledge structures and rebuild them as a result of integrating two knowledge areas. Some people are better disposed to dismount and rebuild knowledge structures and probably therefore more inclined to innovate along the way.
I have noticed another issue concerning the nature of the knowledge. To me there seems to be a difference between having the “knowledge gravity” concerned with the “inner workings” and how and why something is used. The more knowledge people have about the internals of i e know how things really works, the less innovative they seems to be about new areas of application, commercial values, or customer values.
I think this has to do with the ontological border between the internal mechanisms and the surface as an interface to a complex outside world. When working with the internal mechanisms we are more likely than not to have a mental model embodying a converging mindset where the solution can be one and directly testable against another function or specification. On the other hand when we are working with overall design and are looking for new application areas or trying to understand how potential customers behave there are never single testable solutions. The answers are of a fundamentally different kind and you are forced to have a diverging mindset.
A converging mindset is characterized by looking into your existing toolbox of solutions, judging, sorting, testing and discarding in order to find a working solution to a problem.
A diverging mindset on the other hand is characterized by a very primitive and generic toolbox, an open mind and an urge to look into an issue to see if things works at all. There doesn’t necessary have to exist a defined problem and a person with a diverging mindset is more likely to design new and different things.
I first came across the concept of converging and diverging problems in a short article of Charles Handy some time ago. Converging problems could be exemplified by “How long time does it take to drive to Bath?”. The idea is that there is one well defined and verifiable answer to the question. Diverging problems, on the other hand, could be exemplified with “Why do anyone want to go to Bath?”. This second question is of a fundamentally different kind and is more close to many of the questions concerning management, design and innovation. The problem, according to Handy, is that the educational system is built around strategies for solving converging problems.
A couple of years ago a two friends at Karlstad University wrote a paper about an experiment where a group of users was invited to participate in an innovation process for end user services for mobile phones. During two weeks a large number people divided in test groups were provided with new mobile phones and notebooks to write down ideas about possible new services for that phone that pop up in their daily life. An interesting result was that the test group without technical knowledge outscored the group with technical knowledge both from a qualitative and a quantitative perspective. An even more interesting result came from another group consisting of non-technical people, who half-way through the experiment received some education about technical possibilities. After they received their mid-experiment lecture, i e learned more about the inner workings, their innovation score dropped.
Is it possible that they were dragged over from an external and diverging mindset to an internal and converging mindset and thus became less innovative and more judging?
The article is not available on the Internet but here is the reference:
Managing User Involvement in Service Innovation: Experiments with Innovating End Users
Peter R. Magnusson, Jonas Matthing and Per Kristensson
DOI: 10.1177/1094670503257028 2003; 6; Journal of Service Research
