08/29/2012 10:36 am ET Updated Oct 29, 2012

High Tech Knowledge Brokering

How do engineers contribute to concepts through the integration of new technologies and turn inventions into innovative applications satisfying new or existing user needs? While interviewing engineers at an automotive technology center in Silicon Valley, they shared with me their methods of analyzing, organizing, learning and implementing for successful innovation.

This particular automotive technology center is in the midst of the high-tech world and within reach of the latest technology developers. Sponsoring projects and working together with Stanford and Berkeley as well as conducting six months' development projects with outside firms, the center is able to create new contacts outside of its traditional automotive field. They create new and unique applications by leaving the development of technology to their high-tech partners and focusing on linking these with user needs, as defined by their mother company.

It is well understood that one can never define a new problem by approaching it in the traditional way and, within the engineers' experience, the difficulty with problem definition becomes the presumed problem solution possibilities with which they are saddled. In preparation for this, the firm collaborates with an industrial design company and conducts joint kick-off projects so that the likelihood of multiple perspectives on any problem is greatly increased.

With short development projects of three to six months, the company relies on accelerated learning, and they do this by utilizing and working hands on with experts in various areas to learn the tacit knowledge. Various technologies are benchmarked and a "prototype often" approach is used. Farming out the prototyping while handling the analyzing and managing themselves, optimizes their resources and enables them to quickly cycle through technology search, design, prototyping and testing.

Brokering entails finding non-obvious connections and searching for ways in which to encourage unexpected analogical connections to happen. Seemingly random search paths maintain the potential for creating unexpected connections and innovative ideas can quickly turn into real products when the tacit knowledge about an idea is turned into an explicit artifact. These can then be shared with the rest of the organization and Power Point presentations will not suffice here.

Another important aspect is to make sure their ideas have been accepted by headquarters, which the team ensures by getting an up front commitment and continually updating the team at headquarters on their progress and receiving feedback.

Within the company, decisions are primarily based on gut feelings and the engineer's personal interests. Decision-making based on gut feelings has the advantage of facilitating action, however, since the feedback loop is weak, the gut feeling might have little to do with reality. The Stanford approach, "Prototype early and often," was adopted by the teams and does a good job of tuning the technology and its implementation quickly. This rapid turnaround in projects at the company resolves some of the weak "user feedback" issues.

This consistent, but loose process is a strong approach to technology search and data management and it is very similar to the one used by industrial design companies. Checking assumptions and using "prototype often" along with reviewing technical and interface aspects continually validates the process. As for many top-tier firms, the main opportunities for improvement seem to lie in exploring how problems are being framed and evaluated before even getting started. It is all in the amount of homework that has been done.... and, as engineers are so fond of saying, "measure twice, cut once."