I avoid writing about my job too often. But, I have gotten a lot of questions recently on how the concept for Invention Machine Goldfire came about and its path to market innovation. It’s an interesting case because not only is it about a technology and product innovation; it also takes us into the realm of innovating innovation.
Birth of a concept
In the winter of 2002, Trident Capital invested in a company called Invention Machine. Trident tapped Mark Atkins and me to be the turnaround team. (Mark and I had just been part of a successful exit for Trident in where he was CEO and I was CTO.) We had helped with the investment due diligence for Trident, and we felt the company had some interesting technologies. However, the existing products and positioning were not optimal but could be realigned to produce great value.
Sitting at the Au Bon Pain across the street from the office, Mark and I discussed the strategy for the company. On a napkin, we mapped out a concept to create a new software platform for innovation that would bring together some of the company’s technology and knowhow assets. This new product would combine innovation methodology with state of the art semantic technology to make is easier for knowledge workers to innovate. Mark asked me if would be possible to do; I told him it would. He asked how long it would take; I told him we would have a deliverable product in 10 months. Of course, identifying a product concept is a far cry from delivering a product. There were some important things that needed to be understood along the way.
Assessing resources; Understanding the job
Few things are entirely new. All innovations build on the past. New products evolve from the changing needs of customers as they interact with incumbent solutions to do today’s jobs. For this reason, the first issue I tackled was to understand the resources we had to work with and the jobs that customers wanted to get done.
From the resource perspective, it begins with the people. I interviewed every person on the product team to understand the scope of skills and the depth of the team. Fortunately, we had very strong people on the team including a world class research group. Another aspect of resource was the existing technology. The company had a grab bag of componentry from the existing products. Some of it would be reusable, but much was not going to contribute to the new product. The third internal asset of the organization was its institutional learning about innovation best practices. The company had been engaged in innovation consulting for over a decade with some of the leading innovation companies in the world and had helped these companies to successfully build repeatable innovation practices.
The other key asset was the customer base. Most of my first 45 days at Invention Machine was spent on the phone interviewing clients around the globe, learning from them what they did. Each interview recorded not just what the client did with our software, but also the nature of their work, what they did outside of our software, and what they wished they could do differently. This interaction was the key to further developing the original concept into a strategic path to delivering value.
Moment of synthesis
There was no aha moment. Innovation doesn’t really happen like that. Rather, it was like a photographic image gradually appearing as you watch the paper sitting in the developer bath. The pieces were fitting together. Innovation is a full life cycle activity. At each point in the lifecycle, knowledge workers have two main challenges: indentifying the right concept, and finding the optimal solution to the problems of realization of the concept. These challenges occur across and at every level of the entire value creation chain. Software tools provide problem analysis frameworks for thinking about and modeling innovation challenges. The resulting models can be thought of as networks of requirements and problem statements. These statements can be mapped into conceptual representations of solution templates and correlated with information captured in knowledge databases to identify precise solution concepts for the problems. In short, we could imagine a system where as an engineer, designer, or scientist went about their work, the software would automatically source and deliver high relevance information and speed the time to solution.
Validating value
A concept not delivered in merely a concept. If it does not deliver value and is not accepted by the customer, there is no innovation. In the fall of 2003, we delivered the first version of Goldfire to customers. A module called the solution manager provided a new capability where the software figured out what question the knowledge worker needed to ask based on the problems implied in their models and sourced high relevance concepts without the user needing to submit queries. User feedback was strong; user liked the integration of best practices and knowledge access. The new platform delivered value for the innovation workers.
Endless innovation
Of course, innovation is a continuous process. As new solutions are introduced, our vantage point and understanding evolve as do the goals and aspirations of our customers. Through studying what innovation workers need to do, we have continued to evolve the product with a number of changes. Some of these have been incremental enhancements, but others have been big leaps forward. That is a familiar pattern for most products. There is a broad spectrum of change that occurs in the innovation process. It is important to swing for the fences if you are going to find the big innovation that sets you in a class by yourself, but the incremental innovations are important too. Small innovations build value and more importantly, when pursued with the same innovation methods hone your innovation capabilities so that you are always ready to innovate on demand.
I hope you found this recounting of one path to innovation interesting.
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