“stockout, really strong demand, … despite a price four times higher han the market price, the success of SEB’s ActriFry, the first electric oil-less deep fryer, has exceeded every forecast.” The downside for Rémy Décosse, SEB’s Production Manager is that confronted by “Asian competition that invests increasingly in Research and Development, the SEB Group needs an innovation like Actify every year. We have to reach this rhythm of launching breakthrough products if we want to succeed.”
The future of innovation management software
According to an APQC study from 2004 most companies know how to manage incremental innovation but few succeed in breakthrough innovation. The most common reason mentioned is that the efficiency of the New Product Development Process depends heavily on the quality of its inputs, i.e. project proposals. So, in early 2002, a new area of management appeared: Front End of Innovation, i.e. getting to grips with and managing the early stages of the New Product Development process.
There are plenty of software applications available for capturing, developing and selecting ideas. Despite Web 2 features to facilitate collaboration around ideas, none of them is equipped with features specifically aimed at achieving the breakthroughs companies require. Some promise attractive environments with animation, while others vaunt efficiency. However, that is the least that one could expect.
What if innovation practitioners had a tool that could glean the most pertinent information from scientific articles, specialist sources and manage an idea bank enriched by their own colleagues and customers? What if they had a tool that allowed them to sift and sort, categorize and assess, and finally allowed them to perceive the white spaces of opportunity.
The history of many inventions we now use daily (washing machine, automobile, walkman, post-it, and so on) shows that innovation results from the intelligent combination of ideas, existing technologies, problems raised by customers, and other factors. The combinations are often the result of chance (a meeting at a show, coming across new knowledge, reading) but they can also result from in-depth knowledge of the technological environment, the competition and customer needs.
Innovation management software must embed artificial intelligence that favours these combinations and assists the analysis of product environments. Data mining capabilities must leverage the millions of items of information related to innovation that can be found in Customer Relationship Management databases (customer feedback), scientific databases and many other sources. It will speed up the meeting of ideas and the people who contribute to identifying innovations.