Every business wants to be innovative. We all see other companies that are innovative and we wonder how can we pull off the same thing. Since we only see the results we sometimes think “How did that one great idea fall in their lap?” But it doesn’t work that simply. Talk to anyone in the film industry and they’ll tell you they get thousands of pitches and see tons of scripts yet a studio may only produce a dozen films a year. How does that filtering process work? How can it be improved?
Crafting “Innovation Tournaments” as Karl T. Ulrich, CIBC Professor of Entrepreneurship and eCommerce, describes is the key to improving results from innovation. Ulrich is also the author of the book entitled “Innovation Tournaments: Creating and Selecting Exceptional Opportunities”
Innovation requires matching
There are solutions, and there are needs. Innovation is a new match between a solution and a need. To make that match, argued Ulrich, you have to hold an innovation tournament. Pointing to successful innovations such as Pixar films, Merck’s Zocar, and the OralB Cross action toothbrush, Urlrich said that all of them revealed their respective products through an innovation tournament. Each started with hundreds and sometimes thousands of ideas and through a series of filters weeded them down to just one superb innovative idea.
In these three examples, they held closed tournaments, which mean that things were handled internally. But there are open innovation tournaments, such as American Idol and the X-Prize, which makes it possible to find innovative ideas from anywhere.
What a tournament does
The job of a tournament is to identify raw opportunities, create criteria for discrimination, throw up a barrier, and let the exceptional ideas get through. Sounds simplistic, and it can be, but you need to look at the entire tournament system holistically to know what you’re trying to uncover. To help you out with the process, Ulrich has created an idea management tool called the Darwinator to help users manage an innovation tournament.
Four ways you can improve innovation
Ulrich reviewed four different aspects that can improve the process of innovation.
- Increase the number of opportunities generated – The more ideas you get, the quality of ideas increases dramatically. What you may not know is that just having ten or 20 ideas isn’t enough. Increase the number to a few hundred of ideas and you’ll see a significant increase in the quality. If the goal is to find the best idea, you need to increase your sample size, because ultimately you’re looking for that one great idea.
- Shift the mean quality of the opportunities generated – Everything in corporate life tells us we want to repeat the same product exactly the same time every time. But during an innovation tournament you want the complete opposite. It’s better to have 99 bad ideas and one exceptional idea, than 100 exactly the same good ideas. You want variability.
- Increase the variance in the quality of opportunities generated – Ulrich actually skipped description of this, but I think this plays very much into the previous item. Variance is important for innovation. If everything’s the same, then nothing’s being innovated.
- Increase the accuracy in evaluating opportunities. A single filter should have three mini-filters within. You want to measure the mini-filters, but you don’t want to necessarily exclude based on a single one. Rather a combination of all three. For example, Ulrich talked about a company pitch filter that was comprised of three mini-filters: opportunity pitch, concept pitch, and business plan pitch. Each is evaluated, but have varying scores. For example, a company can have a great opportunity pitch and concept pitch, but the reality of it is poor and therefore has a bad business plan pitch. And the complete opposite can happen as well. If you wanted to truly get the top results, you need to go very deep in the beginning so you don’t cut off the exceptional ones that start slow but rise quickly. In essence, you want to craft the shape of the funnel to keep in those ideas that have high uncertainty to succeed, but then cut them off when it’s time to cut them off.
Creative Commons photo by mathplourde.
