Imagine you’re a manager faced with a budget cycle and an unwieldy portfolio of projects, each with a marketer or chemist attached who assures you this project is the greatest idea ever. You need to identify both short- and long-term improvement opportunities. To do so, you need to diagnose your company’s innovation practices and capabilities. The diagnosis can be quite different from one company to the next, and that’s one of the reasons why adopting industry benchmarks doesn’t work.
The innovation effectiveness curve represents the value and quality of a company’s innovation portfolio. The shape and height of this curve reflects how much a company could ultimately expect to earn from its innovation investments and how much organic growth these investments will generate.
To build an effectiveness curve, you plot annual spending on innovation projects against the financial returns from those projects, measured as a projected internal rate of return.
You do this on a project-by-project basis, which means the curve contains data about every active project in the company’s pipeline. While each point on the curve represents the return on a particular innovation investment, the area under the curve reflects the company’s total projected return on annual innovation investment.
The height of the curve offers a verdict on the innovation capability’s power to drive returns and generate growth. The higher the curve, the greater the overall returns on innovation investment.
Businesses can change the curve. One company that improved in the short-term is Bayer MaterialScience AG, a subsidiary of Bayer AG that produces polymers used in high-performance plastics, coatings and sealants. BMS’s effectiveness curve revealed a lengthy tail, which suggested an opportunity to redistribute resources. The company looked closer at lower-performing projects and discovered that these projects tended to target a different customer segment and be in a different product category than projects higher up the curve.
Understanding which customer segments and categories generate higher innovation returns let BMS reprioritize new product initiatives and redeploy resources in R&D, sales and marketing such that they supported the higher-return markets, customers and categories. The result was that BMS increased its ROI by 14%.
This graphic displays BMS’s effectiveness curves, both the original and the improved one after reallocation.
This article is adapted from “Which Innovation Efforts Will Pay?” by Alexander Kandybin, which appeared in the Fall 2009 issue of MIT Sloan Management Review. The complete article is available at http://sloanreview.mit.edu/smr/.