Well-defined problems lead to breakthrough solutions. When developing new products, processes, or even businesses, most companies aren’t sufficiently rigorous in defining the problems they’re attempting to solve and articulating why those issues are important. Without that rigor, organizations miss opportunities, waste resources, and end up pursuing innovation initiatives that aren’t aligned with their strategies. How many times have you seen a project go down one path only to realize in hindsight that it should have gone down another? How many times have you seen an innovation program deliver a seemingly breakthrough result only to find that it can’t be implemented or it addresses the wrong problem? Many organizations need to become better at asking the right questions so that they tackle the right problems.
Here are three stories of organizations in very different fields that did a spectacular job of defining the problem. This in turn attracted the right kind of innovators and led to breakthrough solutions.
The Subarctic Oil Problem
More than 20 years after the 1989 Exxon Valdez oil spill, cleanup teams operating in subarctic waters still struggled because oil became so viscous at low temperatures that it was difficult to pump from barges to onshore collection stations.
More than 20 years after the 1989 Exxon Valdez oil spill, cleanup teams operating in subarctic waters still struggled because oil became so viscous at low temperatures that it was difficult to pump from barges to onshore collection stations.
How the Problem Was Defined. In its search for a solution, the Oil Spill Recovery Institute framed the problem as one of “materials viscosity” rather than “oil cleanup” and used language that was not specific to the petroleum industry. The goal was to attract novel suggestions from many fields.
The Breakthrough. A chemist in the cement industry was awarded $20,000 for proposing a modification of commercially available construction equipment that would vibrate the frozen oil, keeping it fluid.
The ALS Research Problem
By the late 2000s, researchers trying to develop a cure or treatment for amyotrophic lateral sclerosis (ALS, or Lou Gehrig’s disease) had not made much progress. One major obstacle was the inability to detect and track the progression of the disease accurately and quickly. Because researchers could not know precisely what stage ALS sufferers had reached, they greatly increased the pool of participants in clinical trials and lengthened their studies, which drove up costs so much that few treatments were developed and evaluated.
By the late 2000s, researchers trying to develop a cure or treatment for amyotrophic lateral sclerosis (ALS, or Lou Gehrig’s disease) had not made much progress. One major obstacle was the inability to detect and track the progression of the disease accurately and quickly. Because researchers could not know precisely what stage ALS sufferers had reached, they greatly increased the pool of participants in clinical trials and lengthened their studies, which drove up costs so much that few treatments were developed and evaluated.
How the Problem Was Defined. Instead of framing its initiative as a search for a cure, Prize4Life, a nonprofit organization, focused on making ALS research feasible and effective. The solution it sought was a biomarker that would enable faster and more-accurate detection and measurement of the progression of the disease.
The Breakthrough. In 2011, a researcher from Beth Israel Hospital in Boston was paid $1 million for a noninvasive, painless, and low-cost approach, which detects ALS and assesses its progression by measuring changes in an electrical current traveling through muscle. This biomarker lowers the cost of ALS research by providing accurate and timely data that allow researchers to conduct shorter studies with fewer patients.
The Solar Flare Problem
In 2009 NASA decided it needed a better way to forecast solar flares in order to protect astronauts and satellites in space and power grids on Earth. The model it had been using for the past 30 years predicted whether radiation from a solar flare would reach Earth with only a four-hour lead time and no more than 50% accuracy.
In 2009 NASA decided it needed a better way to forecast solar flares in order to protect astronauts and satellites in space and power grids on Earth. The model it had been using for the past 30 years predicted whether radiation from a solar flare would reach Earth with only a four-hour lead time and no more than 50% accuracy.
How the Problem Was Defined. NASA did not ask potential solvers simply to find a better way to predict solar flares; instead, it pitched the problem as a data challenge, calling on experts with analytic backgrounds to use one of the agency’s greatest assets — 30 years of space weather data — to develop a forecasting model. This data-driven approach not only invited solvers from various fields but also enabled NASA to provide instant feedback, using its archived data, on the accuracy of proposed models.
The Breakthrough. A semiretired radio-frequency engineer living in rural New Hampshire used data analysis and original predictive algorithms to develop a forecasting model that provided an eight-hour lead time and 85% accuracy. He was awarded $30,000 for this solution.
Critically analyzing and clearly articulating a problem can yield highly innovative solutions. As these stories illustrate, organizations that ask better questions and define their problems with more rigor can create strategic advantage and unlock truly groundbreaking innovation. Asking better questions delivers better results.
This blog post was excerpted from the Spradlin’s article “Are You Solving the Right Problem?” in theSeptember issue of the magazine.
DWAYNE SPRADLIN
Dwayne Spradlin is the president and CEO of InnoCentive, an online marketplace that connects organizations with freelance problem solvers in a multitude of fields. He is a coauthor, with Alpheus Bingham, of The Open Innovation Marketplace: Creating Value in the Challenge Driven Enterprise (FT Press, 2011).
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