Innovation: Marginal Gains vs The Big Idea

Wednesday, March 15, 2017

5 minute read

Innovation: Marginal Gains vs The Big Idea

Nowadays, every business is talking about innovation as a means of competitive differentiation or disruption. But just how realistic is it to strive for continuous evolution, or even revolution? In his session at Basware Connect UK 2016, the Undercover Economist, Tim Harford, drew on examples from the worlds of sport, genetic engineering and defence to compare the merits of marginal gains with the riskier pursuit of chasing genuine innovation.

Marginal Gains – little by little

The philosophy of marginal gains is all about small, incremental improvements that cumulatively produce a significant delta of change. Take British Cycling, for example. Team GB used to be also-rans in world cycle sport, yet today are regarded as a dominant force, having won more medals in track cycling during the last three Olympic Games than the rest of the world put together. Much of this success is attributed to sports scientist Matt Parker, Head of Marginal Gains at British Cycling.  

Matt identified seemingly trivial opportunities for performance enhancement – 1% improvements in areas that were overlooked by everyone else. These ranged from spraying alcohol on bike wheels to increase tackiness, to the importance of good hand hygiene and sleep on physical stamina, and even electrically heated pants to keep muscles at peak operating temperature between races. Individually, these tactics wouldn’t transform the team’s fortunes, but in aggregation, have been repeatedly proven to increase the athletes’ probability of success.

All manner of organizations have jumped on the marginal gains bandwagon, particularly now that data is available on every process: any fine-tuning can be rigorously A/B tested and optimized, and results can be obtained quickly and cheaply. But are we becoming attracted to the ease and safety of marginal gains at the expense of other, higher-risk ways of generating innovation?

The Big Idea – a giant leap of faith

At the other end of the spectrum is the long shot. The great conceptual leap. The radical idea that everyone said would never work. The kind of big, bold, blue-sky thinking resulted in the development of the Spitfire – an “interesting experiment” that ended up playing a major role in saving the free world in WWII, at a production cost of just £9,500. It’s the vision that enabled the smart phone to not only shake up the entire mobile industry but also revolutionize the way we live and work. It’s the dogged determination of mavericks like Mario Capecchi – a molecular biologist with a remarkable backstory – who was explicitly urged not to waste funding on tinkering with mouse genes. He wilfully disregarded these exhortations and went on to win the 2007 Nobel prize for creating the ‘knockout mouse’, which has helped us understand how genes may cause or contribute to non-communicable diseases in humans.

Big ideas require a willingness to fail and fail again, but with high risk comes the prospect of massive reward. However, do we really want an innovation system that only serves the stubborn genius? What about career-conscious, risk averse folk who are perhaps less charismatic or prodigious but nonetheless have great ideas?

It’s not an either/or proposition

Organizations must be prepared to foster both types of innovation, triangulating the long shot projects with the small, incremental improvements. If you pay for marginal gains, you’ll stand to achieve some level of differentiation. If you invest in big ideas, you should brace yourself for a lot of failure but the potential payoff can be wholesale disruption of your marketplace, or even making the world a better, safer, healthier place. If you want to shoot for the moon without assuming any of the risk, consider crowdsourcing your brief for innovation. A great example of this was the Netflix Prize – an open competition held by the streaming service that put a million dollars up for grabs for whoever developed the best collaborative filtering algorithm to predict users’ film ratings. Whatever approach you decide to pursue, remember that innovation can and must work for all of us, not just the occasional lucky genius.

Click here to watch video of Tim’s presentation in full >>