In 2012 MIT Professor Amos Winter was asked to develop a lighter, cheaper prosthetic leg for the huge Indian market. And not just a bit cheaper: the new limbs needed to be 90% cheaper than those sold in western markets to meet the needs of the over half a million amputees unable to afford prosthetics that often cost tens of thousands of dollars and lasted only 2-3 years. Under these dramatic constraints, Winter’s team went back to fundamentals and reframed the problem: what could the science of movement teach us about how to design and deliver a radically different prosthetic? Rather than taking a traditional approach, which sought to mimic a human foot, the team focused on a tunable but passive foot design that would instead mimic lower leg movements. By 2019, Winter’s team had unveiled their new, low-cost solution — one that could cheaply and easily be tailored to a patient’s weight and height. It was fundamentally different from existing products in terms of cost, design, and material. This achievement was only possible because the initial constraints imposed on the challenge forced a complete re-thinking of the problem.

This story reminds us of a consistent lesson from the research on innovation: while unshackled creativity might intuitively seem to be the best route to novelty, actually some of the most innovative outcomes are produced when innovation is constrained.

But the type and quality of constraints matter. Leaders we talk with (especially in the public sector) typically impose two common constraints on their innovation teams: budget and risk. They tell teams their innovation must cost no more than a certain amount — a figure based on assumptions about what kind solution the team will deliver. Relatedly, the constraints on risk communicate to the team: “don’t do anything too risky, especially something that might cannibalize existing business” or “don’t fail because that’s not what gets you promoted.”

Unfortunately, neither constraint is particularly helpful in practice. In fact, they often produce unintended negative consequences by narrowing innovation to tried and tested solutions and precluding a radical reframing of the problem. As a result, a team’s potential to reimagine solutions is fundamentally hampered from the start.

But during the Covid-19 crisis, the urgency of the problem prompted traditional budget/risk constraints to be replaced by two alternatives — one that we believe support genuine innovation:

1. constraining outcomes, e.g. “the new antibody test must have this level of sensitivity” or “the new ventilator must have this functionality”;

and then, within the context of this new target outcome:

2. constraining time, e.g. “we need a reliable test by Q2” or “the new hospital must be ready in a week.”

Constraining outcomes and time has precedent in a number of existing strategy concepts. One of us (Johnson) has shown how, in the content of strategic change, leaders need to specify clear, long-dated outcomes if managers are to be able to respond with the best ideas about how to deliver a new strategy or change. Another similar concept is that of the Commander’s Intent. Here, military leaders give their soldiers a clear message about what needs to be achieved and by when, e.g., “we need to capture that territory by the tomorrow,” but leaves it to those on the ground to decide how to do this. Notice that the Commander’s statement doesn’t say: “you can’t spend more than this much” or “we can’t lose any men.” Instead, it states outcome and time constraints so soldiers own how this gets done and can respond as on-the-ground conditions change and enemy tactics emerge.

So, why do these alternative constraints — outcome and time — work better, and how can we most effectively use them?

[Here’s the first approach.]

The Outcome Constraint

The key feature of the outcome constraint is, unsurprisingly, its focus on the end result. It defines what does a good solution does for users, payers, or investors rather than the process or rules by which it’s produced. We have identified three approaches by which leaders impose effective outcome constraints.

First, the organization can choose to set a single, big new constraint — one that forces people to think about the problem in a fundamentally different way. Make a new prosthetic leg that’s 90% cheaper than existing products is an example of this.

Connect the world’s remotest areas to the internet is another. This was the outcome-based challenge that Google, through its ‘X’ unit (formerly Google X), set the ‘Project Loon’ team. By focusing on the outcome rather than making assumptions about how it would be delivered, this team developed the idea to connect remote areas using giant stratospheric balloons rather than by laying cable in the ground. what might seem like a crazy idea is now being realized: Project Loon is now partnering with telecoms companies to provide internet services in remote areas of Africa and Latin America.

Of course, such 10x rather than 10% projects won’t always succeed. But even if the ideas they produce don’t all fly, they are often a source of genuinely new ideas. And that’s because having big, audacious goal creates an environment where the ideas need to be so big and new in order to deliver the outcome, that big, new ideas are exactly what you get.