Everyone who works in innovation will regularly hear clients asking about how to “de-risk” innovation. In a world where consumers have more choice than ever before, how can we provide an increased sense of confidence about the solutions we deliver?
While no solution is ever a sure thing, behavioral economics can help. It is increasingly used by companies across industries — from health care and financial services, to the public sector and consumer goods — to fortify solutions based on an understanding of consumers’ cognitive and behavioral biases. In a nutshell, these insights help us understand what people are likely to actually do, not what they say they’ll do.
In the user-centered design world, combining principles from behavioral economics with user research and a client’s business context allows us to more systematically de-risk innovation solutions. At Doblin, we call this Behavioral Design, and it’s founded on the following key principles:
1. Insights into humans’ “irrational” decision-making can strengthen the design of smart-on-paper solutions.
How often have you bailed from a website simply because you don’t want to create and remember yet another username and password? Or bought an expensive item that sits in a closet unused because the idea of throwing it out feels wasteful? Or taken a walk around the block just to push that step-counter from 9,798 to 10,000?
Behavioral design allows us to incorporate our knowledge of these kinds of “irrational” behaviors into solutions, designing for real people and their behavioral tendencies rather than perfect versions of ourselves.
2. Behavioral insights are grounded in quantitative and experimentally tested findings.
User-centered design embraces surprising insights, generative open-ended research, and synthetic thinking… yet the very attributes that make design thinking such a powerful tool for innovation are often hard to quantify. As a result, businesses often hunger for quantitative validation to assure them of an innovation concept’s viability.
In contrast, the roots of behavioral economics grew from discipline of research experiments and quantifiable results. While behavioral tendencies are exactly that — not a rule of law, but an increased likelihood — we can leverage this quantitative foundation to foster a greater degree of assurance and confidence about the value of interventions early on.
3. Knowledge of behavioral biases can supplement — not replace —“here and now” user research.
Piyush Tantia’s recent article in SSIR1 thoughtfully suggested that Behavioral Design is the new Human-Centered Design. But what if it’s not an either/or equation? What if, instead, we borrow the best of both worlds: using qualitative end-user research to understand people’s latent needs in the context of their lives, and behavioral design to inform solutions grounded in human behavioral biases? Exclusively focusing on user needs runs the risk of ignoring important cognitive biases, but only considering behavioral interventions neglects important inputs like someone’s sense of identity, what they value, and their incoming experiences… all of which inform behavior.
This combination is powerful because our behaviors and choices are shaped by both our inherent human tendencies and the world we live in. Each supplies a part of the picture. Today many of us have smartphones, subscribe to Netflix, and use Venmo. These things did not exist in 1967, and the activities they support will likely take radically different forms in the future, but our human tendencies to dislike loss more than gain (loss aversion) or overinvest in things we own (endowment effect) are forever.
4. Innovative solutions almost always demand behavior change, whether initial uptake or ongoing adoption.
History is littered with examples of “can’t lose” solutions that lost out to alternatives or just never got traction. Why is this the case?
It can partly be explained by the fact that designing for behavioral change is often inherent in innovation, but is a notoriously difficult problem to solve. We rarely make choices in a vacuum: New solutions have uncertain value, and must often overcome our investment in older technologies or solutions (as anyone who replaced a record collection with CDs might recall). Intentionally building on known behaviors or habits can only help. For example, car sharing companies have extended and expanded the existing mental model of car rental, while Warby Parker shifts the familiar activity of eyeglass frame shopping from store to home.
To a certain degree, innovation remains a test of faith — smart solutions are no guarantee of success. But applying behavioral design thoughtfully can go a long way toward de-risking those good ideas.
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Ruth Schmidt is an Innovation Program Leader at Doblin, where she leads teams and senior clients in applying design methodology to frame and solve complex challenges. At Doblin, Ruth combines deep experience in user-centered research with design-centered strategies, working closely with organizations to help them think about and solve for their business challenges in ways that address an ever-increasing pace of change.