October 12, 2012
Designing For Better Decision-Making
Consider for a moment the line outside a half-empty nightclub or the “billions served” tagline. These indicators signal popularity, and they instigate that quiet but undeniable human urge to see what all the fuss is about. This phenomenon is known in social psychology and behavioral science circles as “social proof,” and it’s one of the mostly broadly acknowledged mental shortcuts we humans make. In short, it means that people look to others to uncover the proper action, especially in uncertain environs. This herding behavior happens without the benefit of conscious thought, and it has long been exploited by advertisers great and small. As social designers, knowing how this and other cognitive shortcuts work can mean the difference between a successful social intervention and one that falls flat.
A few weeks ago, Reboot had the honor of participating in StartupOnomics, an invitation-only summit on behavioral economics and startups hosted at Public Works in San Francisco.
For the uninitiated, behavioral economics investigates how people make economic decisions in the world. It amends the most sacred theorem of economics, “the rational actor theory,” to argue that people are not perfectly rational in their consumption and financial behaviors. Nor are they completely irrational; rather, they exhibit something that the famous polymath Herbert Simon coined “bounded rationality.” Roughly, we make the best decisions we can, given the information, time, and willpower at our disposal.
We were at the conference — although it occupies a bit of an adjacent space to our core disciplines — because we thought there might be something to be gleaned for the ethnographic and design research methods at the core of Reboot’s process. Indeed, we know that both fields seek to understand how the environment of the decision-maker inevitably shapes the decision, and attempt to ensure our designs do as much as possible to account for this context. An important tenant of behavioral economics states that we humans have imperfect intuition about what we do and the reasons we do it. Design research methodology, in seeking to understand how human behaviors fit into larger context, employs multiple means to understand behaviors and motivations (for example, moving beyond individual interviews to also conduct shadowing exercises and contextual observations).
StartupOnomics featured presentations on the broad array of tools available to decision architects, but was not simply an academic exercise. The organizers sought “founders, designers, product people and other professionals that are trying to have a big impact by changing the way people behave.” By inviting today’s risk-taking startups, this conference seemed aimed at shortening the historically long cycle by which research becomes widely applied.
Most interestingly, the gathering pushed attendees to devise real-world, testable ways to apply behavioral economics principles in our own work. For Reboot, this meant we left with a least one practical, actionable test to consider running.
The thought-up experiment concerns the principle of reciprocity – in essence, the idea we want to do nice things for those who do nice things for us. As part of our ongoing social accountability work in Nigeria with the World Bank, we are launching a poster campaign to inform and encourage citizens to use a service to provide their feedback on the status of health clinics and agricultural assistance in their communities. The service includes a health or agricultural tip as part of the reward for completing the text-message-based survey.
The insight was this: if instead we switched the order and offered the tip first, it would function not as a reward, but as a gift. This gift, if as desirable as we assume, could increase the goodwill that citizens have for the service, and may result in more information-sharing in the short term and enhanced citizen engagement in the long term. In our communications, we could include some intimation of this gift, which may increase participation. We may try this gift for a sample of the locations to determine if it has the intended effect.
As is to be expected, not everybody feels warmly toward the idea of designing and structuring decision environments. Some say that it feels a little manipulative. However, there are two strong counter-arguments. The first is that designing decision environments does not strip the agency of the people in these environments; people are still absolutely free to make whichever decision they want. Instead, the designed decision environment simply nudges them in a mutually agreeable direction. The second point is even simpler: building a program or designing a service is in itself building a decision environment; the designer is engaged in influence. Behavioral science counsels that these environments should be created carefully, being mindful of user goals. Put another way: the choice is not whether to design a decision environment, it is whether the design is ham-handed or thoughtfully constructed.