Transitions tend to prompt reflections on where we’ve been, and in looking back behavioral design has much to be proud of given that the field barely existed ten years ago! But these moments also tempt us to project what lies ahead. Behavioral design has already taken multiple forms—intriguing curiosity, presumed silver bullet, flavor of the month, competitive advantage—but it’s also a maturing discipline that is still in the process of being codified. So it’s worth pondering: what does the future hold?
Until we can predict the future, foresight methods used in design to help us explore what could be might be the next best thing. The well-known strategic tool called scenario planning, for example, pits two dimensions of uncertainty at perpendiculars to generate four speculative futures. It’s no crystal ball; rather, its value comes in forcing us to concretely imagine and play out the collision of extreme forces far in advance, to surface potential implications and provoke thinking about how we might address or adjust to them. Think of it as a low-fidelity prototype or simulation that allows us to try on different future conditions before facing the real deal.
As with any method, scenario planning is only as good as its inputs, and selecting the right dimensions of uncertainty is more likely to lead to more insightful results. When used for strategic planning purposes, external forces—like the availability of resources or market changes—are often the biggest unknowns that need to be understood. But given the nature of our query, we might want to select vectors that are more attuned to emergent uncertainties about the practice of behavioral design itself instead.
One common source of tension in maturing disciplines is the degree to which they become increasingly democratized as they becomes better known and accepted. The emergence of design thinking is a classic example, where in gaining advocacy and buy-in it also became more commoditized (for proof, just search for “design thinking certificate”). We might call this dimension of uncertainty centralization of expertise: that is, whether know-how remains rooted in formal training or traditional academia, or whether proficiency is broadly distributed and accessible through a wide range of sources.
If that dimension explores where expertise resides, a complementary axis might consider how expertise is applied to problems, or the generalizability of application. Behavioral design prides itself on delivering high-efficacy, context-specific interventions informed by well-documented experiments from the literature, but the precision of these bespoke interventions can also lead to a “see-one/solve-one“ mindset and reluctance to apply lessons from those successes to other challenges or contexts. Our second useful dimension of uncertainty, then, might be the degree to which the field sticks with specialized application or finds a way to generalize and employ findings more confidently across settings.
Using these two intersecting dimensions—centralized to democratized expertise, against specific to generalizable applications of knowledge—we create four quadrants, each of which yields a glimpse into potential future versions of the profession.
So, what might this mean? In its current form, behavioral design is probably already closest to centralized specificity. But if this center of gravity became even more extreme, the field might grow analogous to medicine or law, solving specialized problems with high, but narrow, accuracy and requiring advanced degrees, even licensure, to practice. This would suggests a potential rise in credentialing to demonstrate credibility and doubling-down on RCTs and precisely targeted solutions; on the downside, this might also lead to a certain elitism or insularity that inhibits broader scaling.
Democratized specificity, alternately, might mean the field splinters, embedding behavioral expertise into other disciplines that apply behavioral insights to domain-relevant problems in radically different ways. This could impact how practitioners pursue mastery in a world where, for example, career paths increasingly expect practitioners to specialize in “behavioral wellness” or become a “vehicular behavioralist” rather than being behavioral generalists.
Democratized generalizability projects a path where broad familiarity with principles from behavioral science is basically taken for granted and easily accessible, akin to how —for better or worse—WebMD has allowed laypeople to self-diagnose themselves. For behavioral design, this might mean that experts relinquish some of their authority in favor of widely available tools that support DIY behavioral problem-solving… with the potential tradeoff that these less nuanced applications may read as hopelessly misguided or lightweight to those with deep expertise.
Finally, a world of centralized generalizability might retain a more traditional path to mastery but also harness pattern identification to generate potential hypotheses more effectively and efficiently. This might not only allow practitioners to more confidently apply lessons from contextually specific successes and learn from what didn’t work, but also potentially deliver on the promise of bringing behavioral design to new problem areas.
Of course, these paths are not truly mutually exclusive; medicine, for example, is founded on credentialed specialization, yet also has generalists and easy-access self-diagnostic content and tools online. But each of these potential scenarios has unique implications for how behavioral design might demonstrate its impact and staying power in the future. After all, “impact” can be interpreted and measured in multiple ways, from improving metrics for individual interventions, to expanding the footprint of behavioral practitioners, to embedding behavioral perspectives further upstream to address root causes, to scaling prior successes across new contexts. How we, and the field, choose to make a dent is largely up to us.