Re-Framing Innovation: Integrating Behavioural Science and Design
NUDGING HAS RIGHTFULLY EARNED ITS PLACE in public policy as an effective, efficient and relatively low-cost lever for addressing knotty challenges grounded in very human ‘irrational’ behaviour: Which message will encourage citizens to get out the vote or pay their taxes on time? What mix of social norms, commitment devices and prompts increases medication adherence? These kinds of behavioural interventions are primarily designed to achieve efficiency and cost savings within current processes and structures, through solutions to known, discrete behavioural challenges. Think of it as ‘process improvement’, nudge-style.
Life, however, is full of complexity and adaptation that can’t be tested with a randomized control trial. While field experiments and pre-tests can bring us closer to the intricacies of real life, nudging’s natural habitat of well-defined, present-tense inputs and processes may be at odds with the introduction of new-to-the-world contexts or the ambiguity of the future. Nudges — and behavioural science more generally — can absolutely help people save more for tomorrow, today; but the fact is, tomorrow may be characterized by a completely different set of life-stage or employment norms and conditions that upend our current conceptions of retirement above and beyond the mechanics of RRSPs and 401(k) accounts.
This led us to wonder: To what extent is a focus on evidence-based solutions of testable hypotheses contributing to a form of confirmation bias — inadvertently limiting our sense of which problems and spaces are ripe for behavioural attention and confining our ability to imagine new applications and definitions for what ‘good’ could look like? Nobel Laureate Richard Thaler and his co-author Cass Sunstein have recognized that nudges are just one piece of the behaviour-change puzzle. So, what’s missing?
Part of the solution, we suspect, is hiding in plain sight: Behavioural science can and should continue to make important contributions through nudges and its other methods, but we believe it can
Consider . In this conception, the bottom left corner is where behavioural science thrives and design plays a supporting role. This is where understanding behavioural challenges and pitfalls helps us improve existing choice architecture — like redesigning forms and setting smart defaults. Here, design ensures that the behavioural solutions are focused on helping (or redirecting) people to complete particular actions by taking their context into account.
