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are viable and sustainable, desirable for all stakeholders and
technologically feasible to build.
Organizations as diverse as the Mayo Clinic, Procter &
Gamble, IBM and the U.S. government have successfully inte-
grated a design mindset into how they conceive of, build and de-
liver services and experiences. There is already significant buzz
around applying Design Thinking to add value to behavioural
interventions; but the value of applying behavioural insights to
design problems is equally clear. Struggles with uncertainty,
helping users achieve what they value, confirmation bias, time
discounting — all of these concepts are inextricably embedded
in the challenges that design sets out to solve. By coming in to a
situation fully armed with a knowledge of behavioural tenden-
cies and levers, we can vastly improve our chances of designing
more robust and effective solutions.
Consider Figure One. In this conception, the bottom left
corner is where behavioural science thrives and design plays a
supporting role. This is where understanding behavioural chal-
lenges 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.
The top right corner is where design takes the lead and be-
havioural science plays a supporting role. Here, the landscape
consists of larger, more complex systems and scenarios, some of
which may not even exist yet. This is where design can help us
envision what could be, while behavioural science provides in-
sights into cognitive shortcuts and tendencies that might derail
people from acting in their own best interests. Solutions in this
space might take shape as a new welfare system like universal
basic income or a new way to choose, negotiate and manage
health insurance.
This new model draws its inspiration from Bansi Nagji and
Geoff Tuff’s Innovation Ambition Matrix, which they introduced
in 2012 as a means to guide organizational investments in innova-
tion. The matrix was itself a riff on a framework by management
theorist H. Igor Ansoff, consisting of a simple 3×3 matrix defined
by two axes: Where to play, defined as a continuum of playing in
existing markets with existing customers on one end, to creat-
ing entirely new ones at the other; and How to win, which ranged
from existing products up to entirely new offerings.
This visual representation and line of thinking has helped
companies re-frame innovation in two important ways. First, it
provides a new language to describe the nature of innovative so-
lutions as core (optimizing current processes and offerings), ad-
jacent (reaching adjacent customers, developing incrementally
new offerings) and transformational (achieving market disrup-
tion), according to their position within the matrix.
Second, the model introduces a way to re-conceptualize
innovation as a ‘landscape’ in which one can gauge how the in-
dividual innovation initiatives within a company sit relative to
one another — in other words, taking a portfolio or systems view.
This allowed organizations to clarify their innovation goals more
holistically and helped them better plan and measure the collec-
tive success of innovations.
Borrowing the language of [former Rotman School Dean]
Roger Martin and [former Procter & Gamble CEO] A.G. Lafley
from their best-selling book Playing to Win, the frames of ‘where
to play’ and ‘how to win’ provide businesses with new ways of
describing and thinking about innovation — thinking that allows
them to be both more precise and more strategic. Transplanted
into a behavioural context, this structure has the potential to help
us imagine a broader landscape of challenges to address.Where to Play
Nagji and Tuff ’s ‘where to play’ axis focused on the ‘stretchiness’
of potential audiences and markets in the context of gaining a
competitive advantage. In our reimagined behavioural version,
we translate this strategic focus on audience as ‘in whose best in-
terest’ the behavioural interventions are designed — individuals,
multiple stakeholders or entire systems.INDIVIDUALS. Examples where nudges focus on an individual’s
best interest abound. Richard Thaler and Shlomo Benartzi’s
Save More Tomorrow plan — which in its initial rollout nearly
quadrupled 401(k) contributions compared to prior rates—is a
classic case; healthcare interventions aimed at habit formation
such as medication adherence also fall into this category.MULTI-STAKEHOLDER. These interventions multiply the impact of
solutions by solving simultaneously for multiple answers to ‘in
the best interest of x’. As an example, consider blind auditions,
in which orchestras improved the gender balance of their hiresNudges are just one piece of the behaviour-change puzzle.