The central premise of the book is that we often succumb to the temptation of a tidy-minded approach to getting something done, but we could be better served by embracing a bit of mess. Tim illustrates his thesis through a number of interesting lenses.
From cognitive psychology, Tim draws on the work of Shelley Carson, a Harvard professor who measured the abilities of Harvard students to filter out unwanted stimuli (if you find it hard to filter out conversations going on around you in a busy restaurant, then you have weak attentional filters). Some of the Harvard students had particularly weak filters.
You might think that this kind of messiness would be a disadvantage. But it turned out that many of the most creative students – those who by their early 20s had already published their first novels or produced a stage show, had the weakest filters of all. Details that seem to be irrelevant can – in some people’s hands – spur our creative minds.
Computer science gives us a different perspective. It would take a lifetime to try every conceivable layout for the components of a silicon chip. The temptation is to make a series of small changes to the layout of the chip that gradually improves its performance. This can work pretty well. But Tim argues that introducing a ‘judicious dose of randomness’ is likely get you a better result – by trying a series of random layouts, seeing which works best, and then making more gradual improvements.
Something not dissimilar to this happened when London Underground train drivers went on strike in 2014. Suddenly, millions of commuters were forced to try a new route for the first time. When the trains started running again, around 5 per cent of commuters stuck with their new routines – they’d found a better route, but needed a bit of messiness to jolt them into making a change.
From social psychology, Tim draws on the research on that shows that diverse teams tend to outperform uniform teams. In studies of mock trials, for example, mixed juries outperformed all-White juries. Similarly, groups of friends who know each other do less well at solving murder mysteries than a group with another person unknown to everyone else.
The new perspective of another person seems to help the group to perform. But one of the interesting reasons for this is that the members of more diverse teams feel a greater need to consider and justify their arguments than when they are in settings in which everyone is similar. It was knowing this literature that led BIT to develop Applied, our online tool to help organisations remove implicit bias from their recruitment decisions (precisely because individuals have a tendency to recruit people like themselves).
Messiness could represent a bit of a challenge to policymakers who probably have a bias towards neatness. But we think that the approach can be a useful complement to more standard practices. The Behavioural Insights Team itself was created as a kind of ‘skunkworks’ operation to inject new ways of thinking into policymaking. One simple way of introducing messiness into the policymaking process is to take a lesson from the musician Brian Eno, who uses ‘Oblique Strategies’ cards that encourage musicians to do seemingly random things – like switching roles, or ‘twist the spine’. BIT’s EAST cards seek to do something similar, albeit slightly less obliquely.
So it seems that we can all learn from Tim’s central thesis – by injecting a little bit of messiness, we might generate ideas we would never previously have thought of.