The Behaviour Business. Richard Chataway

      25 www.theguardian.com/public-leaders-network/small-business-blog/2014/feb/03/nudge-unit-quiet-revolution-evidence

      26 This was mainly because the minister for health wanted a major announcement she could make on World No Tobacco Day on 31 May 2012 – which was eight weeks away. Whilst it was a stretch to make this target, it was the right thing to do in hindsight. The minister had an eight-minute slot on primetime TV programme The Project (the Australian version of The One Show) where she talked about the app for most of that running time. This PR exposure was hugely effective at driving downloads, which snowballed from there.

      27 See page 10 for an explanation of social proof.

      Chapter 3: Test-Tube Behaviours – How to Deliver Marginal Gains Using Behavioural Science

      ‘Sciencing the shit’ out of problems

      In the Oscar-nominated movie The Martian, Matt Damon plays a NASA botanist stuck on Mars. His crew have departed after they have (reasonably) assumed he has been killed by an accident during their mission.

      Damon’s character survives. It will be several years before a rescue mission can reach him – but he only has sufficient supplies to last a few months. As a highly qualified scientist, he does not panic. He decides to solve the problem in the most effective way possible.

      In his words, he decides to “science the shit” out of the problem.

      He consults the notes left behind by his colleagues, experiments using the limited resources at his disposal – including a highly creative way of growing potatoes with the help of his own faeces – and he keeps himself alive.

      Not only is this a great movie, but it is also a powerful allegory for the way science has solved mankind’s problems. The houses we live in, the food we eat, the transport we use: all of these contain innovations that were developed by scientists using the scientific method.

      A hypothesis based on existing evidence, followed by a deduction, and tested through observation. Then repeat.

      And yet, in business, little work is scientifically based. In fact, most of it involves no experimentation and an awful lot is based on outdated assumptions. Isn’t it time we removed the guesswork?

One of the characteristics of governmental behavioural teams like the BIT is their use of best practice, scientific methods. Often, this means using randomised controlled trials (RCTs). David Halpern, CEO of the BIT, calls them the “gold standard of evidence-based policy”.28

      RCTs are a methodology developed by medical science, where the efficacy of a medicine (for example) is tested by evaluating that medicine against a control condition, that is, one where no medicine (or an existing medicine or placebo) is given. Patients are allocated at random (hence the name), with the aim of eliminating bias. Data is then analysed to look for statistically significant differences between the two groups’ outcomes to determine not only effectiveness, but also potential side effects.

      Social (including behavioural) science experiments generally involve testing a behavioural intervention (nudge) against a control condition – which is usually no change. In one BIT tax experiment for HM Revenue and Customs, they tested a social proof letter saying, “Most people pay their tax on time”. This was then evaluated against the existing HMRC letter, with taxpayers receiving one of the two letters at random. The test letter resulted in a 15% increase in the number of people paying before the deadline.

Having seen the overall success of this new letter in getting people to pay their tax on time, the BIT team interrogated the data a bit further. They found that amongst the top 5% of taxpayers, the social proof message had actually reduced the likelihood of paying on time by 25%.29

      Amongst this group – it failed.

To find out what did work for this group, the BIT ran another RCT in 2015 to see what message worked best amongst the highest taxpayers. This turned out to be a loss aversion30 message based on the effect on public services of not paying tax – this increased payment rates by 8% amongst the highest taxpayers.

      And, thus, progress was made. Hypothesis, deduction, observation.

      Or, to put it another way: test, learn, adapt. In this case, it was only possible to understand how behaviour was heavily influenced by this context (i.e. the choice architecture) by sciencing the shit out of the problem.

      Loss aversion

      You may have experienced FOMO (fear of missing out), or the realisation that you want to do something (e.g. going to a party or seeing a movie) not because you especially desire it, but because you fear regretting not doing so. This is a manifestation of a particularly prevalent behavioural bias: loss aversion.

      Put simply, loss aversion is the tendency for our behaviour to be more influenced by the risk of a negative outcome (loss), than the chance of gain. We generally feel the loss of £5 more keenly than gaining £5. It explains related biases like the endowment effect (that we value something we own more highly than an identical item we don’t) and scarcity bias (our increased desire for things we think are in short supply).

      Evolutionary psychologists explain this in terms of our survival instincts. In a world of scarce resources, we needed to ensure that we harness and keep as much as we can, while we can, for fear it might be gone tomorrow. Even in a world of relative abundance, this still guides our behaviour.

      Consequently, we also have a present bias: we value things more today than in the future, largely because we can better visualise what we can do with resources (e.g. money) now. It explains why we are generally so bad at saving for retirement, and often reach the end of the month with less money in the bank than we expected.

      This bias is used frequently by businesses, particularly in marketing, through limited time offers, closing down sales and the like. In the digital world, when buying tickets or hotel rooms, for example, we often see it through nudges like ‘only 5 left at this price!’ Instinctively, this makes us want the product more and we become more likely to purchase immediately. But, note the clever phrasing here: ‘at this price’, means the price could just as well go down as up! Our inherent bias makes us assume that if we don’t grab it now, it will cost us.

      When working with the call centre described later in this chapter, we experimented with using loss aversion for customer benefit. When talking about the benefits of moving to online banking – specifically that it is safer, quicker, and better for the environment (because it removes the need to send out paper statements) – we found we could significantly increase the likelihood of customers taking up the service by simply suggesting that if they didn’t, they would miss out. Previously, customer service representatives (CSRs) had quite rationally talked through these benefits, but found customers tended to ignore the information or cut them off before they finished.

      Simply saying that a customer would miss out by not changing worked much better – often without the need to even say what the benefits are (suggesting they already knew what they were, they were just too cognitively lazy/uninterested to change). If a customer queried this, the CSR could then talk them through the advantages, but, in most cases, the decision had already been made.

      This is yet another example of how much faster our instinctive system-1 processes are than our more conscious system-2 ones – and more influential.

Learning from failure

      In his book Black Box Thinking, the journalist Matthew Syed contrasts two industries – medicine and aviation – in terms of how they encourage best practice and avoid the negative outcomes of failure (which is often