The Behaviour Business. Richard Chataway

industry does not generally adopt a scientific approach in its response to failure. Medical mistakes are often covered up, ignored, or worse – usually for fear of reprisal and legal action.

But as Syed puts it: “science [is] a discipline where learning from failure is part of the method.” This is why the introduction of black boxes in the 1960s – that retain all data pertinent to an air crash (which is then shared globally amongst the entire industry)31 – has had such an impact on aviation safety.

Indeed, 2017 was the first year on record where there was not a single fatality as a result of a commercial airline crash. A total of 399 people died globally solely in freight and military crashes that year – by contrast, in 1972, a total of 3,346 people were killed.32

      Syed categorises this scientific approach to failure as characteristic of a ‘growth mindset’ (as opposed to a ‘fixed mindset’) for organisations, and the best way to deliver incremental improvements through marginal gains. He quotes the philosopher and scientist Karl Popper: “The history of science, like the history of all human ideas, is a history of … error. But science is one of the very few human activities – perhaps the only one – in which errors are systematically criticised and fairly often, in time, corrected. This is why we can say that, in science, we learn from our mistakes and why we can speak clearly and sensibly about making progress.”

      If a business wishes to progress, grow and succeed, then understanding the merits of a scientific approach, and the value of testing, is critical. It must also recognise that this process is an iterative one, where we can learn as much from failure as from success, as with the BIT HMRC experiment. In this way, behavioural science – by requiring testing to establish what works in a realistic context – can increase the effectiveness of established management techniques based on continuous improvement and marginal gains, such as kaizen, lean thinking, and agile processes.

Applying a growth mindset to business challenges

As an example of this, in 2017/8 I worked on a project with partners at OEE Consulting,33 a leading services and operations management consultancy. The client was an outsourcer that ran a call centre for one of the UK’s largest savings banks (having over 20 million customers). OEE Consulting were developing a number of new processes and systems, based on lean principles, to deliver better processes in the call centre. These had both an efficiency (i.e. money-saving) objective and an effectiveness one (i.e. delivering better service for customers).

I was brought in to advise on how we could deliver better customer service through addressing what customer service representatives (CSRs) were saying on the phone. That is, using behavioural nudges to improve the quality of outcomes for both customers (more successfully answering their reason for calling, such as making a balance transfer) and the bank (reducing the duration of calls so they could handle more, as well as encouraging customers to take up online and paperless offerings).34

One example: our analysis found a surprisingly high number of people were failing the mandatory security checks. After listening to calls, we discovered this was because the framing of these checks was very formal, and slightly confrontational. CSRs were in effect saying that if customers could not prove their identity, the bank could (and would) not help. With older customers in particular, this interrogatory approach was causing them undue stress – which has been proven to affect mental availability35 and the ability to recall information. As a result they would frequently panic and get their answers to the mandatory security questions wrong. This lengthened the call, as well as making it unsuccessful and frustrating for the customer.

With a few small tweaks to the wording, we changed the scripts to frame them more positively (e.g. from “if you prove your identity” to “when you prove your identity”)36 and even said to customers that they could “take their time”, to put them more at ease – a counter-intuitive solution. By slowing down the conversation, this would actually reduce the overall length of the call.

      It is an example of how behavioural science tells us that how you say something is as important as what you are saying – if not more so.

      This was one of multiple interventions (nudges) employed. For practical reasons it was not possible to run a full RCT to isolate each nudge. Instead we ran a controlled pilot where a representative sample of CSRs in the call centre were trained and coached in using these nudges over a 12-week period, and we monitored the outcome of those calls versus the rest of the call centre.

      Referring back to our three criteria for a behavioural business from chapter 1: we were using data to build an accurate picture of what worked; we verified it through experimentation; and we had hard data on what was actually happening through data based on behavioural outcomes (the outcome of the phone call). There was a clear, direct link between what our decisions were as a business, and a behavioural outcome.

Over the course of the pilot, there was an 11% reduction in the duration of calls versus the control,37 worth potentially millions of pounds due to the thousands of calls handled every day. Customer satisfaction levels increased, and we could prove overall success in terms of efficiency and effectiveness based on behavioural outcomes. Subsequently the training and process was rolled out to the other 300 CSRs in the call centre.

The value of testing

      But, you may be thinking, for my business to make best practice use of insights from behavioural science, does this mean I need to be conducting RCTs every time I want to nudge a behaviour? Do I need a team of behavioural science PhDs conducting longitudinal, statistical analysis on the most effective subject line before I send an email?

      Well, as in the example above, experience says no. RCTs are not the only way to experiment, and in the world of business they are often not practical for reasons of time or money. Besides, in the real world, human behaviour is complex. With over 200 different behavioural biases identified in research, the sheer number of influences on our behaviour often make it impossible to isolate the impact of individual nudges.

      Richard Shotton, author of The Choice Factory and expert in applied behavioural science in marketing, says the most important thing for experimentation is creating a realistic context, not just sample size. “Context is hugely important, and hugely under-estimated,” he says. “The two reasons for testing are for persuasion and proof, using observed and not claimed data.”

      For example, I have seen the exact same phrasing used in scripting for two different call centres achieve two entirely different outcomes. But this simply emphasises the importance of testing in the relevant context. In the example above, had we simply applied the academic principles blindly without piloting first it would have been an unacceptable business risk – and completely unscientific.

      Leigh Caldwell, co-founder of The Irrational Agency and author of The Psychology of Price, agrees. “You never know for sure what’s going to work until you test in the field,” he says. “Everyone is influenced by context, because everyone has their own view of the world.”

Even Richard Thaler himself says: “Make your research about the world, not the literature.”38

The difference is that in business, what we do is not subject to peer review, nor do we publish our experiments in academic journals. That would wholly undermine any competitive advantage. As Rory Sutherland,39 author of Alchemy: The Surprising Power of Ideas That Don’t Make Sense, vice-chairman of Ogilvy UK, and the foremost advocate of behavioural science in marketing, puts it: “Let me briefly explain what business and behavioural science have in common. They both do experiments. Apart from that, everything is slightly different.”40

      Businesses seek competitive advantage above all else, and, as we have seen, a scientific approach to changing behaviour can drive progress and innovation to deliver that. Whether that is achieved by academically robust experimentation, or simply adopting a mindset of continuous testing and learning, hypothesising and deducing, is largely irrelevant. This also means businesses should not be unduly concerned about the current academic debate about whether certain experimental psychological studies can be reproduced – the so-called replication crisis. Especially when one considers the replication