behavioural economics

Continuing the discussion on Daniel Kahneman’s System 1 (intuitive fast thinking) and System 2 (rational slow thinking), some curious things happen when people study surprising data. As I write this article in June 2019 there are media reports in France of exactly what I am about to describe, a surprising ‘cluster’ of cancer cases in a relatively small area. This just reinforces the message I wrote a couple of years ago (see below) about similar American and Swiss studies.

Kidney cancer in the United States

Daniel Kahneman asked his readers to consider the example of the data for the incidence of kidney cancer in the 3,141 counties of the United States. “The counties in which the incidence of kidney cancer is lowest are mostly rural, sparsely populated, and located in traditional Republican states in the Midwest, the South and the West. What do you make of this?” I have recently seen a similar type of study here in Switzerland. Our rational minds immediately get busy trying to analyze why the geography or being Republican might cause cancer. For the Swiss study, I worked out that it was probably the healthy rural lifestyles that provided the benefit. Fresh air, fresh vegetables, plenty of exercise. How could that not be the reason?

What about the worst places?

However, the counties with the highest incidence of kidney cancer had exactly the same profile. The somewhat similar Swiss study concentrated on this aspect. The TV news report interviewed a person who talked about the use of pesticides in agriculture, various treatments in the vineyards and so on. Seems perfectly logical to think that the rural population would be far more exposed to them. In addition, the rural populations are poorer and probably have more difficulty getting high-quality health care. There were discussions of ‘cancer clusters’ in areas with the highest rates.

The key words were…

In reality, the most important words in the description of the counties with high rates of kidney cancer were ‘sparsely populated’. Counties in the United States have populations that range from under 500 to over 10 million. According to www.kidneycancer.org, the lifetime likelihood of anyone contracting kidney cancer is 1 in 63. In a small county, it does not take many cases for the percentage to be unusually high. The general randomness of cancer over the entire country means that there will of course be some small counties, with quite small numbers of cancers, but with relatively high or relatively low incidence percentages. The extremes are what grab the headlines. Next time you see a story about something like scientists studying why people in some small village live such long lives, treat it with suspicion. A similar village just down the road may have a population with an unusually short average lifespan. That’s statistics!

Use care when presenting your data

Customer experience data commonly has small numbers. If, for example, you are presenting NPS scores for 40 countries, it is very likely that both the highest and lowest scores will be from countries with relatively small sample sizes. This has little to do with statistical significance. If you are looking at enough items, each with 90% confidence, one in ten is just going to be a relatively poor reflection of reality. I used to present NPS benchmark scores for 45 enterprise software companies each quarter. It was very common to see a new small company top the list for a single quarter. If trends from prior quarters did not support this, I told my audience we should wait until the following quarter to react. If the prior quarterly trends did support it (as was the case with ServiceNow’s gradual move from awful NPS scores to great ones), I proposed immediate action.

Nobel laureates by per capita

Another entertaining example and research question would be the following: Why do the Faroe Islands have the highest number of Nobel Prizes by capita? Let’s send out a research team to study their education system and copy it everywhere! In fact, the reason is that they have had one Nobel, and have a population of just over 48,000.

Regression to the mean

If you have loads of data and a consistent trend for something, such as transactional NPS scores for a call center, be careful how you react when you see a substantial short-term change from the trend. To give an analogy, behavioral psychologists generally agree that punishing children for unusually bad behavior does not work, and can even have negative long-term effects. (These psychologists believe that rewarding good behavior works far better.) However, most parents believe punishment does work, and works well. The reason for this belief is regression to the mean. The child has a certain average behavior, trending in a certain direction. They then do something that is unacceptable, and outside the prior average. The parent punishes them and the behavior returns to the prior average. That would have happened in any case, even without any intervention. That is, it will regress to the mean. The only time you have act in new ways is when the trend has actually changed (as it does in fact do if you reward good behavior over time). If you are constantly seen to reward or punish people for what are really single random deviations from their normal trend, you will lose credibility.

Looking forward

Next time I will discuss whether you should adjust or ‘weight’ your research results in any way before you report them. It’s a tricky subject without simple answers. I hope I can reduce the complexity for you. And that post will also include a ‘true or false’ learning test.

As is often the case, the above is a slightly-edited version of a chapter in one of our books; in this case Net Promoter – Implement the System All of our books are available in paperback and Kindle formats from Amazon stores worldwide, and from your better book retailers.

In his book Thinking, Fast and Slow [1], Daniel Kahneman describes two ways our brains function. He refers to them as ‘System 1’ and ‘System 2’. At their most superficial, you can think of System 1 as intuition, and System 2 as rational thought. He offers persuasive arguments that System 1 acts first, and that System 2 is lazy, and does its best to avoid work.

Relevance to NPS

For NPS to be a trusted metric, it must work for both System 1 and System 2. The Ultimate Question 2.0 concentrates on System 2. This book’s content on survey design, improving response rates and things like the automated analysis of verbatim responses all appeal to System 2. I consider the System 2 work to be necessary but insufficient for success. You also have to appeal to the fast-acting intuitive reactions of System 1 thinking. The following are some items for you to consider.

Sequence of presentation

Kahneman describes an experiment set up by Solomon Asch [2]: subjects were given descriptions of two people and asked for comments on their personalities. Here they are. What do you think of Alan and Ben?

• Alan: intelligent, industrious, impulsive, critical, stubborn, envious.
• Ben: envious, stubborn, critical, impulsive, industrious, intelligent.

Most people describe Alan far more positively than Ben. Because the first word used to describe Alan is ‘intelligent’, the more negative character traits are considered to be justified. However, the words used to describe Alan and Ben are identical. Only the sequence has changed. The first thing that is presented has a disproportionate effect on your message, and sets the tone for all the rest. For example, if the overall message you want to communicate is that your company is making good progress, don’t start with the only negative story. When you are going to talk about what you need to improve and what is going well, start with what is going well. Of course, if you have just taken over the customer experience responsibility, you may want to be Machiavellian and start with the bad news, implicitly blaming it on the prior leadership. You could then reverse the sequence for the same information a few weeks later, and people will think you are making progress. Naturally, if you do this blatantly or often, you will lose trust.

Jumping to conclusions

We all jump to conclusions without being aware of it. Kahneman offers the example, “Ann approached the bank” to illustrate this point. You almost certainly formed an image of a woman walking towards a bank, possibly to deposit money. However, the statement is ambiguous. If we had also been told that Ann was on a canoeing trip, our conclusion would be different and we would see her paddling to the side of the river.

A lot of customer experience information is ambiguous. People’s System 1 will jump to conclusions and System 2 will sleep, unless you force it into action. You have probably heard of the metaphor of blind people trying to identify what they are touching, when each is able to feel just one part of an elephant. Turn this on its head and you have confirmation bias. If your audience has been primed to think, for example, that customer service is awful, they will use whatever they can in your data to support that conclusion, and may not even realize they are doing so.

How to get System 2 to work

In other words, how do you get people to react totally rationally to the NPS numbers you present and the financial business case you may be making? The sad truth is that you can’t do much about it. Your best solution is to force your System 1 to look at what you are going to present. Think in terms of someone who is going to ignore most of the data. What are they going to see when they look at your slides? What are they going to hear when you speak? Their intuitive, emotional reaction will win out. System 2 will act only for brief periods. Plan on it.

There is some science that suggests that asking people to do a simple mathematical puzzle that requires System 2 to get the correct answer will help engage System 2, at least for a brief period. Priming people by giving them a puzzle to do in a break, or just having it on the screen before your presentation may help. There is also evidence that making something difficult to read forces System 2 to engage. In any case, you should kick off by using a real customer quote or example, appealing to your audience’s emotions before you start showing data.

[1] Daniel Kahneman: Thinking, Fast and Slow, published by Farrar, Straus and Giroux, 2011, ISBN 978-037427631.

[2] The full set of Asch’s experiments in this area is described in the article below. The example used is “Experiment VI” in the article.
http://www.all-about-psychology.com/solomon-asch.html.

Looking forward

The next article in this series will examine ‘the law of small numbers’, an important thing to consider when you have small sample sizes.

As is often the case, the above is a slightly-edited version of a chapter in one of our books; in this case Net Promoter – Implement the System All of our books are available in paperback and Kindle formats from Amazon stores worldwide, and from your better book retailers.