Transcription
[Music] Oh, hello and welcome, and welcome back, uh, to another year. And, um, uh, just to say, what a delight it is to be back.
Now, I'm going to talk about something really important in a minute. I'm going to talk about the lazy why, the fact that I think we are generally too easily content with one explanation for anything. But then, traveling in on the train, I suddenly had an idea about how to solve social media. So I thought I'd talk about that instead.
Now, the great commentator Thomas Sowell said that political activism is simply a way for useless people to feel important. And it suddenly occurred to me, it is too easy to express opinions on social media without any particular grounding or without making any contribution to the wider society. So I decided the solution to social media, if Elon's listening, is simply to create a new social medium where every opinion you post has to be accompanied by a useful solution. And only when you get enough votes for the solution does your opinion get published. So there you are, you have a cost of entry. In order to express an opinion, you have to do something useful first. So I think that's a fair principle to establish here.
So today, before I start talking about a wider and important philosophical question, I'm going to talk about the problem of commemorative benches, which I spotted only a week ago. Okay?
Now, I've got a flattened deal down on the Kent coast, and one thing Deal doesn't have a problem with is places to sit. In fact, the capacity of the commemorative benches along the seafront probably exceeds the population of the town, uh, even at peak season. Okay? By contrast, when I go to London Bridge station, which costs something like 750 million pounds, there's absolutely nowhere to sit. And I was trying to work out why this complete uneven distribution was occurring. And I realized there's a feedback loop, isn't there? Right?
Because if you look at commemorative benches, there's a fundamental logical problem. What they typically say is, "In memory of Uncle Bob, dates, who always lived, loved sitting in this spot." Right? Now, I don't know if you've spotted this slight problem. I don't like to pick apart, um, the thought processes of the recently bereaved, but the very fact that he loved sitting in this spot probably means that there was already a place to sit. Okay? And therefore, by definition, that is not a place where you need to supply a chair. By contrast, okay, places where you don't love sitting, because there's nowhere to sit, are completely unfurnished.
So I think what we need to do is just rewrite that line. Okay? And my children have instructions that if ever I die, there's going to be a bench at platform 5 of London Bridge station. It says, "In memory of Rory Sutherland, who could never find anywhere to sit here." Now, you can solve problems, but you've got to spot them first. You've got to spot the asymmetries, the inequalities, the disproportionate attention given to one thing rather than another.
And this is what brings me, I think, to billion-dollar behaviors. And it goes back to a meeting that took place in Napa Valley in about 2008. And it was a mixture of Daniel Kahneman speaking about his latest findings on behavioral science, but present along with a lot of great behavioral scientists like, I think, Richard Thaler, for example, were pretty much, you know, about a quarter of the unicorns at that time from Silicon Valley. Larry was there, Sergio was there. I'm using first names just to flatter your own recognition. I don't know them personally. Okay? Jeff Bezos was there, etc. Um, I think, uh, Sean was there from Facebook, Sean Parker was there from Facebook. And as Daniel Kahneman presented, most of these people actually drank in what he had to say and realized that if he was right, and he probably mostly was, this had huge implications for their business. And I think they were right to think that.
And shortly thereafter, you had actually Jeff Bezos talking about, you know, machine learning algorithms that could generate 70,000, you know, 70 million nudges in a day, for example. But the most interesting take, I think, uh, in the whole evening was, um, a behavioral scientist called John Kenny. And he was sitting in the room, and he suddenly had an epiphany, which was that it was actually behavioral science, the, and only behavioral science, that could explain why the people sitting around him were billionaires. In other words, if we want to understand, uh, what it is that made Google successful rather than say, Ask Jeeves, okay? If we wanted to understand what it was that made these organizations disproportionately successful, the answer more commonly lay in a behavioral explanation than in a technological explanation. And I think it was a very interesting observation from John Kenny. He's a very brilliant decision scientist.
And thinking about that, how often, how much time, how much effort do we spend in business looking at what succeeds and going deeper into the question of why? Now, if you want me to summarize very shortly what I think is wrong with business today, uh, there's a bit too much Taylorism and there's not enough Druckerism. Okay? In other words, there's too much quantification of what it, what already is, and there's too little speculation, exploration, experimentation about what could be. And it occurs to me that if you look at the extraordinary effort we put into data collection, that seems to me completely unmatched by corresponding effort looking for interesting causation.
And I set out to wonder why that might be. Why is it that we make so little effort, uh, to consider what might be alternative explanations? And I think what I call this is the hyperactive what and the lazy why. That we put an enormous amount of energy into measuring things, quantifying things, assembling effectively statistics for presentation upwards within the organization, for presentations to stockholders, for the construction of narratives to stockholders. But actually, the effort that goes into the assembling of all this information isn't matched by a commensurate effort in asking what the causality might be.
And then I thought of the oldest question in behavioral science, which is, "Why did the chicken cross the road?" And I noticed that in this question, okay, there are always two assumptions. The assumptions are that there's only one chicken and there's only one reason. And what we tend to do, I think, is that once, and I think the explanation for this might come down to the work of people like Dan Sperber and the argumentation hypothesis, that actually, as human beings, we haven't really, uh, inherited or evolved the brains of scientists. What we've inherited is the brains of lawyers. And what I was always taught in negotiation training is that if you have one good reason to say no, advance that one good reason, then shut up. Okay? In other words, if you have a great alibi, if you have a single conclusive case for the defense, you make that case and then you stop. You don't go on adding other reasons because if one of your supplementary reasons is weak, the opposition will then pick that apart. And I think something there, I think explains quite a lot of human behavior.
I think, by the way, the greatest application as yet for behavioral science won't be in understanding individual consumer behavior, which is fairly naturally where it has its beginnings, because apart from anything else, that's where it's easiest to measure. I think the really big value for behavioral science will ultimately come from understanding social behavior, but also from understanding institutional behavior. Because we always have this view, I think, that individual consumers when they make decisions are biased. But then when you put a lot of consumers behind a desk in an office, in a workplace, and you put them around a room in a meeting, somehow those biases even out. I don't think that's true. I think sometimes those biases actually become amplified. And so understanding what's going on in collective default decision-making in terms of our approach to causality and reasoning seems a really important area for inquiry.
And what we see time and time again is what I call this lazy why. That once there is a satisfactory rational explanation, we deliver that, and then our brain says, "Right, got that. Move on. Nothing to see here." And I think it's a very, very dangerous assumption that there's only one chicken and there's only one reason why it crossed the road.
I'll give you a couple of examples of this. Let's take a sale, okay? You're all familiar with it. Everywhere in the world, shops will have a sale. And if you went to an economist and said, "Why do you think shops are crowded during the sale?" They will say, "Because the prices are lower." And that, by the way, is perfectly true. It's an absolutely reasonable and accurate answer. But is it the whole truth?
And this is the distinction I want to make. Because I think if we delve a little bit deeper into what a sale is, okay, I think you'll notice about three different things going on. Yes, there are lower prices. Okay? Now, I have a vague contention that if you actually staged the sale and put loads of signs up saying "Sale" and you paid actors to queue outside the shop, okay, that even without reducing the prices, you would create a fairly significant uptick in demand. Okay? I think that's possible. I also think it's true to say that if you simply cut your prices and didn't create the theater around the sale, by putting stickers in the window and by creating an air of desperation, I think in that case, I think in that case, actually, to be honest, you wouldn't sell that much more.
I think there are multiple things going on. I think it's a lollapalooza effect. I think there are multiple behavioral things happening in combination. And we will be much better off if we try and understand more than one of them. But what we tend to do is we default to the first plausible rational explanation, exactly as a defense lawyer might do. Okay? We've got that point. Answered. That's it. Done. Nothing to see here.
And so in a sale, I think there are multiple things going on. I think there are lower prices. I think there's also scarcity value, because implicit in the idea of a sale is something very different from ordinary shopping, which is, once it's gone, it's gone. There is implicit in it the idea of scarcity, the idea that actually these are the end of line things from the last season, and there is a limited number of them available. And there is also a huge amount of social proof going on. One of the really important things about physical retail is it puts you in an environment where lots of people are shopping, which therefore makes shopping seem fundamentally normalized. Okay? And I think sales without the crowds, without the queues, don't have the same value as, um, as sales which are effectively the product of all three of those things in parallel.
Now, I've always wanted to do, just in alignment with this, I've always wanted to do an experiment. Which is, when you have 50% extra free on something, whether it's a bottle of shampoo or it's a chocolate bar or anything else, how much of the extra purchase that results comes from the price change? And how much of it comes from the sense that there's a deal? Okay? How much it may come from salience, the fact that, you know, the other shampoo or the other chocolate bars or the other soaps or the other soap powders don't have an interesting bright red flash on them, but this one does. I always wanted to do that experiment.
But then I realized that, of course, to do that experiment will be completely illegal, because it would actually entail claiming that something was cheaper or on offer while keeping the price basically unreduced. And I asked this question once to someone, not an Ogilvy client, I hasten to add, but someone in a very large client organization. They said, "We already know the answer to that question." I said, "How on earth can you know the answer to that question? It's completely illegal to do the experiment." You know, to do that experiment, what you'd have to do is put 50% extra free on a box of soap powder and then put the price up by 50%. How could you possibly do that? And they said, "Very simply, by mistake. About once or twice every few years, someone fails to key in something into a spreadsheet. And so there's a great box of something on the shelf, and it says 50% extra free, and the price has gone up by 50%. There's actually no saving." I said, "Well, what happens?" He said, "I can't give you exact figures. He said, but basically, you wouldn't believe it, to be honest. The sales go up by almost as much as if you left the price where it was before."
Now, that's an interesting finding because it suggests the why of what's going on in a price-value equation is rather more complicated and rather more nuanced than simply comparing utility to the sticker price of the object. It strikes me as very, very interesting because what it suggests is there is a value in feeling that you are getting, compared to some baseline measure, a better deal than you would have done last week, a better deal than you'll get next week, or a better deal than your mate is getting down the road. There's some value to that relative perception. It isn't just about a price-value equation. There's some little element of kind of game theory going on in the process as well.
Now, the reason I think it's really important to do this kind of thing is because, not only because, well, two things actually. Why? Unlike what generates ideas, if you ask, you can answer lots and lots and lots of "what" questions. You can compile a lot of statistics, you can get a lot of factual information. Generally, there are exceptions, and you know, brilliant statisticians can do this, but mostly it doesn't generate the kind of insights that really generate interesting and new ideas. Okay? On the other hand, if you come up with an interesting "why," you're probably 75% there. It's a wonderful thing that if you can actually reframe the question, if you can ask a different question or come up with a different explanation, the likelihood that it generates a creative solution, which mostly will work, but certainly will be worth testing, is just inordinately higher. Why is inordinately more valuable than what? And yet businesses spend 90% of their time effectively asking a "what."
And the reason it matters so much is because if you get the "why" wrong through a lazy assumption, it leads to a huge amount of misdirected effort. So I'll give you an example of this, which I think has been wonderfully, uh, corrected, but it took more or less a lifetime of work by a man called Dr. David Metz, who is the chief scientific officer for the UK Department of Transport. Every single transport measure was based on an assumption, which is, why do people want faster forms of transport? And in every case, for decade after decade, the assumption was to save time. The models that actually justified transport investment were effectively predicated on the fact that anybody in transit was economically useless, economically inert, and therefore the more time they had to do things which weren't traveling, uh, the greater the economic and value they would enjoy.
And Metz spent years looking at what people actually did when they got access to faster transport. He discovered something very strange, which is hugely important because the whole of transport policy changes once you understand this, which is basically, whatever forms of transportation you give people, and this pretty much goes back to the Roman era, other than people obviously who are professional drivers or who have very unusual circumstances, most people are pretty happy to spend one hour to maybe 70 minutes a day pootling about the place. Okay? And if you give them new forms of transportation that are faster, they do not use it to save time. They use it to travel further afield. They use it to maximize opportunity, to maximize the places they can go, the places they can work, the places they can live. Okay?
And so this interesting kind of ceiling in what is natural human behavior, which is really something, you know, essentially innate and evolved, okay, it lies outside the field of conventional sort of economic maximization thinking. Can allow you now with a different "why" to actually invent completely new forms of transportation or transit. So one of the things Metz understands very well is people care about, in some ways, you know, two things. They care quite a lot about comfort. They also care about the predictability of driving time. That low variance in driving time really matters. Now, I would argue that perhaps for 50 or 60 years, the assumption about what transport was supposed to do has actually massively killed what would have been interesting investment in slow but dependable forms of transportation, because without a time saving, they couldn't actually see a benefit.
And this is what I mean by the fact that if you can discover a new "why," suddenly whole new solution spaces open themselves up in a way that's completely magical. I find this fantastic. I think one of the vital things we have to do is simply spend more time asking "why," even when the ostensible answer seems to be obvious and complete. We need to spend more time looking for further and different explanations. And again, as John Kenny discovered, that explanation for why something is happening probably lies somewhere in the field of behavioral science and psychology.
There's a wonderful thing, I think, called Dobzhansky's Law in evolutionary science, which says, "Nothing in nature makes sense except in the light of evolution." And to a great extent, I extend that and say, "Nothing much in business makes sense except in the light of behavioral science." As I said last year, not everything is behavioral science, but behavioral science is in everything. For a complete explanation of something, the non-behavioral solution to any question which actually involves collective or individual human behavior and decision-making probably isn't cutting it. And as a result, your failure to include it is narrowing your solution set and limiting your creativity. Because what's generally provides creative constraints, and "why" generally creates creative springboards. I think that's a vital thing to understand.
And so when we go back to that original and oldest question in behavioral science, uh, "Why did the chicken cross the road?" Every single time we ask that question, we have to consider two possibilities: there's more than one reason, and there's more than one chicken. And maybe the chickens don't all have the same reason. Once you do that, you escape from the tyranny of averages, and suddenly new, sunlit uplands of creative possibilities start to emerge. That's my promise to you. It's a promise, it's a claim. But since I solved the bench problem, okay, at the beginning, I think it's, it's, it's what you like, like it's to say, is an opinion that I've now paid my dues to share.
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