The Origins of Fear of Failure

The Law of Diminishing Marginal Utility basically says that the more that we have of something (as denoted by increases in the Quantity measured on the horizontal axis) the less and less additional satisfaction we get from each additional unit of it.

At its simplest level this just means that if you eat a big bowl of ice cream, while each spoonful is making your tastebuds tingle as your dopamine is released when you start… about halfway through you’re probably a lot less keen on the taste of ice cream and each spoonful is giving you less and less satisfaction.

Clearly this is the case for ice cream because eventually you will feel sick, but it is also the case for many things: it would be nice to have a Ferrari but if you had 10 Ferraris most people who read this would probably not get the same happiness from the 11th Ferrari as you got from owning the first one. It would be nice to go on holiday but you probably wouldn’t be getting the same utility from the 66th day as you got from the first one. And even where money is concerned, while it would be nice to make a million pounds, but Warren Buffet almost certainly doesn’t get the same thrill of making a million pounds after having made thirty six thousand of them already that we would. Indeed as Arnold Schwarzenegger once said “Money doesn’t make you happy. I’ve got fifty million dollars. I’m no happier than when I had $48.”

The effect of this apparently irrelevant aspect of our psychology however could not be more profound when it comes to the decisions that we make. In other posts I’ve referred to the way in which otherwise rational people like Stuey Ungar and Nick Leeson made apparently insane decisions because of the allure of the upside and the limited downside associated with them. They gambled as a result of their emotional situation at the time. Well this is the opposite. Diminishing marginal utility means that most of the time we actually get LESS pleasure from our gains than we get pain or potential pain from our losses.

This muted upside and exaggerated downside in our Emotional Expectation calculation is what stops a lot of us from achieving the Long Term results that we want: we are scared of losing what we have in order to gain what we desire. Often, that is because we don’t even know what it is that we desire. Sometimes we do but we’re not prepared to lose what we have in order to achieve it in the Short Term.

Sometimes this fear is good. It’s what stabilizes our society. America’s delinquent youth don’t fear the downside as much as weedy academics – which is why they label them irrational and uncontrollable. It’s fashionable now to blame the parents, of course, but what it they’re not scared of what they’re parents have to say or do.

If Nick Leeson had been a little more frightened of his Mum or Dad then maybe Barings bank would not have gone the way it did. Likewise, if Kenneth Lay or Jeffrey Skilling had feared the eternal flames of hell a bit more then maybe they would not have tried to swindle their shareholders out of millions and embrace their own personal and corporate downsides to quite the same extent.

But there is a downside to this fear too. And it is a downside which costs similar shareholders a great deal more in the Long Run than a couple of corporate frauds no matter how massive and illegal they have been in recent years. The fact is that much more pervasive fraud is occurring every single day in boardrooms and offices every single day in companies across the world as leaders make decisions in direct contravention of the legal requirement to operate at all times in the shareholders best interests. They don’t. They don’t even come close to doing so. They operate largely out of a sense of self-preservation and fear of short term failure. I certainly would if I were in their situation and had the weight of quarterly shareholder reports bearing down on me on a daily basis. These are not the conditions necessary to motivate people to take the necessary risks to be the best at what they are doing.

On the last bend of the women’s BMX event in the 2008 Olympics British cyclist Shanaze Reade gave up a certain silver medal place in order to overtake the leader and push for gold. She failed, came off her bike and went home without a medal or – she says – any regrets. She was prepared to lose what she had in order to gain what she desired.  Would she have done the same had she had to report her results to a group of shareholders at the end of every race? Shanaze Reid went into that race as the world champion and the out and out favourite. And she got to that place by consistently being prepared to lose what she had in order to gain what she desired.

The ability to lose what you have in order to gain what you desire ultimately this is what will define your ability to achieve what you want – whatever that may be. The question is how do we embrace that mindset in poker, business and life?

Nick Leeson – King of the Rational Emotional Decision Makers

Nick Leeson is a working class lad made good. Then made bad. Then made good again. His story is famous the world over. He is the man who brought down an entire bank. Exactly how this was allowed to happen is of course a Black Swan in itself but it did and the fallout was immense, not least for Leeson himself who ended up in a Singapore jail for several years before laudably coming back with a vengeance and writing a book about his recovery and the effect that stress can have and how to beat it.

The exact details of what happened in 1995 are obviously complicated but essentially the principle is exactly as the world understands it: by the end of 1992, the amount concealed in the error account was £2m, but the end of £1994 it was £208m and by 23 Feb 1995 Leeson fled the country leaving a note saying “I’m sorry” and an account which held £827m in losses. Essentially, Leeson had got caught in a spiral of loss partly due to his decision to use a system to try and correct what began as fairly modest errors.

The system – known as the Martingale system – is known to gamblers and traders the world over and must be the cause of more unhappy nights in Vegas than any other. Essentially, it says if you lose your first bet (of, let’s say $1) you simply double it on the next spin, or hand, and if you lose that, simply double it again and so on and so on until you, eventually win, as you eventually must. The inherent problem with the system is that in theory it works perfectly. At some point within an infinite period of time, however, the monkey on the typewriter will bash out the works of Shakespeare or at least a sonnet or two! What the laws of probability don’t say, however, is WHEN! Which means that an infinite bankroll is required to make the system work in practice, something that even Warren Buffet doesn’t have. And neither did Barings Bank!

But here’s the question: why – when he was £100 million pounds down, did Leeson – an apparently intelligent, determined young man keep going? Why not throw in the towel, concede defeat and do the time that he was ultimately sentenced to do? Why push the envelope until the point of no return and potentially destroy everything for everyone in the process.

The answer lies in the meanings or values that Leeson placed on the different possible outcomes of the potential opportunities available to him.

The only thing that meant anything at all to him at that point was just breaking even. Reducing the losses to £70 or £40 million meant nothing. He was still going to lose his job and almost certainly go to jail in this eventuality. Increasing the losses to £200, £300 even £400 or £500 million was not going to worsen the situation for him really. He had got to a stage where the downside remained the same and the meaning of the upside (his possible reward) was everything. Effectively doubling through and breaking even meant safety, it meant freedom, it meant employment, it meant an end to the stress which eventually gave him cancer. It meant getting the life he loved back.

In this way Nick Leeson was no different to the millions of gamblers who step inside the billion dollar casinos in Las Vegas or Sun City or Mayfair or anywhere around the world. Largely otherwise intelligent, rational people make decisions for an evening which deep down they know will cost them money. People who play slot machines, for the most part, know deep down that the house will win in the long run. I’m not saying that there aren’t people in those places who become convinced that they are “hot” or that they have a “system”.

For Nick Leeson, whatever the probability of the downside, the meaning he placed on losing even more money was minimal. The only thing which meant anything at all to him was breaking even. This was immoral, certainly, given the consequences of his actions for thousands of people but rationally… well, rationally it made sense! Given a similar lack of moral fibre any one of us might well do the same in the same situation.

Certainly given a different situation which, for example, forced us to make a decision to do something which might kill us but which might also very well save the life of our child, which mother or father would not take this course of action? Naturally, this is a hypothetical situation with no detail at all and the first thing you would want to know would be the probabilities involved – but we’ve already covered that. The point is that the meaning we place on the possible upside as a parent would far outweigh the potential downside. Somewhat morbidly, in order to more closely simulate Nick Leeson’s emotional calculation we would probably have to assume that we were likely to die in either event – a factor which would make the ultimate decision a no-brainer.

The situation that Leeson found himself in was very different to going into a casino with £50 (or even £50 million like Kerry Packer did) that you’re happy and prepared to lose. It’s more akin to the position that the poor sap who has heard about the Martingale system finds himself in after maxing out two credit cards in a desperate bid to win back that first $10 after a statistically freakish but eminently possible 10 spin losing run (1024 -1 against). Now, we are anything but happy. We are anything but prepared. But in much the same way, if for very different reasons, there is very little additional pain we can experience. It’s not just our credit cards that are maxed. So are our pain levels. And the only way is up.

Posted 02:47pm by Caspar and filed in Decision Making, Risk

Stu The Kid and the Rational Emotional Mind

About twice a week, I have the privilege of working with leaders in the UKs public, private and third sectors in my “Risk Taking and Decision Making” seminars. In addition to giving them what I hope are some interesting, sometimes inspiring, insights into Risk, Uncertainty and why they do what they do, we also have a lot of fun. Specifically, we play a game very similar to (but obviously not actually) Deal or No Deal in which the people in the room are asked to BUY the box from me, rather than SELL it to me as they being asked to do on the television show.

I sell in a number of different ways: sometimes an auction, sometimes a negotiation, sometimes a closed envelope bid. But no matter how I sell it, the same phenomenon happens every single week. At the beginning of the session, I give them a specific number of poker chips (their scarce resource) and inform them that the team or individual at the end of the session with the most number of chips will get cheered and free drinks all night (depending on the client, you’re not allowed to do this in the civil service). The losing team, however, will be booed! They think I’m joking so I repeat myself. The losing team will be booed. It’s amazing how the promise of a cheer and a boo focus the mind of competitive colleagues but focus it they do and when it comes to sell the box… everyone… and I mean everyone… values it completely differently. Why?

In order to understand this, let’s consider the story of Stu “The Kid” Ungar. Born on the Upper East Side in 1953 to Jewish parents Stu was exposed to gambling at a young age. By the age of 10 he had won his first local gin rummy tournament and soon after he dropped out of school to play full time, earning thousands of dollars in the process. Rummy – a game with as much variance, or short term luck, as poker – is theoretically difficult to dominate, but Stu managed it. He didn’t just beat his opponents, he destroyed them mentally.

One night he beat Harry “Yonkie” Stein, the man widely regarded as the best player in the world before Stu came along, so consummately that Stein gave up the game soon afterwards. Soon afterwards, no one would play him. He had to offer handicaps to people to get them to take up the challenge but even that didn’t work so he moved to Las Vegas and took up poker.

The first time he ever played No Limit Texas Holdem was in the he won the World Series of Poker main event in 1980. He won it. And came back in 1981 and won it again! During the course of his career he played in 30 tournaments with buy-ins of $5,000 or more against the best players in the world and won 10 of them! He was the best of all time, and he knew it. As he himself exclaimed: “Some day, I suppose it’s possible for someone to be a better no limit hold ‘em player than me. I doubt it, but it could happen. But, I swear to you, I don’t see how anyone could ever play gin better than me.”

During the course of his life he is estimated to have won more than $30m at the poker table including the $1,000,000 first prize for winning the 1997 World Series, the third of his three titles in the big one. He was found dead in his room of a cocaine overdose in November 22 1998. He had just $882 to his name. His friend Bob Stupak took up a collection at his funeral to pay for the services.

Stuey Ungar was one of the quickest and most brilliant statistical minds ever to play the game. He used to shout out probability calculations across the card table to two decimal places. He knew every probability there was to know and those that no one knew he calculated in seconds. He took the most brilliant calculated risks that the game has ever seen but he died practically broke after having lost everything on dice and horses.

How could a man with more understanding of Expectation than anyone who ever lived repeatedly and willingly throw millions of dollars away in the course of a lifetime?

The reason cannot be the different probabilities involved or even the different  possible potential outcomes, but the meanings we apply to the those outcomes. And they are different for everyone.

Most people go into a casino with a certain sum of money in their pocket which they are willing and happy to lose. “I have £50 for the evening” they say “and then it’s home to bed.” So the potential emotional downside for them is limited. They went intending – or at least agreeing – to lose £50 so when it happens it is no big deal. The meaning they have decided to place on that loss is minimal. But the upside… oh the upside…

Dopamine is a neurotransmitter commonly associated with the pleasure system of the brain providing feelings of enjoyment and reinforcement which motivates a person proactively to perform certain activities. Dopamine is released (particularly in areas such as prefrontal cortex) by naturally rewarding experiences such as food, sex, drugs, and neutral stimuli that become associated with them.

Dopamine is good because by reinforcing the things which keep us alive, (giving those things an emotional upside) we continue to make decisions which give us a release of dopamine. The meaning or value we apply to the feeling that dopamine induces is positive although we are largely out of control of this process. The drugs that trade illegally in our society are, not surprisingly, those which also precipitate a release of dopamine into the body.

Now we start to get an insight into the life of an addict who is getting massive dopamine highs from his wins and almost no emotional lows from his losses. Stu Ungar’s intense and detailed knowledge of the mathematics of his investments on the nags were irrelevant to him. Because that was not the part of his brain that was doing the deciding. And the part of him that was didn’t care about the losses. He just lived for the wins.

Labeling Stu Ungar however as irrational, however, or bemoaning the kids who are apparently immune to the threat of tougher sentences or even a greater likelihood of being caught is to completely miss the point, however. These people are not irrational in the sense of being unpredictable or insane or delusional or unaffected by the consequences of their actions. Far from it. There is research showing evident links between aggression and dopamine because obviously before the development of a justice system there was as much of an evolutionary advantage to being aggressive and defending one’s life as there was to taking risk and exploring new territory.

No, It’s not that Ungar or delinquent teens in America are irrational. That’s not the problem. Indeed, the problem is quite the opposite. It is that they are intensely rational, constantly weighing up upsides and downsides and probabilities thousands of times a day, like the rest of us. The problem is not the absence of a calculation, it is the INPUTS into that calculation. It is the meanings that they place on those outcomes that are the problem.

More specifically it is that for whatever reason, the thought of losing a hundred thousand dollars didn’t bother Ungar any more than we’d be bothered by the thought of losing 50 pence and thought of going to prison doesn’t bother a portion of American teenagers anymore than it bothers us to be stopped by police for having a headlight out. Conversely, the thought of winning half a million (away from the poker table) gave Stu Ungar shivers of excitement and the thought of beating someone and stealing their wallet still gives some people a rush of dopamine which kept their prehistoric ancestors alive.

We can argue about what causes the particular meanings and values which these people place on the different possible outcomes until the cows come home, the fact is that these people are not being irrational any more than the acquisitions team of one of the world’s biggest companies who told me once that quite early on in their final confabulation, despite the mass of data thrown up by the due diligence someone in the room would pose the question “how do we feel about them?” In other words “OK, what meanings do we place upon these numbers?”

In another room full of senior executives culled from the upper echelons of British industry there is a different decision to make: how much to give me for my box. With offers varying hugely across the room, it’s clear that despite their similar backgrounds and capabilities we have a room full of people here who place very different meanings on the upsides and downsides involved.

I personally find this endlessly interesting because of course there isn’t even any money at stake, just status or reputation given that they are effectively just playing a game with their colleagues. Some of them – perfectly reasonably – don’t really care about it arguing that “they’re just poker chips” and therefore are often prepared to bid whatever is necessary for the chance of opening the most lucrative box. Others, though they might not like to admit it, care deeply and don’t want to do anything which might mean they have the least at the end of the day. As one participant exclaimed as he banged his fist on the table, exasperated with the collective decision-making of his colleagues: “What are you lot most driven by… the thrill of the cheer or the fear of the boo?”

As I remarked at the time, a better examination of why we do what we do in poker, business and life is actually hard to find: what are you most driven by? … the thrill of the cheer or the fear of the boo?

Dealing with Change

Gleicher’s Formula for change – created by Richard Beckhard and David Gleicher – provides a useful framework within which to consider how and why people do what they do.

The formula states that people will change when D x V x F  are greater than R… where D is Dissatisfaction with the present, V equals Vision of the future, F equals First steps and R equals Resistance.

Translated back into the language that I have been using in these different posts, V is the upside, F is a way of making that upside look more likely in the minds of the throng by making it apparently easy to obtain and R is the nature and likelihood of the downside. D is interesting though because D pertains to an aspect of human motivation that I want to write a lot more about in the future.

The fact is that the people whom Gleicher and his acolyte want to change using their equation – like all of us in any situation where a decision must be made – have a CHOICE between one course of action or another, maybe many: Whether to hold the door open or not, what to select from the menu, which bank to give our money to, which car to buy, which school to entrust with our children, whether to drive or get the train, turn left or right, jump or stay put…

And each of these options or opportunities available to us has its own unique Expectation. Why we do what we do is a result of not just one but many – maybe even a huge number – of Expectation calculations which we do in the moment of decision as we consider the possible futures of a large number of potential scenarios and then decide to do the one which comes out best for us.

D – Dissatisfaction with the present can roughly be translated as potential downside of NOT changing and therefore may very well include potential negative reinforcement of such a choice although, in the positive atmosphere of management-speak, it is not voiced in those terms! According to Versario (1980) only 10% of management efforts in change programmes are focused on negative reinforcement with 90% concentrated on “selling the benefits” or creating the V of the positive choice to do what ultimately management want people to do. This may well make for a nicer world but not necessarily the most efficient use of those scarce resources time energy and money.

When weighing up the different possible courses of action and behavior open to them, if people perceive a great deal of possible pain associated with the downside of making the decision to change and very little possible pain associated with the decision not to – guess which has the better expectation in the moment of their decision?

Posted 02:35pm by Caspar and filed in Decision Making, Leadership

Using The Psychology and Science of Decision Making to Change People’s Minds

In his magnificent Influence: Science and Practice, Robert Cialdini cites authority and likeability as two of the most effective factors we should cultivate when trying to influence someone’s decision. He writes about certain click-whirr responses which we have in reaction to certain situations such as someone’s celebrity or sense of humour or dress – particularly a uniform or white coat. Why do such qualities affect influence over a subject? Because wittingly or unwittingly (it doesn’t really matter) they are ascribing a higher probability to the reward or benefit or upside which that person is promising will accrue as a result of whatever investment (actual or potential) is required.

While a good deal of the job of branding and advertising is to convince the consumer of the perceived relative value of the particular good or service in question, much of it is aimed at increasing the perceived likelihood of accruing such quality. If I walked into Harrogate, for example, with no previous experience or knowledge of the place, I’d probably have very little idea which café or restaurant to eat in. Someone might have told me that Betty’s was a good bet, but – imagine that I don’t know anything about Betty’s – what are the chances of me enjoying a delicious cheese on toast? Perhaps Betty’s is owned by the sister of the person who recommended it to me.

Stuck in Harrogate with no other information, I might well decide to go to McDonalds because – as distinctly average as their burgers are – at least I am all but guaranteed to receive exactly the same burger every time. Their branding – coupled with my experience of that brand – would certainly make this the safe option for me in this situation. My expectation calculation would entail a tiny probability of disappointment and a tiny probability for thrill and a 99% probability for delivering the same satisfaction as it always has done. To say that McDonalds almost always meets – but does not exceed – our expectations is true with both a small and capital E. That’s precisely why we use that word in that way colloquially.

As it happens, if I were to “take the risk” and venture over to Betty’s, while I could only guess how likely that delicious Rarebit might be, my probability assessment may be swayed by the long queue of people extending out of the door. This “social proof” as Cialdini calls it – or the belief in something because others believe it to be true – is often dangerous and misleading but rightly or wrongly, it is a powerful factor in the formation of our probability assessment. If this visual information were coupled with a raving review from the Michelin guide – something with a lot of “authority” – then I might well apportion a high enough probability to this delicious dish to join the queue, something which in itself is quite an investment of my scarce resource, time. It had better be good.

Crucially, my conscious mind and voice will now be is now saying things like “I hear this place is excellent” and speaking as if I have a newfound certainty about my chosen destination – again resorting to the single outcome prediction which can be woefully disillusioned. My subconscious, however, will remain considerate of all the information available to me and will be performing investment calculations almost continually that actually have the power to change my mind at any time, leading me to walk out again if the queuing time becomes too long or if I witness people leaving clutching their stomachs in pain.

Nowhere is the importance of understanding probabilities more acute than in the process of change management where companies spend millions trying to persuade their staff to spend less time doing one thing and more time doing another. If only they fully understood the principles behind why we do what we do! Simply communicating the benefits of change is like simply increasing the fine for not having a ticket while leaving the number of traffic wardens unchanged. It is like someone telling me in precise but dispassionate terms exactly how delicious the food is in Betty’s without producing any kind of evidence to increase my perception of the probability.

The fact is that during any kind of half decent change management procedure, very few staff are unaware of why it’s necessary and what the benefits will be to them individually and collectively as a result. They simply don’t believe it! The likelihoods that they ascribe to accruing those benefits are just too small to have any positive impact in their Expectation calculation.

Coupled with this is the weight of the potential downside that the upside has to overcome. Anyone who has ever watched Quentin Tarantino’s Reservoir Dogs will be familiar with the mind’s response in the face of incomplete information. During the seminal scene of that film in which a man has his ear cut off during a disgusting torture, the audience is teased by Tarantino the director who – rather than showing any of the gory details – simply moves his camera up and to the left. All we see is a door in the wall. The mental images that we produce, however, are far more traumatic that anything a fake blade and a few prosthetics could ever produce.

Similarly, when faced with an uncertain future, people tend to have what psychologists call “catastrophic fantasies”, that is, worst case scenarios dominate their thoughts. The potential downsides in people’s emotional calculations are enormous and exist with a high probability of coming about. No amount of stating the benefits of a potential vision of the future is going to compensate for that if the vision looks highly unlikely to the person who ultimately has to make a decision about to change their behaviour or not.

The bottom line is that all decisions are made through a combination of upside and downside assessment in which likelihood calculations are integral. I am NOT saying that people do this consciously every time and I’m definitely not saying it’s rational much less accurate. I’m just saying that people do it and so if you want to motivate and persuade people then you need to take this on board. Cialdini’s various influencing tactics are basically just ways of interacting with people on this level in a powerful and not always discernible way.

Posted 02:25pm by Caspar and filed in Decision Making

All Decisions as Investments

All decisions are investment decisions, when you think about it. We tend to think of investment as being about the allocation of that scarce resource that is money and usually for a period of time but money is just one of many scarce resources that we have at any given moment. Others include time, energy, attention, liberty, health, reputation, credibility and life itself.

Consider first the obvious investment decisions: whether to buy a house, a car, a suit, a meal… The decision in each case is whether to part with a sum on money, in exchange for a large variety of tangible things and emotional feelings in return: some bricks, steel, cloth, steak, a feeling of security, a feeling of status, a faster way of getting from A to B (thus more time), and in all cases a sense of comfort and/or satisfaction. In only one of these cases do we really seek a financial return in exchange for our financial investment and there – as with all of these returns – we know that there are no guarantees.

Less obviously investment decisions are the choices we make about whether to stay in bed or do revision, which route to take to work, or how long to spend training new employees. Once again, though in each case we need to make an investment of a scarce resource, in this case, time and the choice is which of the available opportunities is going to yield us the best return. Bed or revision; leisure or career. This route or that route: the known or the unknown. Training or meeting; long term investment or short term productivity.

At the far end of the scale are the investments that we make without, apparently, “spending” anything at all. How is jumping out of an airplane an “investment”? Or opportunistically stealing a car? Or crossing  the room to chat up a girl? Many people would consider all of these high risk decisions and yet the amount of investment necessary beyond the obvious relatively minimal time involved seems small. How come?

John Smith (I’ve obviously changed his name here) is a successful man. Now retired from the organisation that made him millions, he mentors entrepreneurs of a variety of different ages and stages. His qualification for such a task is as the former CEO of the UK division of an international organisation. Himself a victim of an uncertain future: the advent of Google and Wikipedia left his business virtually worthless at no fault of his own. Fortunately, John saw change coming and made a series of investments one of which was to become a Lloyds name.

“I was attracted to the idea of making money without actually investing anything although I knew my assets were ultimately at risk. I took out some mitigating insurance to protect some but basically it was on the line.” Fortunately, the insurance crises of the 1990s didn’t affect John too much and while he made some losses on the deal the net effect (overall, in The Long Term) was positive.

This form of investment, i.e. putting something at risk without actually handing it over is the kind of investment decision in which we are engaging much of the time. When we jump out of a plane, we accept the possibility of loss of health or life, without ever actually investing it. When we commit a crime we accept the possibility of loss of liberty. When we cross a room to chat up a girl we accept the possibility of loss of status or reputation as we walk back again covered in Martini and shame.

All these possible outcomes are being factored in to our expectation calculations every time we make a decision to do anything. Hundreds, arguably thousands, possibly millions of times a day our minds are executing tiny Expectation calculations: investing time, energy, status, passion, reputation, money, health and wellbeing into opportunities that may or may not yield returns such a happiness, love, more time, more status, spiritual satisfaction, money, safety…. Even when eating food or walking down the street we accept tiny chances of possible downsides but we know we have to embrace them in order to survive. The consequences of staying bed and never consuming anything are much greater.

The concept that people think about potential consequences when they take actions is not universally accepted, by any means. But it is the prevailing view. And the man who first proposed it is a Nobel Laureate. In Tim Harford’s The Logic of Life he relates the story of Gary Becker and his theory of rational crime which first came to him while late for a doctoral examination and started weighing up the pros and cons of parking illegally. Just because an economics professor considered his decisions in such a way, however did not mean that juvenile delinquents did likewise. Becker’s young colleague at Chicago, Steven Levitt, co-author of Freakonomics, did the research comparing different US states with different ages of majority – that is ages to be tried in the court and sentencing levels -  in order to test the hypothesis that juvenile delinquents similarly considered consequences of crime when making their decision to offend.

It showed conclusively that length of sentence – or level of potential investment – had a pronounced effect on a potential offender’s likelihood or propensity to offend. But some are not convinced. In a paper entitled Body Count – Moral Poverty and How to Win America’s War Against Crime and Drugs, authors William J Bennett, John J Dilulio and John P Walters said that 1990s America was in a state of crisis. America was home to an increasing number of violent teenagers who “do not fear the stigma of arrest, the pains of imprisonment or the pangs of conscience. They perceive hardly any hardship between doing right (or wrong) now and being rewarded (or punished) for it later”. Indeed Levitt himself argued that while tougher sentencing worked up to a point, past that point America was just building jails with no discernible effect on the crime rate.

The question posed is twofold: firstly, are criminals rational or irrational when it comes to making their decisions about offending, or indeed anything they do, and secondly (in either event) if tougher sentences have ceased to have any effect, how do you effectively motivate someone to commit less crime? You change their intuitive probability calculation, that is the likelihood that they ascribe to getting caught.

Lying next to my computer as I write this is a disc which was posted to me with an accompanying letter addressed to Mr Caspa (sic). Apparently, if I insert it into my disc drive I will receive £1,500 to spend in the Golden Lion Casino!!! Isn’t that incredible??? What’s more incredible is the fact that I have no intention of ever taking it out of its case!!! Why? Because as lucrative as that potential upside is, my onboard probability machine tells me that is highly unlikely that I am ever actually going to receive it. The fact that there is a potential downside which involves the potential investment of my time and sanity is almost incidental. I just don’t believe that I will accrue the upside and therefore I simply decide not to it.

These “too good to be true” offers are everywhere in our lives from posters on lamp-posts enticing us to “earn £200 an hour in our spare time” to self help books which people dismiss on the grounds that “if it was that easy to have the life of my dreams then everyone’d be doing it…”

The fact is that we may well be wrong. It doesn’t matter. The probabilities that we ascribe to possible outcomes are critical in determining whether we choose to invest actual (or potential) time, money or status into an opportunity that promises their delivery or not. We’re always doing little calculations… but some of their impacts are huge.

The Impact of that Low Frequency High Impact Risk

I’m often fascinated by the fact that people perceive poker players as gamblers but people making business decisions outside a casino as sane, calculated risk-takers. If only that were true! Negative expectation bets are placed around the boardroom table just as often as the poker table. It’s just that every time a company goes pop, it’s considered to be an exceptional event that cannot possibly repeat itself in that form.

Consider for a moment a hypothetical game of roulette in which every number across the table appears to be offering a 20% return. Put your money on black and red comes up… you get 20% back. Put your money on 12 and 33 comes up… you get 20% return. Feels good, but there’s a catch.

In this apparently profitable game, if the 00 hits two spins in a row, you will be liable for 1000 times whatever you have on the table on that spin! Be clear about this… if you have $50, you will owe $50,000! OK, you reason but the chances of 00 hitting twice in a row are incredibly slim. 2.7% x 2.7% to be precise or 0.072%, roughly 7 in 10,000 spins. At 30 spins an hour, you could happily play all month without reasonably expecting it to happen! But what is your Long Term Expectation now?

Well for every dollar you invest in this situation now:

99.93% of the time you’re going to win $0.20 – that’s an upside Expectation of $0.199

0.07% of the time you’re going to lose $1000 – that’s a downside Expectation of – $0.70

Thus, giving you an overall expectation of $0.199 – $0.70 which equals – $0.5001. We’re losing nearly half a dollar for every dollar we invest.

Traditional risk management is about the need to prepare for this highly unexpected event. When United 93 went down in Pennsylvania, the impact extended well beyond the grief of the families of the brave deceased. It hit United Airlines too in ways that it could never have imagined. In 1992 one of the most profitable companies in the world posted the biggest corporate loss in history. The world had changed and IBM had failed to change around it. In 2008 Lehman brothers, RBS, Merril Lynch and some of the biggest financial institutions hit the wall and others, even Citigroup, came to their knees.

When Black Swans happen, their impacts can be devastating. They come from left field – from off the charts – and wipe out years of growth and achievement. The most important question, when they happen, is not could someone have prevented the risks. Naturally someone could have. Everyone can prevent something but no one can prevent everything. The real question is whether or not the risk that the organisation was taking on was priced correctly. In other words, was the company playing poker with a positive Long Term Expectation despite Short Term Losses? Or roulette, with some profitable Short Term wins but a negative Long Term prognosis?

In 1998 when the US banking sector started extending mortgages to the sub-prime sector part of the reason was definitely an imperative for profit. The oft untold side of this story, however, is that the other reason was a mandate from the Clinton administration to start making loans available to the underclass of American society. This socially well-meaning policy came with political strings attached, however. It just simply would not have looked good to charge one rate of interest to the predominantly white middle class and another – significantly higher one – to the predominantly black working class. And anyway, the economy, and house prices, were strong… So a compromise was reached. The rate of interest was perhaps not as high as it should have been, but for a long time, no one seemed to mind.

Whether or not the rate charged was correct given everything we knew at the time, the fact remains: In the same way that the world’s best skydiver could die tomorrow due to uncertainty, so can the world’s best run companies go under. In Why Most Things Fail Paul Ormerod observes that of the 100 biggest companies in the US in 1905 only 36 of them still exist today! How many of our 100 biggest companies will be with us in the next century, or the next decade… or next year?

Posted 02:14pm by Caspar and filed in Decision Making, Risk

The Buffet of Life

Warren Buffet, the world’s richest man has two rules of investment. 1) Don’t lose money. 2) Don’t forget rule 1). It’s a neat aphorism but it doesn’t exactly describe the practice. While not losing money is important because – as he says – a 50% loss requires the correction of a 100% profit, he has another, much more important maxim which is the secret to his success as an investor: “I buy a stock which I would be happy to earn even if the stock market were to close for 10 years”. What he means by that is that, within reason, whatever the value of the stock in the short term (and of course they go down as well as up) he’s happy to trust the phenomenal amount of work he’s done before buying the stock and place his faith in its Long Term prospects. Short term losses are a possibility in the quest for long term gain.

Argos prints 2 million brochures ever year. Of these it estimates that 88% are either thrown away or not directly responsible for a single sale. Naturally it wants this number to be as low as possible. But since the remaining 12% generate revenues in excess of £3bn a year – paying for the additional catalogues with much to spare – the short term losses are soon forgotten.

The life of a door-to-door salesman is not a happy one. Whatever the weather they are outside in the neighbourhood trying to sell whatever they have to whomever will be good enough to chat to them. A good door to door salesman works on a hit rate of about 5-8% success for every door he knocks on. Short term failure, long term success.

One organization, The Amway Corporation sought to increase that figure and came up with the idea for a “BUG” – a pack of free samples which it leaves with the customer for 24, 48 or 72 hours. During this time, the customer uses some of the products, with no obligation, and at the end of the period has a 15% chance of becoming a closed sale, a threefold increase on their natural propensity to buy. In just a few years, the Amway corporation has gone from a basement operation to a $1.5bn company. By increasing it’s short term losses, it increased its long term results.

Warren Buffet understands – like Argos and Amway – does everything he can to make sure he is as successful as possible, that’s why the first rule is Don’t lose money. But just like Argos and Amway,  Buffet knows that the ONLY way he’ll annualize 23% a year is by accepting short term setbacks and devaluations in his stock prices along the way. He doesn’t panic. He knows he’s in it for the long term, in his case 10 years. Not all of us have that luxury.

The decision making process – calculating risk

I’m often minded to think back to the “financial crisis” and the causes and fall out therein. As an exercise in uncertainty, you don’t have to go much further than the life of Sir Fred Goodwin. Once revered as the banker who led Royal Bank of Scotland from relatively small provincial institution to the fifth largest bank on the face of the planet. Now reviled as the man who bankrupted it in the process of doing so.

Getting to grips with the fundamental aspects of risk what we now have to understand is that that even if Fred Goodwin were the most competent and brilliant banker on the planet… the law of uncertainty says that there is still a probability that what happened would have happened. It has before and it will again. That’s not to say that Goodwin did all he could to prevent it. But it is to say that no-one could have done everything. For in any system there will always be things we cannot control: “A man does all he can and his destiny will reveal itself.”

The most important question as viewed through this lens is, therefore, did they do all they could? Were the models used by financial institutions accurate? Benoit Mandelbroit has been warning for a long time that they aren’t. According to conventional wisdom taught around the world, he says the chances of the fall in stocks on August 31st 1998 at 1 in 20 million; the odds of the Dow’s fall by 7.7% the previous day 1 in 50 billion and the odds of black Monday 1997 1 in 10 to the power 50, “odds so small” he says “they have no meaning”.

Nothing is certain. Everything has just a probability. The important thing, where the world’s finances are concerned, is to estimate the probabilities effectively. If bankers think the chances of meltdown are less likely than they actually are then obviously they’re going to take more risks than if they estimate them accurately. Likewise in life, if we don’t know the probabilities of outcomes associated with what we do then we’re going to make similar uneducated, potentially poor, decisions.

Ultimately, whenever we do anything our minds consider future possibilities much like an actuary calculating the value of an insurance policy. At a subconscious level we understand and accept uncertainty and do a multitude of tiny little calculations that will ultimately decide what we do. Specifically, we are always multiplying probability by outcome or impact of an possible event: we know the probability of our plane crashing is very low, but we feel that the actual impact of such an event would be huge combining as it does not only the chance of dying in a fireball but also falling 30,000 ft beforehand! Probability times potential outcome here (to give a result that will of course differ for each of us) usually creates a number high enough to cause concern but not enough to stop us making the decision to “take the risk.”

Asking someone on a date is a very different kind of risk. On this occasion, the overall potential impact of the downside is indignity or shame of possible rejection. Not as great, perhaps, as dying in a fireball. But the probability of experiencing it is higher, hence the fear that many of us have of it and why many are less inclined to do it than get into an airplane – or even jump out of one.

The exact probability we’d put on being rejected is going to differ from person to person and situation to situation. In order to make this decision, then, we need not only to make some kind of assessment of the chances of a negative response but also how significant the pain of this possible rejection might be – something that will depend on a large number of private, personal, considerations, not least whether we’ve experienced it before.

But there’s another consideration we take into account in order to make this and every other decision that we ever make: for pain and hurt are not the only possible outcomes of this action. There’s also the potential reward of success – and of course the probability of experiencing it.

And by putting these two probabilities and outcomes together – success and failure – we come up with an expectation which ultimately will define what we decide to do. Whether or not our decision turns out for the best or course is a very different matter!