Cover feature - Gambling on business

It is possible to calculate gambling risk with a surprising degree of accuracy and success, so what lessons are there for those facing business risk?

Alex Blyth.

Between 1979 and the early 2000s a group of students and graduates from the Massachusetts Institute of Technology won - quite legitimately - hundreds of thousands of dollars playing blackjack in Las Vegas casinos. The group, known as the Amphibians, had worked out how to calculate the risks involved in the game, and how to win at it, and, until they were discovered and banned by casinos, they were phenomenally successful.

The story is currently being told in cinemas around the country in 21, a film starring Kevin Spacey. It is also making some observers think about what lessons the story provides for the business world. After all, if it is possible to calculate gambling risk with this degree of accuracy and success, is it not possible to do the same for business risk?

Playing the casino

Yuchun Lee is now the chief executive of Unica, a Massachusetts-based software company, which he founded in 1992. Today the 42-year-old employs 500 staff and manages a firm with annual revenues of $100m (£51m). However, just a decade ago he was a key member of the Amphibians.

He explains how they did it: 'In every game, apart from blackjack, the casino has an advantage over the player. In blackjack each individual hand is dependent upon those that have gone before. So, if you are able to count the cards that have already been dealt, you know the odds of certain cards coming out and, over time, you can ensure that you are placing large stakes at the right time and so winning.'

Wayne Lochner, CEO of dealing service Betbrokers, agrees that with certain games it is possible to calculate risk. He says: 'There are many financial models that predict or manage risk in casino environments and in sports wagering. It is all about how much data you can collect, its accuracy and the variables. The models are the same as financial trading. Pension funds gamble or trade in the equity markets with the same appetite to risk that a professional trader or gambler would approach a sports event.'

Making it work for business

However, with business it is not as simple as counting cards. Dr Morten Lau is senior lecturer in economics at Durham Business School. He is conducting research on strategies in the television show Deal or No Deal, and he comments: 'In blackjack you have six or eight packs of 52 cards to consider, and the dealer has to follow certain rules. In business there are many more variables to consider and the rules of engagement are much less clear-cut. This is not to say that you cannot calculate risk in business, just as those students did with blackjack. It just means that business is vastly more complicated, and so you need to invest more in working out your gameplan.'

Ryan Kneale, market analyst at dealing service, agrees. 'At we take bets on share prices and other financial markets,' he explains. 'This means that we have to know, at all times and for every market on which we take bets, what will happen to our profit and loss if each market goes up, down, or stays flat over different time periods. We often draw parallels between this work we do delivering our business, and the work we do managing our business.'

He continues: 'For example, if a member of staff quits, we can see the effect that it will have on the workload of other staff, but it is harder to estimate the overall effect on the company. Random factors come into play, most of which relate to human sentiment both inside the company and among suppliers, clients and so on. Larger companies, with a large number of human and capital components, could well model operational risks using similar methods to those of bookmakers.'

Modelling for larger corporates

Some of those larger corporates are now doing almost exactly that. For the past seven or eight years, the leading Formula One teams have used modelling software to assess how their decisions will play out in individual races. In 2006, Smith Bayes, a software company, spun out of the McLaren team, and now sells this modelling software to Fortune 500 companies.

Simon Williams, CEO, says: 'We're currently working with a large European telecommunications company, helping it assess the risk of bundling its services together. We're also working with a leading FMCG company on how it should deploy its advertising budget. These models have been proven to work in Formula One, and they're now proving equally useful in the business world.'

Many companies already do this modelling using simple spreadsheets, and might baulk at the £100,000 annual cost of the Smith Bayes software, but Williams claims his software represents a significant advance.

'The crucial factor is agility,' he argues. 'McLaren's race plan would last three seconds - from green light to the first corner. Then they would need a new plan, which took into account what had happened. In business it is equally critical to build a rapid and accurate strategy/feedback loop, and that's why this is such a powerful planning tool.'

Learning from gambling

There is, of course, a limit to how much a business can predict risk. Scholar and sometime mathematical financier Nassim Nicholas Taleb has described certain significant but hard-to-predict events as 'black swan' events, and he posited the twin towers attack of 11 September 2001 as an example. While businesses can to some extent model future events and manage risk, they can never do so entirely.

Despite this, Yuchun Lee has no regrets about abandoning the casino high life to set up Unica, a company that helps businesses identify future customers. He believes that what he learned in his time as a member of the Amphibians stood him in good stead for running a business.

He concludes: 'My time in the casino taught me two things. Firstly, ensure you're playing a game where you have an edge. Gambling where the odds are stacked against you is a bad idea, so pick the right business to be in. Secondly, be in it for the long-term. In the short-term a bad player can win and a good player can lose, but over time the good player will do better. So, in business, if you're certain you have an edge in your market, don't get put off by a downturn. Hold your nerve and stay in it for the long-term.'

Risk no more, p114


Here are Accountancy's top five biggest business gamblers of all time. For some it worked out. For others it didn't.

1) Kerry Packer

Australian media tycoon Kerry Packer will always be most famous for one story. One evening in a casino, Packer turned to a stranger to ask why the other man was getting such attention from the staff. The Texan replied that he was in the oil business and worth $100m. Packer's legendary reply was: 'Toss yer for it.' The oil man walked away.

2) George Soros

By the early 1980s, Hungarian-born George Soros had a personal fortune of £16.5m, and was eyeing what he felt was an over-valued pound. He borrowed £6.5bn of sterling and converted it into a mixture of French francs and Deutschmarks. On Black Wednesday, 16 September 1992, Soros' bet paid off. He made £1bn and became famous as the man who broke the Bank of England.

3) Nick Leeson

Nick Leeson once made almost $30m (£15m) in a single year for Barings Bank in Singapore. However, this success went to his head and by 1995 he was covering up enormous losses. In a last-ditch attempt to save himself he made a massive bet on the Japanese stock market, which went badly wrong when a huge earthquake in Kobe sent the Nikkei index plummeting. Leeson ended up with a six-and-a-half-year jail sentence, and Barings Bank went bust.

4) Thomas Watson Jr

In 1964, IBM produced roughly 70% of all computers made. Its market dominance seemed unassailable. Then on 7 April that year Thomas Watson Jr gambled the company's future on the IBM System/360, a new type of computer that many people thought would be entirely unnecessary. The System/360 still survives today as the IBM mainframe, and has for the past 40 years provided the basis of that multinational's enduring success.

5) Sir Clive Sinclair

For so long everything went right for entrepreneur Sir Clive Sinclair. He made a small fortune from the first pocket calculator, the first pocket television and the ZX Spectrum, the best-selling computer of its time. However, in 1985 he gambled on the C5, the world's first commercial electric car. Built by Hoover, with a top speed of only 15mph and a range of just 10 miles, even a sale price of £399 wasn't enough to make it popular, and Sinclair ended up losing £7m and having to sell his company.

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