Thinking outside the box needed to seal finance deals
Think Twice: Harnessing the Power of Counterintuition by Michael J Mauboussin; Harvard Business Press; €21
INTELLIGENT PEOPLE often make big mistakes, sometimes with disastrous consequences. In the business world, mergers and acquisitions provide numerous examples of bad decision-making, for instance. Research confirms that in about two-thirds of the cases of mergers in the United States, value was destroyed for the acquirer. The explanation for the continued enthusiasm for acquisitions boils down to one thing: a belief on the part of managers that they can beat the odds.
Over-optimism and the illusion of control are two of the classic mistakes people make in assessing risk, Michael J Mauboussin points out in this insightful book.
A strategist with a US money management firm, he acknowledges that his peers are among the worst offenders. Research shows that in aggregate, money managers who actively build portfolios deliver returns lower than the market indices over time. The reasons? Markets are highly competitive, managers charge fees that diminish returns and markets also have a dose of randomness, ensuring all investors see good and bad returns from time to time. Despite the evidence, active money managers behave as if they can defy the odds and deliver market beating returns.
Instead of taking an inside view, managers need to take an outside view. Four steps are needed to do this, he says. First, they need to select a reference class that is broad enough to be statistically significant. In the case of mergers and acquisitions, the market responds more favourably to cash deals done at small premiums than those financed by debt at large premiums.
Secondly, they need to assess the distribution of outcomes, noting average outcomes, most common outcomes and extremes of success or failure. Thirdly, they need to make predictions and fourthly, they need to assess the reliability of their prediction and fine tune. For some, this is easier than others. Weather forecasters stand a good chance of getting it right most of the time, while book publishers are notoriously poor at picking winners. The worse the record of prediction is, the more you should adjust your prediction towards the mean.
Poor decision-making can also be influenced by incentives – as was clearly the case in the sub-prime fiasco – or by bias. In an experiment, Prof Max Bazerman of Harvard Business School asked a group of over 100 accountants to review five ambiguous accounting scenarios.
Half of the accountants were told they were the firm’s auditor. Those who played the auditor role were 30 per cent more likely to find the accounts compliant with regulations, suggesting that even a hypothetical relationship with the firm shaped judgment.
To avoid mistakes, managers need to examine the full range of alternatives. They should also seek dissenting opinions. While this is emotionally challenging, it prevents “group think”, where colleagues try to reach a consensus and avoid conflict.
Previous decisions and mistakes should be recognised and not reimagined in a better light and we should avoid making decisions while we are highly emotionally charged. Stress, anger, fear, anxiety, greed and euphoria are all poor mental states for quality decision making.
We also need to understand how incentives motivate our decisions. The financial ones are obvious but non-financial ones like reputation and fairness are less easy to spot yet still important in driving our actions.
Putting yourself in the shoes of others is one of the most powerful ways to facilitate better decisions. Rather than simply thinking about the character of others in evaluating the choices they will make, it is important to also consider the situation that they are in. Failure to do this is a common mistake, the author says.
A recurring theme for Mauboussin is how technology can be used to make less subjective and generally more successful decisions.
Snowed under with job applicants, Google dismissed the traditional interview process and instead decided to use algorithms to identify attractive employees.
As Mauboussin notes, technology is assisting more accurate predictions. The biggest obstacle however, is the discomfort most of us have handing over decisions to computers or collectives. While the evidence against experts is damning, human nature remains a high hurdle.