Good decision-making is impaired by two things: limited information, and by the decision-maker being too narrowly focused – especially when events or conditions are abnormal, or outside the decision-maker’s experience.
This is confirmed by a study published in April 2012 by Miguel Lobo of INSEAD Abu Dhabi and Dai Yao of INSEAD Singapore (“Human Judgement is Heavy Tailed: Empirical Evidence and Implications for the Aggregation of Estimates and Forecasts”). The study not only confirms the importance of information flow and good decision-making, but broadens the topic and also adds a useful method for making decisions based on conflicting forecasts (covered in next post).
The study crunched numbers from 20,000 estimates and forecasts from 17 databases from two focus groups – a panel of MBA graduates and the forecasts of 50 economists. It was focused on events at the extreme ends of the bell-curve of probability – their likelihood, and the accuracy in forecasting them.
It determined that extreme events (the “one in a thousand” outcomes) don’t fit into the predicted smooth bell-curve, but are more common and have a bigger impact than expected. That’s reasonable – they’re more common than expected because the world keeps changing faster than it used to. And they have a bigger impact than expected because, although we have a handle on things when they are going as normal, we’re likely to be way off in our understanding and responses when the abnormal occurs. (That shows the value of experience… and provides a natural plug for experiential learning!)
Surprisingly, the survey found that within any given field, subject-matter experts were just as likely as non-specialists to grossly misestimate data and forecasts. In fact everyone tended to underestimate the chance of extremely unlikely events (deemed to be in the order of likelihood of 1/1,000) by a factor of 10. The immediate result is that contingency plans for catastrophes are given a much lower importance than they should have. (Think Hurricane Katrina.)
The study identifies the problems stemming from three related areas:
- Overconfidence in one’s own knowledge and judgment;
- Reliance on the knowledge and judgment of a single other individual, rather than a group;
- Failure to source as wide a range of data and opinions as possible.
Now we are back to the value of rapid and accurate data, of knowing where to get it from, and of being supported actively and proactively by the various people who see different things. It is important to widen your sources of information, of forecasts, and of opinions, and it is better to have too much information than too little. But with the potential for information overload you need to have your own understanding of where information comes from, and a confidence that the person providing the information is business literate (so that their numbers are believable, and they are using business terms and ratios the same way that you would use them).
And I would add a fourth cause of poor decision-making:
- Lack of experience.
Many people rise to senior positions through their career-long expertise in R&D, or Sales, or Engineering. Then they suddenly find themselves managing multimillion dollar budgets without having acquired a background in business finance.
Fortunately people in a position like this can take the business expertise they have and, by participating in a facilitator-led business simulation for two or three days, can extend their understanding to gain a solid working use of business finance, from financial statements to ratios, from KPIs to pricing and costing.
This is what Andromeda Training offers: the experience of running all aspects of a business, in order to fill in the gaps of understanding and to allow decision-makers to widen their sources of information and opinions, and make decisions that are best for the long-term health of the company.
so all those times when I say ‘1/100 chance of yada’ and my business partner thinks I am being overly dramatic (because it is probably only 1/1000)… I am actually being accurate? Definitely good to know!