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Making good decisions about risk
December 30, 2014
A popular habit at New Year’s is to make resolutions for the coming year. It’s not a bad idea, but many people, including me, have a hard time following through on a list of stuff to either stop or start doing. For example: quit unhealthy habits, get in better shape, read more books, etc. So I resolved to stop making resolutions for New Year’s. Instead, I’ve adopted a philosophy of trying to make better decisions.
Let me note straight away that I don’t always make better decisions. But I’ve tried to do things differently, learn as much as I can to make an informed decision, and then make the best choice I can. Decision-making is the real key in executing any plan, and it’s essential in the context of risk management. Deciding whether and when to take a certain action – or deliberately to avoid an action – can mean the difference between spectacular success and epic failure.
In between those extremes, however, is a range of significant outcomes. Good decision-making can provide opportunities for greater success. Poor decision-making can limit one’s options or make recovery more challenging, and it can have a big impact on your colleagues and others.
Why do people make poor decisions when it comes to risk? Sometimes it’s because we have a tendency to be overly optimistic. We subconsciously minimize things that are unpleasant to confront. “It’ll be OK,” “We’ll be good” and other rationalizations can fool us into thinking that if we say it enough, those thoughts will hold true. At other times, people make poor decisions because we’re in a rush or elect not to analyze available data. In between unbridled optimism and pure analytics is a healthy balance that can help us make better decisions.
This conclusion is supported by neuroscience, a branch of science that explores decision-making. Every decision we make occurs in our brains, which process, analyze and organize responses to all the information we take in. Daeyeol Lee, a professor of neurobiology and psychology at Yale University, who also directs Yale’s laboratory of cognition and decision making, suggests that poor decisions often result from impulsivity – not taking the time to analyze relevant data – as well as a focus on the short term.
Professor Lee makes a very good point. Taking a longer-term view, or at least recalling long-term goals, can help improve certain decisions. Avoiding impulse is also wise. I believe that to make better decisions, you have to understand what your choices are. The more you know about the options, the better informed your decisions can be.
Know your options and choose
Decision support tools are widely available today to people whose job is to mitigate and manage risk, and that’s one of the advantages of living in the era of Big Data. It’s possible to gather an enormous amount of information on a lot of things, but eventually, a decision must be made.
“Paralysis by analysis” sometimes afflicts organizations, and that’s a sinister condition because it can lead to inaction. A decision deferred is really a decision not to act. When facing risks, inaction often is an unwise decision.
Take, for example, a risk manager whose organization is accumulating a high rate of slip-and-fall claims. Disagreement about how best to mitigate this liability could lead the organization to delay implementing effective safety measures or change behaviors. That could be costly.
Once a risk emerges, risk professionals should gather as much as data as they can to understand it and the root causes of the exposure. That analysis should lead to identifying specific actions to remedy the problem. The organization needs knowledge but it also must decide to do something. Just as often, investments are necessary to support decisions on risk. Those investments might include purchasing additional insurance limits or new coverages altogether, retaining more risk intentionally and self-insuring a portion of the exposure, or increasing the risk management budget for operational changes and behavioral incentives.
We need to be able to trust the data we analyze to make decisions. If we can’t trust the data, well, that’s a different problem that needs fixing.
Kim Holmes, senior vice president of strategic analytics at XL Group, observes that analytical models will be wrong some of the time “because no model is perfect. We just want it to be less wrong than what we used before. Our goal is to have incremental improvement, not perfection.”
Incremental improvement each year is a great aspiration for people, too. Here’s to making better decisions.
About the AuthorRegis Coccia is an insurance journalist and content strategist. His columns on insurance and risk topics appear periodically on Fast Fast Forward.
The views expressed in this column are the opinions of the author and do not necessarily reflect the opinions of XL Group.