As part of the process there is another, more insidious issue that is inherent in decision-making: bias.
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and weighed as part of the process; for a superintendent, it is common to have to make a decision that balances risks to the agronomic, fnancial and aesthetic needs of the golf course. As part of the process there is another, more insidious issue that is inherent in decision-making: bias. Everybody has biases but they are not all the same. Biases are created through life experience, failures, successes, fears and assumptions, and they impact how information is processed and how risk is evaluated. For a manager who must make decisions that can dramatically affect multiple aspects of a business, like a golf course operation, being aware of decision-making bias and working to minimize the impact can be worthwhile. Back to basics The study of bias originated in neoclassical economic theory. Economics seeks to predict the behavior of markets based on the actions of individual investors. Problems would arise when economic models would expect individual investors to act rationally all the time, making the prediction of the markets, and therefore economic performance, possible (assuming the protection of the rule of law and equal access to information and opportunity). The reality was that individuals did not always act rationally (in fact, they rarely do), and therefore economic prediction was diffcult. The culprit was the “heuristic biases” held by the individual decision-makers — fawed methods of thinking or learning that are inherent in all people become internalized and impact thinking and decision-making without notice by the individual (from Niall Ferguson’s “The Ascent of Money,” 2008,
Penguin Books). • Availability bias: decisions are made based on the information that is known as opposed to the information that is required. • Hindsight bias: an assumption is made that there is a greater probability of an event reoccurring, particularly if there were negative consequences. Decisions are made to protect against the likelihood of the reoccurrence even though the actual likelihood of the reoccurrence is very low. • Induction bias: broad rules are applied to decisions or data that are not relevant to the data or the decision being made. • Disjunction bias: overestimating the probability that multiple, high-probability events will all happen while underestimating the probability that one, low-probability event will happen. • Confrmation bias: accepting data that confrms a previously held hypothesis while rejecting any data that would contradict it. • Affect bias: making decisions based on preconceived value judgments that interfere with the assessment of data and the probable outcomes of the decision. • Scope bias: an abnormally high value is assigned to a cost of a decision because the decision-maker is unwilling to sacrifce an asset. This frequently arises around discussions concerning tree removal. • Calibration bias: an assumption is made that the “best case” scenario is the most probable outcome. • Apathy bias: abdicating the individual responsibility of a decision to conform to the actions of a group so as not to be an outlier if the result of a particular decision is negative. For instance, choosing to remove snow from greens because nearby golf courses are also doing so. Managing biases An experienced superintendent has likely experienced all of these biases at some point while making decisions. That is because these biases are inherent to every decision-maker and to every decision-making process. These biases can apply to the process itself, the raw data being used, to the sources of that information or the evaluation of the risks/benefts. Therefore, they can be diffcult to identify and virtually impossible to eliminate. The desired goal is to be aware of these biases and to manage them, either through the process or through the individual, to mitigate