The rational model conjures up an image of the decision maker as a super calculating machine. But we know that managers must make decision within tight time constraints and with less information than they would like to have. Three concepts have emerged over the years to help managers put their decision making in perspective: bounded rationality and satisfying, heuristics and biases. These concepts are neither good nor bad per se. Rather they help us keep in mind that we human beings do have limits as we our minds to confront the world.
Bounded Rationality and Satisficing:
In trying to described the affairs that affect decision making Herbert Simon, among others, has proposed a theory of bounded rationality. This theory points out that decisions makers must cope with inadequate information about the nature of the problem and its possible lack of time or money to compile more complete information an inability to remember large amounts of information and the limits of their own intelligence.
Instead of searching for the perfect or ideal decision, managers frequently settle for one that will adequately serve their purposes. In Simon’s terms, they satisfice, or accept the first satisfactory decision they uncover, rather than maximize, or search until they find the best possible decision. What the effective decision maker learns to do is satisfice with a clear sense of goals for the organization in mind.
Ideas on bounded rationality have demonstrated that people rely on heuristic principles, or rules of thumb, to simplify decision making. Loan officers, for example may screen mortgage applicants by assuming people can afford to spend no more than 35 percent of their income on housing. Three heuristics show up repeatedly in human decision making. These are general cognitive guides people use intuitively.
Availability: People sometimes judge an event’s likelihood by testing it against their memories. In principle it is easier to recall frequently occurring events. Thus, events that are more readily available in memory are assumed to be more likely to occur in the future. This assumption is based on the experience of a lifetime, and it seems reasonable enough. However, human memory is also affected by how recently an event occurred and how vivid the experience was. Thus, a risk manager recently caught in a flood is likely to overestimate the importance and frequency of flooding the next time he or she procures insurances.
Representatives: People also tend to assess the likelihood of an occurrence by trying to match it with a preexisting category. For example, employers may rely on stereotypes of sexual racial or ethnic groups to predict an individual job candidate’s performance. In a similar way product managers may predict the performance of a new product by relating it to other products with proven track records. In fact, however, each individual or product is a new commodity not just the representative of a group and should be judged accordingly.
Anchoring and Adjustment: People do not pull decisions out of thin air. Usually, they start with some initial value, or ‘anchor’ and then make adjustments to that value in order to arrive at a final decision. Salary decisions for example, are routinely calculated by assuming last year’s salary to be an initial value to which an adjustment must be made. Unfortunately depending heavily on the single factor of initial value tends to obscure relevant criteria. In addition, different initial values lead to different decisions.
In extending the Nike product line from shoes to other types of sports equipment, Nike managers reply on a heuristics that athletes will be drawn to the Nike name and logo. They also assume that customers will choose Nike products on the basis of heuristics for reasons of availability representation. Nike sells shoes so they probably know something about socks and shorts and anchoring.