Decision-Making Models Whenever a Particular Problem, Situation,

¶ … Decision-Making Models

Whenever a particular problem, situation, or choice is encountered, there are a number of different ways in which individuals and teams can go about trying to find solutions. Sometimes, problems are quite concrete and the required solutions present themselves fairly readily: when one is ungry, the solution is to eat, and if there is some food readily available, the problem is easily solved without a lot of high-order thinking. But what if food is not readily available, and money to purchase food is scarce? Now the problem takes on a greater complexity, and a series of decisions, trade-offs, and actions must be taken in order to solve the problem of hunger without creating other problems in other areas (e.g. problems with the law created by stealing food, not being able to pay rent because of the cost of food, etc.). When problems reach this level of complexity, simple answers no longer exist, and a different approach must be taken in order to develop solutions.

One method that can be very useful is simulating the situation and the outcomes of the situation based on specific decisions and solutions. A very simple example of a simulation technique can be derived from the above hypothetical situation of the hunger problem. First, several different solutions to the hunger problem would have to be imagined: one could steal food, sell their furniture to buy food, attempt to forage for edibles in the wilderness and/or in other people's garbage, or attempt to find short-term employment that pays immediately. There are other solutions as well, but these are enough to start a simple simulation.

The next step in a simulation approach to problem solving is to determine the potential outcomes of each of the proposed solutions. Stealing food is among the fastest and easiest options, but has very high risks of long-term detriments that -- in most situations -- outweigh the short-term benefits of the theft. Selling ones furniture could potentially yield enough money for several days' or even weeks' worth of food, but the eventual costs of replacing the furniture as well as the inconvenience of living without furniture makes this option less desirable. The other solutions also have benefits and drawbacks; a simulation process enables one to view the various benefits and drawbacks and make a determination as to the best choice by viewing all of the potential outcomes. Many problems can be quantified to a greater degree than the hunger problem as defined, and simulations can be conducted from an enhanced mathematical and statistical perspective.