Jeffrey Robinson, AQI
It is fairly well accepted that ‘risk’ and ‘uncertainty’ impact decision making activities and make them more complex and difficult. Unfortunately, it is not always clear, from the way we use these terms, how risk and uncertainty influence how we should act when complex decisions are being considered. Part of the problem is that there are several different terms used to refer to these complicating factors. The words ‘risk’, ‘impact’ and ‘cost’ are used almost interchangeably… as are ‘probability’, ‘frequency’, ‘likelihood’, ‘certainty’, or ‘uncertainty’. To a great degree, when any of these factors are present we tend to analyze problems more carefully in order to make the best choices and to avoid potentially undesirable outcomes. There are many different analytical techniques that can used to break down details of a problem, explore the underlying factors to project likely outcomes and prioritize possible choices and courses of action. These include Failure Mode Effects Analysis, regression analysis, correlation analysis, root cause analysis, Ishikawa diagrams, Cause-Effect matrices, and a myriad of quantitative risk analysis techniques. However, this general tendency to analyze things when risk is perceived can be detrimental and can lead to a phenomenon known as the “paralysis of analysis” in which far more time is spent perusing and processing data than is necessary or appropriate. To understand how risk or uncertainty affect the decision making process, we must first carefully define these terms and examine the nature of choice and action taking with a more formal approach. This paper presents two important concepts. The first is a rigorous definition of risk and uncertainty. The second is a taxonomy that clearly suggested different modalities of action for the different combinations of these two factors. Hypothetical case studies are provided to illustrate the rationale behind this action model, which clarifies when quantitative analysis ‘is’ and ‘is not’ appropriate. This model can be applied to projects of all types including software development and process improvement projects. If used during project selection and prioritization, it can be effective in avoiding excessive analysis activities and minimize the tendency to overanalyze whenever risk or uncertainty are present in any proportion. Developing a formal methodology for assessing and managing risk is important to optimize utilization of resources and mitigate the effects of potentially undesirable outcomes. Knowing when and how to analyze risk is important, but it is equally important to understand when such analysis is not warranted and would only cause unnecessary cost and delay. Managers and decision makers need to understand that decisive action without excessive risk analysis is still possible when risk and uncertainty occur alone. Only then will they be able to act confidently and appropriately when either or both are present.