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Software Project Management under Uncertainties
Software Project Management with Heuristics and Biases
The problem associated with all the aforementioned methodologies lies in the estimation of project input variables: task durations, start and finish times, cost, resources, etc. If input uncertainties are inaccurately estimated, it will lead to inaccurate results regardless of the methodology of project scheduling.
Tversky and Kahneman
[14] have proposed that limitations in human mental processes cause people to employ various simplifying strategies to
ease the burden of mentally processing information to make judgments and decisions. During the planning stage, software project managers rely on heuristics or rules of thumb to make estimations. Under many circumstances heuristics lead to predictably faulty judgments or cognitive biases.
Following are short descriptions of some heuristics that affect the estimation of project variables for software project management.
The availability heuristic
[2,13] is a rule of thumb in which decision makers assess the probability of an event by the ease with which instances or occurrences can be brought to mind. For example, project managers sometimes estimate task duration based on similar tasks that have been previously completed. If they are making their judgment based on their most or least successful tasks, it can cause inaccurate estimation.
The anchoring heuristic [14] refers to the human tendency to remain close to the initial estimate. For example, anchoring will lead to an overestimation of the success rate of the project with multiple phases because the chance of completion of each separate phase of the project can be an anchor in estimating the success rate for the whole project
[9].
Judgments concerning the probability of a scenario are influenced by amount and nature of details in the scenario in a way that is unrelated to the actual likelihood of the scenario
[12]. It is called the representativeness heuristic. This heuristic can lead to the “gambler’s fallacy” or belief that a positive event is overdue because a series of negative or undesirable events have already occurred.
Decision makers can be exposed to many cognitive and motivational factors that can lead to biases in perceptions. This effect is often referred to as selective perception. For example, estimation of a task’s cost can be influenced by the intention to fit the task into the project’s budget. As a result, some of the project parameters can be overestimated.
Plous
[11] has made some general recommendations for mitigating the negative impact of these and other heuristics. It is very important to keep accurate records and make estimations based on reliable historical data. Compound events should be broken into smaller events, which have known probabilities of occurrence. Discussion of best- or worst-case scenarios, for example the estimation of the most optimistic, the most likely, and the most pessimistic durations in PERT, can lead to unintended anchoring effects. To reduce dependence on motivational factors, Plous recommends the analysis of problems without taking expectations into account.
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