A but these heuristics can bring powerful biases.

A structured and successful project demands good
decision making. It is important for project managers to know how heuristics
and biases can influence their decisions, leadership and guidance. Heuristic
approach for decision making uses a method that comes from past experience but
not intended to reliable for all the scenarios. As discussed in the featured
paper – “Heuristics and Biases in Project Management- Vol. VII, Issue I –
January 2018” Often we apply a rule of thumb to make judgments and form
decisions ignoring other important parts of information and analysis. We might
look to these heuristics as normal, but these heuristics can bring powerful biases.
Heuristics and its associated biases can give rise to an unseen negative impact
on the effective management and execution of a project. Tversky and Kahneman (1974) in their article have focused how
heuristics have affected human decision-making.

 

While planning the project activities, project
managers often make decision by applying rules of thumb or heuristics.  Managers using heuristic approach for making
decisions are ubiquitous because the ability to perform the rational analysis
is limiting due to limited time, limited information and cognitive limitations
(Trumper and Virine, 2018).

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  The choice for relying upon our intuitions or
past experiences deviate the decision from reality and statistical analysis. But,
it is important to minimize the impact of these heuristic. To mitigate the
effects of heuristic it is important to challenge not only our decision making
process but also underlying assumptions. By identifying and acknowledging the
presence of the rule of thumb and their possible biases and then, applying
tactics appropriately to balance them, leaders can combat their negative
effects.

 

References: Virene L,
Trumper M, Virine E, (2018) Heuristics and Biases in Project Management, PM World
Journal, Lov. VII, Issue I

Tversky, A., & Kahneman, D. (1974). Judgment under
uncertainty: Heuristics and biases. Science, 185(4157),1124–1131.