IIM Indore Study Finds ‘Good Enough’ Decisions Can Reduce Uncertainty In Short-Term Projects
Indore (Madhya Pradesh): In a finding that could reshape how managers make decisions in uncertain and rapidly changing business environments, a new study by Indian Institute of Management Indore has found that choosing a “good enough” solution rather than constantly pursuing the optimal one can substantially reduce uncertainty, particularly in shorter-duration projects. The study, conducted by…
An Indian Institute of Management (IIM) Indore study suggests that choosing a "good enough" solution instead of constantly pursuing the optimal one can significantly reduce uncertainty, particularly in shorter-duration projects. The research, led by Prof Sasanka Sekhar Chanda and published in the Computational and Mathematical Organization Theory, builds upon Duncan’s theory of organisational uncertainty, which previously focused on task complexity and environmental turbulence.
Chanda's study expands on this by examining the manager's decision-making approach as well. Using a simulation model, the researchers represented organisations as groups of decision-makers facing varying environmental conditions. The findings support Duncan’s central proposition that uncertainty rises with task complexity and environmental turbulence, but reveal that a satisficing approach—accepting a solution that meets an adequate threshold—can substantially reduce uncertainty in shorter-duration projects, with only a slight trade-off in the probability of organisational success.
This research implies that organisations should reevaluate how managerial performance is assessed, considering the level of uncertainty they had to overcome to achieve outcomes, rather than solely focusing on results. The study also highlights the potential benefits of encouraging a satisficing approach to reduce cognitive load and burnout, promote resilience, and shift managerial focus from perfection to learning and adaptation.
Written by urgent.news from Free Press Journal's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
