Quantifying Nescience: A Decision Aid for Practicing Managers

Abstract

Aristotle's dictum scio nescio (I know that I don't know) may serve as a source of enhanced performance for organizations. Awareness of nescience sets the direction for further inquiry, as managers tend to move in the direction that they believe will reduce nescience most. However, nescience is difficult to quantify, so, to date, managers have primarily relied on intuition. Observing business analytics practices in three industries-semiconductor manufacturing, medical diagnostics and social media analytics-suggests that nescience can be measured using metrics from information theory. In semiconductor manufacturing, strategies for problem solving can be explained in terms of Shannon's entropy formula, which indicates the most effective pathway for reducing nescience and identifying the practice with the highest benefit/cost ratio. In medical diagnostics, variants of this formula can be used to reduce nescience to improve the quality of diagnosis. Social media analytics firms reduce nescience to identify loci of influence in online social networks. Nescience is measured by centrality and centralization metrics from information theory. In the aggregate, these observations suggest that metrics for nescience that are based on information theory may serve as a decision aid for practicing managers.