By now there are hundreds of examples … in which analytics involving the most traditional of data sources outperform traditional modes of decision-making. …
Each case … involves “sorting” or “prioritization” decisions that (a) are central to an organization’s operations; (b) are made repeatedly, typically by experts relying on professional judgment in varying degrees; and (c) incorporate quantifiable information that is readily available, yet commonly used only in informal or limited ways.
And furthermore, it turns out that in each case a fairly simply predictive scoring equation can be counted on to outperform unaided professional judgment.
The finding in fact dates back to the 1954 publication of the psychologist Paul Meehl’s book Clinical Versus Statistical Prediction. Meehl’s “disturbing little book,” as he later called it, documented 20 studies comparing the predictions of human experts with those of simple models. The types of predictions ranged from how well schizophrenic patients would respond to electroshock to how well prisoners would respond to parole. Meehl concluded that in none of the 20 cases could human experts outperform the models.
Author: Jim Guszcza
Source: Deloitte Review
Subjects: Decision Making, Organizational Behavior, Trends / Analysis
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