Organizations often rely on the professional judgment of many employees with similar titles and job responsibilities.
Consistency is an important feature of such decision-making: no organization would want a case to be treated differently depending on the employee it was assigned to or the mood the employee was in when she received the case. However, individual biases and random factors often impede consistent judgment and result in suboptimal conclusions.
A process that produces judgments or decisions is noisy when its outcomes are susceptible to the effects of irrelevant factors. Noise is invariably costly and is a major issue wherever human judgment is involved: in interviews with job candidates, in economic and political predictions, or in loan underwriting decisions, for example. Evidence suggests organizations that depend on the judgments of individual employees typically do not appreciate the severity or economic consequences of noisy processes.
At TGG, we have expertise and experience in improving the reliability of judgments and decisions in an organization. Our principals first identify the problems caused by biases and noise in decision-making and then design transformative ways to mitigate these problems through proprietary tools and processes.
Could you reduce employee error through science-driven decision aids?
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