Managerial control systems based on learning curve models

Abstract

SUMMARY Human operator output in the performance of repetitive tasks increases with practice, resulting in the ‘ learning curve ’ graph well known in industrial engineering circles. This paper describes the construction of a systems model of the learning curve, the model parameters such as the learning time constant being readily estimated graphically from historical data or in advance of the event using a digital computer algorithm. Learning curve models for individual operators, and for groups of operators, are then used as basic elements in a managerial control system, the inputs to this system being operator effort, industrial engineering effort, and material and financial resources, whilst the output will be completed tasks. The managerial control system is designed to increase productivity by considering four separate feedback loops incorporating the monitoring of individual performance, monitoring of training schemes, updating of time standards, and identification of worker spare capacity leading to group incentive and bettor performance. Each loop is illustrated by an example taken from industry, with associated cost benefits estimated directly from the learning curve models.

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