The correlation between long-term productivity and short-term performance ratings of harvester operators

Human operators are key determinants of the performance of most production systems, so individual performance is of intrinsic interest when evaluating current and proposed systems for forest operations. Such evaluations can be useful for diverse purposes, for instance, planning, incentive-setting, control and costing. Hence, various evaluation methods have been developed, all with pros and cons. Here, we compare subjective, short-term ratings of the work-related behavior of 12 harvester operators and their long-term output (harvested volume per unit time), based on observation periods of a few hours and data gathered over two months, respectively. It was found that competent raters can filter the many, interacting behavioral components and translate short-term observations into grades that reflect the operator’s long-term output well (Spearman’s r(s) > 0.9). Moreover, substantial variations in performance values obtained by both methods were found, probably at least partly attributable to variations in individual performance of both the operators and the raters. We argue that both of the studied methods could be used to adjust population norms (e.g. productivity functions) to the individual’s performance, with sufficient accuracy for normal production purposes (e.g. planning). However, in a scientific context it could be questioned whether the expected uncontrolled variation in operators’ performance is most efficiently minimized by the introduction of uncontrolled variation in rater’s behavior and/or historical data, or if other precautions could be taken to improve the reliability of the data.