Using worker personality and demographic information to improve system performance prediction

Abstract

This paper presents an approach to modeling workers where human performance has a significant impact on system productivity. Highly technical industries such as semiconductor manufacturing and service industries like banking are relying on fewer but more skilled workers. In these systems, productivity depends on worker availability and organization; therefore, modeling system performance may require accurate representations of individual worker behavior. This paper examines the tradeoffs in including information about the demographics and personalities of workers in system performance simulation models. A series of actual and simulated experiments in which personality and demographic data are used in different ways to model the performance of a team of workers is reported. Significant differences are found in predicted system performance demonstrating that model validity depends on the methodology used for modeling workers. These results have practical implication for the managerial processes of recruiting and selecting individual workers, as well as organizing teams of workers and assigning them to tasks.

Behavior in operations management: Assessing recent findings and revisiting old assumptions

“…Models have been developed in the areas of job design (e.g., Wong and Campion, 1991) and socio-technical systems (e.g., Bendoly et al, in press;Huber and Brown, 1991) that specifically address the human factors of work systems, and how variation in performance interacts with the task itself. However, except for the recognition that individual differences are a major cause of work-rate variability (Dudley, 1968;Knott and Sury, 1987;Salvendy and Stewart, 1975;Juran and Schruben, 2004), little has traditionally been done to incorporate individual differences into OM research. This has changed recently with the work of Bartholdi and Eisenstein (2005), , and Zavadlav et al (1996).…”

“…Johnson et al (2002) find that the intentions relative to award allocation in a manufacturing setting are partially based on reputation and attribution of motive. Juran and Schruben (2004) show that variability of human reactions should be considered when modeling production systems.…”

Improvement of the planning reliability by the integration of human skills in project risk management

“…The latter is generally studied with a focus on the allocation based on technical skills of the personnel considered. Indeed, it is proved that the efficiency of a system is closely linked to the allocation of personnel according to their skills [13]. A similar problem that is as well considered in the literature is the team building considering personnel skills.…”

Nine Doctrines of Service Productivity

“…According to the principle of this doctrine, it is proper to define service productivity by a set of results or output of the service received by customers (Alcantara, 1987;Green, 2003Green, , 2005Juran and Schruben, 2004). Customers' participation in the service process is one of the characteristics which distinguish service industry from manufacturing industry.…”