Functional flexibility and team performance

Abstract

This study deals with workforce flexibility defined in terms of 'multifunctionality' and 'redundancy'. These concepts refer, respectively, to the number of different tasks a worker has mastered and the number of workers that are qualified to do a specific task. A third factor to be considered is worker efficiency. These elements of workforce flexibility support a team of workers in dealing with absenteeism and a fluctuating mix in the demand of human resources. The main focus of this study is on the impact of the distribution of workforce flexibility among workers on team performance. In this study, team performance is measured as the shortage of labour capacity, the minimum time needed to perform all tasks (e.g. the timespan) and the total cumulative production time. Two extreme assignment methods, which include a linear goal-programming formulation that minimizes the shortage, makespan and production time, are used in a full orthogonal factorial experimental design (2.2.5.5). The MANOVA results show that a uniform distribution of multifunctionality results in a shorter makespan and lower total production time. The more absenteeism, the stronger these effects. Absenteeism has a very negative impact on all performance measures, independent of the distribution of flexibility. This study shows that, in cases of absenteeism, the workload of the bottleneck worker will increase relatively more than the workload of the remaining operators. Since the bottleneck worker determines the makespan, there will be greater waiting time for the other team members. This may be contra to intuition which tells us that absenteeism will increase the relative workload (or utilization level) of the remaining workers. With respect to the distribution of redundancy, our study shows that each task should be mastered by at least two workers in order to reduce the negative impact of low to moderate levels of absenteeism. Above this minimal level of task redundancy, labour flexibility needs to covary with the demands on capacity for each task.