EMPLOYEE-TASK ASSIGNMENTS FOR ORGANIZATION MODELING: A REVIEW OF MODELS AND APPLICATIONS

摘要

In this study, we present a review of task assignment problems in organizations, an area that has become more important as tasks become more complex and personnel skills become more specialized. The challenge is to design task assignments that meet all requirements and result in the best organizational performance. The consequences of poor design include failed tasks, reduced efficiency, and inability to meet deadlines. Moreover, inequity of workload between employees can cause lack of job satisfaction, loss of motivation and also boredom. In general, work processes in organizations consist of different tasks, which require different expertise. Personnel usually have various degrees of qualifications and their performance may vary for different tasks. The outcome of the work process depends heavily on which tasks are assigned to which personnel. Performance of an organization can be increased by assigning the tasks to the most qualified available personnel. However, it could result in overloading some personnel while the others remain under-loaded. So, the even distribution of the workload between them also needs to be taken into consideration. In addition, it helps to increase organization's productivity by distributing personnel's knowledge, time, and attention more extensively. We review task-employee assignment problems in organization modeling with the computational models that have been reported in the literature with their applications. Human factors engineering, in terms of workload in organizational modeling is included as the work process performance is heavily dependent on the human (personnel). Based on the initial findings, we propose to investigate an improved workload model that allows the use of optimization of select constraints, such as balancing workload among team members. While current workload models allow the evaluation of workload among team members interacting in a work process, it is up to the analyst to suggest improvements. By providing an optimized solution, we present the Engineering Manager, that can then be adjusted to meet practical criteria.