Can a Buffering Strategy Reduce Workload Related Stress

The support services industry remains a competitive business operating on very stringent budgets, metrics, and milestones. Given the heavy and varying workloads that are characteristic in this business, stress is a common all-too-common phenomenon and emerges from different sources. In this context, we use an agent based approach to examine whether using a workload buffering strategy based loosely on the Leaky Bucket Algorithm can help to manage work-load-related stress. We use our workplace stress model to see the implications of such a buffering approach on workload related stress at an individual level and on macro indicators such as turn-around time (TAT). The experiments show that the strategy can help not only reduce the stress but also provide knobs to the operations managers to manage workload and to ensure compliance. We conclude with implications for future research and practice.