Introduction
Service-based operations, especially those functioning in a Business Process Outsourcing (BPO) environment, operate with one non-negotiable expectation—quick turnaround without compromising on quality. Yet, when teams start facing increasing overtime, missed targets, and inconsistent agent utilization, it’s a clear sign that resource deployment needs a closer look. A leading service sector organization facing such challenges turned to Production Modeling India (PMI) for a comprehensive capacity validation study.
Client’s Challenge
• Bottlenecks causing missed turnaround time (TAT) commitments
• Inconsistencies in workload distribution resulting in both overtime and idle time
• Lack of visibility into real-time agent utilization
• No dynamic method to validate or simulate operational changes in resource allocation
How Simulation Helped Fix Overtime and Underutilization in a Service Sector - A Case Study
PMI’s Approach
PMI began by visualizing operations at a granular level to capture every nuance of the service process. The study included:
Process-specific metrics such as arrival patterns, line-item sizes, and task completion times were analyzed. Randomized inputs were also simulated to reflect real-life demand variability.
A dynamic baseline model was created to reflect the current process. All intricacies—such as wait times, bottlenecks, and agent behavior, were integrated and validated.
The team tested new strategies within the model, particularly shifting allocation to the start of the process, which drastically improved flow.
Key outputs like agent time-in-state, job queue times, overtime occurrences, and TAT misses were extracted and analyzed.
Findings & Recommendations
• Both overtime and idle time were found to coexist due to poor scheduling.
• Several bottlenecks were uncovered, hidden behind average performance metrics.
• A new resource allocation strategy, modeled and tested, resulted in better agent utilization and reduced job queue times.
• PMI delivered a validated method to forecast agent requirements dynamically, based on fluctuating demand.
Conclusion
PMI’s simulation-led approach turned complexity into clarity. The client not only gained control over resource allocation but also laid the foundation for a smarter, data-backed workforce planning system.