Simulation-Based Decision Support for Call Centre Staffing Optimisation: A Case Study from the Palestinian Telecom Sector

Tamer Haddad; Ramiz Assaf; Siraj Zahran; Mohammad Kanan

doi:10.31181/dmame8220251497

Authors

Tamer Haddad Industrial and Mechanical Engineering Department, Faculty of Engineering, An-Najah National University, Nablus, Palestine.
Ramiz Assaf Industrial and Mechanical Engineering Department, Faculty of Engineering, An-Najah National University, Nablus, Palestine.
Siraj Zahran Industrial Engineering Department, College of Engineering, University of Business and Technology, Jeddah, Saudi Arabia
Mohammad Kanan Industrial Engineering Department, College of Engineering, University of Business and Technology, Jeddah, Saudi Arabia

DOI:

https://doi.org/10.31181/dmame8220251497

Keywords:

Discrete Event Simulation, Call Centre Optimisation, Decision Support Systems, Staffing Strategy, Customer Service Analytics

Abstract

This research introduces a decision support model based on simulation, designed to enhance staffing strategies and elevate operational performance within a technical support call centre operated by a prominent Palestinian internet service provider. Call centres frequently encounter challenges arising from fluctuating customer demand, often resulting in extended waiting times and elevated abandonment rates, which adversely affect customer satisfaction. To mitigate these issues, a discrete event simulation was developed through the ProModel© platform, integrating statistically fitted probability distributions for call arrival patterns, call handling durations, and customer abandonment tendencies. Following validation, the simulation was utilised to assess various staffing alternatives, with particular focus on reallocating personnel across different shifts. The findings revealed that moving a single agent from the morning shift (8:00 AM to 4:00 PM) to the high-demand afternoon shift (4:00 PM to 12:00 AM) yielded significant enhancements in key performance indicators. This adjustment resulted in a 15% reduction in average customer waiting times and a 27% decrease in call abandonment rates, achieved without increasing the overall staffing level. The study underscores the practical utility of simulation modelling as an evidence-based approach to resource allocation in service-oriented environments. The adopted methodology aligns with established standards in call centre simulation and presents a transferable framework suitable for similar applications within emerging economies.

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