| Summary: | TELUS, a large Canadian telecommunications company primarily based in Western Canada, provides a full range of telecommunications products and services including data, Internet protocol (IP), voice and mobile wireless services. Every month TELUS processes high volumes of customer orders either for new service or changes in existing service. Within TELUS, the Assignment and Activation group processes all orders and is responsible for changes in the mainframe computers and switches as well as coordination with field service representatives that actually perform physical installations of and changes to customer equipment. The challenges faced by the order processing center include difficulty meeting current throughput and lead time requirements, as well as uncertainty regarding the metrics used for quality and process measurement. Further, increased competition in the telecommunications industry has pressured TELUS to cut costs, resulting a major workforce reduction and widespread process and service reorganization. This thesis describes the development and application of simulation to study the Assignment and Activation group. The data analysis and model development procedure is outlined and results are discussed. Although simulation model development was hindered by difficulties collecting process data, the model building and data analysis process helped identify several opportunities for improvement. The steps required to continue developing the simulation, therefore enabling more detailed questions about the process to be evaluated, are also outlined. Based on the simulation analysis it is recommended that better data collection be implemented to measure key metrics, especially processing time distributions. Putting the uncertainty in the confidence level of the processing estimates aside, this study found that improving the Auto Front End Assignable or the exception rates would have a negligible effect on throughput if the processing times are close to average. In addition, shifting the days out ahead by three days resulted in a 3% increase in on-time completions. Finally in most of the scenarios evaluated, the operator utilization appeared unrealistically high indicating a general staff shortage.
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