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Switchboard simulation to improve productivity and customer service

E D LaCourse1

  • 1Straub Clinic and Hospital, Honolulu, HI, USA.

Journal of the Society for Health Systems
|January 1, 1996
PubMed
Summary

This study optimized switchboard staffing using industrial engineering methods and simulation modeling. The approach improved both productivity and customer service quality through data-driven scheduling.

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Area of Science:

  • Operations Research
  • Industrial Engineering
  • Simulation Modeling

Background:

  • Classical industrial engineering and operations research techniques are often underutilized in practical applications.
  • Optimizing staffing and resource allocation in service environments like switchboards presents ongoing challenges.
  • Integrating analytical methods with operational data can yield significant improvements.

Purpose of the Study:

  • To apply multichannel queueing analysis and workload data to determine optimal switchboard staffing.
  • To develop an analytic simulation model for interactive analysis of coverage requirements.
  • To demonstrate the effective use of classical techniques for enhancing productivity and service quality.

Main Methods:

  • Utilized multichannel queueing analysis, a classical operations research technique.
  • Developed a personal computer-based analytic simulation model for switchboard operations.
  • Employed interactive analysis with detailed workload distribution data.

Main Results:

  • Successfully determined optimal switchboard coverage requirements.
  • Developed effective staffing schedules optimized for time of day and day of week.
  • Achieved a tangible improvement in both operational productivity and customer service quality.

Conclusions:

  • Classical industrial engineering and operations research techniques remain highly relevant for solving modern operational problems.
  • Analytic simulation modeling, combined with operational data, provides a powerful tool for optimizing service environments.
  • Close collaboration between analysts and management is crucial for successful implementation and problem-solving.

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