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Limousine Service Management: Capacity Planning with Predictive Analytics and Optimization

Author

Listed:
  • Peng Liu

    (Department of Statistics and Applied Probability, National University of Singapore, 117546 Singapore)

  • Ying Chen

    (Department of Mathematics, National University of Singapore, 117546 Singapore)

  • Chung-Piaw Teo

    (Institute of Operations Research and Analytics, National University of Singapore, 117546 Singapore)

Abstract

Thelimousine service in luxury hotels is an integral component of the whole customer journey in the hospitality industry. One of the largest hotels in Singapore manages a fleet of both in-house and outsourced vehicles around the clock, serving 9,000 trips per month on average. The need for vehicles may scale up rapidly, especially during special events and festive periods in the country. The excess demand is met by having additional outsourced vehicles on standby, incurring millions of dollars of additional expenses per year for the hotel. Determining the required number of limousines by hour of the day is a challenging service capacity planning problem. In this paper, a recent transformational journey to manage this problem for the hotel is introduced, having driven up to S$3.2 million of savings per year while improving the service level. The approach builds on widely available open-source statistical and spreadsheet optimization tools, along with robotic process automation, to optimize the schedule of the hotel’s fleet of limousines and drivers and to support decision making for planners and controllers to cultivate sustained business value.

Suggested Citation

  • Peng Liu & Ying Chen & Chung-Piaw Teo, 2021. "Limousine Service Management: Capacity Planning with Predictive Analytics and Optimization," Interfaces, INFORMS, vol. 51(4), pages 280-296, July.
    • Handle: RePEc:inm:orinte:v:51:y:2021:i:4:p:280-296
    DOI: 10.1287/inte.2021.1079
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