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Dynamic Workforce Scheduling for British Telecommunications plc

Author

Listed:
  • David Lesaint

    (Intelligent Systems Research, BT France, 11, place des Vosges 92061, Paris La Defense, France)

  • Christos Voudouris

    (Intelligent Systems Research, BT Adastral Park, MLB1-PP12, Ipswich IP5 3RE, United Kingdom)

  • Nader Azarmi

    (Intelligent Systems Research, BT Adastral Park)

Abstract

British Telecommunications plc (BT) employs thousands of field engineers across the UK to maintain networks, repair faults, and provide service to customers. To allocate work efficiently, BT developed Work Manager, an information system that automates work management and field communications. In 1996, the Intelligent Systems Research group of BT enhanced Work Manager with a dynamic scheduler (DS) based on a combination of heuristic search and constraint-based reasoning. Rolled out in 1997 and reaching 20,000 engineers in 1998, DS with Work Manager is saving BT $150 million a year on operational costs. When deployed over the targeted workforce of 40,000 people, the system will save an estimated $250 million a year.

Suggested Citation

  • David Lesaint & Christos Voudouris & Nader Azarmi, 2000. "Dynamic Workforce Scheduling for British Telecommunications plc," Interfaces, INFORMS, vol. 30(1), pages 45-56, February.
    • Handle: RePEc:inm:orinte:v:30:y:2000:i:1:p:45-56
    DOI: 10.1287/inte.30.1.45.11615
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    Citations

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    Cited by:

    1. Voudouris, Christos & Owusu, Gilbert & Dorne, Raphael & Ladde, Cedric & Virginas, Botond, 2006. "ARMS: An automated resource management system for British Telecommunications plc," European Journal of Operational Research, Elsevier, vol. 171(3), pages 951-961, June.
    2. Valls, Vicente & Pérez, Ángeles & Quintanilla, Sacramento, 2009. "Skilled workforce scheduling in Service Centres," European Journal of Operational Research, Elsevier, vol. 193(3), pages 791-804, March.
    3. Chen, Xi & Hewitt, Mike & Thomas, Barrett W., 2018. "An approximate dynamic programming method for the multi-period technician scheduling problem with experience-based service times and stochastic customers," International Journal of Production Economics, Elsevier, vol. 196(C), pages 122-134.
    4. Marina Chugunova & Anastasia Danilov, 2023. "Use of Digital Technologies for HR Management in Germany: Survey Evidence," Rationality and Competition Discussion Paper Series 485, CRC TRR 190 Rationality and Competition.
    5. Jeroen Beliën & Brecht Cardoen & Erik Demeulemeester, 2012. "Improving Workforce Scheduling of Aircraft Line Maintenance at Sabena Technics," Interfaces, INFORMS, vol. 42(4), pages 352-364, August.
    6. Voravee Punyakum & Kanchana Sethanan & Krisanarach Nitisiri & Rapeepan Pitakaso, 2022. "Hybrid Particle Swarm and Whale Optimization Algorithm for Multi-Visit and Multi-Period Dynamic Workforce Scheduling and Routing Problems," Mathematics, MDPI, vol. 10(19), pages 1-20, October.
    7. Chen, Xi & Li, Kaiwen & Lin, Sidian & Ding, Xiaosong, 2024. "Technician routing and scheduling with employees’ learning through implicit cross-training strategy," International Journal of Production Economics, Elsevier, vol. 271(C).
    8. Steve Batstone & Geoff Pritchard & Golbon Zakeri, 2016. "Noninvasive Test Scheduling in Live Electricity Markets at Transpower New Zealand," Interfaces, INFORMS, vol. 46(6), pages 482-492, December.
    9. Quintanilla, Sacramento & Pérez, Ángeles & Lino, Pilar & Valls, Vicente, 2012. "Time and work generalised precedence relationships in project scheduling with pre-emption: An application to the management of Service Centres," European Journal of Operational Research, Elsevier, vol. 219(1), pages 59-72.
    10. Chen, Xi & Thomas, Barrett W. & Hewitt, Mike, 2016. "The technician routing problem with experience-based service times," Omega, Elsevier, vol. 61(C), pages 49-61.

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