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What’s Wrong with My Dishwasher: Advanced Analytics Improve the Diagnostic Process for Miele Technicians

Author

Listed:
  • Segev Wasserkrug

    (IBM Research – Haifa, 3498825 Haifa, Israel;)

  • Martin Krüger

    (Miele Smart Home, 33332 Gütersloh, Germany;)

  • Yishai A. Feldman,

    (IBM Research – Haifa, 3498825 Haifa, Israel;)

  • Evgeny Shindin

    (IBM Research – Haifa, 3498825 Haifa, Israel;)

  • Sergey Zeltyn

    (IBM Research – Haifa, 3498825 Haifa, Israel)

Abstract

Miele, a leading appliance manufacturer, was looking to optimize the ways in which it solves customer problems quickly and efficiently. A crucial part of this task is the precise diagnosis of faults before and during technician visits. A correct diagnosis allows technicians to bring with them the necessary parts and complete the repair with minimal time, effort, and spare parts. We created a system to help Miele optimize its service process based on statistics learned from historical data about technician visits; the data contained both structured and unstructured (textual) data that had to be combined to create a probabilistic model. We used a novel process in which a semantic model informed the creation of the probabilistic model as well as the analysis pipelines for the structured and unstructured data, combining expert knowledge with a large amount of heterogenous data. The results of our pilot study demonstrated a significant improvement in efficiency concomitant with an increase of an already very high first-fix rate.

Suggested Citation

  • Segev Wasserkrug & Martin Krüger & Yishai A. Feldman, & Evgeny Shindin & Sergey Zeltyn, 2019. "What’s Wrong with My Dishwasher: Advanced Analytics Improve the Diagnostic Process for Miele Technicians," Interfaces, INFORMS, vol. 49(5), pages 384-396, September.
    • Handle: RePEc:inm:orinte:v:49:y:2019:i:5:p:384-396
    DOI: 10.1287/inte.2019.1006
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