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Using analytics to support a utility’s initial response to the COVID-19 pandemic amid an uncertain evidence base

Author

Listed:
  • Schlegelmilch, Jeff

    (Director of National Center for Disaster Preparedness, Columbia University, USA)

  • Paaso, Aleksi

    (Director of Distribution Planning in Smart Grid & Innovation, Commonwealth Edison, USA)

  • Ratner, Jackie

    (Senior Project Manager of National Center for Disaster Preparedness, Columbia University, USA)

  • Saxena, Gunjan

    (Research Staff Assistant at National Center for Disaster Preparedness, Columbia University, USA)

  • White, Zackery

    (Research Staff Assistant at National Center for Disaster Preparedness, Columbia University, USA)

  • Aguilar, Susanna

    (Senior Analyst in Smart Grid Programs, Commonwealth Edison, USA)

  • Kushner, Daniel

    (Manager of Smart Grid Programs, Commonwealth Edison, USA)

  • Matevosyan, Norayr

    (Manager of Grid Data Science, Commonwealth Edison, USA)

  • Ortega, Jaime

    (Director of Grid Analytics, Commonwealth Edison, USA)

  • Bahramirad, Shay

    (Vice President of Engineering and Smart Grid, Commonwealth Edison, USA)

Abstract

Energy utilities play a critical role in fostering disaster resilience. Much of the world is increasingly dependent on the availability and reliability of safe and efficient energy. In addition to its importance for industrial, commercial and household functionality, energy provision is increasingly significant in determining health and equity outcomes during a disaster. Amid the COVID-19 pandemic, issues of workforce protection and absenteeism are critical for public safety as well as for the continuity of operations for utilities and the businesses that rely upon them. However, COVID-19, and pandemics generally, have rapidly evolving and imperfect evidence available to support rapid and real-time decision making. This article reflects the initial setup and operations of frameworks utilising analytics to support decision making from March through July 2020 for a major US electric utility. These initial strategies have enhanced decision making and provided a foundation for additional integration of the evidence base and use of analytics for anticipated decision support in the coming phases of the COVID-19 pandemic, as well as for future pandemics of unknown aetiology.

Suggested Citation

  • Schlegelmilch, Jeff & Paaso, Aleksi & Ratner, Jackie & Saxena, Gunjan & White, Zackery & Aguilar, Susanna & Kushner, Daniel & Matevosyan, Norayr & Ortega, Jaime & Bahramirad, Shay, 2021. "Using analytics to support a utility’s initial response to the COVID-19 pandemic amid an uncertain evidence base," Journal of Business Continuity & Emergency Planning, Henry Stewart Publications, vol. 14(3), pages 226-238, March.
    • Handle: RePEc:aza:jbcep0:y:2021:v:14:i:3:p:226-238
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    JEL classification:

    • M1 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation

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