The three stages of workforce optimisation: Moving beyond the industry standard

Dakota Crisp, Jess Brown, Jack Claucherty, Davis Busteed, Anna Schultz and Jonathan Prantner
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Dakota Crisp: Data Scientist, RXA, USA
Jess Brown: Senior Data Scientist, RXA, USA
Jack Claucherty: Data Scientist, RXA, USA
Davis Busteed: Senior Data Scientist, RXA, USA
Anna Schultz: Marketing Coordinator, RXA, USA
Jonathan Prantner: Chief Analytics Officer and co-founder, RXA, USA

Applied Marketing Analytics: The Peer-Reviewed Journal, 2022, vol. 8, issue 1, 26-36

Abstract: Erlang-C has long been the industry standard for call centre staffing. As callcentres evolve and staffing concerns move to other industries, the standard methodsdon’t always work as expected. While traditional scheduling methods focused ontranslating historic demand into staffing needs, the estimation of demand and thelogistics of scheduling employees have not always been equally considered. Through theanalysis of multiple use cases from distinct industries, this approach evaluates all threestages of workforce optimisation and explores the gap between theory and reality.

Keywords: optimisation; staffing; call centres; ensemble learning; Erlang-C; automotive; forecasting (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2022
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