Capturing and Analysing Employee Behaviour: An Honest Day’s Work Record

For a range of reasons, organisations collect data on the work behaviour of their employees. However, each data collection technique displays its own unique mix of intrusiveness, information richness, and risks. For the sake of understanding the differences between data collection techniques, we conducted a multiple-case study in a multinational professional services organisation, tracking six participants throughout a workday using non-participant observation, screen recording, and timesheet techniques. This led to 136 hours of data. Our findings show that relying on one data collection technique alone cannot provide a comprehensive and accurate account of activities that are screen-based, offline, or overtime. The collected data also provided an opportunity to investigate the use of process mining for analysing employee behaviour, specifically with respect to the completeness of the collected data. Our study underlines the importance of judiciously selecting data collection techniques, as well as using a sufficiently broad data set to generate reliable insights into employee behaviour.

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Publication Details

Journal
Data & Knowledge Engineering
Published
2024-08-31
DOI
https://doi.org/10.1016/j.datak.2024.102350
Citations
1
Primary Topic
Business Process Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.53
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article

Capturing and Analysing Employee Behaviour: An Honest Day’s Work Record

Iris Beerepoot, Tea Šinik, Hajo A. Reijers
1 citations
Data & Knowledge Engineering
Business Process Modeling and Analysis
0.53
article

Capturing and Analysing Employee Behaviour: An Honest Day’s Work Record

Iris Beerepoot, Tea Šinik, Hajo A. Reijers
article en
1 citations

Abstract

For a range of reasons, organisations collect data on the work behaviour of their employees. However, each data collection technique displays its own unique mix of intrusiveness, information richness, and risks. For the sake of understanding the differences between data collection techniques, we conducted a multiple-case study in a multinational professional services organisation, tracking six participants throughout a workday using non-participant observation, screen recording, and timesheet techniques. This led to 136 hours of data. Our findings show that relying on one data collection technique alone cannot provide a comprehensive and accurate account of activities that are screen-based, offline, or overtime. The collected data also provided an opportunity to investigate the use of process mining for analysing employee behaviour, specifically with respect to the completeness of the collected data. Our study underlines the importance of judiciously selecting data collection techniques, as well as using a sufficiently broad data set to generate reliable insights into employee behaviour.

Data & Knowledge EngineeringVol. 154
Utrecht University (NL)
Openalex Percentile: Top 27%
Business Process Modeling and Analysis
0.53
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