Workforce Analytics in Teleworking

Claudiu Vasile Kifor; Sergiu Stefan Nicolaescu; Adrian Florea; Roxana Florenta Savescu; Ilie Receu; Anca Victoria Tirlea; Raluca Elena Danut

doi:10.1109/ACCESS.2021.3129248

IEEE Access (Jan 2021)

Workforce Analytics in Teleworking

Claudiu Vasile Kifor,
Sergiu Stefan Nicolaescu,
Adrian Florea,
Roxana Florenta Savescu,
Ilie Receu,
Anca Victoria Tirlea,
Raluca Elena Danut

Affiliations

Claudiu Vasile Kifor: ORCiD; The Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, Romania
Sergiu Stefan Nicolaescu: ORCiD; The Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, Romania
Adrian Florea: ORCiD; Department of Computer Science and Electrical Engineering, “Lucian Blaga” University of Sibiu, Sibiu, Romania
Roxana Florenta Savescu: The Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, Romania
Ilie Receu: ORCiD; The Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, Romania
Anca Victoria Tirlea: The Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, Romania
Raluca Elena Danut: ORCiD; The Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, Romania

DOI: https://doi.org/10.1109/ACCESS.2021.3129248
Journal volume & issue: Vol. 9
pp. 156451 – 156464

Abstract

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The recent COVID-19 pandemic has accelerated the interest in new software tools to monitor the computer-based activities of employees working remotely (teleworking), and the demand for better analytics functionalities to be offered, focusing on employees’ performance and work-life balance. In this paper, we aim to analyze the habits of teleworking employees based on their interaction with the computer: how the employees are involved in different types of activities (actual work, recreation, documentation), and which are the most intensive periods. A conceptual framework for workforce analytics was developed for this purpose, together with tools and applications, that can provide useful information on different categories of activities where employees are involved. Knowledge generation is performed in four phases: collecting, processing, organizing, and analyzing the data to create valuable insights for the organization. Based on this framework, we developed a case study in an IT company, where two categories of employees, developers and software consultants, were monitored for 114 days, with 3.5 million events being generated and processed. The results showed different habits for consultants and developers, in terms of working activity structure, working schedule, inactivity time and interaction with the computer. Differences were also identified when we compared our results with previous research that monitored software developers working in-house: remote workers tend to organize their program for a longer period during the workday, and spend less time on meetings but longer time for programming. On the other hand, both categories of employees (in-house and teleworkers) show highly fragmented work, switching windows after very short periods of activity, with a potential negative impact on productivity, progress on tasks, and quality of output. The research results can be used in future employee productivity studies when searching answers to a fundamental question for workforce analytics – why are some employees more productive than others?

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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