Workforce Analytics in Teleworking
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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9620096/ |
| _version_ | 1818751638687449088 |
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| author | Claudiu Vasile Kifor Sergiu Stefan Nicolaescu Adrian Florea Roxana Florenta Savescu Ilie Receu Anca Victoria Tirlea Raluca Elena Danut |
| author_facet | Claudiu Vasile Kifor Sergiu Stefan Nicolaescu Adrian Florea Roxana Florenta Savescu Ilie Receu Anca Victoria Tirlea Raluca Elena Danut |
| author_sort | Claudiu Vasile Kifor |
| collection | DOAJ |
| description | 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? |
| first_indexed | 2024-12-18T04:38:45Z |
| format | Article |
| id | doaj.art-b3fffca7982c49d9b8f8bcc21b53ab8d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-18T04:38:45Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-b3fffca7982c49d9b8f8bcc21b53ab8d2022-12-21T21:20:46ZengIEEEIEEE Access2169-35362021-01-01915645115646410.1109/ACCESS.2021.31292489620096Workforce Analytics in TeleworkingClaudiu Vasile Kifor0https://orcid.org/0000-0001-8983-552XSergiu Stefan Nicolaescu1https://orcid.org/0000-0002-3548-4688Adrian Florea2https://orcid.org/0000-0003-0278-4825Roxana Florenta Savescu3Ilie Receu4https://orcid.org/0000-0003-0706-7008Anca Victoria Tirlea5Raluca Elena Danut6https://orcid.org/0000-0001-5049-3905The Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, RomaniaThe Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, RomaniaDepartment of Computer Science and Electrical Engineering, “Lucian Blaga” University of Sibiu, Sibiu, RomaniaThe Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, RomaniaThe Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, RomaniaThe Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, RomaniaThe Research Center for Sustainable Products and Processes, “Lucian Blaga” University of Sibiu, Sibiu, RomaniaThe 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?https://ieeexplore.ieee.org/document/9620096/Computerized monitoringworkforce analyticsemployee performancedata processingdata engineeringdata analytics |
| spellingShingle | Claudiu Vasile Kifor Sergiu Stefan Nicolaescu Adrian Florea Roxana Florenta Savescu Ilie Receu Anca Victoria Tirlea Raluca Elena Danut Workforce Analytics in Teleworking IEEE Access Computerized monitoring workforce analytics employee performance data processing data engineering data analytics |
| title | Workforce Analytics in Teleworking |
| title_full | Workforce Analytics in Teleworking |
| title_fullStr | Workforce Analytics in Teleworking |
| title_full_unstemmed | Workforce Analytics in Teleworking |
| title_short | Workforce Analytics in Teleworking |
| title_sort | workforce analytics in teleworking |
| topic | Computerized monitoring workforce analytics employee performance data processing data engineering data analytics |
| url | https://ieeexplore.ieee.org/document/9620096/ |
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