Analysing the modern determinants of key performance indicators of employees
DOI:
https://doi.org/10.17308/econ.2024.3/12284Keywords:
key performance indicators, performance, employee, organisational structure, organisational changes, automation, digital economy, outsourcing companyAbstract
Subject. Given the current tough competition, companies have to search for new methods of enhancing their performance in order to maintain their position in the market. The main resource facilitating the growth of any company is human capital. Therefore, it is important to find ways to enhance the efficiency and performance of employees maintaining a balanced organisational structure.
Purpose. The purpose of the study was to analyse the connection between the KPIs and characteristics of employees in an organisation.
Methodology. The article considers the dependence between KPIs shown by employees of large organisations and various personal and organisational characteristics. Using regression analysis, we determined the characteristics that affect KPIs the most, namely variables corresponding to conformism and the social influence (e.g. average KPIs of other employees). We also identified three groups of variables and performed a more detailed analysis of their dependence on all the other factors: workflow, KPI rate, and the number of employees.
Conclusions. Based on the performed analysis, we suggest recommendations on the possible changes in the organisational structure aimed at achieving maximum performance rates and at further automation of the process. We believe that such an automated process will help to enhance organisational performance without significant expenditure and to plan organisational changes more carefully.
Downloads
References
Варфоломеев, В.П., Кондратова, С.В., & Захарова, М.В. (2016). Управление компанией по ключевым показателям эффективности. Экономический анализ: теория и практика, (8), 134 – 146. [Varfolomeev, V.P., Kondratova, S.V., & Zaharova, M.V. (2016). Company management by key performance indicators. Economic Analysis: Theory and Practice, (8), 134 – 146. (In Russian).]
Гоголева, Т.Н., Юрова, Е.С., Канапухин, П.А., & Никитина, Л.М. (2022). Профессионально-квалификационные трансформации качества труда в информационном обществе. Вестник Воронежского государственного университета. Серия: Экономика и управление, (4), 5 – 18. [Gogoleva, T. N., Yurova, E. S., Kanapukhin, P. A., & Nikitina, L. M. (2022). Transformations in the qualification aspect of labour quality in an information society. Proceedings of Voronezh State University. Series: Economics and Management, (4), 5-18. (In Russian).] https://doi.org/10.17308/econ.2022.4/10596
Игнатьева, О.В., & Вашаломидзе, К.В. (2023). Факторы и резервы роста производительности и эффективности труда на предприятии. Труд и социальные отношения, 34(3), 31-38. [Ignateva, O.V., & Vashalomidze, K.V. (2023). Faktory i rezervy rosta proizvoditel'nosti i effektivnosti truda na predpriyatii. Trud i social'nye otnosheniya, 34(3), 31-38. (In Russian).] https://doi.org/10.20410/2073-7815-2023-34-3-31-38
Лапидус, Л. В., & Полякова, Ю. М. (2022). Гигономика: новые возможности для цифровой трансформации бизнеса в условиях высокой турбулентности цифровой среды. Вестник Института экономики Российской академии наук, (5), 23 – 46. [Lapidus, L. V., & Polyakova, Yu. M. (2022). Gig economy: the new opportunities for business digital transformation under high turbulent digital environment. The Bulletin of the Institute of Economics of the Russian Academy of Sciences, (5), 23 – 46. (In Russian).]
Сысоева, Е.В. (2020). Совершенствование компонентов кадровой стратегии в эффективности деятельности организации. Инновации и инвестиции, (11), 153 – 157. [Sysoeva, E.V. (2020). Improving the components of the HR strategy in the effectiveness of the organization. Innovations and Investments, (11), 153 – 157. (In Russian).]
Щепина, И.Н., Маслова, И.М., & Гоголева, Т.Н. (2023). Анализ использования цифровых технологий в организациях российских регионов. Вестник Воронежского государственного университета. Серия: Экономика и управление, (1), 65 – 82. [Shchepina, I. N., Maslova, M. I., & Gogoleva, T. N. (2023). Analysis of the use of digital technologies in organisations in the regions of Russia. Proceedings of Voronezh State University. Series: Economics and Management, (1), 65-82. (In Russian).] https://doi.org/10.17308/econ.2023.1/10965
Barends, E., Rousseau, D., Cioca, I. & Wrietak, E. (2023). High-performing teams: An evidence review. Scientific Summary. London: Chartered Institute of Personnel and Development.
Chan, A. P. C., & Chan, A. P. L. (2004). Key performance indicators for measuring construction success. Benchmarking: an international journal, 11(2), 203-221. https://doi.org/10.1108/14635770410532624.
Chung, K. S. (2018). A Comparative Study among KPI Developing Methods. Journal of Korean Society for Quality Management, 46(4), 863-876. https://doi.org/10.7469/JKSQM.2018.46.4.863.
Gong, Y., & Yu, Q. (2019). Evolution of conformity dynamics in complex social networks. Symmetry, 11(3), 299. https://doi.org/10.7469/JKSQM.2018.46.4.863.
Gupta, P. K., & Venkateswaran, N. (2021). The role of KPI-121 0.25% in the treatment of dry eye disease: penetrating the mucus barrier to treat periodic flares. Therapeutic Advances in Ophthalmology, 13, 25158414211012797. https://doi.org/10.1177/25158414211012797.
Khanagha, S., Volberda, H.W., Alexiou, A., & Annosi, M. C. (2022). Mitigating the dark side of agile teams: Peer pressure, leaders’ control, and the innovative output of agile teams. Journal of Product Innovation Management, 39(3), 334-350. https://doi.org/10.1111/jpim.12589.
Mathieu, J. E., Gallagher, P. T., Domingo, M. A., & Klock, E. A. (2019). Embracing complexity: Reviewing the past decade of team effectiveness research. Annual Review of Organizational Psychology and Organizational Behavior, 6, 17-46. https://doi.org/10.1146/annurev-orgpsych-012218-015106.
McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual review of sociology, 27(1), 415-444. https://doi.org/10.1146/annurev.soc.27.1.415.
Murase, Y., Jo, H. H., Török, J., Kertész, J., & Kaski, K. (2019). Structural transition in social networks: The role of homophily. Scientific reports, 9(1), 4310. https://doi.org/10.1038/s41598-019-40990-z.
Onnela, J. P., Saramäki, J., Hyvönen, J., Szabó, G., Menezes, A., Kaski, K., Barabási, A.-L. & Kertész, J. (2007). Analysis of a large-scale weighted network of one-to-one human communication. New journal of physics, 9(6), 179. https://doi.org/10.1088/1367-2630/9/6/179.
Onnela, J. P., Saramäki, J., Hyvönen, J., Szabó, G., Lazer, D., Menezes, A., Kaski, K., Barabási, A.-L. & Kertész, J. (2007). Structure and tie strengths in mobile communication networks. Proceedings of the national academy of sciences, 104(18), 7332-7336. https://doi.org/10.1073/pnas.061024510.
Setijono, D., & Dahlgaard, J. J. (2007). Customer value as a key performance indicator (KPI) and a key improvement indicator (KII). Measuring Business Excellence, 11(2), 44-61. https://doi.org/10.1108/13683040710752733.
Spiegler, S. V., Heinecke, C., & Wagner, S. (2021). An empirical study on changing leadership in agile teams. Empirical Software Engineering, 26, 1-35. https://doi.org/10.1007/s10664-021-09949-5.
Zhou, H., & He, Y. (2018). Comparative Study of OKR and KPI. International Conference On E-Commerce And Contemporary Economic Development. https://doi.org/10.12783/dtem/eced2018/23986
Zolotina, O. A., Razumova, T. O., Sotnikov, Ya. A., Nastavnyuk, A. V., & Frerichs, H. (2023). Digital transformation of high-performing teams. Population and Economics, 7(2), 60-93. https://doi.org/10.3897/popecon.7.e98911.
