Samatoev A.T., Lapidus L.V., Polyakova Yu.M. IDENTIFICATION OF LABOR PRODUCTIVITY FACTORS BASED ON BIG DATA ANALYSIS ON THE LEVEL OF KEY PERFORMANCE INDICATORS IMPLEMENTATION OF EMPLOYEES AND MANAGERS OF THE COMPANY IN THE MODERN CONDITIONS

DOI: https://doi.org/10.15688/ek.jvolsu.2024.4.19

Artem T. Samatoev

Organizational Design Expert, Polyus Management Company LLC, Krasina St, 3, Bld. 1, 123056 Moscow, Russian Federation, This email address is being protected from spambots. You need JavaScript enabled to view it. , https://orcid.org/0009-0009-3941-4925

Larisa V. Lapidus

Doctor of Sciences (Economics), Professor, Head of the Laboratory of Applied Industry Analysis, Lomonosov Moscow State University, Leninskie gory, 1, Bld. 46, 119991 Moscow, Russian Federation, This email address is being protected from spambots. You need JavaScript enabled to view it. , https://orcid.org/0000-0002-9099-6707

Yulia M. Polyakov

Candidate of Sciences (Economics), Engineer, Laboratory of Applied Industry Analysis, Lomonosov Moscow State University, Leninskie gory, 1, Bld. 46, 119991 Moscow, Russian Federation, This email address is being protected from spambots. You need JavaScript enabled to view it. , https://orcid.org/0000-0002-0499-8344


Abstract. The article analyzes factors that potentially determine the dynamics of changes in labor productivity of employees in a large outsourcing company as their length of service in the company increases based on big data analysis (10,651 observations). Key performance indicators (KPIs) of employees hired by the company for the period from 2020 to 2023 were selected as indicators of the level of employees’ labor productivity. Based on the results of the analysis, we can conclude that the monthly increase in the level of KPI implementation is associated with two factors: the average level of KPIs of colleagues and length of service in the company. The results obtained allow the authors to propose an approach to increasing the labor productivity of new employees and creating highperformance teams, as well as to calculate the potential economic effect of implementing such an approach. The results obtained in the study will be of interest to practitioners and employees in the scientific field. Specialists in human resource management (HRM) departments can use in their work the proposed approach to increasing the productivity of new employees, while the qualitative and quantitative assessments obtained from the analysis may be of interest to current scientific employees.

Key words: KPI, labor productivity, employee, organizational structure, organizational changes, automation, digital economy, outsourcing company.

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IDENTIFICATION OF LABOR PRODUCTIVITY FACTORS BASED ON BIG DATA ANALYSIS ON THE LEVEL OF  KEY PERFORMANCE INDICATORS IMPLEMENTATION OF EMPLOYEES AND MANAGERS OF THE COMPANY IN THE MODERN CONDITIONS by Samatoev A.T., Lapidus L.V., Polyakova Yu.M. is licensed under a Creative Commons Attribution 4.0 International License.

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