Staff turnover management based on HR analytics data

Staff turnover is one of the most pressing problems faced by companies in the context of a growing shortage of staff. The article is devoted to the development of recommendations for improving staff turnover management based on HR analytics data. Based on the analysis of publications devoted to the...

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Main Authors: M.V. Chudinovskikh, A.N. Tkach, D.Y. Korolkov
Format: Article
Language:English
Published: Ural State University of Economics 2024-10-01
Series:Цифровые модели и решения
Subjects:
Online Access:http://usue-journal.ru/en/issues-2024/69-anglijskij-yazyk/tsmiren/10/510-staff-turnover-management-based-on-hr-analytics-data
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author M.V. Chudinovskikh
A.N. Tkach
D.Y. Korolkov
author_facet M.V. Chudinovskikh
A.N. Tkach
D.Y. Korolkov
author_sort M.V. Chudinovskikh
collection DOAJ
description Staff turnover is one of the most pressing problems faced by companies in the context of a growing shortage of staff. The article is devoted to the development of recommendations for improving staff turnover management based on HR analytics data. Based on the analysis of publications devoted to the problem of turnover, the main metrics that are used to analyze staff turnover are systematized. To expand the possibilities of justification and management decision-making, an assessment is given of the possibility of using the theory of personnel cycling, as well as a deeper study of turnover problems based on statistical methods. The developed recommendations can be used to analyze data on turnover in the company and develop measures aimed at improving the efficiency of the turnover management process.
format Article
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institution Kabale University
issn 2949-477X
2782-4934
language English
publishDate 2024-10-01
publisher Ural State University of Economics
record_format Article
series Цифровые модели и решения
spelling doaj-art-3c0e369e73744808be0e23f61ec4a8922025-01-07T09:02:52ZengUral State University of EconomicsЦифровые модели и решения2949-477X2782-49342024-10-0133889710.29141/2949-477X-2024-3-3-7Staff turnover management based on HR analytics dataM.V. Chudinovskikh0A.N. Tkach1D.Y. Korolkov2Ural State University of Economics, Ekaterinburg, Russian FederationJSC SVEL Group, Ekaterinburg, Russian FederationJSC SVEL Group, Ekaterinburg, Russian FederationStaff turnover is one of the most pressing problems faced by companies in the context of a growing shortage of staff. The article is devoted to the development of recommendations for improving staff turnover management based on HR analytics data. Based on the analysis of publications devoted to the problem of turnover, the main metrics that are used to analyze staff turnover are systematized. To expand the possibilities of justification and management decision-making, an assessment is given of the possibility of using the theory of personnel cycling, as well as a deeper study of turnover problems based on statistical methods. The developed recommendations can be used to analyze data on turnover in the company and develop measures aimed at improving the efficiency of the turnover management process.http://usue-journal.ru/en/issues-2024/69-anglijskij-yazyk/tsmiren/10/510-staff-turnover-management-based-on-hr-analytics-dataturnoverretentionpersonnelstages of personnel cyclinghr analytics
spellingShingle M.V. Chudinovskikh
A.N. Tkach
D.Y. Korolkov
Staff turnover management based on HR analytics data
Цифровые модели и решения
turnover
retention
personnel
stages of personnel cycling
hr analytics
title Staff turnover management based on HR analytics data
title_full Staff turnover management based on HR analytics data
title_fullStr Staff turnover management based on HR analytics data
title_full_unstemmed Staff turnover management based on HR analytics data
title_short Staff turnover management based on HR analytics data
title_sort staff turnover management based on hr analytics data
topic turnover
retention
personnel
stages of personnel cycling
hr analytics
url http://usue-journal.ru/en/issues-2024/69-anglijskij-yazyk/tsmiren/10/510-staff-turnover-management-based-on-hr-analytics-data
work_keys_str_mv AT mvchudinovskikh staffturnovermanagementbasedonhranalyticsdata
AT antkach staffturnovermanagementbasedonhranalyticsdata
AT dykorolkov staffturnovermanagementbasedonhranalyticsdata