HR Analytics and the decision-making process: an evidence-based management approach
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/12/12139/tde-23022023-195912/ |
Resumo: | HR Analytics (HRA) has gained attention from practitioners and scholars under the promise of providing basis for better decision making. However, the question regarding how HRA can be effectively used to support decisions in organizations remains answered. Although some suggest Evidence-Based Management (EBM) as the theoretical approach through which HRA would effectively contribute to decisions, the idea has not been empirically tested. Therefore, studys objective is to analyze how HRA leads to talent decision making through the EBM approach. Analysis of how HRA leads to decisions were grounded on (a) the structure of decision problems (PS), the stages of the decision-making process (DMP) where HR analytics centers its contributions, (c) the quantitative analytical methods (QAM) employed in data analysis and (c) the interaction among HR Analytics and EBM along the process. Basic qualitative research was employed to assess HR Analytics decision processes performed in organizations located in Brazil. The study relied on 8 semi structured interviews with professionals who have leaded or taken an important part in a HR Analytics decision process. Content and template analysis were employed as data analysis methods. It was found that PS and QAM were not decisive to shed light on how HRA leads to decision-making. The evidence-based management approach seemed relevant to (a) provide evidence needed to the execution of quantitative analysis and (b) to intermediate HRAs inputs to decisions. Results also shed light on the nature and different roles of these inputs. |
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HR Analytics and the decision-making process: an evidence-based management approachHR Analytics e o processo decisório: uma abordagem evidence-based managementAnalytics decision making processBusinessEvidence-based managementGestão por evidênciasHR AnalyticsHR AnalyticsProcesso decisórioHR Analytics (HRA) has gained attention from practitioners and scholars under the promise of providing basis for better decision making. However, the question regarding how HRA can be effectively used to support decisions in organizations remains answered. Although some suggest Evidence-Based Management (EBM) as the theoretical approach through which HRA would effectively contribute to decisions, the idea has not been empirically tested. Therefore, studys objective is to analyze how HRA leads to talent decision making through the EBM approach. Analysis of how HRA leads to decisions were grounded on (a) the structure of decision problems (PS), the stages of the decision-making process (DMP) where HR analytics centers its contributions, (c) the quantitative analytical methods (QAM) employed in data analysis and (c) the interaction among HR Analytics and EBM along the process. Basic qualitative research was employed to assess HR Analytics decision processes performed in organizations located in Brazil. The study relied on 8 semi structured interviews with professionals who have leaded or taken an important part in a HR Analytics decision process. Content and template analysis were employed as data analysis methods. It was found that PS and QAM were not decisive to shed light on how HRA leads to decision-making. The evidence-based management approach seemed relevant to (a) provide evidence needed to the execution of quantitative analysis and (b) to intermediate HRAs inputs to decisions. Results also shed light on the nature and different roles of these inputs.A prática de HR Analytics (HRA) tem ganhado atenção do mercado e da academia através da promessa de fornecer fundamentos para a tomada de decisão nas empresas. No entanto, a literatura aponta pouco entendimento a respeito de como o HRA pode ser usado para direcionar a tomada de decisão nas organizações. Apesar de haver menções ao evidence-based management (EBM) como uma possível lente teórica para a tomada de decisão com o HR Analytics, esta relação ainda não foi empiricamente testada. No entanto, o estudo tem como objetivo analisar como HR Analytics leva a tomada de decisão nas organizações através da abordagem Evidence-Based Management. A análise de como o HRA leva a tomada de decisão foi baseada (a) na estrutura de problemas decisórios (PS) (b) nos estágios do processo de tomada de decisão onde o HRA acontece, (c) nos métodos quantitativos empregados na análise de dados, por fim (d) na interação ente o HRA e o EBM ao longo do processo decisório. A pesquisa qualitativa básica foi usada para coletar dados a respeito de processos de tomada de decisão realizados com o HR Analytics. O estudo contou com 8 entrevistas semiestruturadas com profissionais que lideraram (ou tiveram uma participação importante) em algum processo de tomada de decisão com HR Analytics. Os dados foram analisados através de análise de conteúdo e template analysis. Os resultados mostraram que PS e QAM não foram decisivos para o entendimento de como o HRA leva a tomada de decisão. O EBM por sua vez, mostrou um papel importante tanto como (a) provedor das evidências necessárias para a execução das análises quantitativas, como quanto (b) intermediador dos inputs do HRA para o processo decisório. Os resultados também mostraram a natureza dos diversos inputs que o HRA pode prover para a tomada de decisão nas organizações.Biblioteca Digitais de Teses e Dissertações da USPVasconcellos, LilianaScaf, Amanda2022-11-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/12/12139/tde-23022023-195912/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2023-03-29T13:30:30Zoai:teses.usp.br:tde-23022023-195912Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212023-03-29T13:30:30Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
HR Analytics and the decision-making process: an evidence-based management approach HR Analytics e o processo decisório: uma abordagem evidence-based management |
title |
HR Analytics and the decision-making process: an evidence-based management approach |
spellingShingle |
HR Analytics and the decision-making process: an evidence-based management approach Scaf, Amanda Analytics decision making process Business Evidence-based management Gestão por evidências HR Analytics HR Analytics Processo decisório |
title_short |
HR Analytics and the decision-making process: an evidence-based management approach |
title_full |
HR Analytics and the decision-making process: an evidence-based management approach |
title_fullStr |
HR Analytics and the decision-making process: an evidence-based management approach |
title_full_unstemmed |
HR Analytics and the decision-making process: an evidence-based management approach |
title_sort |
HR Analytics and the decision-making process: an evidence-based management approach |
author |
Scaf, Amanda |
author_facet |
Scaf, Amanda |
author_role |
author |
dc.contributor.none.fl_str_mv |
Vasconcellos, Liliana |
dc.contributor.author.fl_str_mv |
Scaf, Amanda |
dc.subject.por.fl_str_mv |
Analytics decision making process Business Evidence-based management Gestão por evidências HR Analytics HR Analytics Processo decisório |
topic |
Analytics decision making process Business Evidence-based management Gestão por evidências HR Analytics HR Analytics Processo decisório |
description |
HR Analytics (HRA) has gained attention from practitioners and scholars under the promise of providing basis for better decision making. However, the question regarding how HRA can be effectively used to support decisions in organizations remains answered. Although some suggest Evidence-Based Management (EBM) as the theoretical approach through which HRA would effectively contribute to decisions, the idea has not been empirically tested. Therefore, studys objective is to analyze how HRA leads to talent decision making through the EBM approach. Analysis of how HRA leads to decisions were grounded on (a) the structure of decision problems (PS), the stages of the decision-making process (DMP) where HR analytics centers its contributions, (c) the quantitative analytical methods (QAM) employed in data analysis and (c) the interaction among HR Analytics and EBM along the process. Basic qualitative research was employed to assess HR Analytics decision processes performed in organizations located in Brazil. The study relied on 8 semi structured interviews with professionals who have leaded or taken an important part in a HR Analytics decision process. Content and template analysis were employed as data analysis methods. It was found that PS and QAM were not decisive to shed light on how HRA leads to decision-making. The evidence-based management approach seemed relevant to (a) provide evidence needed to the execution of quantitative analysis and (b) to intermediate HRAs inputs to decisions. Results also shed light on the nature and different roles of these inputs. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11-10 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/12/12139/tde-23022023-195912/ |
url |
https://www.teses.usp.br/teses/disponiveis/12/12139/tde-23022023-195912/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Biblioteca Digital de Teses e Dissertações da USP |
collection |
Biblioteca Digital de Teses e Dissertações da USP |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
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1815257293555499008 |