Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling

Detalhes bibliográficos
Autor(a) principal: Daum, Thomas
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/69618
Resumo: Data-driven decision making and well-developed analytical capabilities are generally perceived as fundamental for being a competitive organization nowadays. Nevertheless, especially publicly-led organizations show little agility towards technical advancement and face difficulties in developing necessary capabilities. The following case demonstrates how the Portuguese national body for employment and professional training, IEFP, engaged in a data-driven “profiling” model to combat long-term unemployment (LTU). The case walks the reader through the whole project-lifecycle, starting with IEFP´s previous touchpoints with data science over modeling and implementation of profiling, data curation, until managerial challenges which occurred along the way. The study reveals difficulties of a public organization linked to the usage of data-science and encourages students to look for ways on how to overcome those problems and push the progress forward.
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spelling Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profilingIEFPLong-term unemploymentData-driven decision-makingProfilingDomínio/Área Científica::Ciências Sociais::Economia e GestãoData-driven decision making and well-developed analytical capabilities are generally perceived as fundamental for being a competitive organization nowadays. Nevertheless, especially publicly-led organizations show little agility towards technical advancement and face difficulties in developing necessary capabilities. The following case demonstrates how the Portuguese national body for employment and professional training, IEFP, engaged in a data-driven “profiling” model to combat long-term unemployment (LTU). The case walks the reader through the whole project-lifecycle, starting with IEFP´s previous touchpoints with data science over modeling and implementation of profiling, data curation, until managerial challenges which occurred along the way. The study reveals difficulties of a public organization linked to the usage of data-science and encourages students to look for ways on how to overcome those problems and push the progress forward.Zejnilovic, LeidRUNDaum, Thomas2019-05-14T13:36:10Z2019-01-252019-01-25T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/69618TID:202225194enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:33:02Zoai:run.unl.pt:10362/69618Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:34:59.953570Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling
title Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling
spellingShingle Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling
Daum, Thomas
IEFP
Long-term unemployment
Data-driven decision-making
Profiling
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling
title_full Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling
title_fullStr Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling
title_full_unstemmed Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling
title_sort Human-machine systems vs. the unemployment spell: how IEFP embraced data-driven decision making with profiling
author Daum, Thomas
author_facet Daum, Thomas
author_role author
dc.contributor.none.fl_str_mv Zejnilovic, Leid
RUN
dc.contributor.author.fl_str_mv Daum, Thomas
dc.subject.por.fl_str_mv IEFP
Long-term unemployment
Data-driven decision-making
Profiling
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic IEFP
Long-term unemployment
Data-driven decision-making
Profiling
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description Data-driven decision making and well-developed analytical capabilities are generally perceived as fundamental for being a competitive organization nowadays. Nevertheless, especially publicly-led organizations show little agility towards technical advancement and face difficulties in developing necessary capabilities. The following case demonstrates how the Portuguese national body for employment and professional training, IEFP, engaged in a data-driven “profiling” model to combat long-term unemployment (LTU). The case walks the reader through the whole project-lifecycle, starting with IEFP´s previous touchpoints with data science over modeling and implementation of profiling, data curation, until managerial challenges which occurred along the way. The study reveals difficulties of a public organization linked to the usage of data-science and encourages students to look for ways on how to overcome those problems and push the progress forward.
publishDate 2019
dc.date.none.fl_str_mv 2019-05-14T13:36:10Z
2019-01-25
2019-01-25T00:00:00Z
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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