Deriving public sector workforce insights: A case study using Australian public sector employment profiles

Ghosh, S; Zheng, Y; Lammers, T; Chen, YY; Fitzmaurice, C; Johnston, S; Li, J

Deriving public sector workforce insights: A case study using Australian public sector employment profiles

Ghosh, S Zheng, Y Lammers, T

Chen, YY Fitzmaurice, C Johnston, S Li, J

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, 10086 LNAI pp. 764 - 774
Issue Date:: 2016-01-01

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Field	Value	Language
dc.contributor.author	Ghosh, S	en_US
dc.contributor.author	Zheng, Y	en_US
dc.contributor.author	Lammers, T https://orcid.org/0000-0003-1000-2395	en_US
dc.contributor.author	Chen, YY	en_US
dc.contributor.author	Fitzmaurice, C	en_US
dc.contributor.author	Johnston, S	en_US
dc.contributor.author	Li, J https://orcid.org/0000-0003-1833-7413	en_US
dc.date.issued	2016-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016, 10086 LNAI pp. 764 - 774	en_US
dc.identifier.isbn	9783319495859	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/100172
dc.description.abstract	© Springer International Publishing AG 2016. Effective approaches for measurement of human capital in public sector and government agencies is essential for robust workforce planning against changing economic conditions. To this purpose, adopting innovative hypotheses driven workforce data analysis can help discover hidden patterns and trends about the workforce. These trends are useful for decision making and support the development of policies to reach desired employment outcomes. In this study, the data challenges and approaches to a real life workforce analytics scenario are described. Statistical results from numerous workforce data experiments are combined to derive three hypotheses that are useful to public sector organisations for human resources management and decision making.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-319-49586-6_55	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Deriving public sector workforce insights: A case study using Australian public sector employment profiles	en_US
dc.type	Conference Proceeding
utslib.citation.volume	10086 LNAI	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	10086 LNAI	en_US

Abstract:

© Springer International Publishing AG 2016. Effective approaches for measurement of human capital in public sector and government agencies is essential for robust workforce planning against changing economic conditions. To this purpose, adopting innovative hypotheses driven workforce data analysis can help discover hidden patterns and trends about the workforce. These trends are useful for decision making and support the development of policies to reach desired employment outcomes. In this study, the data challenges and approaches to a real life workforce analytics scenario are described. Statistical results from numerous workforce data experiments are combined to derive three hypotheses that are useful to public sector organisations for human resources management and decision making.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/100172