A strategic approach to workforce analytics: Integrating science and agility
Workforce analytics is a major emerging trend in human resource management. Yet, despite the enthusiasm, there exists a misunderstanding of how organizations can successfully use workforce analytics to achieve important organizational outcomes. This article proposes ways to overcome this execution d...
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| Vydané v: | Business horizons Ročník 61; číslo 3; s. 397 - 407 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Inc
01.05.2018
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| ISSN: | 0007-6813, 1873-6068 |
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| Abstract | Workforce analytics is a major emerging trend in human resource management. Yet, despite the enthusiasm, there exists a misunderstanding of how organizations can successfully use workforce analytics to achieve important organizational outcomes. This article proposes ways to overcome this execution dilemma and achieve organizational success with workforce analytics through the integration of agile development with scientific research. We use a number of company examples to outline five key parts of an agile workforce analytics process: (1) prioritizing issues, (2) integrating deductive and inductive approaches, (3) preparing and validating data, (4) applying multiple methods in concert to support decisions, and (5) transforming insight into action to improve business outcomes. |
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| AbstractList | Workforce analytics is a major emerging trend in human resource management. Yet, despite the enthusiasm, there exists a misunderstanding of how organizations can successfully use workforce analytics to achieve important organizational outcomes. This article proposes ways to overcome this execution dilemma and achieve organizational success with workforce analytics through the integration of agile development with scientific research. We use a number of company examples to outline five key parts of an agile workforce analytics process: (1) prioritizing issues, (2) integrating deductive and inductive approaches, (3) preparing and validating data, (4) applying multiple methods in concert to support decisions, and (5) transforming insight into action to improve business outcomes. |
| Author | Lengnick-Hall, Mark L. Lengnick-Hall, Cynthia A. McIver, Derrick |
| Author_xml | – sequence: 1 givenname: Derrick surname: McIver fullname: McIver, Derrick email: derrick.mciver@wmich.edu organization: Western Michigan University, 1903 W. Michigan Avenue, Kalamazoo, MI 49008, U.S.A – sequence: 2 givenname: Mark L. surname: Lengnick-Hall fullname: Lengnick-Hall, Mark L. email: mark.lengnickhall@utsa.edu organization: University of Texas at San Antonio, San Antonio, TX 78249, U.S.A – sequence: 3 givenname: Cynthia A. surname: Lengnick-Hall fullname: Lengnick-Hall, Cynthia A. email: cynthia.lengnickhall@utsa.edu organization: University of Texas at San Antonio, San Antonio, TX 78249, U.S.A |
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| Copyright | 2018 Kelley School of Business, Indiana University |
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| DOI | 10.1016/j.bushor.2018.01.005 |
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| Keywords | Advanced analytics Human resource management Agile development Workforce analytics |
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| References | Acito, Khatri (bib0005) 2014; 57 Barends, Rousseau, Briner (bib0010) 2014 Conboy, K., & Fitzgerald, B. (2004). Toward a conceptual framework of agile methods: A study of agility in different disciplines. In Ulrich, Dulebohn (bib0115) 2015; 25 Rasmussen, Ulrich (bib0090) 2015; 44 Available at Gaker, W. (2015, November 10). Pfeffer, J., & Sutton, R. (2011, September 3). Trust the evidence, not your instincts. Wright, P. M. (2008). Human resource strategy: Adapting to the age of globalization. Beck, K., Beedle, M., Van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., et al. (2001). Chen, Ravichandar, Proctor (bib0030) 2016; 59 Ward, Marsolo, Froehle (bib0120) 2014; 57 Guenole, N., & Ferrar, J. (2014). Active employee participation in workforce analytics. Marler, Boudreau (bib0080) 2017; 28 Souza (bib0105) 2014; 57 SHRM Foundation. (2016). Guenole, N., Feinzig, S., Ferrar, J., & Allden, J. (2015). Boudreau, Ramstad (bib0025) 2005; 44 Siegel (bib0100) 2013 (pp. 37–44). New York, NY: Association for Computer Machinery. Hirsch, Sachs, Toryfter (bib0065) 2015; 6 Lawler, E. E. (2015, May 20). Talent analytics: Old wine in new bottles? Ulrich (bib0110) 1998 Becker, Huselid, Ulrich (bib0020) 2001 Deloitte (bib0040) 2017 Kotter (bib0070) 1996 Earley (bib0045) 2015; 58 |
| References_xml | – year: 2013 ident: bib0100 article-title: Predictive analytics: The power to predict who will click, buy, lie, or die – year: 2017 ident: bib0040 article-title: Rewriting the rules for the digital age: 2017 Deloitte global human capital trends – volume: 44 start-page: 129 year: 2005 end-page: 136 ident: bib0025 article-title: Talentship, talent segmentation, and sustainability: A new HR decision science paradigm for a new strategy definition publication-title: Human Resource Management – volume: 57 start-page: 571 year: 2014 end-page: 582 ident: bib0120 article-title: Applications of business analytics in healthcare publication-title: Business Horizons – reference: Guenole, N., Feinzig, S., Ferrar, J., & Allden, J. (2015). – reference: (pp. 37–44). New York, NY: Association for Computer Machinery. – year: 2001 ident: bib0020 article-title: The HR scorecard: Linking people, strategy, and performance – volume: 57 start-page: 595 year: 2014 end-page: 605 ident: bib0105 article-title: Supply chain analytics publication-title: Business Horizons – volume: 59 start-page: 635 year: 2016 end-page: 644 ident: bib0030 article-title: Managing the transition to the new agile business and product development model: Lessons from Cisco Systems publication-title: Business Horizons – volume: 25 start-page: 188 year: 2015 end-page: 204 ident: bib0115 article-title: Are we there yet? What’s next for HR? publication-title: Human Resource Management Review – reference: Conboy, K., & Fitzgerald, B. (2004). Toward a conceptual framework of agile methods: A study of agility in different disciplines. In – volume: 44 start-page: 236 year: 2015 end-page: 242 ident: bib0090 article-title: Learning from practice: How HR analytics avoids being a management fad publication-title: Organizational Dynamics – volume: 57 start-page: 565 year: 2014 end-page: 570 ident: bib0005 article-title: Business analytics: Why now and what next? publication-title: Business Horizons – year: 2014 ident: bib0010 article-title: Evidence-based management: The basic principles – reference: . Available at – year: 1996 ident: bib0070 article-title: Leading change – reference: Guenole, N., & Ferrar, J. (2014). Active employee participation in workforce analytics. – reference: Gaker, W. (2015, November 10). – reference: Wright, P. M. (2008). Human resource strategy: Adapting to the age of globalization. – year: 1998 ident: bib0110 article-title: Delivering results: A new mandate for human resource professionals – reference: Pfeffer, J., & Sutton, R. (2011, September 3). Trust the evidence, not your instincts. – volume: 6 start-page: 7 year: 2015 end-page: 9 ident: bib0065 article-title: Getting started with predictive workforce analytics publication-title: Workforce Solutions Review – reference: SHRM Foundation. (2016). – volume: 58 start-page: 493 year: 2015 end-page: 500 ident: bib0045 article-title: Data analytics in auditing: Opportunities and challenges publication-title: Business Horizons – volume: 28 start-page: 3 year: 2017 end-page: 26 ident: bib0080 article-title: An evidence-based review of HR analytics publication-title: International Journal of Human Resource Management – reference: Lawler, E. E. (2015, May 20). Talent analytics: Old wine in new bottles? – reference: Beck, K., Beedle, M., Van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., et al. (2001). |
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| Snippet | Workforce analytics is a major emerging trend in human resource management. Yet, despite the enthusiasm, there exists a misunderstanding of how organizations... |
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| SubjectTerms | Advanced analytics Agile development Human resource management Workforce analytics |
| Title | A strategic approach to workforce analytics: Integrating science and agility |
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