Abstract
This chapter attempts to improve the understanding of how HR professionals can add value to decision making and improve business performance. We discuss human resource management (HRM ) practices , also known as high-performance work practices (HPWPs), and the role of human resource information systems (HRIS) and human resource analytics (HRA) in executing HR practices and workforce-related decision making. Based on our summary of the latest research, our findings suggest that where HRIS software can facilitate more efficient execution of HR processes by increasing the availability and delivery of HR information, HRA can enable the creation of novel insight into the impact of executed HR development initiatives, but can also identify new opportunities to improve the performance of key business activities. By starting from the identification of a business problem and then deploying appropriate descriptive, predictive, and prescriptive HR metrics and analytics to assist in solving the business problem, we find that HR professionals can create a level of value as yet discovered in but a few organizations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Beatty, R. W., Huselid, M. A., & Schneier, C. E. (2003). The new HR metrics: Scoring on the business scorecard. Organizational Dynamics, 32(2), 107–121.
Beer, M., Spector, B., Lawrence, P. R., Mills, D. Q., & Walton, R. E. (1984). Managing human assets. New York: Free Press.
Carlson, K. D., & Kavanagh, M. J. (2012). HR metrics and workforce analytics. In M. J. Kavanagh, M. Thite, & R. D. Johnson (Eds.), Human resource information systems: Basics applications and future directions (pp. 150–174). Thousand Oaks, CA: SAGE.
Cohen, D. J. (2015). HR past, present and future: A call for consistent practices and a focus on competencies. Human Resource Management Review, 25(2), 205–215.
Colakoglu, S., Hong, Y., & Lepak, D. P. (2010). Models of strategic human resource management. In A. Wilkinson, N. Bacon, T. Redman, & S. Snell (Eds.), The sage handbook of human resource management (pp. 31–50). London: SAGE.
Davenport, T. H. (2013). Analytics 3.0. Harvard Business Review, 91(12), 64–72.
Delery, J. E., & Doty, D. H. (1996). Modes of theorizing in strategic human resource management: Tests of universalistic, contingency, and configurational performance predictions. Academy of Management Journal, 39(4), 802–835.
Deloitte. (2015). Deloitte global human capital trends 2015. Deloitte University Press. https://www2.deloitte.com/content/dam/Deloitte/at/Documents/human-capital/hc-trends-2015.pdf.
Deloitte. (2016). Deloitte global human capital trends 2016. Deloitte University Press. http://www.workdayrising.com/pdf/Deloitte_GlobalHumanCapitalTrends_2016_3.pdf.
Dewett, T., & Jones, G. (2001). The role of information technology in the organization: A review, model, and assessment. Journal of Management, 27(3), 313–346.
Dulebohn, J. H., & Johnson, R. D. (2013). Human resource metrics and decision support: A classification framework. Human Resource Management Review, 23(1), 71–83.
Fletcher, C. (2001). Performance appraisal and management: The developing research agenda. Journal of Occupational and Organizational Psychology, 74(4), 473–487.
Garcia-Chas, R., Neira-Fontela, E., & Castro-Casal, C. (2014). High-performance work system and intention to leave: A mediation model. The International Journal of Human Resource Management, 25(3), 367–389.
Garvin, D. A. (2013). How google sold its engineers on management. Harvard Business Review, 91(12), 74–82.
Gorry, G., & Scott Morton, M. (1971). A framework for management information systems. Sloan Management Review, 13(1), 55–70.
Guest, D. (1997). Human resource management and performance: A review and research agenda. International Journal of Human Resource Management, 8(3), 263–276.
Higgins, J. (2014). Bringing HR and finance together with analytics. Workforce Solutions Review, 5(2), 11–13.
Huselid, M. A. (1995). The impact of human resource management practices on turnover, productivity, corporate financial performance. Academy of Management Journal, 38(3), 635–672.
IBM. (2015). Starting the workforce analytics journey: The first 100 days. New York: International Business Machines Corporation.
Katz, D., & Kahn, R. L. (1978). The social psychology of organizations (2nd ed.). New York: Wiley.
Kavanagh, M. J., Thite, M., & Johnson, R. D. (2011). Human resource information systems: Basics, applications, and future directions: Basics, applications, and future directions. London: SAGE.
Kroon, B., Van De Voorde, K., & Timmers, J. (2009). Cross-level effects of high-performance work practices on burnout: Two counteracting mediating mechanisms compared. Personnel Review, 38(5), 509–525.
Lawler, E. E., & Mohrman, S. A. (2003). HR as a strategic partner: What does it take to make it happen? Human Resource Planning, 26(3), 15–29.
Niu, L., Ju, J., & Zhang, G. (2009). Cognition-driven decision support for business intelligence: Models, techniques, systems, and applications. Berlin: Springer.
Patel, P., Messersmith, J., & Lepak, D. (2013). Walking the tight-rope: An assessment of the relationship between high performance work systems and organizational ambidexterity. Academy of Management Journal, 56(5), 1420–1442.
Pfeffer, J. (1998). The human equation: Building profits by putting people first. Boston: Harvard Business School Press.
Posthuma, R. A., Campion, R. A., Masimova, M., & Campion, M. A. (2013). A high performance work practices taxonomy: Integrating the literature and directing future research. Journal of Management, 39(5), 1184–1220.
Rasmussen, T., & Ulrich, D. (2015). Learning from practice: How HR analytics avoids being a management fad. Organizational Dynamics, 44(3), 236–242.
Silvester, J., Anderson, N., Haddleton, E., Cunningham-Snell, N., & Gibb, A. (2000). A cross-modal comparison of telephone and face-to-face selection interviews in graduate recruitment. International Journal of Selection and Assessment, 8(1), 16–21.
Simon, H. A. (1960). The new science of management decision. New York: Harper & Row.
Snape, E., & Redman, T. (2010). HRM practices, organizational citizenship behaviour, and performance: A multi-level analysis. Journal of Management Studies, 47(7), 1219–1247.
Spinks, N., Wells, B., & Meche, M. (1999). Appraising the appraisals: Computerized performance appraisal systems. Career Development International, 4(2), 94–100.
Stone, D. L., & Deadrick, D. L. (2015). Challenges and opportunities affecting the future of human resource management. Human Resource Management Review, 25(2), 139–145.
Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015). The influence of technology on the future of human resource management. Human Resource Management Review, 25(2), 216–231.
Stone-Romero, E. F., Stone, D. L., & Salas, E. (2003). The influence of culture on role conceptions and role behavior in organizations. Applied Psychology, 52(3), 328–362.
Straus, S. G., Miles, J. A., & Levesque, L. L. (2001). The effects of videoconference, telephone, and face-to-facemedia on interviewer and applicant judgments in employment interviews. Journal of Management, 27(3), 363–381.
Sullivan, J. (2014). A walk through the HR department of 2020. Workforce Solutions Review, 7–9.
Tootell, B., Blackler, M., Toulson, P., & Dewe, P. (2009). Metrics: HRM’s holy grail? A New Zealand case study. Human Resource Management Journal, 19(4), 375–392.
Ulrich, D., & Dulebohn, J. H. (2015). Are we there yet? What’s next for HR? Human Resource Management Review, 25(2), 188–204.
Wright, P. M., Gardner, T. M., Moynihan, L. M., & Allen, M. R. (2005). The relationship between HR practices and firm performance: Examining causal order. Personnel Psychology, 58(2), 409–446.
Wu, P., & Chaturvedi, S. (2009). The role of procedural justice and power distance in the relationship between high performance work systems and employee attitudes: A multilevel perspective. Journal of Management, 35(5), 1228–1247.
Yeung, A. K., & Berman, R. (1997). Adding value through human resources: Reorienting human resources to drive business performance. Human Resource Management, 36(3), 321–335.
Zhang, Z., & Jia, M. (2010). Using social exchange theory to predict the effects of high-performance human resource practices on corporate entrepreneurship: evidence from China. Human Resource Management, 49(4), 743–765.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 The Author(s)
About this chapter
Cite this chapter
Heimonen, J., Mattila, J., Kultalahti, S. (2017). Human Resource Intelligence—Enhancing the Quality of Decision Making and Improving Business Performance. In: Kohtamäki, M. (eds) Real-time Strategy and Business Intelligence. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-54846-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-54846-3_6
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-319-54845-6
Online ISBN: 978-3-319-54846-3
eBook Packages: Business and ManagementBusiness and Management (R0)