Leveraging Predictive Analytics for Workforce Planning, Succession Planning, and Organizational Development

References

[1] Anderson, P., & Lee, J. (2019). Predictive analytics in organizational change management: A case study. Organizational Dynamics, 48(3), 45-52. https://doi.org/10.1016/j.orgdyn.2018.12.002

[2] Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency, 149-159. https://doi.org/10.1145/3287560.3287583

[3] Bose, I. (2020). Predictive analytics in human resource management: Transforming workforce planning. Human Resource Management International Digest, 28(3), 23-25. https://doi.org/10.1108/HRMID-02-2020-0023

[4] Boudreau, J. W., & Ramstad, P. M. (2007). Beyond HR: The new science of human capital. Harvard Business Review Press.

[5] Cascio, W. F., & Boudreau, J. W. (2011). Investing in people: Financial impact of human resource initiatives (2nd ed.). Pearson Education.

[6] Cummings, T. G., & Worley, C. G. (2014). Organization development and change (10th ed.). Cengage Learning.

[7] Davenport, T. H., & Harris, J. G. (2017). Competing on analytics: The new science of winning. Harvard Business Review Press.

[8] Gal, U., Jensen, T. B., & Stein, M.-K. (2020). Breaking the vicious cycle of algorithmic management: A virtue ethics approach to people analytics. Information and Organization, 30(2), 100302. https://doi.org/10.1016/j.infoandorg.2020.100302

[9] General Electric. (2019). Predictive analytics and organizational change: A GE case study. Retrieved from https://www.ge.com

[10] Harvard Business Review. (2013). How Google uses data to build a better worker. Retrieved from https://hbr.org

[11] IBM. (n.d.). AI and predictive analytics in HR: Transforming talent management. Retrieved from https://www.ibm.com

[12] Jones, A., Smith, K., & Lee, R. (2020). Building leadership pipelines with predictive analytics: A case study. Journal of Leadership Development, 12(4), 56-62.

[13] Kiron, D., Prentice, P. K., & Ferguson, R. B. (2014). Raising the bar with analytics. MIT Sloan Management Review, 55(2), 29-33. https://sloanreview.mit.edu

[14] Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR analytics. The International Journal of Human Resource Management, 28(1), 3-26. https://doi.org/10.1080/09585192.2016.1244699

[15] Microsoft. (2018). Empowering teams with data: Microsoft’s approach to organizational development. Retrieved from https://www.microsoft.com

[16] P&G. (2016). Procter & Gamble: Leadership development case study. Retrieved from https://www.pg.com

[17] 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. https://doi.org/10.1016/j.hrmr.2015.01.002

[18] Ulrich, D., Kryscynski, D., Brockbank, W., & Ulrich, M. (2017). Victory through organization: Why the war for talent is failing your company and what you can do about it. McGraw-Hill Education.

[19] Van den Broek, E., Sergeeva, A., & Huysman, M. (2021). When data practices become oppressive: The role of power asymmetries in people analytics. Organization Science, 32(3), 760-779. https://doi.org/10.1287/orsc.2020.1379

[20] Walmart Global Tech. (2022). Data-driven workforce management: Insights from Walmart. Retrieved from https://www.walmartglobaltech.com

@article{1706859,
      author = {Vivian Ntombizannele Gunda, Joshua Muzira},
      title = {Leveraging Predictive Analytics for Workforce Planning, Succession Planning, and Organizational Development},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {7},
      pages = {50-54},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706859.pdf},
      abstract = {In an era characterized by data-driven decision-making, predictive analytics has become a revolutionary instrument for Human Resources (HR). This paper analyzes the capacity of predictive analytics to revolutionize personnel planning, succession planning, and organizational development, enabling companies to anticipate trends, mitigate risks, and align their objectives with future demands. Utilizing advanced analytics, HR managers may predict workforce needs, recognize high-potential candidates for leadership positions, and improve organizational agility through focused development programs. The article discusses significant hurdles, ethical considerations, and optimal practices for the implementation of predictive analytics in HR, providing actionable insights for effective adoption. Ultimately, we analyze upcoming trends, such as the incorporation of artificial intelligence and real-time data, establishing predictive analytics as a strategic facilitator for developing resilient, future-ready businesses.},
      month = {January},
  }