Prior To Beginning Work On This Discussion Forum Read 392829

Prior To Beginning Work On This Discussion Forumread Chapter 12 Inapp

Prior to beginning work on this discussion forum, Read Chapter 12 in Applied Psychology in Talent Management . Read the article Data Science and Predictive Analytics Enabling Better Hiring Mechanisms for Enterprises Links to an external site. . This article introduces predictive analysis and discusses the benefits of its use in helping to improve the quality of hiring, leadership development, and employee turnover. Research and read at least two additional articles on human capital predictive analysis. Using the two articles you researched on human capital predictive analysis as well as any of this week's required articles, discuss how predictive analysis is being used to help make human resource decisions.

Additionally, address how, as a manager, you might use predictive analysis to create a strategic global competitiveness from a company’s human assets. Be sure to give specific company examples to support your discussion and position on the topic. Your initial response should be a minimum of 200 words.

Paper For Above instruction

Predictive analysis has revolutionized human resource management by harnessing data science to inform strategic decision-making. In the context of talent management, predictive analytics involves analyzing historical data to forecast future HR outcomes such as employee turnover, leadership potential, and hiring success. The use of predictive models allows organizations to optimize recruitment processes, enhance leadership development programs, and reduce turnover rates, ultimately improving organizational performance (Lilian & Mahyudi, 2020). An example of this application is IBM's use of predictive analytics to identify high-potential employees and tailor personalized development plans, which has led to increased retention and productivity (Sharma, 2021).

Additionally, recent studies emphasize the importance of integrating multiple data sources, such as employee engagement surveys, performance metrics, and external labor market data, to refine predictive models further (García & Ramos, 2022). For instance, Google employs predictive analytics to identify traits linked with high job performance, enabling the company to select candidates more likely to succeed in roles (Bock, 2015). These insights guide recruitment decisions with enhanced precision, aligning talent acquisition with strategic goals.

From a strategic perspective, managers can leverage predictive analytics to build global competitive advantages by effectively managing human capital. For example, a multinational corporation like Unilever uses predictive models to forecast future talent needs across diverse markets, allowing the company to develop targeted training programs and succession plans (Kaufmann & Ellis, 2020). This proactive approach ensures the development of a versatile and skilled workforce capable of adapting to rapid market changes. Furthermore, predictive analytics can identify potential leadership pipeline members worldwide, ensuring that companies remain competitive across regions.

By integrating predictive analytics into HR strategy, managers can make more informed decisions that foster innovation, agility, and sustainable growth. For example, Microsoft employs data-driven talent management practices to predict future skills requirements and align workforce development accordingly, ensuring continuous competitiveness in the technology industry (Johnson & Thomas, 2019). Thus, predictive analysis in human resource management is vital for creating strategic, globally competitive organizations that capitalize on their human capital assets.

References

• Bock, L. (2015). Work Rules!: Insights from Inside Google That Will Transform How You Live and Lead. Twelve.
• García, P., & Ramos, V. (2022). Enhancing HR Decision-Making through Multisource Predictive Analytics. Journal of Human Resources Analytics, 8(2), 45-62.
• Johnson, R., & Thomas, E. (2019). Data-Driven Workforce Planning in the Tech Sector. Harvard Business Review, 97(4), 112-119.
• Kaufmann, L., & Ellis, D. (2020). Global Talent Management: Strategies for Competitive Advantage. International Journal of Human Resource Management, 31(7), 956-974.
• Lilian, R., & Mahyudi, M. (2020). Predictive Analytics in Talent Acquisition: Enhancing Recruitment Outcomes. Journal of Applied Soft Computing, 96, 106655.
• Sharma, R. (2021). Human Capital Analytics and Organizational Performance. Human Resource Management Journal, 31(2), 285-300.