I believe that a program of HR metrics and workforce analytics might prove essential through enactment in Regional Hospital. The drive would prove helpful for management, especially the HR department of the establishment in addressing pertinent underlining issues that affect the organization. Some of the factors in question include high risks of turnover and in explicit and implicit forms, the point of staffing problem. The top administration will thereby be capable of mitigating adversities accruing from costly labor which Regional Hospital witnesses.
For the opportunities regarding where and how metrics and analytics might be applied in Regional Hospital, I envisage construing benefits in sectors such as operational experiments, data mining, and predictive analysis. The first factor presents the most appropriate foundation of the decision-making process for HR, which would contribute to the effectiveness of operations. For the second factor, HRM and HRIS processes bear the foundation in catapulting the attribute to the knowledge of masses. Data mining involves singling out the existing patterns that facilitate the identification of unrecognized causal mechanisms (Sherief, 2017). The findings are essential in making decisions and would assist in future predictions inherent in predictive analysis.
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The three analyses and associated metrics that I think might be useful for consideration for Regional Hospital, in my opinion, are average revenue for an employee, cost per hire, and establishment of the average time to hire. The first factor can prove helpful in depicting the overall efficiency of the establishment by clearing the air on matters concerning the value and quality of the hired employees. The second attribute entails a reflection of the emerging costs that Regional Hospital would incur in hiring the incoming employees, coupled with the efficiency in the recruitment process. Lastly, the average time to hire captures the aspect mentioned above and the hardship when filling for a particular job position.
References
Kavanagh, M. J., & Johnson, R. D. (Eds.). (2018). Human resource information systems: Basics, applications, and future directions. Sage Publications.
Sherief, A., (2017). Mining dynamics: Using data mining techniques to analyze multi-agent learning. Journal of Intelligent Systems, 26(4), 613-624.
