Staffing Problem Solution: HR Metrics and Workforce Analytics

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Introduction

HE metrics program and workforce analytics will play a significant role at Regional Hospital, especially when it comes to improving quality of care and performance efficiency. According to Kassick (2019), HR metrics are data (numbers) that provide descriptive detail about given processes or outcomes (p. 55). Therefore, the metrics will guide the facility in solving its staffing problem. By using workforce analytics, the organization will be able to audit its HR initiatives and measure their success.

Opportunities Regarding How Metrics and Analysis Might Be Applied

There are several opportunities regarding how and where the metrics and analytics might be applied as far as Regional Hospital is concerned. For instance, the two can be applied in data gathering on the number of employees reporting to different shifts (morning, evening, and night). The same extends to the number of patients seen by care providers during each shift. Workforce analytics will help identify different patterns of matching optimal skills in relation to available employees. The idea is to ensure that employees are assigned appropriate shifts for an optimum outcome.

Three Analyses and Associated Metrics

The first analysis to consider is data mining, which will guide the facility in addressing the staffing problem. This will be achieved through enhanced decision-making where key patterns in the data set will be identified with the help of correlations and multiple regression methods (Durai et al., 2019). Regional Hospital, as a result, will be able to identify any existing causal mechanisms. Second, a productive analysis will facilitate the process of developing models of organizational systems needed to examine the impact of introducing new changes. The last type of analysis is operational experiments, the role of which will be to inform the facility regarding the best approach toward implementing HR metrics program within the organization.

Benchmarking

While benchmarking remains a critical component of organizational success, it might prove ineffective for Regional Hospital. The possible reason is that benchmarking, if adopted, will not help the hospital resolve the problems associated with its staffing issues due to different functions undertaken by different departments. More importantly, direct comparison of HR benchmarking with other organizations might fail to provide realistic evidence of relative standing, nor give guidelines for forecasting the potential effectiveness of the actions (Durai et al., 2019, p. 3). Overall, the HR departments vary widely, thus, making it difficult to undertake benchmarking.

Developing a Program of HR Metrics

Regional Hospital managers should strive to understand the existing differences between HR metrics and workforce analytics before they develop a program that integrates them. Similarly, they need to have an insight regarding the issues that ought to be addressed. This, in return, will help them apply the appropriate metrics and workforce analytics. Most importantly, the managers must consider the context of the data if they are looking forward to successfully applying analytics to the problem.

Possible Problems with Establishing HR Metrics

The process of establishing an HR metrics and workforce analytics program is not without its problems. First, the team must understand that the number of metrics used does not determine the outcome or success. Managers must understand that metrics provide limited information that could be used to identify a problem within the organization. However, the challenge lies in the fact that there is no clear basis of which metrics are more effective (Durai et al., 2019). Second, assessing and reporting HR metrics does not result in better organizational performance.

References

Durai D, S., Rudhramoorthy, K., Sarkar, S. (2019). HR metrics and workforce analytics: it is a journey, not a destination. Human Resource Management International Digest, 27(1), 4-6.

Kassick, D. (2019).Workforce analytics and human resource metrics: Algorithmically managed workers, tracking and surveillance technologies, and wearable biological measuring devices. Psychosociological Issues in Human Resource Management, 7(2), 55-60.

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