HR Analytics and the Implementation Imperative

Abstract

The adoption and implementation of human resources (HR) analytics typically stems from the need to address a specific and key business issue that requires measurement. Such a problem ought not appear hassle-free or expedient to measure, but rather crucial and salient. Put differently, the volumes of gathered HR data should not be the starting point of HR analytics, but rather the business needs that cry for an accurate and rapid solution. Therefore, HR analytics should abide by the pull phenomenon that starts from addressing a specific business case, such as the size and cost of workforce, productivity threshold and bottleneck, recruiting and talent retention. Following the pull phenomenon, the HR department collaborates with IT and data experts to deploy the best set of analytics to address the business problem that has been already identified. This collaboration is necessary to identify key causalities and develop and adjust key performance indicators that are best reflective of the issue at hand. Once these indicators and indices are properly identified and engaged, the business user or decision-maker just needs to monitor the accurate input of underpinning causalities of the problem. Concurrently, the HR team should install a sequential process for data gathering to feed the selected indicators. HR analytics cannot resume its function unless or until all these steps have taken place and are corroborated with a change plan that comprises specific actions for amending HR practices related to the business processes in which the bottleneck or the deficiency occurs. All in all, HR analytics intervention follows an iterative process that should be closely evaluated and measured to keep the focus on business priorities and communicate accurate intelligence that is actionable and in real time.