HR departments have always had access to data of people in large organizations, and data scheduling and analysis has been done for the purpose of understanding patterns and trends of employee behavior. Moving away from providing operational support to the business, the HR function is now seen as a strategic function. What is different in today’s current context is the use of digital technology in HR and the ability it provides to the HR function to aggregate large amounts of data, build models for insightful analysis and use this for real-time decision making. The HR function is slowly becoming a data-driven function especially in large companies that are starting to use analytics tools effectively to enhance their effectiveness and support work teams.
Every aspect of the HR function provides scope for the application of HR analytics and relies on the organization’s critical needs to select areas in which analytics can play an important role. Employee turnover is a major area of concern for most. In order to enhance employee retention, it may be useful to analyze factors that may lead to exits, growth opportunities, promotion prospects, compensation, and organization culture and to build appropriate data models that will help in extracting insights.
HR analytics can support the personalization of learning paths and the improvement of job content based on matching the competencies required for the job with the identified skills. Such practices would reduce the outsourcing of certain skill sets and the resulting high costs and increase the longevity of employees in the organization. Predictive analytics can also help identify the success factors of teams and determine which teams are most likely to achieve the most, given their working, collaboration, and communication styles.
HR metrics contribute to business value; However it must align with business needs. Therefore, the HR analytics process should begin with the stated business objective followed by the identification of metrics that will define business objectives. Next, collect and analyze the data that leads to gaining insights. Finally, communicate about the impact of these ideas on the organization. Oftentimes, while the HR function wants to use predictive HR analytics, there is limited consumption and resultant actions and HR efficiency is restricted.
In order to deliver HR analytics, prerequisites must be in place. This includes data selection, purification, data quality assurance, creating appropriate models that can answer senior leadership inquiries, and willingness to experiment, as well as investing in analysis tools. The shift from reactive to proactive ways of working will be possible with the help of powerful analytics. It should be possible to build a strong case for investing in HR analytics through measures such as enhancing productivity, lowering costs, enhancing employee engagement, reducing voluntary exits, enabling a culture of learning, accelerating turnover or reducing employee turnover. To be able to demonstrate financial value and ROI, it is important to integrate HR data with other applications such as blending employee engagement with financial benchmarks or employee retention with high customer satisfaction scores that would be a strong case. In order to make organizations ready for the future, leaders must be able to embrace technology and analytics.
The writer is Chairman of Global Talent Track, a corporate training solutions company