HR analytics seems to be the latest buzz word within HR these days with its potential to transform HR practices, and the way HR is perceived in organizations. HR policies and processes have always played a huge role in business strategy, but quantifying their impact has always been a problem for human resources (HR) executives. Gut feeling and historical practices determine the answers to questions such as “Which method of performance appraisal will yield the best results?” or “What is the impact of training programs on the business' bottom-line?”
In a recent Economist Intelligence Unit survey of 418 global executives, an overwhelming 85% said that their HR team didn’t excel at providing insightful metrics. Historically, HR has been associated with soft skills such as communication and people management, rather than hard skills such as statistical analysis. However, as organizations move towards integrating HR strategy with business strategy, it becomes immensely critical to transform HR into a data driven function with the analysis of right kind of data, rather than just relying on guess work and adhoc spreadsheets. A 2014 HR Survey of CHROs also predicts 66 percent of the organizations are significantly increasing investments in Workforce Analytics. However, before getting started, there are certain fundamentals that organizations must be clear on. Some of these are:
Developing Clear Objectives
The business questions to be answered through analytics should be prioritized by the order of their impact. Crunching all HR data available, in order to identify patterns and correlations won’t yield effective results and hence, should be avoided. Experts suggest that companies should start with measuring simple metrics such as workforce diversity, attrition levels etc. over regular intervals of time to get an initial grasp on company position and eventually move on to solving complex issues such as finding the impact of training investment on profit margins.
Identifying Right Data To Provide Strategic Impact
Most of the organizations rely on data residing with ERP (Enterprise Resource Planning) systems for analysis. In most cases, it serves as a good starting point for deriving insights on recruitment, and performance. However, combining this data with data from exit interviews, employee engagement surveys etc. would lead to even better insights. Some of the important metrics can be overall talent retention rate, cost to hire talent, time to hire talent, revenue per full-time employee, diversity statistics etc. For more complex business problems, for instance, which kind of staff resolve customer queries most efficiently, HR data needs to be integrated with customer service data.
Incorporating Findings In Business Conversations
HR needs to make sure that there is a clear line of sight between HR metrics analysis and business profitability. In some cases, it is observed that HR department carries out the analysis regularly, but fails to present the results in a business context. An investment In HR analytics involves a lot of investment from the company, and hence, needs to prove its worth.
The Roadblocks
While analytics can deliver higher return on investment (ROI) in a standalone manner, HR departments in organizations are finding it difficult to synthesize “multiple unintegrated sources” of people and organizational data to build a comprehensive plan around this technology. One research study shows that more than 80% of HR professionals rate their ability to analyze data as “low” – a worrisome trend in a function that is now increasingly data-driven. In another study, 75% of surveyed companies believed that using people analytics was “important”, but only 8% believed that their organization was “strong” in this area.
Organizations must take cognizance of the fact that investing in people analytics is essential for gaining competitive advantage, and requires substantial investment at the earliest to get traction. However, they must also understand that analytics is no substitute for direct employee engagement, but just a supplemental tool to gain better insights. The need of the hour is to build a strong intersection between data and human behavior, so as to drive phenomenal results for the organization.