Going beyond basic Analytics: Making HR strategic
Advanced statistical modeling, data-based algorithms and analysis and its `predictive and prescriptive ability’ are hot requirements in the world of HR today.
Despite its process-driven approach HR has been largely dependent on the professional’s intuition. With increased focus on lowering the cost per employee, HR departments and consultancies are adopting a data driven analytics approach for greater accountability. Companies are increasingly relying on the strength this new data-based objectivity brings to businesses.
“The constant quest of `getting the right people for the right job at the best cost and time’ is getting more algorithm-based analytics,” says Yeshaswini Ramaswamy, e2e people solutions. “Corporates are looking to HR for a more strategic role in business operations. With this development the expectation today is to adopt a more data-based objectivity, a language that businesses understand, for the entire HR process.”
HR consultancies that have adopted this scientific method have been able to highlight the benefits of using data while making people decisions, thereby providing greater trackable objectivity. These processes are increasingly being incorporated by not just large MNCs and fast growing SMEs but even startups.
This data driven approach to HR management has given rise to a relatively new skill called HR analytics. Nearly 24 per cent organisations are seeking analytical skills while hiring HR personnel, according to a TimesJobs.com study.
Today, HR analytics is not just a simple head count or employee score or attrition data that HR was expected to do previously,” says Vishnu Sarja, HR head, Uniprof Technologies. “It is much more than simple tracking and evaluation that the HR departments were following previously.”
At the core of HR analytics lies data algorithms which are used today in making people decisions across an employee lifecycle. “HR analytics is a data driven approach that carefully analyses correlated data, which has been systematically collected through the employee’s work-cycle,” says Sarja. “A careful analysis of the data with suitable interpretation results in improved talent management decisions. Thus, it is not purely data management but effective interpretation of the available data.”
The HR community seems to be welcoming this new trend. “For quite some time now the HR community has been considered a core contributor to decisions directly impacting the company’s bottom-line. Now, with the ability to actually demonstrate the value-add that the various HR activities bring to the table, backed by data and analysis, the C-level are able to see the benefit that HR analytics brings to the top-line and the bottom-line,” says Ramaswamy.
HR analytics brings in a metrics approach which showcases aspects such as `efficiency-level analysis’ which also help in lowering the HR cost per employee. Several companies have taken this further and developed algorithms which are able to evaluate `efficiency metrics’ of employee engagement, satisfaction and retention.
“Extensive use of advanced statistical modeling and analysis enables `predictive analysis’, which goes a long way in providing information about employee requirement, satisfaction and retention. This, in turn, can be extended to provide prescriptive analytics which helps the management take preventive steps to address future employee issues,” says Sarja