23 January, 2017
HR Analytics: The Next Frontier
If you are looking to embark on the human resources (HR) analytics journey, look no further than the good old recruitment process.
Once the process starts, recruiters use the recruitment brief and their judgement to shortlist candidates for interviews. Firms typically have huge amounts of historical data on employees who have performed well and those who have not. This clustering of employees can serve as a benchmark in selecting new ones. Top employees outperform average employees by up to eight times, so historical data has great potential.
The interview process has various stages and there are dropouts in every stage. The questions to be asked are: what stage sees the most dropouts and why? Is it due to of low compensation figures, or is the process is taking too long? If low compensation is the reason, what is the delta that will lead to better salary elasticity?
Among those that are hired many drop out in the first six months. The questions here are: what made them quit, and how can the firm identify the kind who are likely to leave soon?
These questions indicate how data-led approaches can help transform the recruitment process. There are opportunities that lead either to process improvements—the domain of efficiency—or to better HR decisions—the domain of effectiveness. An analysis by McKinsey and Co. found recruitment efficiency can be improved up to 80%.
Enterprises can tap the mountains of data they capture to foster new ways of decision making. For instance, the increasing availability of employee data in core IT applications is stimulating a fact-based approach to improve HR decisions.