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Data Anlytics

Data Analytics techniques have been embraced by sales and marketing departments of companies to help improve their bottom line and marketing campaigns. Employee hiring has also significantly benefited from using data analytics. But the employee benefits administration function of HR has mostly been sluggish to adopt them.

Why is HR Slow to Adopt Data Analytics?

The main reasons for the slow adoption by HR are legacy practices and resistance to a deeper understanding of employees’ needs.

Third party hiring agencies are not constrained by the cultural norms and practices of the hiring companies, so they have utilized analytical techniques to maximize their revenue. But when it comes to managing benefits, companies have primarily stayed with tracking employees’ behavior through spreadsheets and other tabular data documents. Since these tracking documents vary from company to company, they have not been amenable to standard data analysis techniques.

Predictive analytics requires the utilization of more in-depth data. So it is not sufficient to know overall statistics like how many employees sign up for a particular benefit like child care. It is important to know the specific needs of each employee so that the company can offer benefits that have the greatest appeal and utilization. For example, with the rise in childhood anxiety disorders as reported by the National Institute of Mental Health, it would make sense for companies to consider offering benefits that address childhood anxiety disorders. But companies need to collect deeper data about their employees to be able to do this.

Bringing Data Analytics to HR Benefits

The critical component of analytics is data, so HR needs to emphasize data collection with benefits vendors. Historical data can be gleaned from existing vendors, but they should be incentivized to collect all the data that HR needs. Benefit vendor performance must be measured using KPIs. When hiring new vendors, their data collection and analysis capabilities should be a key criterion in selecting them. They should be able to provide data for all areas of benefit like medical, pharmaceutical, worker’s compensation, and FMLA requests.

A benefits program fine-tuned through data analytic techniques will lead to higher employee satisfaction and retention.