If you asked anyone who attended the HR Technology Conference this year what the buzz was all about, you’d probably hear about how data analytics are helping to dramatically improve HR’s influence in smart organizations.
Industry thought leaders Josh Bersin and Barry Libert delivered keynote speeches that touched on how forward-thinking organizations are embracing analytics to transform their HR solutions. There also was the news about ADP’s Benchmarking, powered by the ADP® DataCloud, which won awards for “Top HR Products” and “Awesome New Technologies.” And, ADP client Mark Berry, VP of Human Resources at CGB Enterprises, joined me for a discussion on “Quantifying HR with Advanced HR Analytics”.
Mark and I met 18 months ago when he started at CGB, a holding company with interests in the grain, transportation and insurance industries. Shortly thereafter, CGB started using the ADP DataCloud.
CGB’s Mark Berry and ADP’s Don Weinstein at the 2016 HR Technology Conference
The two critical issues the business wanted to address with the insights gained from analytics were these:
- The loss of talent in key job segments, especially recent college graduates in the first five years on the job.
- The overall cost of the workforce, which was outpacing the organization’s profitability.
The company needed to access benchmarking information to analyze if it was losing people at a rate greater than its industry peers, and whether it was at parity with respect to compensation both internally and externally.
Once CGB saw how its turnover and pay compared to industry peers, it then analyzed the factors associated with employee decisions to leave the organization so it could improve retention and reduce turnover.
This is really where predictive analytics like ADP’s new Turnover Probability solution come into play. ADP’s model draws upon aggregated and anonymized HR and pay data from the 30 million employees within ADP’s Big Data to enable companies to more accurately identify the likelihood of future voluntary turnover. By helping to identify those employees most at risk of leaving, the model helps eliminate the guesswork from identifying likely hotspots of attrition within an organization, and mitigates the business risk of losing valued employees in key jobs, departments and locations.
Of course, the more data you have the more robust your model and insights will be. When you layer our benchmarks on top of analytics, you gain the insight underneath. It’s not just arbitrary data but truly actionable.
According to Mark, ADP was the only company that could provide access to instantaneous key performance metrics based on such a vast customer and user data set.
Some lessons Mark shared from launching workforce analytics include:
1) Focus on the business and its needs. Analytics have no relevance if they aren’t focused on the critical issues that will drive significant outcomes for business leaders. Business support is critical.
2) Know your limitations and seek to overcome them. Technology isn’t a silver bullet to solve for issues, but having integrated HR systems helps.
3) Prove the theory. Show the value of the base investment in analytics to feed the next initiative. Build on your success!
4) Don’t be afraid to ask for help. A company’s IT, accounting, and supply chain units all have capabilities that can be leveraged.
5) Find the right partner. Having the right partner is critical, and being confident that they have your back is integral to success. Stop thinking that the vendor/client relationship is driven by an invoice. It’s driven by a key business need we’re trying to solve together.
The HR industry’s at the dawn of a massive change similar to where Marketing was about 10 years ago. “Show me the return on investment” is starting to be heard in HR as well! The key to getting the best ROI is having analytics at your fingertips and being able to democratize the data. By quickly sharing insights with front-line managers, everyone becomes more engaged and recognizes the insights that can be gained from Big Data to help drive business success.