Traditionally, managers at the 20,000-employee company would contact HR and request the number of people they needed, and the department would call recruiters and kick in the employee-referral program. And then “you prayed a lot,” Hilbert says. By examining aggregate data on where people are hired from, how long they stay employed, how they fit in the corporate culture, and their level of individual productivity, “we’ve taken an art and we’ve made it a science,” he says. Using that data, Hilbert is able to figure out where the company can recruit the best talent at the most affordable price.
Valero can now determine for a specific project whether it’s best — not just financially but also from a strategic perspective — to recruit full-time, part-time, or contract workers, or to outsource the work entirely. Valero also keeps scorecards of which labor sources provide it with its most productive employees and tracks it over the year. An upgrade to the company’s HR Smart talent management software this year will also give the company a “global labor supply chain on demand,” Hilbert says.
The supply-chain approach to labor and detailed analysis of metrics also allow Valero to accurately forecast three years in advance its demand for talent by division and title. To accomplish this feat, the company dumped five years of historical people records into a huge database file, then consulted with Houston-based software vendor HLS Technologies to develop a series of mathematical algorithms for turnover trend analysis by location, position type, salary, tenure, and division.
Those trends were projected forward through another series of algorithms, at which time Hilbert added numbers for the anticipated workforce for future capital projects, new systems, and services. “For the first time, talent pipelines can now be developed years in advance to meet specific future talent needs,” he says. Training programs and succession plans can also be developed in advance. “It’s pretty revolutionary stuff,” Hilbert adds.
CoreStar Financial Group, a mortgage banking company with 190 employees based in Timonium, Maryland, wasn’t worried about its future talent needs, but it did want to improve the skills of the workers it already had. So CFO Tom Monteleone addressed a productivity problem with his sales-intensive employee base using metrics to help guide the decision-making process.
Monteleone collected data on the productivity of each customer-facing employee and crossed it with the “pull-through rate,” an industry KPI that measures how many customers who start the buying process actually complete it. He found that some workers were doing far better than others with their individual pull-through rates. Monteleone weighed several potential solutions, including changes to incentives, hiring, and training practices.
He worked closely with CoreStar’s vice president of retail sales, Kevin Ferguson, to gather data and simulate outcomes to determine which fixes would have the best business impact. “It’s about capturing as much data as you can and organizing it so it makes sense,” he says. “Something is going to stick, and you’re going to understand a new metric.” One option they considered, replacing the poor performers, was determined to be a dead end. Monteleone calculated that the company would lose about four weeks of productivity per person trying to replace a subpar performer and bring a new hire up to speed.