Human resources touches every department across a company, and people are often a company’s most valuable – and expensive – asset.
Why, then, do so many companies make critical HR decisions – like realigning workers to fill shortages in-house versus hiring new workers with the necessary skill sets – without grounding those decisions in HR analytics?
Tim Ringo, a partner in London-based Maxxim Consulting, notes in a recent blog post for Harvard Business Review that many corporations are still using hunches or gut feelings instead of data analytics to make the tough calls related to HR.
“In my experience, organizations that use workforce analytics have the most engaged workforces and they thrive in tough conditions,” he says. “Most importantly, they do fewer headcount reductions because they have lean and efficient workforces to begin with.”
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Now that companies have slowly begun hiring again, here are three ways HR analytics can boost the bottom line:
Raise visibility. Creating a single view of all relevant workforce data is key to correctly aligning talent with the fluctuating needs of the business. For example, data might need to be viewed by business unit, product group and geography to find root causes, profit per employee or to compare compensation with performance.
According to an Aberdeen Group survey, top performing companies are using HR analytics to provide business leaders visibility into talent data. In addition, the survey found that 38% of the top performing companies say they have a single source of the truth for HR data compared to 17% of companies in the lowest performing category.
Align HR data with business data. According to the Aberdeen study, 59% of top performing companies aggregate employee data with business data compared to 28% of the lowest performing companies. Furthermore, 54% of top performing companies combine talent management data with business data compared to 30% of companies in the lowest performing category
In addition, a recent Accenture report found that high performing businesses – those that substantially outperform competitors over the long term and across economic, industry and leadership cycles – are five times more likely to use analytics strategically than low performers.
The Accenture study notes, for example, that if a retailer sees an opportunity around an ad promotion for a “smart” kitchen appliance, the retailer would need to know critical HR data like whether there are enough sales people trained in this complex product and staffed at the right stores at the right times. The retailer would also need to know if there are enough service staff trained to handle customers’ follow-up questions. This data is just as important as supply chain data related to how many appliances are on the shelf, Accenture notes.
Predict the future. Once a company bridges data silos to integrate HR data and business data to help achieve company goals, HR analytics can be used to predict future workforce outcomes. For example, McKinsey notes that Google uses HR analytics to predict the key behaviors that its best managers should have.
McKinsey also found that HR analytics has helped PNC Financial Services confirm its suspicion that its tendency to pick experienced outsiders over internal candidates hurts the bank’s bottom line. In fact, in a number of key job areas, internal candidates are more productive in the first year than experienced external hires. This allows the company to predict the success of future internal hires.
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