The Potential and Challenges of Workforce Analytics

by   |   September 20, 2012 6:40 pm   |   0 Comments

Geri Green of The Results Companies

Geri Green of The Results Companies

For The Results Companies, finding thousands of contact center operators every year to fill positions scattered at 14 locations around the world was “a little daunting at times,” recalls Geri Green, chief marketing officer of the Dania Beach, Fla.-based business process outsourcing firm. “It’s a challenge to figure out how to identify and hire the right people with the right skills.”

So The Results Companies turned to workforce analytics for help. Now armed with sophisticated computer algorithms, historical performance data and personality tests, the company has not only improved its ability to identify top-notch candidates but has slashed attrition rates, revamped its business processes and cut recruitment costs.

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Welcome to the brave new world of HR analytics. Enterprises like The Results Companies are fast discovering the value of HR analytics technology and its potential to improve employee satisfaction, boost retention rates, even flag star performers before they reach their prime. That’s because HR analytics software uses advanced computer models, populated with HR data from personality type to training history, to predict employee success, measure performance, identify prime candidates and analyze market trends.

Deep-pocketed vendors are taking note of HR analytics’ predictive powers. In August, IBM announced its acquisition of talent management software provider Kenexa for a whopping $1.3 billion. Tech titans SAP and Oracle have also jumped in on the action earlier this year with their purchases of SuccessFactors and Taleo, respectively.

With big-name players scooping up companies for their talent analysis capabilities, and a slew of smaller providers like Visier and Evolv drawing attention, talent management has grown into a $4-billion industry.

But for all the activity in the marketplace, there is a lagging sense among executives that they have the competence to use these analytics tools. Only 6 percent of worldwide HR teams feel they are “experts” on the use of analytics in talent management, according to a report from human resources research firm Bersin & Associates. In fact, only 20 percent believe that the data they capture now is highly credible and reliable for decision-making in their own organization.

That’s a shame, according to Charles Goretsky, a principal consultant with Bersin & Associates, who believes that many HR teams are missing “an enormous opportunity to build models that can predict what their business needs are going to be.” Rather than examine past performance of employees, Goretsky says if leveraged properly, HR analytics can act as a crystal ball, enabling companies to anticipate who will and will not be top performers, predict workforce trends and increase returns on HR investments.

Predicting Job Satisfaction
None of which is news to The Results Companies which deployed Evolv’s workforce analytics solution nearly two years ago. Today, job candidates partake in an online assessment that measures everything from skills and personality traits to working style and motivation. Using sophisticated computer algorithms, the system identifies applicants that share the same characteristics, certifications, training experience, education and skills sets as other highly successful contact center operators and customer service representatives.

For example, an HR analytics system can comb a company’s data for factors such as which training programs are most likely to produce top earners, the personality traits most embodied by leaders and how driven a job seeker is on a scale from 1 to 10. By crunching these numbers, the system can identify the job seekers that are not only most likely to excel, but least likely to quit.

“A lot of what we’re predicting is job happiness which equates to longevity,” says Green. “Attrition is one of the most expensive things that we have to deal with as a company.” In fact, since deploying Evolv late last year, The Results Companies has reduced attrition rates by nearly 35 percent, saving replacement costs of “hundreds of dollars per employee – money that goes right to the bottom line,” says Green.

Better matching candidates to job positions has also helped The Results Companies boost performance rates by 20 percent and improve revenue per agent by 4 percent. So too has HR analytics improved recruitment processes: whereas in the past The Results Companies sought out candidates with contact center experience, Green says the company learned “that previous call center experience was not an indicator of success – the data did not support it at all.” All of which has helped broaden the company’s pool of potential candidates.

Combination of Data Sources Add to Insight
The benefits Green cites from her experience are higher than HR executives typically achieve, observers note. So what enables businesses like The Results Companies to reap real business value from HR analytics where so many others continue to stumble? For one, many companies make the mistake of only measuring employees’ past performance rather than collecting vital data about a job candidate’s personality and motivations.

Employees Are Multidimensional

Experts say considering a combination of factors helps analytics systems to assess an employee’s fit and long-term value to an organization. Sources can include:

  • Measurements of past performance
  • Insights into an employee’s sense of curiosity
  • Insights about an employee’s alignment with business objectives, such as improved productivity
  • Insights about the employee’s contributions from other applications such as CRM systems

“The chocolate-peanut butter moment is really getting information about a candidate directly and what he’s predisposed to do, combining this with performance metrics and finding out if there are any correlations between the two,” says Greta Roberts, CEO of software provider Talent Analytics, and a faculty member of the International Institute for Analytics.

For example, by determining just how curious a particular employee is, and entering this data into an HR analytics system populated with historical data, a company can predict a candidate’s performance in a particular role such as a customer service representative or sales professional.

Another strategy: aligning HR analytics with business objectives so that the information you’re gathering about employees is data that can actually improve productivity, reduce attrition and cut costs. “HR analytics needs to be about decision support,” says Goretsky. “That’s one of the most important things HR can do: to produce information and put it in the hands of managers so they can better manage people.”

But that’s not all. HR analytics shouldn’t be implemented in a vacuum. Instead, Roberts says it’s critical that companies integrate their analytics systems with complementary solutions such as sales automation systems and customer relationship management technology in order to enrich their data pool.  “People can get more out of their HR metrics by combining it with additional data sets,” says Roberts.

Of course, an HR analytics system that touches multiple reservoirs of data across an organization is a complex endeavor. But if it’s to provide a truly competitive advantage, and not simply serve as an HR chore, experts say it’s critical that companies create a cross functional team dedicated to the practice of predictive analytics.

“You can’t jump ahead, buy an HR analytics system and start using it,” warns Goretsky. “You have to have the skill sets in HR or an analytics team.”

Cindy Waxer is a Toronto-based freelance journalist and a contributor to publications including The Economist and MIT Technology Review. She can be reached at cwaxer@sympatico.ca  or via Twitter @Cwaxer.

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