Analytics can help determine the value of your workforce.
By Michael Housman
Recruiting is big business. U.S. employers collectively spend nearly $124 billion a year on recruiting, and almost $6 trillion on payroll. With that level of spending, small improvements in outcomes can easily be worth billions or tens of billions of dollars.
Yet, recruiting has largely been an unmeasured process, wherein recruiters screen candidates by their own criteria, including work experience and academic achievement—historically poor predictors of candidate quality. Once hired, systems are seldom in place to measure or track quality of hire in order to continuously improve the recruiting process.
With quality of workforce becoming increasingly critical as a differentiator and a source of competitive advantage, HR professionals must ensure they deliver the best candidates for the money. The most sure-fire way to do this is by using a data-driven approach that leverages quantitative metrics to measure, analyze, create, and sustain a more productive workforce.
Data Analysis Matters
How important is data analysis? Target certainly feels it’s worthwhile. To better understand how to market new products to its customers, analysts at the retailer studied years of customer purchase data to look for patterns that would help them predict the future. What they found was a way to spot pregnancy in the first trimester, based on changes in a woman’s buying behavior. Target identified about 25 products, including scented lotion, cotton balls, washcloths, and hand sanitizer that, when analyzed together, enabled the retailer to assign each shopper a “pregnancy prediction” score and come up with an estimated due date. With this information, Target sent coupons to shoppers timed to very specific stages of pregnancy.
The retailer’s strategy was to entice these women or their husbands to visit Target to buy baby-related products, after which the company’s cue-routine-reward calculators could kick in and start pushing them to buy groceries, bathing suits, toys, and clothing as well. Soon after the new ad campaign began, Target’s mom and baby sales exploded. Between 2002 and 2010—when Target began engaging in targeted marketing campaigns using this type of statistical analysis—Target’s revenues grew from $44 billion to $67 billion.
HR leaders, take note. The amount of money that can be saved for an organization through the use of data analytics is immense. Small changes on the margin that result in sales or productivity increases of just a few percentage points can be worth significant amounts of money. And often they are as easy to find as looking at what kind of lotion a woman purchases.
So how can HR leaders help their companies make the needed changes toward a data-driven approach to workforce development? Three steps are key:
1. Gather data on how hiring programs and new employees are performing. Specifically, organizations need to measure the actual outcomes of the people they hire. Are they staying on the job? How productive are they? What percent of new hires are meeting expectations for performance? What are the performance characteristics of great hires vs. bad hires?
2. Use this performance data to develop a quantitative score for quality of hire. This is especially important for high-volume positions. Having a score for quality of hire creates the core measurements against which all other hiring activities can be judged. It also enables incentives to be set that align recruiters with organizational goals.
3. Track and manage the recruiting process to ensure that the screening tools and process are delivering against their objectives. The screening needs to be proven to be predictive, and the recruiting organization needs to be held accountable for hiring top performers. These data can be used to evaluate its efficacy, identify best practices, and continually raise the bar.
Once companies grasp how to use data and analytics to better understand their workforces, they can take a deeper dive into analytics to gain insight into all aspects of their recruiting process, and to drive further changes and improvements.
Taking the Analytics Plunge
Though the terms “big data” and “analytics” are common buzzwords, it can be difficult to understand how exactly employers can use data analytics to improve their screening and recruiting process. Here are a few examples.
• Use data to optimize sourcing decisions and budgets. Most employers have specific places they post/recruit for jobs, whether that be Craigslist, Monster, job fairs, etc. Yet, HR seldom knows the true effectiveness of these sources. In order to optimize the sourcing budget, HR can use analytics to decipher how much they are spending on each source and how many applicants/hires each of those sources yield. The goal is to minimize the cost per applicant/hire.
• Pay for performance, not just for applicants. The book Moneyball made the point that managers weren’t really paying for ballplayers; they were actually paying for wins. In this context, HR needs to be thinking not just about how much it pays for an applicant, but how much it pays for an employee day, or ideally, how much HR pays to handle a single call. By merging data on sourcing budgets, each employee’s source, and that employee’s performance, HR can determine which source gives HR the most “bang for its buck.”
• Evaluate the efficacy of employee referral programs. Another place
where analytics can shed light on recruiting is employee referral programs. Analytics enable organizations to measure and understand how referral bonuses vary by site and how those differences yield different outcomes in terms of the number and quality of employees that are referred by existing employees. By evaluating natural variation in referral programs, HR can answer a central question: What is the optimal referral bonus that my organization should offer to employees?
• Evaluate the effectiveness of recruiters. Just as an organization’s employees display a tremendous amount of variation in terms of their performances, so do its recruiters. Analysis can show that some recruiters are extraordinarily skilled at identifying and hiring top talent, while other recruiters aren’t nearly as good. Through analytics, HR can adapt methods that assess employee performance to the company’s recruiter population, in order to determine which recruiters are the very best, and then try to understand what makes them so skilled.
• Make sure your recruiters are using the right selection criteria. Recruiters often use their own criteria when selecting applicants, but it’s unclear whether the characteristics they look for are predictors of employee performance. For example, Evolv analyzed data for one company with 20,000 employees and found that no relationship existed between previous work history and future employment outcomes. Recruiters that screen out “job jumpers” and unemployed applicants eliminate approximately 2 to 6 percent of all applicants for limited reasoning. HR can engage in similar analyses to determine what applicant characteristics are the strongest predictors of performance.
• Understand your applicant shelf life. HR can use similar methods, coupled with data from an applicant tracking system, to understand whether the quality of a company’s workforce improves or declines depending on how long recruiters take to contact, interview, and hire applicants. Evolv research has shown that the best applicants have a very short shelf life, indicating that HR should reach out to the top candidates as quickly as possible because they are receiving competing offers and will disappear quickly from the applicant pool.
New technologies and rapidly advancing analytics are changing the nature of the contribution that HR can make to an organization. These advances enable companies to predict employee performance, engagement, and retention as a function of various inputs. By doing so, HR is able to quantify the quality of the hourly workforce, then deliver insight and drive action to improve the recruiting process and overall workforce performance. With quantitative metrics and a focus on the strategic impact of a more productive workforce, the recruiting function is sure to become one of the key drivers of organizational success.
Michael Housman is managing director of analytics at Evolv.