Reimagine Employee Referrals

May 2, 2013 Michael George

employee referralIn our last “Reimagine HR” post we discussed ways to reimagine your talent sourcing effort so that recruiters not only understand your organization’s current talent supply and future demand, but are also actively using cloud, mobile and social technologies in ways to uncover hidden sources of top talent and/or networks of job candidate referrers.

This week, we are going to dig a little deeper into some emerging science around the value of sourcing talent through employee referrals. That’s right, science.

It has long been accepted that hiring a new worker who is recommended by a current employee ups the chances of a good hire over a non-referred candidate. It isn’t difficult to understand why this is the case. Conventional wisdom tells us that current employees understand the company, culture and most likely the nature of the job, and often have direct work experience with the person they are recommending. This allows them to see a “fit” based on a number of factors that go beyond what’s on the job requisition or candidate resume – those intangibles that are hard to quantify but make someone successful in your company.

Equally important is the psychology behind the referral, as both the current employee and new hire have a stake in being right about that fit (even when it turns out to be a mismatch), and will often try to make things workout, where a non-referred candidate is more likely to leave (or be let go) on first sign of trouble.

And, in fact it is true that employee referral programs pay off in a number of key metrics, including reduced time-to-fill, reduced cost-to-fill, improved applicant-to-hire ratio, increased length of employment (retention), and overall profitability (revenue per employee) over any other source.

So naturally, as mentioned in the last post, you’ll want to expand your employee referral program to tap into your current employees’ social networks, right?

Well, here’s where the science may have you rethinking the traditional approach. It turns out the referral payoff comes almost entirely from the company’s top performers. In other words, a recommendation from an average performer doesn’t lead to a more profitable hire and getting a referral from a below average worker can actually be worse than hiring with no referral at all!

In their new research paper, “The Value of Hiring Through Referrals,” authors Stephen Burks, Bo Cowgill, Mitchell Hoffman and Michael Housman suggest companies may want to trade in some of that “conventional wisdom” for some hard-core Big Data analysis.

Steve Lohr wrote a great column in the Sunday New York Times, entitled Big Data, Trying to Build Better Workers, and a great follow up blog post on the topic which he called Scientific Management Redux: The Difference Is in the Data, both worth a read.

In his blog post Mr. Lohr quotes one of the paper’s authors, Stephen Burks, an economist at the University of Minnesota as saying, “The previous work on worker referrals has been mostly anecdotal and impressionistic. It hasn’t been quantified in this way before, the way you can with these rich data sets.”

These “rich data sets” refer to what can be gleaned from an emerging discipline some are calling “workforce science.” Workforce science can be best described as bringing big analysis to Big Data in the field of HR, creating discipline around hiring, promoting, and career planning, which has traditionally relied on managers’ gut feelings about their employees.

In his Sunday Times article, Lohr quotes Peter Cappelli, director of the Center for Human Resources at the Wharton School of the University of Pennsylvania as saying, “This is absolutely the way forward, most companies have been flying completely blind.”

Analyzing workforce data is nothing new, nor is looking for correlations in worker behavior or measuring key performance indicators to build a profile of what a top performer looks like in a given environment. What has changed is the amount of data available to analyze both inside and outside of the organization. Every online interaction including email, chat, status updates – virtually every mouse click – leaves a digital trail.

In the past, organizations were limited to the number of interactions they could analyze by their own employee population, resulting in more guesswork than science. However, with today’s cloud- and mobile-based HCM technologies, hundreds of thousands of employee interactions can be mined for patterns and behaviors in detail not previously imagined in an aggregated way that doesn’t compromise employee privacy. And as any statistician will tell you – sample size matters.

Companies like Evolv and Knack are beginning to tap into the power of workforce science.

Evolv helps organizations tap into, and use, real time performance and attrition data measured across millions of workers to find the skills, attributes and dispositions that make hourly employees succeed. And Palo Alto based Knack uses a combination of online and mobile games, and massive amounts of data to help users discover their unique combination of strengths, talents and personality traits, which in turn is helping some of the world’s leading companies unlock their own “knack” for success and innovation.

This brings us back to improving your referral program. If your top performers are your best source for referral candidates, you may want to rethink (and expand) exactly what kind of information goes into building comprehensive profiles of your organization’s top performers. With new Big Data tools, and a workforce science approach, you may just discover things like an employees’ number of friends at work, frequency of online social interactions, or the types of blogs read provide far more predictability of top performance and success than one’s skills, competencies or work-related experience.

Workforce science is in its early stages, but Big Data is here today. You are creating some by accessing this blog post right now. Clearly it says you are a thought leader! Begin thinking of ways to use all of the interactive data being generated by your workforce, even if you aren’t collecting and storing it today. As Lori Asburry previously blogged about, Big Data Analytics for Workday is closer than you think.

At Appirio, we help organizations reimagine what’s possible in their business with emerging technology, then help them make it a reality. If you’re reimagining ways to use HR Big Data, let us know by giving us some feedback in the comment section below. If we’ve learned one thing it’s that our customers have big imaginations, and no idea is too crazy – share yours!

Previous Article
Jeff Epstein on Board at Appirio
Jeff Epstein on Board at Appirio

By Chris Barbin Today, Appirio announced that Jeff Epstein has joined our Board of Directors as Chair of ou...

Next Article
Customers Speak Out About “Going Google”
Customers Speak Out About “Going Google”

By David Salyers (@davesalyers) What does real estate, modern furniture, movies and CRM software have in co...