So, the CEO comes to your office and asks you, the Talent Acquisition pro, “Which competitor’s employees do well when we hire them to work over here? And what’s the best university we recruit from? Last thing: Do marketing majors or communications majors seem to do better here?” I think most recruiting folks can probably answer those questions using some experience and insight. Good job.
What happens, however, when she drops this line on you as she leaves: “Good info. Send me that data by the end of the week, if you don’t mind.” Data? Holy smokes, you don’t have data. You pulled those answers from memory and trading stories with managers while in line at Starbucks. If you are anything like our team a few years back, you might not even know where to start. After some thinking, we came up with a good idea, but it was three years too late. Story of my life, by the way, but too often the story with HR and data.
Here’s the short version of what happened: the business hit an extended hiring spurt, the recruiting team fired on all cylinders, and the business was happy with the recruiting results. All good. Our clients were happy we were hiring lots of people, but we felt we needed to take a hard look at the now much larger operation and make some big picture decisions.
And there was the problem: we had too little data to perform any type of robust analysis. We were allocating recruiting dollars to sourcing efforts based on gut feelings and stories. We could not prove an idea right or wrong.
Here’s a simple example: Some people said Competitor A’s people were the best fit with us; others said Competitor B. No data, so no real answers. We also targeted a certain university, because there was a feeling that “we really liked” their graduates. We wanted to talk intelligently about recruiting strategy, but first we needed to do a deep dive into our data gathering tactics. For better decisions, we had to grab a lot more data right at the point of hire. We identified a series of data points to religiously track. This was not rocket science data work like they apparently do at the EPA (see pic)…it was a simple and very tactical solution to a problem.
Like a lot of data collection, though, it was a good idea three years too late, because we all know data needs to build.
After we got it, we could dive into strategy and look at promotion rates, attrition, leadership development enrollees etc., and we could see the correlation. Our big picture decisions just got better. Period. Allocating recruiting dollars? How about extra sourcing efforts targeted at Competitor D, because the stats show that their folks typically integrate better into the company? You could also show to the CFO that the referral program deserves more attention and funding, because referral hires get promoted 20% more quickly than any other source. How about more efforts at the school whose grads 80% of the time perform above average in their first year? You get the idea.
Getting data is typically not complex, but it can be labor intensive at the on-set, and that’s the hard part for some HR folks… the long investment and getting down in the weeds for a while to build the system. Trust me though, you’ll start making better decisions with solid data behind you, and the time spent deep diving will be worth it. Start gathering data early.
I have spent the last 20 years of my professional life advising leaders to make great talent decisions to drive business results. In my current gig, I lead talent acquisition and management for a multi-billion-dollar, 100% employee-owned construction company. I geek out on analytics, succession planning, etc. and love it when we position folks to do their best work. That’s fun stuff. I tease bad HR people, because I think we can all do better, myself included. That’s fun, too.