Analyze Your Workforce: People First, Numbers Second

Can you be a people person and a numbers person at the same time? If you’re an HR person, it doesn’t really matter whether you can or can’t. Sugarcoat it as much as you want, but in the realm of business, people are first and foremost numbers. And understanding those numbers – like, really understanding them – has a lot to do with which organizations advance and which organizations decline. If you’re an HR person still wondering whether you need to be good at numbers, let me help you decide: you do.

The Human Resources Executive 15^th Annual HR Technology Conference #HRTechConf was a lot about big data this year.  Big data isn’t just about data. It’s about how you do something with it. It’s about bringing data to life – making it jump from the page where it has sat for so many years and just stared back at us. If you can’t draw conclusions, connect dots, or tell a story from the data you’re giving, that data is dead.

So all of this starts with a workforce analytics initiative. It doesn’t have to be big, it doesn’t have to be complex, and it certainly doesn’t have to define you. But you have to get started. According to a presentation given by Brian Kelly with Mercer at the conference, here are some things to know and tips to bear in mind as you start your own workforce analytics initiative.

• Surprisingly, workforce analytics is still a new and emerging science – no one has really figured it out yet, so you’re in good company.
• Above all else, it is about getting the business leaders the data they need – not the data they think they want.
• Get the basics right first. If you don’t have the foundation to build on, forget the
  higher-impact stuff.
• If you have enough data to make payroll, you have enough to start a workforce analytics initiative.
• Partner with finance at the outset – it will save you the endless migraine
  down the road.
• Myth-busting is one of the best ways to build credibility with data – use data to dispel organizational half-truths or amorphisms.
• There’s enough data to go around – but too much of it can be mind-numbing. Pick the one or two or three things that really matter, and stick with those at first.
• Simplify.
• If you are spending more time gathering the data then you are analyzing it, it’s time to think about an analytics platform.
• Your data will never be clean, and that’s OK. Just get started (data cleanup
  is never over).
• Dashboards are not the be-all and end-all.
• Build it and they will come does not apply to workforce analytics. And just because they come doesn’t mean you want them to – there is change, education, and influence that comes with all of this.
• Don’t go at it alone – expert guidance does and will make a difference.