Second of two parts
No discussion of “the new HR” can get very far without running into the business buzzword of the last year: Big Data.
The ability of technology to bring together huge volumes of information from a variety of sources means we can now tackle problems and provide forecasts that would have been too labor intensive to produce just a few years ago. When it comes to Human Resources, that means better workforce planning, better talent management and quicker ability to adapt to changing markets.
Only 14% of HR teams truly using analytics
If your answer is a nervous laugh, you’re not alone.
An industry study last year found that only 15 percent of organizations believed their HR teams had “strong credibility” when it came to using analytics, compared to 80 percent who said their finance and operations teams did, and more than 50 percent who said their marketing and sales teams do.
The Bersin by Deloitte report further found that only 14 percent of HR teams were truly using analytics – the other 86 percent were focused on reporting only.
Note that I’m using “reporting” here to refer to all the work that goes into collecting, standardizing and publishing data against specified metrics – which is a lot harder than it sounds. “Analytics” is what happens when you add actual analysis to the mix, and are able to start making predictions and prescriptions based on it. (For a longer list of data-related definitions, check out this article I wrote last spring.)
One big reason why HR teams may find it hard to make the leap from basic metrics to sophisticated analytics is the dreaded skills gap.
Is your company really ready?
That gap isn’t as big as those who still think of us as pencil-pushing form fillers would have you believe – between ERP and performance management systems, most of us in HR have pretty good “small data” skills – but it does exist. According to that Bersin report, high-impact talent analytics teams are much more likely to have on board staff who have backgrounds not only in database IT and statistics, but in data visualization and I/O psychology as well.
Even if your team is ready, is your company ready? If the sales team has been trying to use Big Data for two years and hasn’t succeeded, maybe there are larger structural issues you need to tackle first.
Those companies who do best with Big Data are those with existing “cultures of evidence-based decision-making,” according to Jeanne W. Ross, director of MIT Sloan School’s Center for Information Systems Research. In practice, Ross writes, companies who have such cultures do four key things:
- Establish a single source of performance data;
- Give near real-time feedback to decision makers;
- Articulate and update business rules, and;
- Provide coaching to all decision-making staff.
Building your HR data team
In addition to a potential skills gap and corporate buy-in, most of us also face the perennial issue of limited time and resources. So here’s a four-step plan for getting started:
- Know what problems you’re trying to solve – Before making overly generalized investments in data science, focus in on what kinds of questions this data needs to answer. What are the business or team goals that you want to contribute toward? Do this first before the next four steps and you’ve already reduced a major source of churn.
- Think team, not unicorn — Remember that list of skills I mentioned earlier? Don’t expect to find them all in one person. Concentrate instead on building a team of specialists who work well together.
- Assess your skills gap — This is really three steps all on its own. First, based on No. 1, what are the specific skills your team needs to collect and analyze actionable data? Second, who on your team has those skills and/or aptitude toward them that would make them worth sending for further training? Third, who else at your company already has these skills and can you get access to them? For example, if your marketing team has a great data visualization specialist, start talking to her boss about whether you can borrow a week of her time every few months. And remember to reassess — as you become a more mature analytics organization, your needs will start to change.
- Look for targeted external resources — All but the biggest companies will eventually need to use third-party software and services to fill in some of the data science picture. The important thing, however, is to make sure that this is your last step, not your first. Resist the temptation to hand the whole thing over to a consultant who suggests you need to replace every bit of your systems at once. Instead, focus on the problems identified in step No. 1 and only think about outside resources after you’ve identified where your specific needs are.
Build a foundation for success
Finally, don’t get overwhelmed. Build a foundation for success by starting slow and getting the basics of data management right.
Remember that Big Data, in HR or anywhere else, is only as useful as the human intelligence behind it.
Did you miss Part 1? Check out The New HR: If We’re the Business Engine, It’s Time to Make Some Noise
Originally posted on tlnt.com