Chances are you’ve seen the words data analytics floating around the headlines and pages of blogs, articles and conferences. Data analytics has become a huge topic in the HR tech industry. Just Google the phrase, and you will be flooded with results like:
- “the transformation of talent management through analytics …”
- “HR analytics will be one of the most important trends in HR in 2016 …”
- “change your company with HR Analytics …”
- “HR analytics will allow companies to be predictive instead of reactionary …”
- “HR can get a seat at the main table through HR analytics …”
Why all the buzz? What exactly is data analytics or big data, and what is HR supposed to do with it?
To start at the beginning, check out our previous blog post defining big data and data analytics.
Now, let’s dive a little deeper. Did you know that only 6 percent of HR departments polled feel they are “excellent” at analytics (Bersin by Deloitte); only 5 percent of organizations say they are effective at tracking and using talent analytics (InsideHR); and only 4 percent of companies have achieved the capability to perform predictive analysis about their workforce (InsideHR)?
For such a big industry trend, employers seem to be falling short. If data analytics is so amazing and game changing for HR, why hasn’t the industry fully embraced it, and why aren’t companies aggressively using it?
Generally speaking, statistics or analytics aren’t top priorities for HR professionals, and many may also hope data analytics will be a passing trend and exit the headlines soon.
The phrase alone sounds scary and alludes to a sizable undertaking; where is HR even supposed to start?
Another big reason why data analytics hasn’t been embraced: HR isn’t collecting the right data. Collecting the right data is difficult, especially when it resides in multiple systems and formats. We see a lot of HR teams struggle to pull data together from disparate systems.
So where do you start? How can companies start utilizing data analytics?
We recommend starting small with a high impact area. For example, what skills/performance traits do your best sales people have that your middle and low performers don’t? (This should be a significant statistical analysis, not “gut feelings” and judgments.) To truly cull out these unique traits, you need to not just look at the successful people, but effectively compare them to the average and below average performers. How can you change your hiring process to look for these skills? Can you develop these skills in your existing sales force?
Another example: try analyzing your employee base to predict areas that will experience significant attrition. Then create a succession plan to fill the gap with internal and external resources. Proactively work on retention for employees with key skills in key areas.
Don’t feel like you are alone in this. If data analytics really isn’t your thing, bring in some help. Statisticians, data analytics consultants and software vendors all are available to help with your HR data analytics initiatives.
In summary, there is a lot to gain – HR analytics is a big deal! HR houses some great information if you just know how to get it, what to do with it and how to interpret it. Using data analytics is a great way to differentiate your company and gain a competitive advantage. In one of the surveys mentioned above, 89 percent of employers are considering increasing the ability of HR’s use of metrics (InsideHR). It’s not too late; you can still be a leader in this area too.
Is your HR team using data analytics? Share your thoughts on the topic or any tips by commenting below.
Interesting read. Thank you for sharing.
Another reason for confusion in HR Analytics is between “big data” and the data to be actually used for decision making. There is not sufficient standardization in HR to be easily able to put up some metrics which could be tracked and harvested on a recurrent basis.
For example, if you have 100k resumes in your data silo, that is most likely just noise because it’s too biased. The only effective approach is to define the problem, then the metrics (and not add more metrics ever other day), then start tracking them and then evaluate periodically.
The first step (the problem) and the lack of metrics driven HR are the main reasons for software not being able to tackle this effectively -this is likely going to take some time to find success on generalized approaches.
To give a sense of where we stand now, it is not uncommon even for large businesses to use spreadsheets to track metrics (the professional way to do these things is through data lakes).
In my opinion, the driving force behind the analytics trend for HR (simply put: why didn’t this become a hot topic 10 years ago?) is the shift towards mobile to create 2 advantages: input on mobile is structured (taps are usually on multiple-choice queries instead of free input boxes common to desktops and larger screens) and the other is the addiction created by the mobile devices (Bersin put it nicely “as work-life balance becomes work-life blend”)