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6 Things HR Gets Wrong About Big Data

Posted by Mervyn Dinnen

21-Oct-2014 09:00:00

If you're an HR professional and happen to have ventured on to social media, read a blog, visited an HR technology conference or kept up to speed with newsletters from your professional body at pretty much any time in the last year or two then you'll already know that your role is increasingly about data. And the data is BIG. Too big for HR to handle. In fact it's so big that HR practitioners now have to be data analysts or computer scientists, think like finance directors and prove their grasp of talent analytic wizardry to claim that much sought after seat at the table.

 

Big-Data

 

But not everyone would agree. As UK HR blogger Neil Morrison recently pointed out, most people work in smaller companies, or businesses with few data management systems or analytical capability. And data has always been at the root of HR work - payroll, benchmarking, recruitment metrics, engagement, retention to name but a few areas. Certainly we do now have much more data, and its the 3 Vs - Volume, Velocity, Variety - and their almost voracious appetite to dominate the HR agenda that appear to have swept everyone away.

HR practitioners struggling to get their heads around this are not alone. Research from Bersin by Deloitte in the US showed only 4% of companies having some success, 14% on their way to getting to grips with it but that 82% of companies were "still dealing with data management and reporting challenges, trying to get out from under the burden of ad-hoc reports to deliver standard operational metrics".

If data has been an important part of HR for years, whilst many HR practitioners don't work for businesses that will generate the size of data that they are worrying about, maybe we're making too much of a big deal about it? There's little doubt that the availability of more, and access to real time, information should help us to make better decisions, so what are some of the things that HR gets wrong about big data?


It's as Big as You Make it
In the same way that not everything that can be measured needs to be measured, then just because you have access to a lot more information doesn't mean you need to use it all. Think of the areas that could benefit from more insight, possibly those where your current level of information is weak and stronger insight could help with more robust decision making.


It's Not About the Capture
Most tech vendors will talk about the amount of data you can capture, and like any shiny new toy there's an element of wanting to see all the different things your new systems can do. But back in the day job people need effective decisions that make their working lives better, and help add value and efficiency to the business. In other words it's all about using the data, not collecting it.

 

Focus on What You Need to Know
Another area that confuses is a fixation on all the different things that you can now find out. It's not so much a case of what you can predict but what you should, so start with areas it would be useful to find out more about, whether it's business critical or one where you feel you can add value with cost or efficiency improvements.

Correlation vs Causation
With more data available our interpretation shifts from cause to correlation. We now have greater depth of numbers allowing for a clearer view of trends and outcomes, so correlation is enough. One obvious area where this can help is recruitment as we are now able to capture more data around quality of hire, retention and development.

Think Beyond Metrics
Data isn't just numbers. On social media channels and recruitment websites we are creating a lot of data. Each tweet is a data point, as is each Glassdoor rating. New social recruiting technologies enable us to draw insights around culture and behaviours. There is a temptation to see all the potential as quantitative and ignore the benefits of more qualitative assessment.

Look for Practical Case Studies
Many companies are beginning to share stories of how better data analysis has helped with decisions. A good example is from Caesers Casinos around employee benefits. Managers are able to track thousands of variables of how staff use medical services, and one finding was that at a particular site only 11% of employees were being treated at less expensive urgent care facilities compared with a company average of 34%. Taking action, such as re-educating employees and providing alternative facilities led to a 4 year savings of $4.5 million.

Big data isn't a fad, nor this year's snake oil. In our personal and business lives we are creating and collecting huge amounts of data every day and the challenge isn't to turn our HR team into an IT department, but to harness what we now know, and what we can now find out and interpret, into something that helps in making businesses better and employees happier. As Neil Morrison said in the blog I referenced earlier...


"Focus on small data and Big Thinking, taking the information that you have and being really curious and inquisitive about what you can learn from it."

 

Ready to use big data the right way? Register for a demo right now to see how Broadbean can help you see the big data picture.

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Mervyn

 

Topics: Big Data , HR , Mervyn Dinnen