Big data has impacted upon most areas of the business, but one of the slowest to fully adopt it has been the HR department. A recent study suggests there are a couple of reasons why this might be the case.
Foremost is a general lack of data science knowledge in the HR teams themselves. Couple this with a higher interest in the people side of the profession rather than the data side, and the demand aspect of the equation is not exactly conducive to strong take-up.
Secondly, the supply side of the equation is far from ideal as well. Many HR analytics suppliers provide very complex products that do a lot in terms of data management and reporting, but little in the way of strategic analysis. As Clayton Christensen might say, they are failing to appreciate the ‘job to be done’ in the HR department.
Solutions tailored to the job
The paper continues, saying that there is a sense within HR that analytics is only something that can be done with huge databases and expensive solutions. There is no real belief that something as simple as an Excel spreadsheet is enough to get you started.
Even should such data warehousing exist however, the gap between the data scientists that manage it and the HR managers that need insights from it often leads to a breakdown in flow of insight.
This credibility chasm matters, as departments that do have a better grasp of data, such as finance or operations, will quickly jump ahead, and quite possibly implementing decisions that the HR team are neither happy with or supportive of.
Improving data smarts
The paper underlines the importance of building up analytics capabilities within the HR team. It’s rare to have problems that data can’t contribute in some way towards, whether it’s analyzing skills shortages or performance variance.
Careful definition of that problem allows a model to be developed to help address it.
It’s also crucial that HR grasp the nettle and take on some of the more mundane aspects of analytics, such as the management of data and the governance of it. Do members of your team have access to the right kind of data at the right time to make strategic decisions? Is there sufficient data from across the organization to perform your analyses? Do you have the skills in your team to interrogate that data?
There area number of projects to automate the various aspects of data analytics, but for the time being it makes sense to develop skills as best you can. Indeed, many would argue that such is the importance of data, that having a Chief Analytics Officer is a crucial step in ensuring that all parts of the organization have the skills they require.
It’s a topic I touched on in a recent Forbes post, with Zhongcai Zhang, Chief Analytics Officer at New York Community Bank, making the case for the role.
“…elevating the organizational stature of analytics is an essential step in this arduous but rewarding journey of using analytics to better decision making and optimize business processes,” he told me.
Suffice to say, such a role is a long way from mainstream at the moment, but it seems that should it ever become so, their first role might be to help HR get up to speed.
