Needless to say, I am referring to the size of data.
Big Data and HR Analytics were clearly two of the most prominent buzz words of 2014 within HR. The message is clear; the vast amounts of stored data that we have access to today gives great promises for valuable insights within HR and talent management. But the question is; are these promises fulfilled?
Psychologist Schlomo Ben-Hur and consultant Nik Kinley, both authors of the article Turning Talent Data into Talent Intelligence (found here) claim that many organizations today surely spend great resources on gathering lots of information about their employees, but that this information rarely creates bottom-line value. They summarize the challenges related to this into two areas; knowing what data to collect, and knowing what to do with it.
What data should we gather?
The first question touches on both the relevance and the quality of data. Naturally, we need to know what data to focus on, for example what type of data should be gathered and considered when assessing candidates for a leadership position. But just as important is knowing that this information really measures what we want to measure. Few of us would use a hammer to cut a wooden board, but many companies have no idea of whether the selection tools they pay for (e.g. personality or GMA tests) have any scientific support. Because of this, one should always ask test providers for validity data on the products they offer.
What to do with the data?
An important first step in using the available information in a relevant way is to make sure that our actions are really guided by it. This might sound obvious, but the opposite is more common than one might think. A common example is nomination processes of future potential leaders. Quite often, the modus operandi is to let line managers nominate these candidates, and then subsequently rank them through use of other tools. Intuitive as it may seem, research shows that line managers’ nominations are quite often biased. It is not uncommon for managers to nominate candidates that resemble themselves (e.g. male managers nominating men, even when there are women in the team that perform as well or better), or direct reports with whom they have worked more closely, and therefore have a clearer perception of. This means that no matter how valid the subsequent selection tools are, they will only help you rank a group that is already selected on flawed bases. In these cases it would often be a much more relevant use of data to turn the nomination process around, using the most reliable sources of information first.
But the data we collect can be used for so much more than specific decisions of recruitment and/or promotion. The method of investigating correlations between talent assessment data, demography and performance, is powerful. To, for example, compare competency ratings at recruitment with later ratings of who performs the best, or of who chooses to stay in the organization in the long term – that gives us the possibility to make truly intelligent talent decisions and build strategy. In the words of Kinley and Ben-Hur; “Not using talent assessment data to inform people strategy is like buying a sports car and then only ever using it to drive the kids to school.”
So my call for 2015 is; take a moment to think about how you utilize the information that you have available. If you scrutinize yourself and your organization, do you truly base your actions on the information that you have? Are there opportunities for new comparisons of different information sources, that could allow valuable strategic insights and long term gains? Even if the evergreen forests of vast data promises a lot, we can often create great value from what we already know if we only use this knowledge in the right way. Because when it comes to data on our most valuable resource, the people, it is not only size that matters – but how you use it.