Every time I navigate Twitter or LinkedIn I see the term “talent analytics.” Granted, I follow HR-related people, but it’s clearly become more than a hot topic; it seems an inescapable truth that talent analytics is an essential activity for success.
Have you also seen the term being used a lot recently? Do you want to know what it truly looks like in organisations? If so, read on…
Talent analytics of course refers to the increasing importance of data driving HR and talent management practices. Undeniably, objective decision-making methods provide the best rationale (and best chance of buy-in) for a particular course of action. It doesn’t matter whether you’re deciding how to create an acquisition/recruitment framework or structure a training and development initiative. Perhaps you need evidence to diversify and engage your people, or want to predict how your new hires are going to perform. In any case, research shows that hard data gets the job done most effectively.
In fact, a&dc’s own research is demonstrating that HR and talent management professionals are now seeing the value in figures. We surveyed an array of talent management professionals from many industries (41% being HR Directors) and asked how valuable they perceive each of four levels of analysis that can be conducted on employee data (according to Bersin by Deloitte – see our report for a more in-depth look these levels).
‘Reactive’ analysis, ie reporting on typical HR statistics, was seen as at least ‘somewhat valuable’ by most of our respondents. Unsurprisingly, the more proactive levels of analysis, eg analysing information to inform decision making or creating models, were perceived to be more valuable. The most sophisticated form of analysis is about using data in a predictive way, eg to pose future scenarios and conduct various forms of workforce planning. 62% of our respondents said this would be ‘very valuable’ data to access.
However, we also know from research that in reality only 4% of organisations are actually working with this level of data.
Given we also found that many of our respondents are actually not holding data on talent pipelines (56%), outputs from assessment centres (52%), outputs from development centres (33%), 360-degree feedback (52%), psychometric tests (44%) or even promotion data (48%), this isn’t so surprising.
We know now that organisations recognise talent analytics is a good thing to pursue, but they aren’t actually doing it. If they were, what tangible business successes could they expect to see? These talent analytics examples demonstrate the success that data can bring you:
Author: Jordon Jones