Talent Analytics: Old Wine In New Bottles?

A day does not pass without my receiving multiple emails announcing webinars, publications, and workshops focused on talent analytics. Talent analytics has become an important area in both consulting firms and corporations.

Most of the discussion of analytics emphasizes how much can be gained by better talent utilization and the ability of analytics and big data to improve overall organizational performance. It is hard to disagree with this, but it is also important to point out that talent analytics is not a new area by any means. There is a bit of an "old wine in new bottles" about it.

At least since the 1940s, some companies and governments have used talent analytics to improve their selection and talent management activities. But, and it's a very big "but," very few have. The capability has been there, as has evidence to show that organizational performance can be improved by using data and evidence based talent management. Despite this, the use of talent analytics to guide practice has been rare.

There is extensive literature in academia about the failure of companies to use best practices when it comes to talent management, and a strong argument is made in this literature for evidence-based management. The simple fact is, when it comes to dealing with people, many managers trust their "intuition" and "common sense" more than they trust data. This seems to be particularly true when it comes to data gathered by academics and researchers who are not part of their company.

So what is new? Why the flurry of interest in talent analytics? There are a number of reasons. One is that with the growth of information technology, it is much easier to gather data and analyze it. In the past, much of the work on talent analytics was done by a few large corporations (e.g. IBM, AT&T, 3M) who had the staff and resources to do what often were time consuming analytics that required staff expertise or "worse yet", it was done by academics.

Today, the expertise to implement the results of analytics may not be present in most organizations but the data and the ability to analyze it is readily available even in small organizations. Thus, in more and more organizations, it is not possible to justify not acting on data because it was "not invented (or collected) here."

Perhaps the major reason for the greater attention being paid to talent analytics is the growing importance of talent. More and more organizations are dependent on the performance of their talent for their source of competitive advantage. Thus, any improvement in talent performance pays off on the bottom line. This obviously produces a greater incentive for companies to pay attention to talent and to use analytics to help make talent management decisions.

Finally, new kinds of data can be collected that may prove useful in increasing the power of talent analytics. For example, a recent study found that the number of internet messages sent and received by individuals is a good predictor of their turnover. This measure did not exist a decade ago, and until recently could not be easily captured and analyzed.

Overall, at this point in time, there are clearly a number of reasons to believe that talent analytics will continue to grow and be more powerful and that more organizations will use them. The data and computational power are available and, to some degree, the expertise is available to do the analytics and facilitate the implementation of the findings. But, and it is an important "but", it may not be enough to result in very many organizations practicing data-based talent management. In order for this to happen, organizations need the "right culture" and leadership approaches--ones that value evidence-based decision making.

In the absence of a culture, which focuses and values data and practices evidence-based decisions, the availability of data is unlikely to have a great impact. Those who collect and analyze the data need to not just "report" it, they need to be able to tell a story that makes it clear how it relates to the organization's effectiveness. Decision makers need to make it clear that data wins out over opinion!

Without the right kind of culture, leaders who demand data-based talent decisions, and good storytelling, the availability of data is not likely to make a great difference in how organizations manage their talent. For example, they will still make most hiring decisions based on interviews, which have little to no predictive validity! It is not enough to create new wine that is superior to what we have had for decades. It must be put in new bottles that highlight its strategic importance and makes it impossible to ignore!