Over the last few days, I have been reading several articles and posts on Talent Analytics. I have been trying to get into depths on what people mean by talent analytics and what exactly happening out there. So far, the talent analytics seems to be intended for employers and not for employees. This has to change.

One thought stuck me after spending a lot of time reading. I did not seem to get to see anyone talking about how talent analytics will help the employee. Everywhere the benefits to the companies was what was being spoken about. How retention can be reduced. Predictive analytics on who is likely to stay longer in the company. Analytics on costs of employees. Analytics on reducing recruitment cycle time. And so on.

This is great, but what about the employee. Marketing analytics is supposed to benefit the customer, right? If so, should we not be talking about how talent analytics is going to benefit the employee? Or is it not meant to be doing this at all?

If my understanding on Big Data and Analytics is correct, then it is a great development for enabling personalization, customization or individualization i.e. making that one individual make better choice based on her preference or profile, tailoring products and services so that that one individual’s preferences are met.

In this context, I think Talent Analytics also can be a great boon for the HR field provided we start thinking of personalization, customization or individualization of processes, delivery mechanisms, services in the HR space for the individual employee, giving them appropriate choices and helping them make better choices.

For instance, together, the Big Data and Analytics should be helping employers create different delivery mechanisms for learning and development based on the preferences on the ways in which employees learn and what they want to learn. And like in the case of other fields, instead of bombarding an employee with all the choices, present those that are most suitable for the employee. So could be the case of the career move. We could present an employee with those 3 or 4 career slots that the employee is likely to fit well in the 1 or 2 years, the probability of her fit as of now for each of them and what can be done in the next 1 or 2 years to improve the probability.

There is so much to do if we start thinking from the employee angle (as in the consumer angle) using talent analytics. The vital difference in thinking on talent analytics from the employer end versus that from the employee end is that of aggregation and individualization. Whereas in the former we would look for maximising at a group level (cost, retention and so on), we would have to look what works at every individual (or unit) level.

Yes, the biggest problem I think is that we are still crunching data that we have already been comfortably collecting on people – age, gender, education, cost, geography and such. But we are not looking at data that is more vital and that which are not out there. Say for example, learning preference, skills in different areas, future goals and so on. But then we will have to begin on this sometime, if we need to make a meaningful impact in human capital in this personalized world with talent analytics.