Talent Analytics & HR Big Data – Warning!

About a year ago, our organization was in front of the HRO Today community in London. We were participating in the iTalent competition for 2013, the Most Innovative Technology product from HR. And, as many of you know – Aspen was awarded the #1 Most Innovative HR Technology Product, with our Pando platform (Dec. 2013). At that time, we were already managing several dozen organizations and their talent analytics (Major HROs/RPOS, and Global Enterprise Organizations). Today – we are managing well over 200. And, as we approach this busy conference season – Big Data and Talent Analytics are hot topics. Here are a couple of questions that will help you identify those who “do” from those who “teach” (aka posers)…as you hop up and down the aisles at conferences, engage with thought leaders, and talk about talent analytics:

Q1: where do you store your data? Unless they say “terabyte…” = POSER ALERT

Data storage and backup is critical for success. Having the appropriate space and processing ability allows for more complex calculations and the ability to reference even more historical data and make it a better experience for your end-users. Any company that is doing that for a large-scale customer base would have to have a very large data farm at their disposal and they should be pretty proud of their set up.

Q2: what’s your plan for PII and EU data privacy? “Huh?” = POSER ALERT

Social Data is wildly global, as it is most data. The ability to protect the personal information in Europe is wildly different than it is say in the United States. Just because you operate in the United States doesn’t necessarily mean that your data is United States centric only. It may be privy to international law.

Q3: how do you weave ops and finance data alongside HR data? “We only need HR data” or “you can get it all from the ATS/HCM/CRM” = POSER ALERT

Organizations that are involved in talent analytics have already cracked the code on how to weave in financial and business centric data into human capital data. The process should be automated, usually involves connections with the proper financial contacts in the organization, and has to be locked down for confidentiality, security and encryption given the sensitive nature of the material.  

Q4: what’s the difference between reporting and analytics? “They are kinda the same” = POSER ALERT

Reporting is part of talent analytics, but in all honesty, it’s a small part. Ability to look backwards or take a snapshot of where you are at a certain moment of time has been available for some time, it is just easier now given the tools that are at hand. DVD is to reporting as streaming is to talent analytics, to use an analogy.

Q5: how much data munging will be required? “What’s data munging?” = POSER ALERT

The janitorial work, data cleansing, ETL, and other type of work may not be sexy, but it is absolutely necessary and picks up the majority of any kind of data analysis work. Fact is, that one state it is relatively clean, talent analytics is a very business centric and can be handled by business leaders directly. This stuff is definitely NOT easy. If it was, then everybody would be doing it by now, and people would not be talking about how they have to get it done. Making a PowerPoint and putting “big data” or “workforce analytics” on a title slide is not enough though. Caveat emptor.

Props to those that are doing it right – you know who you really are. AG

0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply