Datawarehouses for HR - The Windmill not worth chasing

I had the pleasure to spend time at the IQPC Big Data, and HR Metrics conference. Technically, they were separate conferences - but everyone mingled. But pause on that a bit - the HR analytics community is starting to become big enough that there are now HR metrics folks and HR big data folks - says a lot about the community. One of the bigger questions was around - how to wrap your arms around the data! What was interesting is that while the question was brought up a couple of times - the answer was the same each time, and for each of the panels.

Question: Should HR pursue a Datawarehouse strategy

Answer: NO

So while the answer is simple, here is what most folks explained to back up their answers:

1. Too Much Change:

Now that every function in HR has an application (e.g. learning, staffing, college relations, ER, etc.), There are too many solutions with too many topologies (e.g. Cloud based, hosted, Relational, non-relational) to try and maintain a really big Data warehouse. This makes sense if you think that there are probably more than seven different systems of records within HR, all on different upgrade paths, and all on different renewal cycles. So in a perfect storm scenario, you could be in a case of having to modify your integration files (ETL's) every year due to new data being captured, and/or new applications being purchased by the departments.

2. Too Much Cost:

Given that HR is often a cost-center, there was a strong sense of stewardship about the budget dollars, and no-one could justify the warehouses. It was more focused on those dollars are better spent on tools, training, and/or more human resources. 

So what is the solve? 

Most of the folks at IQPC were still pulling data into a data warehouse - but instead of integrated warehouses (e.g. combined and/or harmonized table structures) most were just bringing in the database images. This allows for folks to query the data, and use a number of tools to combine the data sets (e.g. MS Excel, Tableau, Minitab). 

Setting up for the future:

One of the challenges that I put forth before the group is to think about the future of HR data and how it is growing exponentially. Twitter, Facebook, linkedin.com, benefits data, etc. So instead of focusing on trying to centralize and combine data - which seems to be the impossible task, the challenge is to make sure that the teams are nimble to do adhoc analysis across disparate systems. This means two things:

1. Training - This type of analysis is not easy as it often means needing to write a wide range queries to get at the data, and the critical thinking skills to think about how to use the data and are there any unusual anomalies. 

2. Tools - This also means folks will need to learn a broader set of tools, and also use tools that help integrate the data together. 

Overall, the energy at the conference was pretty amazing as it was clear that we are starting to move into the next generation of HR analytics - and learning to do so much more to add value to the industry and the profession!

As always, if you come across any great studies - please let me know!