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Nov
20 2013

Big Data Update: Are We Getting Ready?

Syndicated from: balance-AND-results

Google, being composed mainly of engineers and having tremendous resources, may be the poster child for applying ‘Big Data’ to HR. They research the relative values of benefits to adjust their offerings. They study leadership keys statistically to determine what skills make the most effective leaders (a business case that’s even hit Harvard)… and much more. More and more it becomes clear that doing data analytics is a core skill HR operations must develop. Like benefits, payroll or health and safety, it is a separate specialty that takes time and dedicated resources to put in place and continued attention to keep going. This is problematic for several reasons. First, the resources necessary include both people and systems. When budgets are tight, making a case to add staff with specialized skills that appear to many to be ‘non-HR skills’ (stats, data base management, user computer reporting, etc.) is likely to be a challenge. Getting access to computer support to find, install and interconnect data collection processes is also likely to become a competition for resources that other departments want as well. A short article and video may help put this in human-scale focus (just note these are sales materials for one of the big consulting providers). Of course the biggest challenge as always is the fact that truly measurable results tend to be a long way down the road. Some companies have the foresight and finances to forge ahead and, again as usual, they will stay ahead as a result. McKinsey & Co. just published an article with a rather stunning graph and back up stats to show just how few these companies are and how vast the number of companies that wallow at barely break-even results, where everything is a ‘game of inches’ to squeak ahead. Oh, to be among the successful few, like the Google’s whose continued growth suggests they’ll retain those success characteristics for a long, long time. This chicken and egg problem needs to be viewed in light of stories like Wal-mart. Sam Walton saw an early IBM 360 computer handling inventory back in 1968 when I was just through key-punching Fortran code into one at university via handfuls of punch cards to try to learn ‘programming’ as it existed back then. We’d hand in 20 cards in a deck to a computer complex jammed with roomfuls of tape decks the size of refrigerators and find out a day later we’d typed one character wrong on one card and have to start over – just to get the answer to adding 2 + 2. In the midst of this Walton recognized the possibility of expanding his few stores into a chain if he could automate inventory and distribution management, so he hired a high paid executive to work on it, buy equipment and build a department (investing resources in something no one else seemed to be as serious about). The rest, as they say, is history. That one bit of foresight set the stage for what is now virtually the largest employer in the world only 50 years later. Looking at McKinsey’s graph, we certainly can’t fault HR departments alone for not making the leap to Big Data analytics, but someone has to lead the charge and keep the issue in front of executive teams or the evolution will never happen in our business life times. If it seems odd coming from HR, so be it. Big Data is a significant add-on to the ‘automation theme’ within HR strategy – one of only about three areas where HR can significantly contribute to dramatic innovation (the others being leadership evolution/engagement and social media applications internal and external). Such inventiveness is what puts companies ahead and keeps them there. Most organizations have the data now in one system or another. It’s a matter of starting small, as the video above suggests, and over time increasing capabilities until the true payoffs are visible. If organizations can’t make that much of a leap, they’re doomed to remain in McKinsey’s ‘game of inches’ struggle for the rest of their existences, I believe. Bookmark and share this post More »

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