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29 2014

Using Big Data for HR Improvement and Strategy

Syndicated from: balance-AND-results

Readers will know I’m a proponent of HR exerting more leadership in the use of Big Data – that means all the data we can get our hands on about our operations and people and the statistical systems to connect it and make it meaningful. We gather mountains of information on performance, training, succession planning, goals, aspirations, survey results, health, safety and absence records and tons more…. The idea of people analytics as one driving component in HR strategy is definitely something I promote, BUT most HR departments don’t (yet) have the systems, resources, trained data crunchers, budgets or support from IT, finance and others to do a fraction of what could theoretically be studied, quantified and discovered if all the data were to be used. In my dreams I imagine a day when HR will have such resources, but I’m wise enough not to be holding my breath for any time soon except in the case of one company: Google. But we don’t all have to be Google to take some very big steps. It’s significant that Google is one of the top 5 richest big companies in the world and among the top innovators. Consequently as impressed as I am with Google’s achievements in measuring and using data to direct HR policy, I’m not convinced every organization can or should try to emulate them, at least not to the extent they do it. Very, very few will be able to afford 3 PhD statisticians in HR nor afford the trained executives to know how to direct them. But that doesn’t mean we shouldn’t pay close attention and make intelligent decisions about what we can copy or can’t. Dr. John Sullivan, always full of opinions, made some good points in two blog posts about Google HR analytics last year and produced a good list of the analytic successes Google has reported in that area. But some of the comments that appeared after the article were instructive. Google still isn’t perfect by a long shot in their HR practices, nor would their approach work everywhere, and some of Sullivan’s comments were a bit unsupported as were more in the second post. I agree the largest part of their success is mostly attributable to their people (as is true in all companies – whatever level of results are achieved – people are driving them), but whether this equates to perfect HR is another question entirely. I agree with his comment that the companies with the most innovators will win, but disagree with his targeting of HR as maybe not staffed with people analytical or skilled enough in math to do their jobs the best way possible. HR needs math and systems experts, for sure, since it is an area lots of people chose thinking they could avoid those tasks, but HR doesn’t need ONLY those, which is sort of implied, any more than all marketers need to be personally competent to do survey building and statistical analysis. If life were entirely mathematical, we could close a lot of university faculties. If you have these capabilities, great. If you don’t, you probably need to pay attention and add some to your list ‘to develop’ and find some helpful seminars, reading or conferences, but don’t count yourself out of the game. Common sense goes a long, long way and, as a former math teacher, math course developer and applied math student before entering HR, I can guarantee you that 99% of the math you need is basic arithmetic that you learned in grade school. One just has to get over the fear that it’s too difficult and pay attention. I’m not kidding – 99% arithmetic! And systems knowledge? Most systems have become easier for users. We’ve all learned Word and email and VPNs and more, so again going further will be easy the less you fear learning and the more you hire a few good, relatively inexpensive experts who can help provided you can lead them (and I mean lead – coach, etc., not ‘tell them how to do it”). One of the foremost skill sets HR needs is the ability to sell, to convince, to influence senior and line managers throughout the organization that we already know answers to a great many HR strategy questions without doing our own massive statistical studies. The skills of selling, convincing and influencing, by the way, are not mathematical though having some good numbers certainly helps. They are political, social, psychological and human – philosophers, lawyers, politicians and others don’t all need advanced math as much as no fear of arithmetic. How many mathematicians to you know who are expert at articulating and selling ideas? Numbers really help and you need to put some on the table and explain them to the business leaders who probably don’t understand them either. It’s your ability to take such information and make it clear and meaningful that helps more than gathering the numbers themselves. Which brings me to a key issue that I keep pressing – we have quite a few numbers available that we consistently overlook and don’t promote – but we also don’t need our own numbers for everything. If you read or listen to this interview with a senior Google manager (former CEO of an acquired company) (also mentioned in my last post) who learned to lead better via short courses at Google, you can see very clearly that what he learned wasn’t at all about numbers, nor was it newly discovered by their statisticians. Their work helped prove to senior Google engineers that this sort of training was needed. My argument in a company would be – “Look, Google proved it, do we need to reinvent that wheel – or should we believe what they and everyone else says – it can work in any company, so approve the training for right here!” Google is pleased to point out that they defined the training details to suit themselves, but the sort of definition the discovered is stuff a good HR trainer or consultant can dig out through interview and needs analysis (the same basic analysis that Google did with extensive numbers). The problem many HR departments have is not that they can’t build the proper training or tell what it is, it is that senior management teams hesitate to fund it… without “proof.” Well proof now exists.

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