Jocks vs. Nerds

“There’s this idea of the jocks vs. nerds thing. That sort of ended when the nerds won decisively. We now live in this era where your big summer tentpole movies can be hobbits and minor Marvel Comics superheroes and boy wizards. If you had told me when I was in junior high there would be a $200 million movie about Hawkeye andBlack Widow, I’d be like, ‘Hawkeye — that guy’s lame!'” Jennings says. “Those nerds started running Hollywood studios, and our captains of industry became Asperger types with acne scars.”

I was reading about what Ken Jennings (of Jeopardy! fame) was up to these days, and there was the above quote that I found hilarious.  It’s totally try though, especially for a guy like me who lives in the Silicone Valley.  High school might have been a time when the jocks ruled the world, and college was a transition time, but once you get into the workforce, there are really grate charismatic guys running businesses, but the people who are really redefining the world and how we change our behaviors to adapt to the world on a daily basis are quite clearly the nerds.

(Credit to the HR Technology Conference and Bill Kutik bringing IBM’s Watson computer for making me think about Ken Jennings)

I’m continuously thinking about analytics these days and I start to think that HR has also started the transition from “people people” to something a bit nerdier.  Maybe we are in that college stage I mentioned above – we’re no longer just the people that you go to for benefits and worker’s comp – that was over a couple decades ago.  We’ve started down the path of Talent Management, and we’re probably still trying to figure that out.  We keep talking about really great analytics, but we really don’t do it well.  I think what we need to really get to a mature level of HR as a profession is we need to get nerdier.

Talent Management:
It’s entirely possible we’ve been wrong for the last decade.  We’ve built these incredible competency models, tracked how and when a goal should cascade, and automated all of our talent processes.  I don’t think the business is convinced that we’ve actually improved the core employee’s ability to get developed.  Think about what you yourself did 10 years ago.  Big deal that you can now enroll yourself in training on-line and you have a cooler performance tool that is not a piece of paper.  Have the majority of employees in any company really experienced a perceptible difference in talent and development outcomes?  I’m guessing not.

It’s entirely possible we need some nerds to take over.  I don’t care how much HR shepherds the process along – if the employee and manager don’t own their own talent, it’s game over.  The only way to do this (that I can currently think of) is to create easy to use, social, real time, talent engines.  I’m thinking of an engine that quickly allows a manager to give feedback or development instructions when and where they think of it, then have seamless execution (again in real time) by the employee.  All of this has to happen without the HR practitioner and then roll up at the end of the quarter or year so we get that macro view of progress.  Without real time integration with the employee and manager though, all we have is another failed HR process.

Where HR gets involved is not in shepherding the process, but instead in managing success.  If we can mine the data and understand who is doing what, what works, and where we are missing the mark, that is where the value is.  Somewhere and some point, process people are still important as we make the transition, and certainly we need great change people to get manager adoption, but what we really need are analytical nerds who get how to interpret data.

HR Analytics:
I really hope we don’t have illusions that we are any good at this – we’re not.  We have technical people and we have functional reporting people helping our organizations create reports.  We have vendors feeding us cool dashboards that we then flip and roll out to our managers and executives.  What seems to be missing to me… the statisticians.

Have you ever talked to the finance guys about what they are doing in their analytics functions?  The stuff they produce is absolutely amazing – and they are set up in a pretty different way than we are.  Financial models are very complicated, but shouldn’t our models of people resources be just as robust?  In fact, if anything we have more complex, more dynamic, and more diverse data sets.  If we were dealing with numbers, our lives would be easier – but we deal with more complexity with less sophistication.  No wonder we walk into the executive boardroom and don’t get credible respect.

It’s interesting – when I look at the type of people HR hires, we automatically know we’re not going to have the best friend relationships with Comp, Payroll, IT, etc…  Those guys are just different from us.  I mean, my God, they are analytical in a totally different way.  Embrace the difference – it’s what HR needs, and it’s not even enough.  I’d love to see us start to hire the nerds – math majors and people who can come up with complex statistical understandings of the HR world.  We are in our infancy for understanding HR, but it’s because we don’t structure our organizations in such a way to create deeper understanding.

Get used to the fact that the nerds have won.

Is Big Data An HR Directive?

I have an argument with my wife every few years.  I tend to like cars with a bit more horsepower.  I mean, that 1 time a year when there is a really stupid driver about to crash into you, a few extra horses comes in handy when you really need to speed away.  The problem is that 99.99% of the time, that extra horsepower is a luxury you really don’t need.  You’d get from point A to point B just as safely, and probably just as fast.  Sometimes though, that engine really does matter.  (My wife wins 90% of arguments by the way)

Everyone in HRIT is talking about big data these days.  Unless I completely don’t get it, I thought this is what we’ve been working towards for years.  I mean, having ALL of our talent data, core HR, learning, recruiting, payroll, benefits, compensation, safety, etc data all in the same place and running analytics against it all was always part of the data warehouse plan.  I mean come on, what else is ETL for if not to grab data from all over the place, aggregate it into the ODS, and then figure out how to make sense of it all?  We’ve built a nice engine that caters to our needs 99.99% of the time.

I’m going to propose something:  Big data does not matter to HR.  It’s just a new naming of something that does matter.  Business intelligence and truly focused analytics is what makes us focus our actions in the right places.  BI, Big Data, I don’t care what we call it.  Just do it.  Either way, HR does not have a big data need at this point.  I’d propose that we can use Big Data technology to speed up our analytics outcomes, but that’s about all we need for the next few years.

In my simplified definition of Big Data, it comes down to two major attributes: the use of external data sources, and the lack of need to normalize data across sources.  If we look at it from this point of view, the reality would state that almost no HR department on the face of the earth is ready to take HR data and compare it with government census data, or employment data.  Let’s get really creative and take local population health statistics combined with local census to get some really interesting indicators on our own employee population health.  Right, we’re just not there yet.

Let me reverse the thinking for a moment though.  What about the other 0.01% of the time that our traditional BI tools just won’t help us out?  Going back to benefits examples, how many global organizations can really directly compare benefit costs across the entire world?  How many of those same global organizations have a great handle on every payroll code?  Much of the problem is that the data is often outsourced, and definitely not standardized.  Collecting the information is problematic in the first place, but next to impossible to standardize annual changes in the second. The beauty of Big Data is that in these cases, you’d actually be able to gather all of that data and not worry about how to translate it all into equal meanings.  The data might aggregate in a more “directional” way than you’d like, but you’d probably still have an acceptable view of what global benefits or payroll is doing.  It seems to me that this puts us quite a bit further ahead of where we are now.

Listen, I know that HR has some place in Big Data at some point in the future, but the reality is that the current use cases for Big Data are so few and far between, and that we have so many other data projects to work on that we should continue investing in the current report and analytics projects.  Big Data will come back our way in a few years.

As I said, my wife usually wins the arguments.  We end up buying a car that has 175 horses under the hood, and I end up wishing we had more once a year.  But inevitably, automakers seem to up the game every few model years and come 5 years down the road, that same car model how has 195 horses.  If I just wait long enough, those extra horses in the engine just become standard.