Big Data For HR & Recruiting: 2 Use Cases

Forget about Google.  One of the world’s favorite sites has got to be LMGTFY.com.  “Let me google that for you.”  With the wondrous world of the internet and ubiquitous information, ubiquitous access through our mobile devices, and ubiquitous connectivity, whenever someone asks a dumb question in email, you get to just send them back a link to LMGTFY.com (since most of the time you don’t actually know the answer anyway – I can’t count the times someone asked me something I didn’t know but I gave them the answer after googling it.)  It’s a bit sad though, that we have such incredible access to information in our personal lives, but our access to HR information seems to be severely limited.  We are just starting to do cool things in HR to answer interesting questions about our employees, but in a couple of segments of the industry, it’s about to get completely fascinating.

(NOTE TO READERS:  I stopped writing about specific vendors a long time ago, but today I’m going to highlight a couple that I think are doing really great work – but it’s more about the work that I’d like to highlight, so don’t take this as a vendor plug!!!)

Oh, we love buzz words.  I know I’ve been writing about big data and social HR a lot this year.  If the last decade was about the shift from HR administration to talent management, the next decade is going to be about creating insights about our people and making them own their own development.  When we talk about information, Google, Yahoo, Microsoft have been creating algorithms to search data for years.  HR just hasn’t had to tools to do it.  Things are about to change rapidly.

Use Case 1:  Using Big Data to Use Your Employees:
Use your employees?  Oh that sounds terrible.  The reality of this is that it’s really cool.  A small company called Careerify (careerify.net) started selling a product last year that allows you to easily grow the volume of high quality employee referrals you get.  What they do, is they allow employees to connect their Facebook, Linkedin, Google+, Twitter and whatever other networks they have, so that you can help them understand when they should refer someone to the organization.  Let’s say for example that you have an opening for an electrical engineer.  Careerify would help you push an internal campaign to your employees, perhaps sending them an email that automatically identifies people in their network who are electrical engineers.  It goes a step further though.  Because you might be linked to a number of the employee networks with a variety of data, you can target the location of people on top of jobs.  But it even gets better… let’s say you know you have a culture of people who are active, outdoorsy, and fit, and there is an electrical engineer who happens to be a bass fisherman and loves to skydive (based on photo tags in Facebook).  This EE would be scored higher than individuals without those interests.

The ability to mine employee networks (with their opt in) and present employees with easily selectable pictures they can click on to invite someone in their network to apply is almost too easy.  We all know that employee referrals are the fastest, highest quality, and lowest cost recruiting source we have, but we just never knew how to make it easy for the employee.  By using big data to reach into employee networks and analyze profile attributes and even tags and update activity, you could literally improve your core recruiting metrics (time to hire, cost of hire, quality of hire) in weeks.

Use Case 2:  Bringing More Information to Recruiters
To be totally honest, I’ve been trying to work out why recruiting is always ahead of the curve when it comes to HR technology.  I think at the end of the day it all has to do with the fact that it’s a function the business actually depends on.  If they (managers) don’t do performance reviews, their organization probably won’t suffer for months or years.  If they don’t fill the open seat though, their productivity is suffering the very next day.  A company called eQuest (been around much longer than Careerify) has been using big data to answer some of those questions around “why aren’t I hiring anyone right now?”  What is interesting and wonderful is the completely different approach organizations like Careerify and eQuest are taking.

eQuest looks at the market through job boards, and correlates your recruiting activity to activity in the market.  Basically, if that same electrical engineer position is still open in 60 days, eQuest can tell you what ever other company is doing differently.  For example, based on what is out on the job boards, you have 3 EE jobs open out of 50 in your local area.  It just might so happen that you are offering a lower compensation rate, so you are getting 60% fewer candidates than the average EE job opening (demand is up, but you have not adjusted to market yet).  Or, it could just be that in the last 6 months, there are fewer EE candidates even looking at and opening those job postings (supply is down).

Unlike Careerify who tries to solve the problem by making it easier for your employees to help you, eQuest tries to solve it by putting better data in your recruiter’s hands.  Both are completely valid mind you, just different approaches to big data.  With either technology, I actually think we are getting closer to LMGTFY.com for HR and recruiting.  When my internal recruiter asks me if “I know anyone,” I’d have to think about it.  But if Careerify asks me, and automatically sends me a clickable picture of 5 people who already match, I only have to think about whether I really want that person around or not.  On the other hand, if my recruiters are asking “Why the F isn’t anyone applying for this job?” eQuest can probably give you a pretty good answer as well.

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.

Bread & Butter

It always frustrates me when I’m dieting – I have to forego one of my favorite food items:  Butter.  Butter (fat) along with bacon fat (fat) is one of those amazing joys of life.  When butter is great, a bit salty, a lot smooth, and a lot fatty, it is a wonderful thing  Unfortunately, one cannot generally eat butter straight off the spoon without incurring some ridicule from friends.  Therefore, one must also eat bread.  To me, bread is not just a necessary evil.  Great bread on its own is also a joy of life.  It can be beautifully crusty on the outside, warm on the inside.  But sometimes when the bread is not great, it’s just a delivery system for the butter.  Perfect harmony ensues when both the bread and butter a great.

HR service delivery (you knew it was coming, don’t roll your eyes) is quite like bread and butter.  Imagine your HR business partners as the bread and butter as amazing data and insights.  When the HRBP is great, you have a wonderful partnership of a person who actively gets to know the business, builds great relationships, communicates, plans and collaborates effectively.  Unfortunately, the HRBP is often paired with crappy systems, inaccurate data, and poor reporting capabilities.  The business wants a partner, but they also want a partner that can help diagnose what is going on with their people.

Butter on the other hand is like great data.  When systems and data are in good order, access to reporting and discovering insights become possible.  Insights into the organization and people don’t mean anything  however if all you have is some people at corporate that don’t have relationships into each business segment.  Data and insights get lost in the fray, lost y the wrong people, poorly communicated, and otherwise rendered meaningless.

Just as you can’t eat butter straight (again without incurring ridicule), you need a good delivery system.  That’s the bread. In this case, the delivery of the insights can’t even be consumed without great HRBP’s.  In a prior consulting firm that I worked for, we used to have a line at the bottom of each powerpoint that said something like, “content should be considered incomplete without contextual dialog.”

We’ve been so caught up in data, big data, business intelligence, predictive analytics that we’ve been on a quest to spend millions of dollars to fix all of our foundational data systems.  In a few years, we’re hoping to deliver amazing insights into the organization.  Pair processes with real time intelligence that allows managers to know exactly what actions to take with people.  I’m the downer guy to tell you that without the context of the great HRBP who understands the business, 80% of that cool data analysis is meaningless.  You don’t get insight without understanding the business – all you have is a cool analytic.

That poses the second problem.  Do we actually have great HRBP’s?  The analysis of that has been done in many other places, but the answer for the vast majority of us is “no.”  We’re spending millions of dollars on the data, but we still have not figured out how to transform our HRBP’s.  I’m not saying they are the HR generalists they were 10 years ago, but they still don’t usually have the full trust of the business, the ability to make business, people, financial, operations… correlations, and they still don’t understand the business the way they understand HR.  We still have work to do here, so realize that we can deliver the data, but whether we can make it meaningful is still uncertain.

In our quest for great data delivery to the business, let’s not forget that it’s the pairing of two great elements partnered effectively together than makes the data meaningful.

(this post was made possible during the consumption of some pretty good bread and butter)
(I thought about using “meat & potatoes” but I’m not quite as passionate about that)

Still Grappling With Data Security

Today I was going through airport security with my wife.  I got randomly selected for a screening, which consisted of wiping my hands with a cottonish fabric and sending it through the scanner that detects explosives or something like that.  After the screening, I commented to my wife, “so don’t all the terrorists know to not go to the gun range or handle their explosives within 24 hours of going to the airport?  It seems to me that this particular screen is really not a deterrent.  Any half intelligent terrorist worth their salt has got to have investigated TSA, right?  ((if I end up on some FBI watch list for this post, I’ll be both highly amused and highly irritated at the same time))

I’ve been trying to figure this out for ages.  You see, the problem is that even if you have stricter limits on access to fields and tables in your security setup, even if you limit the number of users to sensitive information, you should not assume that your data is any more secure from unauthorized sources.  All you have done is make it harder to access.  Now, I’m not saying that making it harder to access is not a worthwhile exercise.  It is.  But let’s be honest with ourselves.  Harder was not the goal.  Impossible was.

Pretty much every reporting engine in the world allows you or the user to somehow download the data.  Before we lay blame on the vendors, let’s realize that it’s our own fault – we placed it as a requirement in every single RFP, or we “ooh’d” and “aah’d” when they demo’d how easy it was to download to MS Excel.  Either way, we lose all control over data security once data is downloaded by the user.  Privacy controls are voided, confidentiality issues arise, and we have no idea where the data ends up.  Not that this is all our fault either.  People who have security access to compensation data for example should know better than to email that stuff around.

There are a couple of nice solutions though, but I’m not sure how perfect anything is since at some point most of our organizations need to have data stored or downloaded.  We could of course disable downloading, and every manager, finance person and HR practitioner would just have to pull up a dashboard and view the data in real time.  Right…  At the same time, I’ve been advocating that all HR decisions are based in facts and data, and I can envision a world where meetings get really dull when we gather executives around the table but were not able to prepare decks full of analytics beforehand.

Here are a few things you can do to improve your reporting data security:

  • Make sure managers are certified and trained regarding their data responsibilities when they become managers and every year.
  • Review your security access periodically to make sure sensitive data is being accessed by the right roles – some roles may no longer need the permissions over time.
  • Build a prominent warning at the top of reports when data is loaded to ensure that dissemination of sensitive data is a breach of security.
  • Scrub your reports frequently – you may find old reports that are run with sensitive data that is not necessary based on the purpose of the report.

This is just one of those problems I keep grappling with.  We keep giving managers and non-HR functions access to more data – I do believe the business requires it.  We want everyone to be able to make decisions in real time, but we don’t trust our partners fully either.  I’m also completely uncomfortable giving up and going with the idea that some data is just going to slip through or saying that it’s just a change management problem.  Anyone have any thoughts about what they have done?  Please ping me.

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.