9 min read

My Learning From People Analytics & The Future Of Work #PAFOW

I spent four days in San Francisco visiting People Analytics professionals and attending Al Adamsen's Talent Strategy Institute : People Analytics and Future of Work Conference.  I am deeply grateful for Al's work, that of the conference speakers, and those people working in the space that were willing to allow me to come by, drink their coffee and chat.

Here is what I learned.

Sometime last year a Deloitte report indicated that growth in People Analytics had plateaued or was slowing, however, at the conference this week Josh Bersin @ Deloitte suggested that over night we have moved into the "Tornado" on Geoffrey Moore's Crossing the Chasm diagram.  Basically, I will paraphrase Josh by saying the long winter is over, the birds are chirping but the sleeping giants have awoken.

Another way of putting this is that is that People Analytics has begun the "Tipping Point" of exponential growth and/or that we have started to pass through the infamous "Hockey Stick" point of inflection on a growth curve. Believe me when I say the VC's ears are perking up. Two years ago, when we presented our ideas we got blank stares. It was like presenting at the Elk's Lodge, with less alcohol. Still, they had a point; "who is going to buy it?" We are in a better market for entrepreneurs, but seeing this now everyone else is rushing in too so we all experience something like a tornado until winners and losers are sorted out. 

If you talk to startup entrepreneurs you get a similar picture, although if you get behind the scenes most will admit some degree of frustration with the market - they are having difficulty connecting with buyers and budgets despite that they have made substantial advances in technology and its possible uses within HR. People Analytics Technologists look at the strange HR customer market in utter disbelief, mirroring how the HR customer looks back. These people need us now more than ever, why aren't they beating down a path to our door? To be realistic,  in our winter analogy, I remind, we are still only in February, the Texas Blue Bonnets don't peak until April. Maybe we can go on a walk together then.

Regardless of where we are on the curve, the original view of "slowing" or "plateau" was clearly incorrect. The argument digresses into methodology.  The Deloitte report suggested growth in People Analytics related titles (on job boards) + their consulting revenue was not what would be expected on an exponential growth path, however this vastly underestimated internal job growth, restructuring and refocusing of staff. It is not a small thing - that may have masked at least a 10x year over year magnitude global increase in investment in People Analytics, in one year. Simultaneously, we see growth at PWC, Hay, KPMG, McKinsey and the rest. This is the nature of this space, we have no sense of the pie or each share. People Analytics related job titles in my network indicate anything less than 2x annual growth estimates are far far far off. 2x growth per year is a more than safe bet.  For example, my network of People Analytics friends have expanded by 1000 people in just over the last quarter. We are in a once in a lifetime shift in HR akin to the emergence of Finance from Accounting or Marketing from Sales. There was a time they did not exist - you can't remember it.  It is big trend, it will have broad impact on the world, potentially every human being, and we are apart of it.

Part of the problem is that to get an accurate estimate of growth we must count roles that can be classified under many different titles (People Analytics, HR Analytics, Workforce Analytics, Workforce Insights, Workforce Intelligence, Talent Analytics). These were all represented at the conference.

Additionally, we should consider I/O Psychologists, which may or may not go into a formal People Analytics job title or function but relate to the same underlying trend. I have heard I/O Psychologists are the fastest growing job in the country, with an expected annual growth rate of 53%. I/O Psychologists are 1 out of 4 types of people you will find in these pop up People Analytics groups.  When I talk about People Analytics I/O Psychologists put their hands on their hips and roll their eyes at me, "What about us, we have been doing this work in organizations for a long time?". Meanwhile they meet by themselves at their conference, SIOP.  If you are not an I/O Psychologist, you probably never heard of it.  :-) Love you I/O guys and gals - I just have to take little jabs because I didn't get my phD - it is my own insecurity. 

We also may or may not be counting folks who sit in an HRIS/HR Technology role that have received a new calling. For many, the focus is shifting from an underlying purpose of organizational HR efficiency to organizational HR effectiveness. The emphasis is changing from "some data, any data", to "how do we get data from here to there?", to the question "What can we do with this data?" We learned that Chevron is well into a multi-year effort to train a distributed network of over 200 HR people on how to support business decisions with data - some of these were previously HRIS analyst positions. None of these people were technically "People Analysts", in a People Analytics usage, and many will never carry this actual title. With no standard professional framework for the function materializing yet (like say Finance or Marketing) it is all very confusing, particularly to those on the outside.

Another part of what is going on is technology fragmentation.  We see a host of new services and products from names we have never heard before AND we see extensions of old services and products from all the names we have heard before. I think IBM has 12.5 different products relevant to our space. I don't even think people who work for IBM know all their People Analytics related products. :-) 

In effort to focus on the solution and not the technology, technologists are pretty much all using words now like, "insights", "actionable", "business outcomes", "tell stories with data", etc. such that without looking carefully at the details it is difficult to know what anyone is really doing, why they are different, and why you would go with one over another.  

Technologists are selling to people that have day jobs and People Analytics typically has never before been one of them - so those who have something to sell are on precarious path. CHROs are inclined to hire and wait. Let's let the new guy (or gal) sort this problem out.

The demographic change in HR is exactly what demographic change is to presidential politics.  Change takes a while to get going, plays out over decade, not always in the ways we expect, but demographics are the most powerful force for change on earth. Similarly change in the People Analytics space has primarily been in repurposed headcount and where it comes from - The_New_HR pitted against the huddled old HR masses whose only remaining options are to join, resist or spout utter non-sense.  In our political skit : Jeb Bush appears overwhelmed with disbelief, Hillary Clinton reminds "I was like you once too", and Donald Trump fights politically correctness with factual incorrectness. Sarah Palin is not in the race but hangs around to entertain us with poetry. With Millennials joining together with GenX in disgust of all that is established, boomers gather in fear, and there either is or should be tear gas everywhere. Sarah Palin, I can write poetry too.

Much like the US Republican Presidential debates, it is a crowded field with differing views and plenty of interesting arguments. It is also a complete mess.  Indeed, isn't this is the way the whole world changes? Fits and starts, a little discomfort, and then one day you wake up and think, "20 years ago what exactly did we do without the internet?"  Millennials, by definition, have no idea. Many of us have already tired of email and Facebook.The Millennials response, "come on everyone, we agree, but let's keep moving." Wasn't this true of every generation before them, just with different technology backdrops? Note the background images of the atomic bombs in our parents generation. I believe I caught the tail end of hiding under the desks bit at school - never mind. Maybe Snapchat and Twitter is not really all that bad after all, not negating the atomic power new ways to communicate have.

Absent shared mindspace (among executives, HR and People Analysts) for a dedicated budget the go to pragmatic solutions for HR is: 1.) Hire more people (go figure), 2.) training (go figure) and 3.) try to leverage existing technology until we can figure out our roadmap and make the business case for what else we need to do this thing (go figure).

Lately I have had no fight in me for "Gloves Off Friday Posts" - apparently needing to recover from my brutal loss to Excel a few weeks ago. What is the current #1 business tool for analysis in the world? Excel.  This is not a scientific assessment, but at the conference the number of negative references to "we had to do this in Excel" or we are "trying to get out of Excel", were something akin to counting "ums" when I speak. "Um, there goes another one." :-)  All of the successful examples of People Analytics provided at the conference that I heard were stories of the journey out of Excel. The conference should have been named: "People Analytics And Your Future At Work After Excel". 

In the field of People Analytics, at the moment, success is found via, "we spent x years and x dollars to get on a scalable technology architecture for People Analytics workflow". In one example provided : 2 years and 3.5 Million dollars: I appreciate the transparency.  The stories of this journey provided just at this conference include: Intuit (Michelle Deneau), RackSpace/Tesoro Corp (Robert Lanning), McGraw Hill (Antony Ebelle-Ebanda), Gap (Anthony Walter), GE (Heather Whiteman),... but this is only a small sample. Nobody disagreed. Nobody was shocked. The story is the same everywhere - there are many more interesting things we can do, but there is little way around the journey  - wrapping arms around the data is a part of the journey. Confront the brutal facts.

It should be mentioned the folks that presented  are just the heros, the survivors. I appreciate Tauseef Rahman for pulling me aside and descretely mentioning the problem of "Survivor Bias" - e.g. we do not hear from the failures so we don't know if they might have done the exact same things and got a different result. Survivor bias may be a problem, but unless you go looking around for skeletons you will probably never know for sure. 

At the moment we have no real measure of success for our field. Success is not measured in terms of speed or cost of implementing a data warehouse and reporting suite, relative to peers. That said there are real differences. Absent any other clear measure of success this might do as a proxy in the beginning. I'm anxious to see what happens with Robert Lanning in his new role at Tesoro - he has a particularly good track record.

It is not that Excel and other ad-hoc tools are not useful, it is just that they don't scale with demand after you actually show people what insights it is possible for them to get in our space. Beware of this - they never knew before how powerful this HR Analytics stuff really was - all bets are off when executives finally see it.

Also at the conference, someone reminded us of one of Amit Mohindra's (Apple) clever laws, which I paraphrase as "upon exposure, demand for People Analytics related insights increases exponentially" My personal experience is the same.  If you believe us, pay careful attention to what this implies. If you do not create a scalable analytical architecture at the outset to meet demand in an equation like T+1 = demand^2, you will fail if you cannot increase resource^2. The math suggests this will probably occur about 1.5-2 years into the role. No worries, opportunities in the space will abound for some time so you will get a second or third chance to get it right at a clean employer.  My learning parallels what Ian O'Keefe (next gen Google People Analytics) says, "we must work three problems simultaneously : efficiency, effectiveness, and user experience".  

Some people are better at managing expectations than I was while working in HR, but in my experience the examples provided indicate this scale problem is a competency for technology, not people.  People are for asking good questions, constructing ways of approaching those questions, finding insights, telling stories, consulting, making decisions, etc. --- technology is simply for scale. These are two different sides of the coin that must be managed simultaneously (and well). You can manage expectations with "no", but we are not equally exposed to executives that understand this word - let the conflicts ensue.

In my biased, not humbly stated, opinion you must use technology to take basic reporting off the table, but you must simultaneously create means to expose that data to a variety of downstream systems to support a complete analytical workflow : statistical applications for data scientists (R, SPSS, Python), niche people analytics applications to augment (varied), and data innovative visualization applications used by other functions of your businesses and executives (Tableau, Domo...). If your data doesn't join sources AND port to these environments efficiently, I don't care how good it is now, you are going to get stuck somewhere. If you are addressing the problem with people your people needs/costs are going to need to expand exponentially with demand. If you do not have an exponential budget (e.g. think Google) and don't have a scalable architecture for repeatability and change, then you have real trouble.  

Other troubles.  If you can't get data into advanced statistical models you will bore and be eventually replaced. If you can't communicate in tomorrow's visual frameworks you will be dismissed.

There is no application that is simultaneously best at all desired functions, or after achieving that mountain will be able to maintain a lead for long, so consider carefully how each technology extends and connects with the other technologies, what technology providers are most facilitative of partnerships, and what the support model looks like.  Who is going to do the work to support changes, when, do they fall under your authority to control? Pay attention to all the tiny little details.


Who is Mike West?

Mike has 15 years of experience building People Analytics from the ground up as an employee at the founding of Merck HR Decision Support, PetSmart Talent Analytics, Google People Analytics, Children's Medical (Dallas) HR Analytics, andPeopleAnalyst - the first People Analytics design firm - working with Jawbone, Otsuka and several People Analytics technology start-ups. Mike is currently the VP of Product Strategy for One Model - the first cloud data warehouse platform designed for People Analytics.

Mike's passion is figuring out how to create an analysis strategy for difficult HR problems. 

Connect with Mike West on Linkedin 


I’m putting together a series of live group webinars where I will be revealing a process for dramatically increasing probability of success of People Analytics - building on a career of success and failures (Merck, PetSmart, Google, Otsuka, Children's Medical Dallas and Jawbone) - and applying new ideas I have developed over the last few years applying ideas from Lean to People Analytics.

The goal of this webinar series is to engage a select group of qualified early adopters, who have access to an organization, are willing to apply the process, report back how things are going, and work out the bugs out together. This group will have opportunity to share their findings with the broader People Analytics and HR community, if you choose.

If you have interest in participating in the webinar series, let me know here: (http://www.misc-peopleanalytics.com/lean-series

And if you know anyone else who you think would, please let them know too!

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