PODCAST - #HRHappyHour 201 - Putting the Fun into Analytics

HR Happy Hour 201 - Putting the Fun Into Analytics

Recorded Thursday January 29, 2015

Hosts: Trish McFarlane, Steve Boese

Guests: Mike Psenka,  Senior VP of Workforce Analytics,  Equifax Workforce Solutions

Ed Pertwee, Head of Workforce Planning, BT

Jennifer Payne, Editor, Women of HR

Listen to the show HERE

In the latest HR Happy Hour Show, Trish and Steve recorded a live HR Happy Hour show from the recent Brandon Hall Excellence conference, where Mike, Ed, Steve and Trish conducted a panel discussion on how to leverage data and analytics for HR and organizational success.

Mike and Ed both shared some excellent examples, (both in the panel and in the HR Happy Hour podcast), of how, where, and to what effect data and analytics are making an impact in workforce planning, compliance, and to improve business results. There are some amazingly powerful applications for using data in a wide variety of contexts - where to locate company facilities, the effect of demographic shifts on performance, and how long commute times impact engagement and satisfaction.

Additionally, Steve defended Carmelo Anthony of the Knicks, Trish let us know that the number '201' should not be said as 'two hundred and one', and we learned that a husband should never question the strength and intensity of his wife's labor contractions.

You can listen to the show on the show page here, and using the widget player below, (email and RSS subscribers will need to click through). 

Check Out Business Podcasts at Blog Talk Radio with Steve Boese Trish McFarlane on BlogTalkRadio

 

As always, you can listen to the current and all the past shows from the archive on the show page here, on our HR Happy Hour website, and by subscribing to the show in podcast form on iTunes, or for Android devices using Stitcher Radio (or your favorite podcast app). Just search the iTunes store or your podcast app for 'HR Happy Hour' to add the show to your subscriptions.

This was a really fun show with some fantastic guests and I hope you enjoy listening!

What Will Happen if we Move the Company: The Limits of Data

Some years back in a prior career (and life) I was running HR technology for a mid-size organization that at the time had maybe 5,000 employees scattered across the country with the largest number located on site at the suburban HQ campus (where I was also located). The HQ was typical of thousands of similar corporate office parks - in an upscale area, close to plenty of shops and services, about one mile from the expressway, and nearby to many desirable towns in which most of the employees lived. In short, it was a perfectly fine place to work close to many perfectly fine places to live.

But since in modern business things can never stay in place for very long, a new wrinkle was introduced to the organization and its people - the looming likelihood of a corporate relocation from the suburban, grassy office park to a new corporate HQ to be constructed downtown, in the center of the city. The proposed new HQ building would be about 15 miles from the existing HQ, consolidate several locations in the area into one, and come with some amount of state/local tax incentives making the investment seem attractive to company leaders. Additionally, the building would be owned vs. leased, allowing the company to purpose-design the facility according to our specific needs, which, (in theory), would increase overall efficiency and improve productivity. So a win-win all around, right?

Well as could be expected once news of the potential corporate HQ relocation made the rounds across the employee population, complaints, criticism, and even open discussions of 'time to start looking for a different job' conversations began. Many employees were not at all happy about the possible increase in their commuting time, the need to drive into the 'scary' center city location each day, the lack of easy shopping and other service options nearby, and overall, the change that was being foisted upon them.

So while we in HR knew (or at least we thought we knew), there would be some HR/talent repercussions if indeed the corporate HQ was relocated, we were kind of at a loss to quantify or predict what these repercussions would be. The best we were able to do, (beyond conversations with some managers about what their teams were saying), was to generate some data about the net change in commuting distance for employees, using a simple and open-source Google maps based tool.

With that data we were able to show that (as expected), some employees would be adversely impacted in terms of commuting distance and some would actually benefit from the HQ move. But that was about as far as we got with our 'data'.

What we didn't really dive into (and we could have even with our crude set of technology), was break down these impacts by organization, by function, by 'top' performer level, by 'who is going to be impossible to replace if they leave' criteria.

What we couldn't do with this data was estimate just how much attrition was indeed likely to occur if the move was executed. We really needed to have an idea, (beyond casual conversations and rumor), who and from what areas we might find ourselves under real pressure due to possible resignations. 

And finally, we had no real idea what remedial actions we might consider to try and stave off the voluntary and regrettable separations (the level of which we didn't really know).

We basically looked at our extremely limited data set and said, 'That's interesting. What do we do with it?'

Why re-tell this old story? Because someone recently asked me what was the difference between data, analytics, and 2015's hot topic, predictive analytics. And when I was trying to come up with a clever answer, (and I never really did), I thought of this story of the corporate relocation.

We had lots of data - the locations of the current campus and the proposed new HQ. We also had the addresses of all the employees. We had all of their 'HR' data - titles, tenure, salary, department, performance rating, etc.

We kind of took a stab at some analytics - which groups would be impacted the most, what that might mean for certain important areas, etc. But we didn't really produce much insight from the data.

But we had nothing in terms of predictive analytics - we really had no idea what was actually going to happen with attrition and performance if the HQ was moved, and we definitely had no ideas or insights as to what to do about any of that. And really that was always going to be really hard to get at - how could we truly predict individual's decisions based on a set of data and an external influence that had never happened before in our company, and consequently any 'predictions' we made could not have been vetted at all against experience or history?

So that's my story about data, analytics, and predictive analytics and is just one simple example from the field on why this stuff is going to be hard to implement, at least for a little while longer.

REPRISE: The Analytics Takeover Won't Always Be Pretty

Note: The blog is taking some well-deserved rest for the next few days (that is code for I am pretty much out of decent ideas, and I doubt most folks are spending their holidays reading blogs anyway), and will be re-running some of best, or at least most interesting posts from 2014. Maybe you missed these the first time around or maybe you didn't really miss them, but either way they are presented for your consideration. Thanks to everyone who stopped by in 2014!

The below post first ran back in March and is a good example of a combination of themes that I love writing about on the blog: NBA basketball and talent management. In this piece I took a look at the trend developing in the modern NBA, where business and tech savvy (and new) team owners are valuing data and analytics skills and experience more than decades of actual basketball experience when making executive hires. As you would expect this change in hiring philosophy will have pretty significant implications for talent, and might just be indicative of bigger talent management challenges. 

Happy Sunday!

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The Analytics Takeover Won't Always Be Pretty

Seems like it has been some time since I dropped a solid 8 Man Rotation contribution here on the blog, so to remedy that, please first take a look at this recent piece on ESPN.com, 'Fears that stats trump hoops acumen', a look at the tensions that are building inside NBA front offices and among team executives.

In case you didn't click over and read the piece, the gist is this: With the increased importance and weight that a new generation of NBA team owners are placing on data-driven decision making and analytical skills, that the traditional people that have been the talent pool for NBA team management and executive roles, (former NBA players), are under threat from a new kind of candidate - ones that have deep math, statistics, and data backgrounds and, importantly, not careers as actual basketball players.

Check this excerpt from the ESPN piece to get a feel for how this change in talent management and sourcing strategies is being interpreted by long time (and anonymously quoted) NBA executives:

Basketball guys who participated in the game through years of rigorous training and practice, decades of observation work through film and field participation work feel under-utilized and under-appreciated and are quite insulted because their PhDs in basketball have been downgraded," the former executive, who chose to remain anonymous, told ESPN NBA Insider Chris Broussard.

One longtime executive, who also chose to remain anonymous, postulated that one reason why so many jobs are going to people with greater analytical backgrounds is because newer and younger owners may better identify with them.

"Generally speaking, neither the [newer generation of] owners nor the analytic guys have basketball in their background," the longtime executive told Broussard. "This fact makes it easy for both parties to dismiss the importance of having experience in and knowledge of the game.

The piece goes on to say that since many newer NBA owners have business and financial industry backgrounds, (and didn't inherit their teams as part of the 'family business'), that they would naturally look for their team executives to share the kinds of educational and work experience profiles of the business executives with which they are accustomed to working with, and have been successful with.

The former players, typically, do not have these kinds of skills, they have spent just about all their adult lives (and most of their childhoods), actually playing basketball. A set of experiences, it is turning out, no longer seems to provide the best training or preparation for running or managing a basketball team. 

But the more interesting point from all this, and the one that might have resonance beyond basketball, is the idea that the change in hiring philosophy is coming right from the top - from a new generation of team owners that have a different set of criteria upon which they are assessing and evaluating talent.

Left to tradition, hiring and promotion decisions would have probably only slowly begun to modernize. But a new generation of owners/leaders in the NBA are changing the talent profile for the next generation of leaders.

The same thing is likely to play out in your organization. Eventually, if it has not happened yet, you are going to go to a meeting with your new CHRO who didn't rise through the HR ranks and maybe is coming into the role from finance, operations, or manufacturing. In that meeting your 19 years of experience in employee relations might be a great asset to brag on. Or it might not be.

And you might find out only when you are introduced to your new boss, who has spent her last 5 years crunching numbers and developing stats models.

TOP HR DATA PLAY: Kill the FTE

I had a fun time riding shotgun to Kris Dunn yesterday on the Fistful of Talent Webinar titled, HR Moneyball:  The FOT Bootstrapper Guide To Getting Started With Big Data, in which KD and I took a look at some the ways that HR/Talent pros can use Big Data and Business Intelligence approaches to raise their games and drive the adoption of so-called 'Data-driven HR' in their organizations.

Of the five 'Big Data' plays in the FOT playbook, I think the one that I dig the most was #3, an idea called 'Salary Cap Utilization'. The basic idea is this - take a play from the world of sports leagues like the NBA and NFL that force teams to operate under a set of rules that govern maximum total player compensation, (the 'Cap'), and apply it inside your organization.

I know what you are saying, that we already do that, it's called the Annual Salary Budget. We've been managing compensation that way forever. Each budget holding group or manager is allotted 'X' amount of dollars he/she can 'spend' on total comp for the year and they (probably subject to a dozen other HR rules around increase percentages, salary bands, etc.), have to sort out how that salary budget is allocated among their staffs.

But chances are you are placing an additional, and probably unnecessary constraint on your managers as well - something called the full-time equivalent (FTE) budget.

The FTE budget tells managers that in addition to the maximum amount of $$ you can spend on comp (The Salary Cap), there is some (kind of arbitrary) maximum number of headcount that you can spend your Salary Cap on, i.e., the FTE budget.

When I first moved into an HR role, managing the HR systems at a mid-sized company, and first encountered the acronym FTE, I had to ask someone to explain it to me, as I had never seen it before. It seemed like a made-up kind of a construct, especially when you have to spend time breaking down and trying to convert worker schedules into their 'full-time' equivalents. And what, really, is 'full-time' anyway? That too, is kind of an arbitrary measurement to some degree.

But $$ are not arbitrary and are not subject to interpretation or manipulation. Everyone understands what a dollar-based budget means.

What are the advantages of dropping the FTE budget/constraint from your playbook?

1. It gives leaders/managers more autonomy on how they allocate compensation across teams. Instead of operating under the dual constraints of 'heads' and $$, they simply have to make it work within the Cap. Need to makes some big changes to reinvent their department? Make it work under the Cap. Want to expand into something new? What can you give up to stay within the Cap? Have 5 all-star, 'A' players that need to get paid or they will walk out the door? Then pay them, just be ready to make the cuts elsewhere to remain within the Cap. 

2. It forces the organization to be more flexible. The overwhelming tendency in an FTE-influenced budgeting scheme is for managers to guard 'their' FTEs like grim death. Have a position sit open or vacant for too long and managers will scramble to fill it with just about anyone, just so they don't 'lose' that precious FTE in the next budgeting cycle. Have a solid employee that wants to transfer out to a role in a different department? A role  that might better suit their skills and enhance their career development? Better be willing to give up an FTE buddy to make that happen.

3. It allows HR pros to be more consultative and progressive when talking about things like merit increases, equity increases, offers above salary band maximums, counter-offers, retention bonuses, and most everything related to comp. Remove that FTE constraint and now more of the comp game is open for discussion and adaptation. HR is working with the business around what is important to the business - the relative cost of performance and how to get the most production from available resources. HR can now be in the game of reporting/advising on Salary Cap Utilization instead of counting up heads, something that in most instances does not really matter.

We had a few other Big Data plays that we shared in the Webinar that were pretty neat as well (Hiring Manager batting average, turnover prediction, Health Care claims per capita), but for me eliminating the FTE might be the simplest and easiest one to get started with. 

Have a great weekend!

The analytics takeover won't always be pretty

Seems like it has been some time since I dropped a solid 8 Man Rotation contribution here on the blog, so to remedy that, please first take a look at this recent piece on ESPN.com, 'Fears that stats trump hoops acumen', a look at the tensions that are building inside NBA front offices and among team executives.

In case you didn't click over and read the piece, the gist is this: With the increased importance and weight that a new generation of NBA team owners are placing on data-driven decision making and analytical skills, that the traditional people that have been the talent pool for NBA team management and executive roles, (former NBA players), are under threat from a new kind of candidate - ones that have deep math, statistics, and data backgrounds and, importantly, not careers as actual basketball players.

Check this excerpt from the ESPN piece to get a feel for how this change in talent management and sourcing strategies is being interpreted by long time (and anonymously quoted) NBA executives:

Basketball guys who participated in the game through years of rigorous training and practice, decades of observation work through film and field participation work feel under-utilized and under-appreciated and are quite insulted because their PhDs in basketball have been downgraded," the former executive, who chose to remain anonymous, told ESPN NBA Insider Chris Broussard.

One longtime executive, who also chose to remain anonymous, postulated that one reason why so many jobs are going to people with greater analytical backgrounds is because newer and younger owners may better identify with them.

"Generally speaking, neither the [newer generation of] owners nor the analytic guys have basketball in their background," the longtime executive told Broussard. "This fact makes it easy for both parties to dismiss the importance of having experience in and knowledge of the game.

The piece goes on to say that since many newer NBA owners have business and financial industry backgrounds, (and didn't inherit their teams as part of the 'family business'), that they would naturally look for their team executives to share the kinds of educational and work experience profiles of the business executives with which they are accustomed to working with, and have been successful with.

The former players, typically, do not have these kinds of skills, they have spent just about all their adult lives (and most of their childhoods), actually playing basketball. A set of experiences, it is turning out, no longer seems to provide the best training or preparation for running or managing a basketball team. 

But the more interesting point from all this, and the one that might have resonance beyond basketball, is the idea that the change in hiring philosophy is coming right from the top - from a new generation of team owners that have a different set of criteria upon which they are assessing and evaluating talent.

Left to tradition, hiring and promotion decisions would have probably only slowly begun to modernize. But a new generation of owners/leaders in the NBA are changing the talent profile for the next generation of leaders.

The same thing is likely to play out in your organization. Eventually, if it has not happened yet, you are going to go to a meeting with your new CHRO who didn't rise through the HR ranks and maybe is coming into the role from finance, operations, or manufacturing. In that meeting your 19 years of experience in employee relations might be a great asset to brag on. Or it might not be.

And you might find out only when you are introduced to your new boss, who has spent her last 5 years crunching numbers and developing stats models.

Have a great week!