Happiness and HR Data - Coming to a delivery truck near you

Sometimes in all the conversation in the HR/talent space about the increased use of data, Big Data, and workforce analytics by HR leaders and organizations that practical, innovative (and possibly somewhat creepy), examples of how all this data coupled with better tools to understand it all are sometimes hard to find. Or hard to understand. Or not really specific enough that they resonate with many HR and Talent pros.

Lots of the articles and analysis about data and analytics for HR end up reading more like, 'This is going to be important', or 'This is going to be extremely important and you are not ready for it', or even 'This is going to be extremely important, you are not ready for it, but I (or my company) is ready to help you sort it out.'

Fortunately for you, this is not one of those kind of articles.

Over the weekend I read a long-ish piece called Unhappy Truckers and Other Algorithmic Problems on the Nautilus site, that provides one of the most interesting and practical examples of how a better understanding of HR data, (among other things), is helping transportation companies plan routes, assign work, and execute managerial interventions, often before they are even needed.

At the core of most transportation and delivery problems is essentially a logistics challenge as the 'Traveling Salesman' problem.  Given a fixed time period, say a day or an 8-Hour shift, and set number of destinations to visit to make sales calls, how then should the traveling salesman plan his route for the maximum efficiency. 

For a salesperson making four or five stops in a day the problem is usually not that hard to solve, but for say a UPS or FedEx delivery truck driver who may have as many as 150 stops in a day - well that problem of math and logistics gets much, much more complex.  And, as the piece from Nautilus describes, the Traveling Salesman problem is not only incredibly important for transportation companies to try and solve, it becomes even more complex when we factor in the the delivery drivers are actual human beings, and not just parts of an equation on a whiteboard.

Check out this excerpt from the piece to see how one (unnamed) delivery company is taking HR and workforce data, couples with the realization that indeed, people are a key element,  and baking it in to the classic math problem of the Traveling Salesman:

People are also emotional, and it turns out an unhappy truck driver can be trouble. Modern routing models incorporate whether a truck driver is happy or not—something he may not know about himself. For example, one major trucking company that declined to be named does “predictive analysis” on when drivers are at greater risk of being involved in a crash. Not only does the company have information on how the truck is being driven—speeding, hard-braking events, rapid lane changes—but on the life of the driver. “We actually have built into the model a number of indicators that could be surrogates for dissatisfaction,” said one employee familiar with the program.

This could be a change in a driver’s take-home pay, a life event like a death in the family or divorce, or something as subtle as a driver whose morning start time has been suddenly changed. The analysis takes into account everything the company’s engineers can think of, and then teases out which factors seem correlated to accident risk. Drivers who appear to be at highest risk are flagged. Then there are programs in place to ensure the driver’s manager will talk to a flagged driver.

In other words, the traveling salesman problem grows considerably more complex when you actually have to think about the happiness of the salesman. And, not only do you have to know when he’s unhappy, you have to know if your model might make him unhappy. Warren Powell, director of the Castle Laboratory at Princeton University’s Department of Operations Research and Financial Engineering, has optimized transportation companies from Netjets to Burlington Northern. He recalls how, at Yellow Freight company, “we were doing things with drivers—they said, you just can’t do that.” There were union rules, there was industry practice. Tractors can be stored anywhere, humans like to go home at night. “I said we’re going to need a file with 2,000 rules. Trucks are simple; drivers are complicated."

Did you catch all the HR/talent/workforce data baked into the model described above?

Payroll, time and attendance, life events that likely would show up in the benefits admin system, scheduling are all mentioned, and I bet digging deeper into the model we'd find even more 'talent' elements like supervisor or location changes, time since a driver's last compensation increase, and maybe even 'softer' items like participation in company events or number of unread emails in their inbox.

The specifics of what bits of talent data aere being incorporated into the process matter less than the fact that in the example the HR data is being mashed up so to speak with the 'hard' data from the truck itself (which is another interesting story as well), and analyzed against past driver experiences to alert managers as to when and where an accident is more likely to occur.

There is even more to the problem than the technical observations from the truck itself, and the alogorithms' assessment of the HR/Talent data - things like Union rules and contracts factor into the equation as well. 

But for me, this example of taking HR data and using it not just to try and 'predict' HR events like involuntary turnover or a better or worse performance review score, and apply it to real business outcomes, (the likelihood of accidents) represents a great example of where 'Big Data for HR' is heading.

I definitely recommend taking a few minutes this week to read the entire piece on the Nautilus site, and then think about some the next time the FedEx driver turns up with a package.

Have a great week!

Off Topic: False Memories

I received an email yesterday from an HR industry person who I have met in person on at least three occasions in the last few years. In the (very pleasant and cordial note), this person indicated how he was 'looking forward to meeting me in person' at the upcoming HR Tech Conference this October.  

Yep, I'm looking forward to it as well pal. Maybe we can spend a few minutes reminiscing about the other three times we've met for the first time.

Whatever, I don't really care that much except I will probably, if I do meet this person again, play it off like we've not met before either, in order to avoid further awkwardness.

But the exchange made me think about memory more generally, and then, (since unlike my 'friend' who can't remember the three times he's met me before), I have fantastic recall, I thought about this recent piece from the MIT Technology Review - Scientists Make Mice 'Remember' Things That Didn't Happen. 

Check out what some of the weird scientists at MIT are up to:

Scientists have created a false memory in mice by manipulating neurons that bear the memory of a place. The work further demonstrates just how unreliable memory can be. It also lays new ground for understanding the cell behavior and circuitry that controls memory, and could one day help researchers discover new ways to treat mental illnesses influenced by memory.

In the study, published in Science on Thursday, the MIT scientists show that they can modify a memory and have a mouse believe it experienced something it didn’t. Susumu Tonegawa, a neuroscientist at MIT, and members of his lab used mice that were genetically modified to allow for certain neurons to be activated with a flash of light; the technique enabled the researchers to activate a memory that caused a mouse to believe it had experienced electrical shocks in a particular box, even though no such thing had happened there. “The process of memory is nothing like a tape recording,” says study co-first author Steve Ramirez. “It’s really malleable and susceptible to the incorporation of new information.

This is all kinds of awesome, and not just because it basically validates most of the premise of Total Recall. 

More from the MIT piece:

More broadly, neuroscientists are increasingly exploring human cognition at its molecular and cellular origins. Someday, this deeper understanding could lead to better or novel treatments, such as memory implants that replace lost memories or novel drugs to boost beneficial memory reconsolidation.

Implants to replace lost memories?

Memory reconsolidation?

Sounds like some great new tools for performance improvment plans everywhere.

But there is one more bit from the MIT piece that might explain that email I received yesterday from the guy who can't remember meeting me: 

Neuroscientist Sheena Josselyn agrees that the results imply that false memories are not as uncommon as many think. “At some point, we shouldn’t really trust our memories, because some things we remember happening didn’t really,” she says.

Ah, so maybe that is it. Maybe I am the one who has got it all wrong here and my email pal is right.

Maybe my 'memory' of our three previous meetings is what can't be trusted. Interesting.

I also remember a time when I had a full head of wavy brown hair too, I hope it doesn't turn out that didn't really happen either.

Have a great weekend!

Committing a felony is against team policy, and other things we shouldn't have to say

Is is quite possible that after the National Basketball Association, my next favorite league/sport to watch and follow is soccer's English Premier League. It is a fantastic sport to watch, and the top level of English teams like Manchester United, Arsenal, and Chelsea are some of the most valuable and popular sports teams in the entire world.

The Premier League club I support is Liverpool, (for reasons too boring to re-tell), and while I am not a super hardcore supporter, I do try and keep up with the off-season player transfers and signings by the club and other elements of club-related news.

But this bit of Liverpool team news that was reported earlier in the week, Liverpool issue list of 'unacceptable' words to fight discrimination made me pause for a moment, as it is once again, in classic 8 Man Rotation style, the worlds of sports and HR colliding.Click to enlarge

Rather than try to summarize the entire piece, I will just lift quote from the Guardian piece referenced above: 

Liverpool have issued members of staff with a list of "unacceptable" words and phrases in their efforts to combat all forms of discrimination at Anfield. (a pic of the leaked list of 'words you better not say is at right)

The guide, part of a wider education programme run by the club, details terms that employees should deem offensive under the headings of race/religion, sexual orientation, gender and disability. Most are self-explanatory and the guide advises that it is "important to understand the context of what's being said", as in the use, under gender for example, of "princess" or "don't be a woman" on the Anfield terraces next season.

Liverpool's list of what is "usually offensive and the club considers unacceptable" has been given to all full-time and casual members of staff who have contact with the public on matchdays or on a daily basis. The club were widely criticised for their support of Luis Suárez when the striker was found guilty in December 2011 of having used racially abusive language towards Patrice Evra but view their education programme as one of several proactive measures taken to combat discrimination.

That is fantastic, (sarcasm on). A list, organized by type of slur, of the things that you probably ought not to say at work, heck, you probably ought not to say anywhere.

I can only imagine the day the HR or Operations folks (or whomever crafted this list) sat around the conference table saying things like, 'There has to be more ways to offend gay people. C'mon - let's think darn it!'.

I get why Liverpool specifically, and football/soccer more generally take the issue of discrimination seriously enough to want to be extremely precise and particular about the standards of behavior and discourse that are expected, and what, again specifically, is unacceptable. There continues to be ugly incident after ugly incident of incredibly offensive and even violent actions that are in one way or another tied back to the sport. They can't pretend that is not the reality and recent history in their industry.

But then again, creating and distributing a printed list of these (mostly), obviously offensive words seems a little strange too. Did they really think their employees don't realize the N-word is offensive and it should not be used in the workplace?

A bunch of years back when he was the head football coach at Oklahoma University, Barry Switzer was asked during a press conference to try and explain the reasons for a recent spate of player run-ins with the law, including a couple of pretty serious charges like car theft and assault. After trying to talk about the team expectations and support structures in place to try and prevent such incidents an exasperated Switzer finally said, 'I didn't think I had to put a sign on the locker room wall saying that 'Commiting a felony is against team policy.'

That story is what I recalled when reading about the Liverpool 'list of things we shouldn't have to tell you not to say, but we can't figure out why enough people don't realize that so we had to make this list to be sure'.

People can be really disappointing sometimes I guess.

Red eye flights, skinny jeans, and being tough enough to work here

Disclaimer: It is a total coincidence that I have the second post about Ford Motor Company in as many weeks. I am not on the Ford payroll. In fact, I have a Chevy truck. So there.

Mission statements, culture maps, or an articulation of the 'vision' or purpose of an organization - these are all fairly common in organizations and often mocked or at least ignored. Usually they are either so vague and obvious that they are meaningless - 'We strive to delight our customers every day', or are so specific and drawn-out that they read like marketing brochure copy - 'Our goal is to be the top-rated supplier of industrial fasteners, ties, and aluminum sprockets to the machine, engine, and turbine sub-assembly markets that we compete in around the world.'

So when you come across a mission statement or a list of operating principles that actually doesn't suck, and doesn't take itself too seriously, (I think a pre-requisite for 'not sucking') that are a part of an organization's DNA it is fairly noteworthy or at least interesting.

So the connection back to Ford, (and once more for clarity, I am a Chevy guy), is this piece from Forbes - Are You Manly Enough to Own a Ford Truck?, that provides a glimpse into some of the unique rules/expectations/operating principles that are apparently a part of the makeup of not just people who buy Ford trucks, but as you will see from some of the items on the list, also the people that work at Ford building the trucks.

Here are a few selections from the list - and I'll have some comments after the break:

• Raw meat is acceptable team food.  Raw fish is not.

• Roller luggage is expressly forbidden, except for golf bags.

• Earplugs are not permitted at NASCAR races or National Hot Rod Association events.

• No whining!

• Airport trams and moving sidewalks are off-limits in order to promote team conditioning.

• No wimpy cell phone ring tones.

• Jackets or ponchos are acceptable rain gear. Umbrellas are not.

• True BFT Truck Team members wear real jeans, not skinny jeans.

• For flights departing at 7 a.m. or later, an office appearance is expected prior to departure. Red-eye flights are expected to maximize productivity.

• There are no “travel days.”

A pretty cool list, if not totally serious, but it does go quite a bit further than most standard mission statements or organizational philosophy statements do to better describe the type of people that will actually be likely to succeed, (or at least get along), in the group.

I like the list because it is descriptive, specific, and funny. The kinds of traits that we often find lacking in most corporate-speak that passes for HR and organizational communication. Are these 'real' rules for working on the Ford Trucks team? Are they actually used in hiring and retention discussions?

I don't know for sure, but that doesn't make them less cool, and it doesn't stop any of us from thinking about our version of a similar list of philosophies, expected behaviors, and personality types of the people that we want to work with and that will succeed.

Have a great week everyone!

Three keys if you want to become a more data-driven organization

So you've bought into it -  Big Data, Moneyball for HR, workforce analytics - all of it. And whatever you call this increased reliance on data, analysis, and more objective information in your talent processes, chances are this represents a pretty significant change to the way you've always done business, how managers and leaders have made decisions, and perhaps most importantly how you evaluate and reward employees.

Of the many tough challenges you have to negotiate if indeed you are the designated numbers geek/quant in your shop, once again the world of sports offers three recent examples, (NOT AGAIN), that help to point out some key focus points or areas of concern as you hatch your nefarious plans.

One - Make sure you as the 'stats' person, knows how to translate the numbers into strategies that are likely to get buy-in from the team. From the SB Nation blog - How and why NBA coaches communicate advanced metric to players, an interesting piece on the Boston Celtics' new coach Brad Stevens and his desire to bring more data and analytics to bear in the organization:

The numbers don't always offer solutions, but they do tend to generate better options and that's all an NBA team can offer with each possession and every front office decision. That's the next step in the analytics movement. What started in blogs has been appropriated by front offices and has now trickled down to coaches. Communicating those ideas effectively to players is the final hurdle.

Two - Make sure the team members know how to and understand the importance of doing more accurate self-assessments in light of the new measurements. It is great when management and leaders make the move towards a more data-driven decision making process, but don't forget the folks on the front lines.

Here is a great example from a recent piece on the WEEI Radio site by former Major League baseball player Gabe Kapler titled STATS 101: Why it's time to re-educate players in meaningful statistics:

To take it a step further, when we discussed our numbers with our agents, it was in the form of the traditional verticals, the ones we used for decades prior. We correctly assumed that our reps were using these statistics in conversations with the general managers of our clubs. We stood in the truth that our value — our worth as baseball players — was wrapped up in these metrics.

Times have changed, but substantially less among players. While progressive front offices have altered the way they evaluate us, we have lagged far behind in the way we grade ourselves. It’s akin to unhealthy communication in a relationship.

Three - Make sure what you are measuring and holding people accountable for, is actually at least largely in their conrol or influence. This really isn't exclusive to a more data-centric approach to business, it applies everywhere. We generally can only control what we can control and penalizing the clever point guard because the slow-footed center can't convert enough of his excellent passes near the rim is not a long-term winning strategy.

More from the Kapler piece:

 If, for example, we taught pitchers about Fielding Independent Pitching — which truly spotlights what a pitcher can control (walks, strikeouts and homers) and removes balls in play, thereby eliminating a fielder’s ability to have an impact on the outcome of a play and consequently a pitcher’s line — we place the responsibility right where it belongs. If we show a hitter how well hit balls and exit velocity/speed off the bat are being examined more and more closely, then the hitter will freak out less when crushing a ball off the pitcher’s forearm and having it ricochet safely into the glove of the first baseman for an out. He may walk back to the dugout thinking, “Ka-ching!” instead of throwing a water cooler and forcing some nearby cameraman to change clothes. 

Let's do a quick review:

One -  make sure you know how to communicate the value and merit of these new statistical approaches to the team. 

Two - make sure the team starts to do their own self-assessments through the lens of these new data-driven approaches

Three - make sure you are holding people accountable for numbers that they can legitimately influence and can they can own.

What other tips or recommendations do you have to transform an organization from one that relies on gut feeling to one that counts on the data?