VIDEO: Take That For Data

Yes, I know this is a few days old, and yes I know the 'Take That for Data' meme has probably already flamed out from your Twitter feed, but there still may be someone out there who missed Memphis Grizzlies coach David Fizdale's epic rant following a playoff loss to the San Antonio Spurs last week.

Tiny bit of backstory to set this up.

In the game of interest, (which the Spurs won), the Spurs were granted a massive advantage in free throw attempts - with one Spurs player Kawhi Leonard shooting 19 free throws himself, more than the entire Memphis team. After the game Coach Fizdale reflects on the loss, and the officiating in an already classic 2:45 minute rant.

Check the video below, and make sure you make it to the end,  (email and RSS subscribers click through), then some comments from me about why this was a really interesting take, (that have nothing to do with basketball).

Not one but two great meme lines in the rant!

But the walk off line, 'Take That for Data' is the one that stuck with me. Mainly because in the same video where Fizdale asserts 'I'm not a numbers' guy, he proceeds to rattle off 12 different statistics from the game - data points that strengthen his argument that the game was poorly officiated and that disadvantaged his team.

Why does this matter at all to anyone except hard core NBA fans?

Because Fizdale in his little rant makes plain the challenge and the tension that often arises in organizations and with leaders when they are pressed to take a more data driven approach to business/HR/talent when they are not naturally inclined to do so.

Don't tell me this is all about the data, then make decisions or drive toward outcomes that are incongruent with the data itself. 

Or said differently, if you are going to be the hero in your organization that will push the 'data' agenda, then be prepared to have your data be called out and your conclusions challenged when others have a shot at interpreting the data as well.

Take that for data.

Have a great week!

On the balance between data and people

Quick shot for a busy Monday. If your organization is one of the many that has or has implemented or has at least considered implementing a more data intensive and analytical approach to the HR and talent management, then I recommend taking a quick look at the comments from a young leader in another discipline where data and analytics have completely changed talent management - the world of professional soccer.

Since Moneyball, and maybe even before that, all kinds of sports (baseball, basketball, soccer, and more), have seen a kind revolution and sea change in the approach to player evaluation, team building, and even in-game strategy driven by the increasing availability of advanced data about player performance and better tools to assess and crunch that data. No leader of even a half-decent professional sports team fails to consider metrics, data, analytics, etc. when making decisions about talent.

And so it has also come to pass that in the 'real' world of work, more and more organizations are or have embraced similar and data driven approaches in their talent management programs. Assessments that validate a candidate's 'fit' for a role, algorithms that assess employee data to flag flight risks, or models that pinpoint expected future leaders are just some of the examples of how data/science/analytics are being used in HR.

But if you have begun adopting these data-driven approaches to talent management processes and decisions how can you know if you have perhaps gone too far, or have let the 'human' part of human resources fall too far by the wayside? 

I think the answer is that it is kind of hard to know for sure, but you probably know it when you see it. But i think it stands to reason that today still, in any field that human performance and human capability are what matters, then it can be dangerous to completely trust the data and fail to consider the people.

Here's what Julian Nagelsmann, (millennial, for what it's worth), manager of the German Bundesliga side Hoffenheim has to say about blending data, analytics, and the 'human' side of management in forming his approach to leading his team. (Courtesy of The Ringer):

I studied sports science and have a bachelor of arts. The variety of football data is becoming more and more specific. You shouldn’t make the mistake of looking at football as a science, but there are more diagnostic tools, and the examination of the human body is improving in football: What effect does AstroTurf have on the body? What does lots of shooting do? What does lots of passing do to muscles? There are always new methods and you have to go with the science, but football will never be a science.

There will be more influence from science to analyze games, and you have to keep educating yourself. But you mustn’t make the mistake of seeing football as something technocratic or based on something that is fed by science. You can develop the person by using scientific aspects in your judgement, but the human is still the focus.

A really interesting take from a manager of a team of highly accomplished (and highly compensated), professional soccer players. Even in sports, where every move, every decision, every physical reaction to game circumstances can and is analyzed, and the subsequent data parsed and performance conclusions reached - Nagelsmann still cautions us to not forget the humans. 

In fact, he goes much further than that - he claims the human has to remain the focus.

Take in the data, be open to the data, don't be a data Luddite - but don't let it become the only tool you use as a manager or a leader.

Super perspective and advice from a leader who sits completely in the nexus of an industry and discipline that has been historically a 'gut feel' business that is being disrupted by data and analytics. 

Use the data. But don't forget about the people.

Great advice for a soccer team or for an organization near you.

Have a great week!

What can we prove?

Over the weekend I went all 'Back in the day' with my 'Generation X movies, ranked' post, but something I heard today made me compelled to fire up the way back machine once again. 

The backstory....

Sitting on a (delayed) plane waiting to get clearance to take off last night and I could not help but overhear the dude next to me carry on a 'You were supposed to turn off your cell 10 minutes ago but obviously you are too important to follow the rules' conversation with what I think must have been his colleague at whatever monkey business they were up to.

My pal in seat 4A kept repeating the following questions to the person on the other end of the conversation, (who I have to think was probably praying for merciful death, or a fire drill):

"Do we know that for sure? Can we prove it?"

So to tie this back to the 'In the day' reference at the top, the (interminable) conversation reminded me of one of my favorite films that I probably could have included on the 'Gen X' list, 'And the Band Played On', an HBO film from 1993 about the discovery of the AIDS virus and the political and medical flights that were hallmarks of the earliest efforts to combat the disease. 

In the film, the doctors and the medical researchers of the CDC are featured prominently - the agency was at the time at the forefront for governmental efforts towards the identification of the virus, understanding its effects, and finally, attempting to identify the best approaches to keeping the virus from spreading. Throughout the film, the CDC researchers and doctors would develop theories about the disease and make (educated) guesses as to what the government and public health officials should be doing to try and stem the danger to the public.

But every time one of the doctors shared his or her theories about what was happening the head of the CDC would respond with the following series of questions, or challenges:

What do we think?

What do we know?

What can we prove?

The motivation behind the CDC head's questions was that the suits in charge would not authorize additional funding for testing and research unless the doctors had a way to prove that their theories about how the disease was being spread and the needed actions to take were accurate. 

Bottom line: It doesn't matter what we think. It even doesn't matter what we know. It only matters what we can prove.

And I think these three simple questions are good ones to keep in mind for HR/Talent pros who are seeking to adopt more data-driven approaches and analyses to their practices of recruiting, development, retention, and succession planning, (and maybe more). 

It is a good reminder because like the CDC head in the movie, the execs that control the budget and the strategic direction for all HR programs are more likely to back ones that are more about what can be proved, and less about ones that are about what some HR person thinks.

What do we think?

What do we know?

What can we prove?

A solid set of questions to use as you frame up your data driven HR projects.

WEBINAR: HR Analytics for Everyday HR and Talent Pros

So by now someone in your organization, maybe even you, is going on and on about data and Big Data and analytics and maybe even predictive analytics being the future of HR and talent management. Seven out of ten surveys say as much, so it must be true, right? A quick Google search of "HR analytics' turns up just north of 14 million results. So it seems like everyone in HR has or will be talking about how important analytics are to the functions.

But in the words of the immortal Al Czervik in Caddyshack, 'So what?' 

What does the HR analytics revolution mean for you, the average, working, front-line HR/Talent pro?

Well glad you, or really I asked. Because my friends over at Fistful of Talent are there to help answer this and many more questions on HR Analytics with the next installment of the FREE FOT Webinar entitled The New HR Math: Dumbing Down HR Analytics for Everyday HR and Talent Pros, (sponsored by HireVue, a company that gets predictive analytics at a whole other level) on May 27, 2015 at 2PM ET.

The smarty-pants geek kids over at FOT will hit you up with the following:

 - 5 HR and Talent Analytics you should stop measuring immediately! You know what looks really bad to your leadership? When HR is using the old math, and everyone else is using the new math!

 - 5 HR and Talent Analytics you should start measuring immediately! Don’t be that parent fighting the good fight, ostracizing your kid from society by not allowing them to use the new math skills! We have the new cool measures you really need to be using in HR and recruiting today

 - 3 Best Practices every HR and Talent Acquisition shop can do right now with their analytics. You now know what the numbers are, but what the heck are you supposed to do with them? Fear not, Tim and Kris watched every YouTube video possible on the new math, they can show you the way!

 - A primer on what’s next once you start using these Predictive Analytics. Since you specialize in people, you naturally understand the move to using analytics that helps you predict the future is only half the battle—you have to have a plan once the predictions are made. We’ll help you understand the natural applications for using your predicitive analytical data as both a hammer and a hug—to get people who need to change moving, and to embrace those that truly want your help as a partner. 

You’re a quality HR pro who knows how to get things done. Join FOT on May 27th at 2pm ET for The New HR Math: Dumbing Down HR Analytics for Everyday HR and Talent Pros,  and we’ll help you understand how to deploy the "new-math" principles in HR that allow you to use predictive analytics to position yourself as the expert you are.

Expressive, boisterous, and unpretentious

Expressive, boisterous, and unpretentious - not sure they would be the first words that would come to mind if I were asked to describe myself, but according to IBM Watson's Personality Insights Demonstration, based on a text analysis of my post about text messaging earlier this week, those are the most accurate descriptors.

It is a fun tool and exercise to try, (you can play along with any of your, or someone else's writing samples here). Simply paste in a block of text, click on 'Analyze', and Watson will let you know how the text sample equates to personality elements like openness, conscientiousness, extraversion, and more.

The tool even generates a neat narrative explaining the person behind the text sample, who knew that 'My choices are driven by a desire for modernity'. That is pretty accurate, I think. Well maybe. 

What's the point of the tool, if not just for a bit of fun?

According to IBM -

The IBM Watson Personality Insights service uses linguistic analytics to infer cognitive and social characteristics, including Big Five, Values, and Needs, from communications that the user makes available, such as email, text messages, tweets, forum posts, and more. By deriving cognitive and social preferences, the service helps users to understand, connect to, and communicate with other people on a more personalized level.

Better understanding, ability to connect with others, and to enable improved interpersonal communications all sound like pretty worthy goals, so at least I am interested in any technological means to assist us humans with these challenges.

Oh, one more thing, the Watson Personality Insights tool also generates a neat looking graphical analysis of the writer's personality - here is mine from the aforementioned post about text messaging.

Like I said, really neat. Although from the looks of the chart I probably need to work on my 'self-transcendence' a little bit. Whatever that means.

You can take the IBM Watson Personality Insights tool out for a spin here, and if you do, let me know what you think.