2013 Self-Care Review

Here are my self-care “results” from 2013. Quick review:

  • My self-care dashboard is a way of tracking personal practices to keep me healthy, high-performing, and sane.
  • Practices tracked: Playing basketball, working out (other than basketball, including one-hour or longer walks), taking non-weekend play days, not checking work email after weeknight dinners, not checking work email on weekends.
  • Everytime I do one of the above, I get a point. I total up my points once a week. There is a theoretical maximum of 25 weekly points, but that’s completely unrealistic. My “ideal” steady state is 10 points per week.

I started tracking in 2012 and found that my four-week rolling average was the best way of tracking my current state of self-care. For example, if I did most of my practices regularly for three weeks, then had a week where I only did one or two, my four-week rolling average would still be relatively high. Conversely, if I had several bad weeks in a row, then had one week where I hit my “ideal” number of 10, I’d still have a relatively low four-week rolling average.

Here are my 2013 rolling averages (in blue) as compared to 2012:

Self-Care Rolling Average 2012-2013

Quick analysis:

  • Overall, I did a much better job of taking care of myself in 2013 than in 2012. My rolling average never hit zero in 2013, and it hit 9 at its peak — double my peak in 2012.
  • My numbers were up in all five categories this year except for working out, which saw a slight downturn. However, I played twice as much basketball this year than last, and I’m in far better shape right now than I was a year ago.
  • The biggest increases were due to me turning off work email. From April through August, I wasn’t working in the traditional sense, which explains the huge improvement. In August, I “officially” launched Changemaker Bootcamp. Later in the month, I started a project with the Garfield Foundation. My rolling average actually dipped below 2012 levels in that time period, again largely due to email. In October, I recognized the trend and adjusted, which led to my numbers going back up to peak 2012 levels, but not to peak 2013 levels.
  • The graphs are cyclical in both 2012 and 2013, and there seem to be some peaks and valleys in common. Some of it is coincidental. In April and May of both 2012 and 2013, I traveled quite a bit — for work in 2012 (where the dip was more unpleasant), for play in 2013 (where the dip was largely incidental).
  • I think my line will always be cyclical, given my personality and lifestyle. I’m good with that. However, I’d like a smaller amplitude, and I’d like the overall average to be closer to 10 than it is right now.

Bottom line: I took much better care of myself this year than last, but I have a ways to go before I hit the right balance. 2014 will be a good test as to whether I’m making systemic improvements, or whether my gains this year were more a reflection of me taking a break. I feel good about it being the former, but we’ll see. Either way, I’m happy about how 2013 went.

You can learn more about how I do my tracking at Faster Than 20. If you’re using my spreadsheet for your own tracking, please let me know how it’s going! If you’d like help getting setup, drop me an email or leave a comment below.

Fuse: Connecting Your Car to the Rest of Your Life

I just backed my friend Phil Windley’s new Kickstarter project, Fuse. Everyone with a car should go back it now. Everyone who cares about data privacy should also go back it.

Every car has an on-board computer with tons of data: your mileage, your average speed, even your tire pressure. When you take your car into the shop, mechanics plug into this computer to access that data so that they can diagnose your car.

I’ve been wanting to access that data myself forever, and it’s not just because I’m a data geek. As someone who travels a lot for business, I track my mileage. Not only is it a royal pain to do manually, it just seems wrong, given that your car already has this data. But until recently, I had no ability to access it.

Fuse unlocks that data, and gives you access. It consists of a device that you plug into your car’s diagnostic outlet and a mobile app that gives you access to that data.

That alone should make you want this. But I’m going out of my way to blog about this project because of what Fuse does under the hood.

The problem with most of the emerging apps in this space is that they essentially trade convenience and coolness for ownership of your data. Most of us don’t pay attention to that. We’re too pre-occupied by the coolness. Some of us feel vaguely uneasy about the trade-off, but we do it anyway. Coolness is a powerful motivator.

Phil has been a leader in the digital identity space for a very long time. He literally wrote the book on it. He’s part of a community of folks who thinks that you — the individual — should own and control your data. Enabling this is a hard technical problem, but it’s an even knottier social problem.

Fuse is built on top of a trust and privacy framework that my friends, Drummond Reed and Andy Dale, have helped evolved. Fuse is cool, compelling, and socially responsible. These are the kinds of apps that will help create the kind of world that I want to live in.

If you’d like to read more about these nitty gritty aspects of Fuse, go check out Phil’s blog. If you’d like to read more about the bigger vision behind technology like this, start with Vendor Relationship Management (VRM).

Don’t forget to back the project!

Two Collaboration Insights from Last Weekend’s Football Games

It’s football season! Today, I came across two gems about this past weekend’s games that spoke to me about collaboration in general.

Data and Impact

In reaming Tennessee Titans coach, Mike Munchak, Bill Barnwell wrote:

Mike Munchak put us all through a lot of field goals for no real reason, and in doing so, he illuminated the difference between meaningful game management and the illusion of impact.

In this one, biting sentence, Barnwell is offering commentary on how we evaluate coaches. When you kick a field goal, you’re putting points on the board, and so it may look like you’re getting results. But the real question is whether kicking a field goal the highest impact move you could have made at the time. The sports analytics movement has shown that some of our most common practices are often the worst moves we can make, even though they give us the illusion of progress.

Sound familiar?

Fundamentals

The Seattle Seahawks have the league’s stingiest defense, and they completely dismantled the San Francisco 49ers powerful offense this past weekend. How did they do it? Gregg Easterbrook wrote:

The short version of the success of the Seahawks’ defense is good players who hustle, communicate with each other and wrap-up tackle. Contemporary NFL defenses are so plagued by players’ desire for spectacular plays that make “SportsCenter” that blown coverages and missed assignments have become de rigueur. Seattle’s defense almost never has a broken play. And those lads can tackle! Seattle misses fewer tackles than any NFL defense. Lots of wrap-up tackles where the runner gains an extra yard are better than a few spectacular hits for a loss, plus frequent missed tackles. Seattle defenders understand this.

Hustle, communicate, execute. It sounds so basic, it’s almost a cliche.

A big reason I developed Changemakers Bootcamp was my realization that getting really, really good at the basics could have a much bigger impact than on inventing new tools or processes. Unfortunately, the vast majority of attention and focus seems to be on the latter rather than the former. We see lots of stories from sports and other fields what a mistake this can be.

Photo by Philip Robertson. CC BY 2.0.

LeBron James, Heroic Leadership, and the Danger of Narratives

For those of you who don’t follow basketball, the Miami Heat beat the San Antonio Spurs last night for this year’s NBA championship. It was a classic series featuring seven future Hall of Famers and going the full seven games.

What made this series particularly fascinating (besides the unbelievable level of play throughout) was that it featured the best player on the planet, LeBron James.

James is a freak of nature. He’s built like a power forward, he moves with the speed and agility of a wing, he sees the floor like a point guard, and he defends all five positions. In human-speak, he is a transcendent basketball Swiss Army knife, not just versatile, but superiorly so.

He also happens to be polarizing for a variety of reasons. He was anointed the future king of basketball while still in junior high school. He decided to leave his hometown team for his current one (an entirely justified decision) in a less than graceful manner, which created a lot of animosity. (Beyond that one minor transgression, which has been completely overblown in a way that all things sports are, James has been a model citizen.) He is the classic Goliath, and we love rooting against Goliath.

Because of this, James is intensely scrutinized and unfairly judged. Now that he’s won back-to-back championships, that scrutiny is likely to fade. But what I find fascinating is why we so easily and incorrectly judged him in the first place.

This series was fraught with those moments. It largely centered around James’s performance (he would go from hero to goat back to hero in a single quarter of play), but no player or coach was spared. And in the end, all of it was wrong.

Zach Lowe wrote in Grantland:

We remember players for their work in big moments, and that is never going to change. But when we overvalue those big moments at the expense of everything else, we do both those players and the game itself something of a disservice. We ignore the role of randomness and luck, as Henry Abbott beautifully reminded us this week. We ignore defense on a possession-by-possession basis, mostly because defense is hard to see and understand.

And we pick and choose which big moments are really big in strange ways that don’t make a lot of sense. Why is Leonard’s missed free throw more important, and more memorable, than the fact that no other Spur made a field goal in overtime? Why is Parker’s missed free throw in overtime less important than Leonard’s miss and Ginobili’s miss in regulation? Why do we eviscerate Ginobili for his eight turnovers while passing over the fact that Miami turned the ball over on three consecutive possessions in the last 1:10 of regulation in an elimination NBA Finals game — including two turnovers by LeBron? The Bobcats might have done better on those three possessions than LeBron and the Miami Heat managed.

The result — the Heat won, the Spurs lost — too often informs our analysis of the process.

These aren’t just wise words about sports, they’re wise words about almost everything we do. The reason stories are so valuable is that we are particularly attuned to them, and we are more likely to learn and integrate knowledge in that form. The problem with stories is that we are so attuned to them, we confuse narratives for truth. It is so easy to assign credit and blame in simplistic and incorrect ways, and to frame it as “rigorous analysis.” Daniel Kahneman has written extensively about our proclivity for finding causality where causality does not exist.

The other thing I found fascinating about this series was how it embodied our collective mindset about leadership. James has consistently been criticized throughout his career for being too unselfish “in the clutch.” In basketball, there is a mythos that it’s the best player’s job to “take over the game” in the fourth quarter, that the laws of team basketball are suddenly rendered irrelevant with the game on the line. We reward players who buy into this mythos, the classic example being Kobe Bryant. And so the common wisdom is, when the game is on the line, there’s no player you’d rather have on your team than Kobe.

But when you look at the data, it turns out that the classic wisdom is wrong. In crunch time, Kobe makes it easier for the opposing team’s defense, because they know with almost utter certainty that he’s going to shoot the ball. And the numbers confirm that this is a poor strategy, as Kobe consistently shoots worse in the last few minutes of a game than he does on average.

For years, James was eviscerated for his crunch time unselfishness, even though he single-handedly made mediocre teams great with his superior team-oriented play. We loved him for his unselfishness, unless it was the final minutes of the fourth quarter, at which point we expected him to get selfish again.

It’s totally irrational, but it’s pervasive not just in sports, but in business and in life. Our classic notion of leadership is of the heroic kind, and even though that’s beginning to change in leadership circles, old mindsets are hard to break.

Photo by Keith Allison. CC BY-SA 2.0.

The Mainstreaming of Analytics

John Hollinger, a long-time ESPN.com columnist and inventor of the Player Efficiency Rating (PER) for evaluating basketball players, is joining the Memphis Grizzlies front office as its Vice President of Basketball Operations.

This is wacky on a number of levels. First, it represents the ongoing rise of the numbers geek in sports, a movement pioneered by Bill James almost 40 years ago, given an identity a decade ago in Michael Lewis’s book, Moneyball, and gaining official acceptance in the NBA five years ago, when the Houston Rockets named Daryl Morey its General Manager. Want to run a professional sports team? These days, an MIT degree seems to give you a better chance than spending years in the business.

Second, Hollinger spent over a decade sharing his thinking and his tools for all to see. Now, all his competition needs to do to understand his thinking is to Google him. Tom Ziller writes:

The major difference between Hollinger and, say, Morey is that we all know Hollinger’s theories. We know his positions, and we’ve learned from his work…. Will his canon hurt his ability to make moves? We can lay out exactly which players he likes based on his public formulas and his writings. Other GMs will know which Memphis players he’ll sell low on. You can anticipate his draft choices if you’re picking behind him. If you’ve got a high-production, low-minutes undersized power forward, you know you can goose the price on him because history indicates that Hollinger values him quite seriously.

This is all a gross simplification: Hollinger’s oeuvre is filled with nuance. He doesn’t rank players solely by PER, and in fact he probably has some adjustments to his myriad metrics up his sleeve. He’s not going to be nearly as predictable as a decision-maker as anyone would be as a writer. The stakes are different, the realities of action are different. But no decision-maker in the NBA has had this much of their brain exposed to the world. Morey isn’t shy, but that big Michael Lewis spread on Shane Battier was as far as we ever got into the GM’s gears. Zarren is notoriously careful about what he says. He might be the only GM or assistant GM in the league more secretive than Petrie.

It’s interesting to consider the implications on the Big Data movement in business (on which Moneyball had a much greater influence than most would probably admit). Business is not a zero sum game like professional sports, so there’s more room for nuance and many positive examples of openness and transparency. Still, for all those who believe that openness and competition do not have to be at odds with each other, this will be fascinating to watch.

Ziller also makes a wonderful point about the importance of communicating meaning from analysis:

In the end, what Hollinger’s hire means is that the ability to do the hard analysis is important, but so is translating that to a language the people on the court can understand. That’s always been a wonderful Hollinger strength: making quant analysis accessible without dumbing it down. Even someone as brilliant as Morey, who has a team of quants, can’t always achieve that.

I’m reminded of a tale from Rick Adelman’s days in Houston. Morey’s team would deliver lengthy scouting reports to the team and coaching staff well before a game. It’d have player tendencies, shooting charts, instructions on match-up advantages — everything you could ask for to prep for a game. And out of all of the coaches and all of the players only two — Shane Battier and Chuck Hayes — would devour the reports. The rest (Adelman included) would leaf through, pretend to care and go play ball. That story might be an exaggeration on the part of the person who told it, but even if that’s the case, it shows how important accessibility is. You can build the world’s greatest performance model. And if you can’t explain what it means to the people using it, it’s worthless.