Management by Baseball

Clarke's Second Law of New Technology (paraphrased):
For every human capability a technology creates,
it disables what exists; this may net out as progress or retardation.

In Baseball (and Beyond Baseball), new technologies that create the capability to do things we've never been able to do before (say, Field F/X, which can measure infinitesimal speed and trajectory and rotational measures for a batted ball) tend to add to human knowledge and  "ability".

New technologies that merely make it easier to do the things we can already do (broom-->vacuum cleaner, for example, or texting instead of voice telephone), change the things we do in foreseeable and unforeseen ways, and they don't always represent net progress. Author Arthur C. Clarke wrote a classic sci-fi story that illustrates this counter-intuitive reality from a military/industrial perspective.

There's a great Management By Baseball example that happened recently that makes this effect, what I call The Peavy Principle, very easy to understand.

PEAVY'S PITCHING PREEMPTS POWERFUL PARAPHERNALIA
According to Adam Kilgore's story in the Washington Post, 

CHICAGO — The answer to how the Washington Nationals would achieve their latest win seemed to reveal itself in the second inning Saturday afternoon. Chicago White Sox starter John Danks walked off the field, a strained muscle having ended his day after six batters. The Nationals could feast on Chicago’s bullpen and chalk up another win. Just the usual.

“I thought we got a break,” interim manager John McLaren said. “I thought we were going to hit their bullpen.”

But after spending two weeks convincing themselves they can’t lose, the Nationals lost to the White Sox, 3-0, before 23,008 at U.S. Cellular field, just their second defeat in 14 games. The Nationals managed two hits and struck out 11 times over 7-1/3 innings against the White Sox’ bullpen, which received a dominant cameo by veteran ace Jake Peavy, making the first relief appearance of his career. {SNIP}

 Peavy dominated for four innings, allowing a single and no walks while striking out seven.

Before each series, the Nationals’ hitters gather in a small room adjacent to their clubhouse. With hitting coach Rick Eckstein, they watch video and study tendencies of each starter they will face and the relievers. Peavy, who started Wednesday for Chicago, fit neither category. “I didn’t see Peavy’s name on that list,” McLaren said.

Though the Nationals never mentioned Peavy in their hitters’ meeting, they still gave credit to his pitching. “The bottom line is, we just didn’t swing the bats well today,” third baseman Jerry Hairston said.

In the last fifteen years (depending on which team, a little earlier or a little later), video library software has given coaches the ability to create, with just a few hours of assembly by the coach or other team aides, wonderfully organized and informative video tutorials on how opponents play, their biases and tendencies and quirks and tells. This new technology replaces a prior, non-technological way of doing it; word-of-mouth verbal sharing of information, three-ring binder collections of data points, exchanged tips in the batting cage before the game, exchanged tips in the dugout during the game.

It's not that none of that pre-video library software information happens; it just has become secondary, delivers less impact than the new way and, therefore, becomes relatively devalued by most of the participants. By making a high-tech system THE WAY to get 'er done, the other ways seem to be "old fashioned" or lower yield.

But for every ability an augmenting technology increases, it undermines an existing capability. By being able to hyper-focus intense information about the White Sox relievers, that attention gets invested, and so a resting starter, Jake Peavy, who comes into a game as a reliever, is glossed over in the chosen techno-path to success. ¿Did the Nationals have three-ring binder back-up? I'm not sure; when interim Manager McLaren skippered in Seattle, I saw him carrying two. But as a recently-appointed interim, he would work with the protocols the team had already worked out. Even if they did have it, the batters would have already tapped their cognitive investment in other, more fluidly-acquired accustomed ways of getting data. They cannot have helped but instinctively valued the video information over the old-fashioned.

In Baseball (an endeavour much more brutally zero-sum competitive than the easier work domain you manage in) a Jedi Master of finding a cognitive edge like White Sox manager Ozzie Guillen, undoubtedly knew there was some tiny (not giant) advantage in putting on the mound an unscheduled reliever, but in Baseball, because it's zero-sum, tiny advantages loom large. The reality that Jake Peavy is a monster pitcher when he's healthy had to have been a consideration as well. And Guillen is as prepared as any manager in any field; he and pitching coach Don Cooper would always, every game have a Plan B for who would come in early in a still-close game if the starter is injured or blown out.

In Baseball, technology that replaces manual + verbal methods may enable people to do what they did before faster or cheaper, but it makes the knowledge more brittle, less hands-on, more shallowly textured. Technology eats some of the nuance while spitting out better volume...what I call The Peavy Principle.

THE PEAVY PRINCIPLE BEYOND BASEBALL...
...is actually quite wide-spread. The most wide-spread example is cell phones replacing land-lines. It's not technology that gives us unprecedented abilities, but does augment the span of places we can use a telephone or type messages or play games or execute frozen pork-bellies futures contracts. Mobile gives us mobility, the capability to call from most anywhere (unless you're a Sprint user in suburban Chicago or an AT&T victim in San Francisco). But the quality of communication goes down as the degraded fidelity eliminates audible intonation and voice affects. Is the trade-off worthwhile? For most users, I suspect the answer is probably yes, but for communications that require clarity (business, romance, intelligence), the loss is palpable and costly.

I'll give you a concrete example from my own practice. I was one of the earliest users of project management software, but I didn't learn on it. Before there was software, PMs worked with a surprising range of physical tools. I used mechanical pencil  on graph paper and, of course, had to do trial and error, making copious use of the Eberhard Faber Eraser Stick (known in the trade as a "poodle penis"). I wouldn't describe this as "the good old days"; it was truly challenging, and I welcomed my SuperProject and later my TimeLine (a now-gone package that was at least 4x as productive as anything on the market today). I was project director on a USEPA contract that had 23 people who through the project worked asynchronously in 10 cities...a massive logistic effort that additionally required a lot of knowledge about the individual talents (no two of whom had the same strengths and weaknesses) and concurrently was an attempt to prove to the agency that a co-op could deliver comparable quality at lower cost.

Setting up a project was faster this way than it is using even good project management software. Recalculating in software is much faster than erasing/rebuilding-by-trial-and-error. Getting the first draft done is much faster in software. But woe to the software-only solution when the plan veers away from the original plan enough that it requires resequencing, or re-applying the individual talents of non-commodity labor from one sequence to another. Because project management software "believes" people are commodities, and it's almost impossible to program human interdependencies or stored knowledge into the database that sequences decisions.

I could actually do this significantly faster by hand. So can most professionals who did or do it by hand, because the physical drawing and erasing of lines, not delegating that to a machine, gives the PM a much stronger and more textured understanding of the interdependencies.

People who learned on software (most contemporary PMPs) and at the same time never do it by hand tend to undervalue the aspects of project management that the software is counter-productive for or simply doesn't do. Most learned-it-using-software suffer from The Peavy Principle, that is, they can do it fast, but by delegating the knowledge to a technology, they can overlook details the technology ignores, filtering out valuable information simply because the software developer didn't value it, or because it was costly or perhaps impossible to embody in software.

By stuffing the data into a digital container, removed from the visible and manipulable world of physical artifacts, they master technology, but undermine the fullness of their craft -- as my associate Athena explained to me when she was taking a PMP certification course, they were teaching people how to operate software, do effective data entry and report their results thoroughly, not how to manage projects.

I'll give you a another equally-painful example, in case you have no experience with project management. Handling data.

Many of us who analyse data for a living actually comb through the raw data before we start analysing it. It's time-consuming, and doesn't always have big rewards, but we find that the exploration gives us a better handle on it and makes it easier to track the exceptions that indicate valuable insights or dirty data. Some of our peers, though, trust data enough to make it an unseen artifact that's hidden in a digital container. Even when they use other software to flag exceptions or pinpoint certain kinds of out-of-scope points, they can miss subtle flaws that the technology helper wasn't programmed to recognize.

Even famous and brilliant scientists who don't respect the data (the noun, the reason for the analysis) as much as the tool used to analyse it (the verb) are missing a key piece of the grammar of data analysis. A few years ago I read a serious clever baseball researcher's article on platoon splits (the ability, for example, of a right-handed batter to hit left-handed pitching overall better than right handed), and he had come to the conclusion that it was not a skill (not a repeatable event, but one driven by luck or other external factors). His results were quite unequivocal.

I was surprised but interested, because platoon splits are a piece of unquestioned protocol and I love to question the unquestioned protocol. I'd fiddled with this problem before without coming to useful conclusions, and he had taken a very different tack in the analysis and had compiled a great swathe of data. I asked him if he would give me a copy of the data to work with, and he generously shared it.

I opened the file with great anticipation and started combing through the individual rows, associating codes with the players they referred to, their seasons, all artifacts I'd never had the pleasure of examining as consolidated numbers. But you can imagine how disappointed I was when I saw that much of the data was flawed, the result of a bad transform routine, one that repeated two of the fields every so many rows (not all rows, not all fields, but regularly making false certain rows in a predictable sequence). Each one of these rows was within scope, and every one, taken alone, was feasible. There were no out of scope characters or out of scope row lengths -- it was a giant pile of broken data that smelled fresh to data cleaning routines, and turned the research conclusions from significant to not. Only a human eye and brain considering patterns would detect the underlying errors.

I did send the deck back to the mathematician with a note, and thanked him. His push back was that I must be mistaken and that errors would have been caught by his technology. He had evolved out of being a scientist and into a technology midwife. If he ever opened his file and looked at it line by line (honestly, an exhausting task), he would have known. The technology that enabled him to adsorb vast piles of data and clean and analyse it and deliver insight by a thousand slices had left him exposed to intellectual death by a thousand cuts. It had enabled vast quantity while degrading critical quality.

What technologies do you use that threaten to impose the Peavy Principle on your efforts? If Baseball, the most productive and accountable user of technology can get screwed up by the Peavy Principle, I'm telling you it can mess you up, too.