Attention D-backs: An Analytics Department Would Be a Wise Investment

Scour the listing of D-backs front office personnel, and you’ll find exactly 90 people listed under “baseball operations.” That’s not counting GM Kevin Towers or new Chief Baseball Officer Tony La Russa — and that’s a lot of guys (very few of whom work out of the D-backs’ main offices). Many of those guys are employed by the D-backs in advisory, supervisory, or scouting roles, because you need cogs like them in a competitive baseball machine.

Where is the analytics department? Several teams, including traditionally old-school outfits like the Kansas City Royals and the Cleveland Indians, have set up units within their baseball operations departments to study and interpret the data made available to all MLB teams. Some have just one analytics employee, like the Philadelphia Phillies. And while I could certainly be wrong, it doesn’t look like the D-backs have a single person in such a role.

We can safely assume that analytics have not been ignored by the organization entirely; like many teams, they almost certainly work with consultants or part-time analysts (probably remotely). But it seems clear from my perspective that the D-backs haven’t implemented any knowledge from analytics at all, or close to it. The problem right now may not be so much that the front office isn’t listening; the problem may be that, right now, there’s nothing to hear.

Wins aren’t cheap, but analytics professionals are

It may not surprise you that data-driven researchers and writers have not ignored their own work. In fact, Brown University student and ESPN Insider author Lewie Pollis has recently done some extensive research on the (irrational) market of front office personnel (here’s an excerpt at Baseball Prospectus, and the entire paper at SABR)

The bottom line: there are hundreds and hundreds of extremely talented researchers and analysts that are willing to work for roughly half of what they might otherwise earn, just for the privilege of working for a baseball team. That’s an inefficiency to take advantage of — especially since hiring some of the right people has a very real possibility of increasing a team’s chances of winning.

As Pollis has suggested, one can think about this in terms of the signing of free agents. Call it $6M, $7M or more, but if you value players in terms of wins above replacement, each win seems to be worth about that amount. Wins are very expensive in free agency.

Could an analytics department increase the D-backs’ win total? It certainly stands to reason. How much are analytics personnel worth to teams like the Athletics, Rays, and even the Pirates? It wouldn’t shock me if the answer was something like five wins. Pollis’s research suggests that just in terms of player acquisition (free agency and trades), the best General Manager may be worth about 7 wins above average, with the worst about 4 wins below average. Analytics isn’t the only thing that makes a General Manager good or bad, but player acquisition isn’t the only way that an analytics department can be useful (think: defensive alignment, promotions, base running strategy, pitch selection or sequencing, etc.). Still, let’s be extremely conservative, if you want: call the benefit of an analytics department a 10% chance of a single win.

A 10% chance of a single win should be worth about $700,000, if we’re using free agency for players as a reference point. And what would it cost to set up an analytics department with 4-5 people, including salary, benefits, and infrastructure? $400,000 at most?

Setting up an analytics department isn’t a leap of faith that doing so will definitely help. Instead, doing so would be based on the premise that it might work. That’s enough to make an analytics department a wise investment.

Hiring a group has benefits

At least three benefits, actually. The first is very simple: if one analyst is helpful, isn’t there a chance that two analysts would be twice as helpful? Only so many people could work on a single thing like defensive alignment before returns start to diminish. But there are dozens and dozens of areas in which analysts could helpfully weigh in, and we’re not talking about hiring a 30-person department here; we’re talking about 4-5 guys. 4-5 guys are 4 or 5 times more helpful than 1, especially because different analysts are likely to have different strengths (and that diversity of strengths would be a goal in the hiring process).

The second also has to do with that diversity of strengths. In fact, a group of 4-5 analysts would probably be greater than the sum of their parts, through working together. I think we can safely assume that at least sometimes, there are multiple ways of looking at a baseball problem. With vantage points all around the mountain, you increase your odds of finding the most efficient way to the top. Some important projects could be completed more quickly with multiple people working on it — and that could lead to earlier implementation. With 4-5 people on staff, an analytics department would be more likely to experiment, as well. Experimentation (think about catcher framing research from the last two years) would sometimes result in helpful information, and sometimes not. Coming up with a helpful strategy that (most?) other teams have not thought of has the potential for a high rate of return, especially in terms of player evaluation (think: if you’re the only team that knows a player is likely worth 3 wins instead of 2, you have a good chance of getting him at a discount).

A third benefit might be that a department would have a department head. A person skilled in analytics is more likely to deploy others on projects efficiently, which is worth a premium on its own. But a department head would also have the understanding needed to know when to beat down AGM Billy Ryan’s door, when to make firm suggestions, and when to scratch the results of a research project and simply move on. When the Tony La Russa news broke, it struck us at the site that maybe, CEO Derrick Hall wasn’t equipped to evaluate or supervise GM Kevin Towers — and as an extension of Hall, La Russa is certainly equipped to do that. It would be easy (if cheap) to wonder if current baseball operations personnel aren’t equipped to handle any information they get from analytics. But at the very least, a department head, sitting in a meeting, would be able to say either “actually, we accounted for that information in our analysis” or “actually, we didn’t account for that in our analysis — but we could if given a chance.”

The burden of persuasion

Someone like me could easily blame the front office for not being open minded. I could assume that in the face of a growing mountain of helpful data, the front office has chosen to prioritize other sources of information, that ignoring analytics is different. After all, when Kevin Towers was asked about player evaluation in December 2012 by FanGraphs’s David Laurila, he responded:

First and foremost, you trust your scouts. Not only their evaluations, but their intuition and projections on players. Of course, now we have so many resources, like the analytics. We certainly look at that end of it as well.

No big deal here. There’s a way to look at this as Towers offering a defense for not using analytics very much (and, after all, he knew he was speaking to FanGraphs). But I think there’s another way to look at it.

When Towers says that the D-backs “look at that end of it as well,” who is he referring to? Is he saying that they farm out some work on some obvious projects, and they look dispassionately at an emailed document’s worth of results? What kind of help does Towers have for interpreting that information, for distinguishing between the vaguely useful and the truly compelling? Is it really Towers’s fault for not listening if the person doing the talking just wasn’t very persuasive?

The answer is yes, but only because hiring someone appropriately persuasive may have been Towers’s responsibility in the first place. It’s not just that the current front office may not really be listening, but it’s also not just that there’s nothing to hear. It’s that, in addition, you need the right person doing the talking, because an analytics department would always have the burden of persuasion. Which is as it should be.

That’s something you just don’t get when you farm out your analysis work. Analysts working part time, or (worse) by assignment, are unlikely to go above and beyond to pull in extra things that could be helpful. They may not even get the chance to explain why they should be given that opportunity.

So it’s time, in the wake of the Tony La Russa hiring, to set up a new department. Since the head of the analytics department wouldn’t be making ultimate decisions, there’s no danger that analytics personnel would ride roughshod over the organization. Ultimately, it would be up to front office personnel like GM Kevin Towers and (more likely) AGM Billy Ryan to listen, and to implement whatever they might be convinced to implement.

I’ll say it one other way: hire an analytics department, D-backs, not because you should know to implement some of what you might learn, but because you don’t know that you don’t need to implement some of what you might learn. In hiring an analytics department with a department head, you can shift the onus of using data-driven analysis onto people whose job it is to handle that. There’s a lot to gain, and almost nothing to lose. Hiring an analytics department isn’t a commitment to use any of what they might learn. All it would be is a commitment to listen.