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“We have all this great data, we’re getting more by the day, I’m getting great information and feedback from the players like, “hey, instead of doing it this way, let’s look at it this way, I think it makes more sense to me in that way.” So [we are] getting that and just trying to whittle it down to the bare minimum that will allow them to compete and execute. Because when you cross the lines, all we want you to do is execute.” Stuart Wallace, Quantitative Analyst, Pittsburgh Pirates


“It takes a lot of work to make something simple.” Jonathan Ive, Chief Design Officer, Apple, Inc.


Everyone knew the shift made sense. We can imagine the thought process in a typical major-league front office as it considered the advantages of the shift:

“Not all hitters have the same groundball distribution. Of course! So let’s match our infield alignment to each hitter’s distribution. How did we not think of this sooner? No matter, we can now track hitters’ groundball distributions, not only overall, but contextually too. Amazing. Let’s get shifting, take away some hits, and win some games. I’ll go to talk to the manager this afternoon.”

Shifting has become the norm as of the conclusion of the 2015 season, but there were some hiccups for some teams along the way. Most publicly, the Astros almost completely abandoned the shift midseason in their first attempt at implementing the shift in 2013. This miss did not cost the Astros, because they were not interested in winning that season; however, it is not difficult to imagine that such misses occur all the time, and that these misses occur at the expense of the teams’ win-loss records. And that these misses do matter.

The Astros were able to implement the shift the following year by improving the design of their implementation process. That offseason, they changed the way the “sold” the shift to their players and managers (their end users), a process that was ultimately driven by a better understanding of the end user.

This story is commonplace outside of baseball as well. In 1987, Apple realized the benefits of having computing technology on your person at all times. They rolled out the Newton Apple MessagePad in 1993. The technology was tremendous for the time, but instead of giving the consumers what they truly wanted, Apple threw as many capabilities as possible at an unprepared consumer. The technological leap forward was clear, but the execution lacked and the benefit was therefore unclear. The Newton ultimately failed.

In 1996, Palm Computer also realized the benefits of having computing technology on your person at all times and rolled out the Palm PDA. It famously focused on three things (contact list, calendar, and to-do list) that its customers would desire and understand. While its successors would fail, the Palm PDA and Palm Pilot were successes.

The difference between the Newton Apple MessagePad and the Palm PDA, just like the difference between rolling out the shift for the 2013 Astros and the 2014 Astros, was in the implementations’ consideration of the end user. Tim Brown, CEO of IDEO, writes in his book Change by Design that

“Innovation has been described as 'a good ideas executed well.' This a good start. Unfortunately, too much emphasis falls on the first half of that proposition. I have seen countless examples of good ideas that never gained traction for the simple reason of poor execution.”

Design thinking improves execution by using the concepts of observation, empathy, prototyping, and feedback, among other techniques. In baseball, where the margins of error are razor thin, implementation can be the difference between playing October baseball and listening to Joe Buck from your couch. There are already indications that teams are working to use design thinking to improve their implementation. We will take a look at these methods from the perspective of design thinkers and, as best we can, those in baseball.

Observation and User Focus

Observation has been described as “listening with your eyes.” This, for design and implementation purposes, is not to be confused with scouting, the evaluation of players’ skills and potential future skills, which is a separate skill in and of itself. Observation of the end user (most likely players, but also possibly coaches and scouts) is not about evaluating their abilities; instead, it is about understanding their habits and behaviors in an attempt to understand their motivators, fears, wants, and needs.

Innovation and strategy advisor Claudia Kotchka says that a major benefit of design thinking is “understanding the customer better than they understand themselves.” She notes that “no one ever asked for an iPhone.” As Roger Martin notes, the best ideas often “do not come out of sending a survey to the customer and asking 'what do you want?' but by deeply, deeply understanding the customer.” To best implement any new process or innovation, though, it is important to understand both parts of Kotchka’s first quote—it is important to understand what the consumer thinks he wants and to understand his underlying desires to know what he actually wants.

Using the iPhone example, consumers thought they wanted better phones and better computers, but what they really wanted was internet, email, and social media connection on their person at all times. Using the shift example, pitchers and coaches thought they wanted an infield defense that would work if the pitcher “made his pitch,” but what they really wanted were better ERAs and win-loss records when the season was over.

If teams are going to be more successful at implementation and changing end user behavior, then they are going to need to be as proficient as possible at deeply understanding the end user. A.J. Hinch, manager of the Houston Astros, notes, “I've always thought in order to get the most out of players, it is important to invest time getting to know them so one can find keys to unlock the best in them.” This, however, does not mean that every person in the organization needs to have as deep an understanding of the end user as the coaches, scouts, or players. What it does mean is that every person involved in innovation and implementation needs to be able to ask the right questions and challenge the right assumptions. But this often cannot be done without being present, without observing the behaviors that are critical during change.

The previously quoted Stuart Wallace is a quantitative analyst in title, but he is not behind a computer all day. Wallace is the Pirates' minor-league equivalent of Mike Fitzgerald, the subject of Ben Lindbergh’s excellent “Sabermetric Road Show” article, and a quantitative analyst who travels with the major-league team. Wallace will spend much of his time traveling to the Pirates' various minor-league affiliates during the regular season.

Being at the fields in person is beneficial to Wallace. He says, “You want to make sure the numbers you are seeing make sense.” Beyond that, Wallace continues, “We’re always looking for ways not only to collect data, but [also ways] to disperse it as quickly and as thoughtfully as possible.” This—thinking about how to disperse information as thoughtfully as possible (and thus with the end user in mind)—is what we mean when we mention that teams are already using the concepts of design thinking. Wallace notes that “it all starts with getting eyes and hands on guys.” Brown preaches this understanding of the end user as a “human-centered approach.” By focusing on the analysis as well as the end user, such an approach is more likely to lead to successful implementation.


Better understanding the end users and their possible intersection with a desired change is a hugely important part of implementation, but it is only the beginning. The idea that we can fully understand the customer and environment and then make the perfect product for that context is a nice sentiment, but not one that jibes with reality. The products, ideas, and innovations that work best are often ones that learn from the mistakes of others (as seen in our above examples). Luckily, design thinking already has a technique that allows us to learn from mistakes without having to publicly fail, that technique being prototyping. “As we say at IDEO, 'Fail early to succeed sooner,'” writes Brown.

In baseball, where there is often little tolerance at the major-league level for the failure inherent in experimentation, teams can prototype new ideas at the minor-league levels. Wallace mentions that the Pirates will often test a new idea with small groups at the lower levels of the minor leagues, allowing them to test and observe new ideas in action. “There’s a great phrase in medicine…that anyone in research will kind of adhere to after a while, which is 'start low and go slow,’” Wallace says. By promoting feedback and testing assumptions, prototyping allows for those implementing to hone and improve (and, if necessary, kill) the innovation before rolling it out on the biggest stage.

While prototyping might best lend itself to the minor leagues, prototyping at the major-league level could also be a boon, especially if it helps with execution in the playoffs. We saw Joe Maddon use a quick hook with his back-end starting pitchers all season, quickly going to his long relievers (usually, converted starting pitchers). According to Sahadev Sharma of Baseball Prospectus Wrigleyville, “Hammel was really angry early on with how he [was] pulled early in games…he was not performing well and Maddon kind of saw the writing on the wall that he had to prepare him for the postseason, that this might happen.” Had Maddon not “prototyped” the quick hook during the season, he might not have been as confident going to his bullpen so early in postseason games, his relievers might not have been as comfortable or familiar with the roles they were being asked to play, and his starters might have been worried about being pulled early instead of solely focusing on getting outs. After losing Game One of the NLDS, the Cubs won the next three games, while only getting 4 2/3, 5 2/3, and 3 innings from their starting pitchers.


Prototyping not only improves implementation by allowing us to test our hypothesis and make changes based on our observations, but also allows us to make improvements based on user feedback. No matter how good our observations or acute our empathy, there are still going to be things the users feel and see that we could not foresee. Building those user insights into our analysis, process, and design is critical in order to optimally implement our ideas. Back to Wallace,

“[feedback is] something we take very seriously, we’re constantly going back to that, will they do it, what do they feel like, do they feel like there’s value there…Their feedback is so critical and so wanted and at the end of the day it’s going to guide that decision in such a huge way.”

A.J. Hinch offered a similar sentiment:

“Players are smart. They are invested. They are hungry for success. They know themselves very well. And they have opinions. If I am trying to get the most out of a player, why wouldn't I listen to his opinion or ideas or feedback? Communication is a two-way street.”

Seeking and valuing feedback also has another benefit: it improves buy-in from those providing the feedback. The more an idea can be “ours” as opposed to “theirs,” the more likely the end user is to embrace the new process.

While these are the advantages, it is important to note that looking for feedback and getting productive feedback are two different things. People—and, thus, organizations—are good at getting feedback they want to hear or comprehending feedback to mean what they want. In order to get the best possible feedback, teams must be analyzing their own process to ensure they are not falling to the usual behavioral biases. They also need to prove to the end user that the feedback is not just hot air, that it is actually being considered and used. The better the observation and user focus at the beginning of the process, the better teams can accomplish these goals.

What’s Next

Through observation, empathy, prototyping, and feedback baseball teams are already starting to improve the implementation process by utilizing design thinking. Improving implementation is probably the easiest, most practical, and least disruptive way teams can leverage design thinking. This may be one solution, as Ben Cherington once posited, to “finding ways to optimize player performance and get guys into the higher range of possibilities.”

While improving implementation is a positive step forward, it is one that (i) has probably already been taken forward by many teams and (ii) will be pretty easily replicated by those who have not. Consequently, it is believable that improved implementation techniques will become (just like scouting and analytics), if they are not already, a means for keeping up with the competition rather than a differentiator. This is not to say that improved implementation (or scouting or analytics) is not important; rather, this is saying that it is critical.

If we are looking for differentiation (which we are), incorporating design thinking into organizations’ cultures for the purpose of improving innovation might be that next step. Tomorrow we will take a look at what “incorporating design thinking into an organization’s culture” means and the way baseball teams might gain a true leg up on the competition by doing so.

Brown, T. (2009). Change by Design: How design thinking transforms organizations and inspires innovation. New York, New York: Harper Business.
Brown, Tim, and Roger Martin. "Design for Action." Harvard Business Review. 1 Sept. 2015. Web. 9 Nov. 2015.
Lindbergh, Ben. "Sabermetrics Gets Soft." Grantland. 19 Aug. 2014. Web. 9 Nov. 2015.

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Really enjoyed this article. This is something I struggle with constantly IRL. Information isn't the problem. Information design is the problem.