Competing Within One-thousandth of a Second

#1 The Source of Belief in Victory



――TCS partners with TCS NAKAJIMA RACING—a professional racing team competing in the SUPER FORMULA series—as both title-sponsor and technology partner. In the first installment of this special serial column, we spoke with Yuki Kato, track-engineer at TCS NAKAJIMA RACING overseeing race strategy, to hear his perspectives on the interplay of digital technologies in today’s formula racing environment.

Taking Full Responsibility for the Machine

The track engineer is central to overall race strategy, taking full responsibility for the machine performance


“I’ve loved motor vehicles my entire life. I enjoy driving cars, have participated in racing from my university days, and have always wanted to work in the automotive sector. There are various fields connected to automobiles, but among them I’ve always held greater interest in motorsports rather than the development of general vehicles. Despite my passion for motorsports, I joined a regular car manufacturer after completing a master’s degree in engineering, with a view to building my knowledge of automotive technology-development first. With a fundamental knowledge-base established, I then planned to transition to a career in motorsports. It transpired that through an acquaintance of mine form university, I would have the fortune to connect with NAKAJIMA RACING. They told me “We are looking for someone like you who can contribute to the team from a technical perspective.” That was the beginning of my career in the world of professional motorsports. Today, I would like to shed a little light on my endeavors there.”

In short, my role in the team as “Track Engineer” is to take full responsibility for the racing machine’s performance. In order to deliver the machine’s best race performance, every piece of preparation prior to rolling out on the circuit is critical. A great deal of forethought goes into how to prepare the machine, with team engineers and mechanics meticulously running a series of scenarios in trial and error. Once the actual race starts, I direct the team on how to run the machine; what tires to use, how many laps to run, what should be checked, and how we should change the settings when it comes into the pit—all this while racing against the clock. I should also note that teams cannot practice freely on the circuit either (only during designated practice sessions). Based on all the work prior to race weekend, we need to formulate and rapidly validate our hypotheses during practice, making final adjustments to ensure we can pull the full potential and best performance from the machine on race day.


Big, nay, Gigantic Data, and the Race

Working trackside, we come face-to-face with swathes of data. From chassis height and suspension stiffness, through to track temperature and which cars are running on what sections of the track; there is a deluge of data to capture. The ways in which data is consumed differs greatly depending upon the source. In the past this meant some was shared on post-it notes (e.g. track temperature), while other data required specialized displays (e.g., chassis weight distribution). There were occasions in the past where one would receive data and think, “Ah, okay,” but not really be able to fully internalize it. This meant that data was being thrown away, in a sense, without deriving true value from it. Having partnered with TCS, however, we have leveraged digital technologies to develop tools for visualizing, handling and controlling the volumes of information. This enables us to apply data-driven insights as we formulate measures to improve our performance.

The tire strategy largely affects the result of the race.

In racing, the level of preparation done prior to race day rather than on the day is critical in getting the machine ready to perform. Once the race starts, it is difficult to drastically change settings in order to adjust to some shortfall (as each modification impacts other parts of the machine). Hence, beyond the machine which we have prepared, it is crucial that we are able to quickly ascertain and visualize all the external factors that come into play.

To give an example, new tires can perform well, but we need to warm them up in advance by running them for a few laps. Yet, how much we should run remains unknown until actually running the track, since the situation differs every time depending on the temperature, the circuit characteristics and condition, etc. The drivers will often ask how many laps they should run before attacking for a qualifying time. Naturally I can’t tell them to trust their gut and, “Go when you feel the tires have enough heat in them.” Not only would it risk us not marking a qualifying time, it would also mean we learn little or nothing from the practice session. To help us make informed decisions about this and other settings, we are leveraging a tool that we have been developing with the help of TCS.

To put it simply, it is a digital tool which can collect and centralize the race data, packaging and presenting it as insights that can be referenced to help decide our strategy. The information is curated via a single dashboard/application, making it easy to access critical insights.

In addition to understanding our own driving results, it helps us to understand what the teams around us are doing in terms of set-up, and how that is then playing out on the track. Up until now, data acquisition and verification methods had been ad-hoc, making it difficult to consistently and accurately grasp driving times and conditions. Now we are not only able to accurately track lap times,  but also make inferences on the causal effects of weather and road surface temperature, and access this data on demand, wherever we may be. This impact this has on enabling real-time decisions is immense. We can compare our situation with that of competitor teams, pull the necessary insight for making strategic decisions, and apply them with speed and confidence. In the world of racing a strategic miss on one lap can mean the downfall of one’s entire race, so the ability to effectively utilize data and insights is critical to success.


The Foundation of Driver-Engineer Trust

Meticulously sharing insights with the driver before the race


Over the last several years, we have tried to better leverage data using digital technology. It was during qualifying at the 2019 SUPER FORMULA season finale in Suzuka that I was truly convinced of the success of our efforts. We were vying for both the driver’s and team’s season championship, so the importance of qualifying was manifold. While we managed to clear Q2, our result was less than favorable despite making our sprint on the third lap when the tires should have been at their peak (given the cold conditions). Feeling something was askew, I quickly reviewed the full field’s data and noticed that the machine marking top time in Q2 had made their sprint on the second lap. Feeding this intelligence to the driver as he rounded out the session, he eagerly committed to making an early sprint in the final round of qualifying. So, I adjusted the tire settings to align with our strategy, and we rolled out into Q3. Placing his belief in my analysis, the driver pushed hard from the very first corner on his sprint lap. I should note that the first corner of Suzuka Circuit accelerates really fast, so it is easy to misread and fail. Regardless, I placed my faith in the data, and the driver in turn placed his faith in me. With the confidence to take a calculated risk, we successfully secured pole position⋆3. This is a prime example of data informing the perfect strategy, and is an experience that I will never forget.

Needless to say, the driver’s performance was impeccable. His ability to execute so flawlessly, however, stems from the fact that I was able to feed him the intelligence needed to fix his mindset with absolute confidence. Again, my own confidence in the strategy came thanks to the data visualization tool that TCS had developed with us. It gave us a clear benchmark against which we could make our strategy calls.


Control the World of Figures

The visualization of the races’ external factors is successfully in progress for the most part. However, there is still a lot of information to be processed. We need to better visualize even fundamental things such as which machines are running on what part of the course, and at what lap-time. That is one of our more immediate challenges.

Leverage the best of both the analog and digital worlds


Moreover, close communication within our team is becoming more important than ever before. We have a rather large contingent, and all it takes is for one member to be out of sync with the strategy for everything to go downhill. In a world where results speak for everything, the quality and speed with which we communicate needs to be continually pushed. The importance of data-insights being derived in real-time is also increasing, so we are leveraging digital mechanisms such as group ware, tablets, and smartphones to facilitate seamless communication. Nevertheless, I myself derive value from the analog task of handwriting. Jotting down notes on crisp sheets of paper in my trusty leather-bound folder helps me to sort my thoughts and filter out the surrounding noise.

Digitalization is not the answer to everything, so we must look to capitalize on the best of both analog and digital to capture, contextualize and effectively convey the information that lies at our feet. On the other hand, some of our young engineers prefer to use tablets in place of notebooks. I’m curious to know how they’re making use of them.

We are currently focused on the process of visualizing the situation around us, but in the near future I would like to work on how we can process the data form within the machine, which influences the machine settings as we get it set-up.



⋆1 The qualifying has three run and the winners proceed from Q1, Q2, through Q3.

⋆2 Alex Palou, the former driver of NAKAJIMA RACING.

⋆3 The winner of the qualifying. The starting position of the final race is decided in the order of finishing, so the standing of the qualifying largely affects the results of the final race.


Yuki Kato 加藤祐樹


Born on December 3, 1986, he is from Saitama Prefecture.

Kato joined Toyota Motor Corporation in 2011. He later joined Nakajima Planning, having been invited by a team member, a fellow alumnus of his university. At Nakajima Planning he assumed the role of SUPER FORMULA track engineer, starting from the fourth round of the 2017 season.


※The information provided is as of September 17, 2020.(AM)


Language Choice : 日本語 | English


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