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March 10th, 2026

From PDFs to Pit Lane: Building a Real-Time Data Product for McLaren Racing

  1. From PDFs to Pit Lane: Building a Real-Time Data Product for McLaren Racing Jon 37:11

In this week’s episode of the PolicyViz Podcast, I chat with Michael Gethers, former Head of Data & Strategy for the McLaren IndyCar team, about how a personal side project analyzing IndyCar timing PDFs turned into a job building real-time data tools for a professional race team. We dig into what it’s like to design data products for engineers, strategists, and drivers who need to understand information instantly while a car is on track. Michael shares how he moved from making public visualizations on Twitter to building an internal analytics application from scratch, why “pretty charts” weren’t enough for the engineers, and how user feedback shaped the product. We also talk about race strategy as a probabilistic data science problem, the difference between dashboards and data products, and what he learned about designing for cognition under extreme time pressure. If you care about dashboards, data storytelling, or building tools people truly use, this conversation is a goldmine.

Keywords: data dashboards, data product design, data visualization, motorsports analytics, race strategy, McLaren IndyCar, telemetry data, timing data, data science in sports, user centered design, dashboard design, real time analytics, D3 visualization, data engineering, analytics application

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My name is Jon Schwabish, and I am an economist, writer, teacher, and data communications expert. I am widely recognized for advancing clarity and accessibility in how analysts, researchers, and scholars communicate their findings. I am the author of four books—Better Presentations, Elevate the Debate, Better Data Visualizations, and Data Visualization in Excel—which provide practical guidance for people looking to improve how they create, present, and communicate data-rich content. I am also the host of the PolicyViz Podcast, the longest running podcast dedicated to helping listeners better understand data and data visualizations.