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Home Management Leadership Growth Strategies Tactics and Strategies

What the Hungarian F1 race teaches about being data-driven

Andrew White by Andrew White
August 16, 2022
Photo by Chris Peeters from Pexels: https://www.pexels.com/photo/man-riding-on-racing-car-12795/

Photo by Chris Peeters from Pexels: https://www.pexels.com/photo/man-riding-on-racing-car-12795/

Did you watch the Hungarian F1 race Sunday, July 31st? Max Verstappen qualified 10th on Saturday but won the race. Lewis Hamilton started 7th and ended second. The pole sitter, George Russel ended up third. The two Ferrari drivers, who qualified 2nd and 3rd and were favoured to perform well, ended up 4th and 6th respectively. Something went array for Ferrari, but what?

What is strategy?

This is yet another story about what strategy really means. On lap 21 the TV camera panned to the corners before the main straight. The two Ferrari drivers of Carlos Sainz and Charles Leclerc were under 1 second apart chasing down the leader, George Russel.

As the camera followed the leading three cars, It looked like the Ferrari was about to overtake the leader. Then we heard over the Ferrari radio, ‘box, box, box’. Box means ‘head to the pits’. Just as Ferrari's speed and tire management looked like it was paying off and they might take the lead while on the track, someone at Ferrari decided to take the cars out of the battle. What? Why?

As the race unfolded things went from bad to worse. One of the Ferrari’s put on hard tires. All the other front runners were on soft or medium tires. A couple of other cars were on hard tires but their race pace was off and they were not competitive. Putting on hard tires didn’t make sense. From there on, Ferrari lost its position and was uncompetitive with the top drivers.

Post-race review

In the post-race interviews, the real problem surfaced. Christian Horner, team principle of the winning Red Bull, gave it away. It seems that on the previous day, in warmer weather, the hard tire did offer higher performance than soft or medium tires. That was what the data said then.

When Mattia Binotto was interviewed, the Ferrari team principle noted that his cars “didn’t perform as expected”. Ferrari had decided to put on hard tires on race day (Sunday) using data from Saturday's qualifying session. Christian’s critical killer phrase was this: “You only had to look up from the screen.”

Here is the story in my words. Ferrari was relying too much on data alone to inform or dictate their strategy. Red Bull and Mercedes all used data, but they added a human element. They had looked up from their screens and saw how the hard tires were actually performing in the cooler weather.

Thus, they discounted the data due to different conditions. Ferrari didn’t. Ferrari assumed the data was reliable, and trusted. And so it was. But the data didn’t apply to the actual race conditions of the day!

What being data-driven really means

Conclusion: to be data-driven does not mean to (only) use data or use data all the time to automate every decision. Some decisions need to be augmented: Machines or humans using data is not always enough. Sometimes you need to look up or away from the data.

So to be data-driven does not mean to (only) use data. I like to say that to be data-driven really means “to help business leaders ask smarter questions of the business and environment around them”. Ferrari didn’t ask a smarter question. They asked a question from the previous day and got an answer for the previous day. The other teams asked a different, smarter question. And ignored the data and expanded their data set. (Toto Wolff quote)

The Ferrari drivers, who should have been on the podium at the end of the race, finished in the doldrums.

Previous blog on F1: Strategy is Learning by Doing (Toto Wolff quote)

First appeared on Gartner Blog Network

Related:  Overcautious counsel costs enterprises US$17M annually
Tags: data-driven strategyGartner
Andrew White

Andrew White

Andrew White, distinguished Analyst and VP, has a primary research focus on the chief data officer role, data and analytics platforms, strategy and operating models, governance, and stewardship. His current role is as Chief of Research, Data and Analytics, and is also Content Lead for Data and Analytics. He has held previous roles including Vendor Lead for Oracle Corp; Agenda Manager for Data and Analytics Programs, and Data and Analytics Leaders (Chief Data Officer).

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