#117 Driving commercial opportunities with Max Métral – Senior Analytics Manager
Max Métral is a self-motivated professional with a successful track record in data science and analytics cross-functional roles for worldwide organizations. He loves to solve complex problems as much as he loves to take up new challenges. Max is passionate about the sports industry and its continually evolving paradigms, and he also enjoys writing articles from time to time.
In this episode, Max dives deep into his background and how he found his interest in data. He has always been interested in answering real-life business problems with data -that’s where it all started. At Michelin, Max studied the speed of cars depending on which side of the road cars drive on. Max explains why he always wanted to move into the sports world. He saw a massive opportunity in the sports world – it’s still a very immature industry when it comes to using data. At the time, Max sent loads of emails to people in the sports industry. One person responded and agreed to have coffee with Max – that person helped Max make his decision about working with sports.
There are two types of data analytics in sports:
Sports analytics – using data to improve performance. Investing in players will be the best bang for your buck. Max didn’t want to get into sports analytics because it doesn’t apply to all sports – can you really utilize sports analytics in the car world?
Business analytics – using data to improve business performance. Once the organization gets bigger, then you can be independent of the players. Teams need sports analytics before getting business analytics right. Max chose to work in the business analytics world because he can go into any industry.
In most sports organizations, there is one data team. When an organization is first trying to understand what to do with a data scientist, they start a centralized team. As a data science group, they can tackle issues that the organization has. Then, the organization will learn what else data science can do for numerous parts of their business. This is a transition period that is going to take a long time. Plus, Max explains the benefits and challenges of being an analytics translator. Analytics translators have to be a jack of all trades. Which means, they are an expert at nothing. Stay tuned as Max dives deep into Formula 1 and how they best utilize data. Plus, Max gives us the scoop about his newsletter.
Enjoy the show!
We speak about:
[00:30] How Max started in the data world
[01:20] What was the first step in your professional life?
[02:35] What was it like working at Michelin?
[04:40] Why did you make a move into sports?
[07:15] What was it like working with football clubs?
[09:00] Was it surprising to work with marketing analytics?
[11:40] Why did you choose business analytics in sports?
[13:20] Why do you think analytics translators are most needed?
[16:40] How is it being an analytics translator?
[18:00] How did you end up working at F1?
[21:00] What stories can you share of the process at F1?
[24:30] How did you choose “data-informed” over “data-driven?”
[25:55] What does your tenure look like at F1?
[35:20] How do you integrate B2B and fans?
[37:35] How do you work with the sports teams?
[40:00] About Max’s newsletter
Resources:
Max’s LinkedIn: https://www.linkedin.com/in/maxmetral/
Max’s Website: https://maxmetral.com/
Max’s Twitter: https://twitter.com/Racing_metral
Sign up for Max’s Newsletter: https://maxmetral.com/my-newsletter/
Formula One on LinkedIn: https://www.linkedin.com/company/formula-one-management-ltd/
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Quotes:
“I was extremely lucky to be the right type of person, with the right type of skills, at the right time.”
“I had to start so many things that I’m not an expert at.”
“It’s always good to do passive research about what people like and don’t like.”
“The fan, the customer, and the consumer might be three different people.”
I always have been interested in solving problems and that is what gets me. If you want to get my interest give me a problem and I am going to try to get you a solution. And I love the idea of answering real life business problems with data and that is what got me into it.
I can also translate it the other way, take the output and talk to businesspeople, explain it in very simple terms
One person that I knew was just being hired by F1 and sent me a Linkedin message “Hey would you be interested in talking” I said sure, within two weeks I was off to go and to move from Manchester to London and work for F1, so that was amazing.
When I was told that there was nothing, it was both super exciting to have a blank sheet of paper to start from scratch and scary because you start from scratch.
They love you; they are so happy that you make their lives easier, so I love it personally.
We are not being data-driven; we are trying to be data-informed.
When you do research you ask people to tell you what they like or they don’t like, so it’s always good to do some passive research as to what people like or don’t like just because they are talking online, on Twitter or anything and to see does it match?
I think what some people get wrong is that they think they see fans as customers and it’s very important not to because my view is the fan, the customer and the consumer may be three different people theoretically speaking.
We are now on YouTube: Watch the episode here: https://youtu.be/4u9xGKFRnTY
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