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Jonathan Hay, Senior Vice President, Business Strategy and Analytics, Boston Red Sox

Describe your career to date

Originally born in Australia, I moved to Boston with my family when I was six years old and grew up obsessing over sports. After graduating Harvard with a degree in economics, I went to work on Wall Street at Morgan Stanley where I ran the firm’s US Inflation Derivative business. After five years, I headed to Chicago Booth to obtain my MBA to pursue my dream of working in sports.  

After graduation, I managed to talk my way into a baseball analytics internship with my hometown Boston Red Sox, working for the esteemed Bill James on projects around player performance projections. I was fortunate to receive an opportunity to apply the same skills to the business side of the house, leveraging data and analytics to help drive revenues at the organization.  

Over the past ten years, I have built my team to encompass data infrastructure, business intelligence, CRM, predictive analytics, and machine learning all with the goal of helping the Boston Red Sox drive success off the field so that we can also find success on the field. 

Data literacy is a key enabler of the value and impact from data. How are you approaching this within your organization? 

One of the most valuable skills I learned during my career is how to communicate complicated concepts in a way that prioritizes listener comprehension and drives impactful decision-making. When I was working on Wall Street and learning tons of new and complicated concepts, I used to call my mother in the evening and try to explain to her what I had learned that day. My reasoning was that if I could explain to my mother why mortgages had negative convexity, then I truly understood it myself. This skill has been immensely valuable as my career has continued in the data and analytics space.  

It is unfair to expect people with very different backgrounds to all speak the same language of data; quite the contrary – those of us in this space must translate our findings into the end–user’s language to push them towards the optimal data–driven solution.  

At the end of the day, nobody cares how accurate or complicated your model is if you cannot push adoption of the results. The art of communication becomes the key agent that allows for the marriage of quantitative and qualitative decision-making in the business world. 

What role do you play in building and delivering conventional AI solutions, including machine learning models? Are you involved in your organization’s adoptions of generative AI? 

I feel my role is as political as it is technical. Artificial intelligence (AI) can be a boon to people across our organization, but it is new, scary, and complicated. For many folks, they see it as a threat to their job rather than a productivity tool. I feel that my job is to work with stakeholders to help them understand what AI is and what it is not, and to help them see that adopting AI in the right ways is only going to make their lives easier. The key is stressing that AI is simply another tool for them to use rather than something that is going to replace them. Only by getting buy-in from those that will ultimately be leveraging these tools can we really deploy AI at scale. 

What are the key challenges to your data function that you are facing as its leader? 

Leadership means hiring great people (ideally people that are smarter than you), putting them in a position to succeed, and supporting them in every possible way. I am extremely fortunate to have a wonderful team around me, and my goal is to make sure I remove all roadblocks to their success.  

I cannot be the go-to expert in everything for the business, so my goal is to be conversational rather than fluent in all topics related to data and analytics. If I can understand the unique challenges that my team members face, I can focus my energies on setting them up for maximum success. 

Jonathan Hay
has been included in:
  • 100 Brands 2022 (USA)
  • 100 Brands 2024 (USA)

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