Inside Hyatt's Push for Self-Service Data and AI

Raymond Boyle has spent decades helping companies like Walmart and Sam’s Club turn data into business outcomes. Now, as Hyatt's Chief Data, Analytics and Insights Officer, he’s helping the hospitality giant prepare for the future of business intelligence and automation: self-service data and AI.

For Ray and his team, that meant investments in infrastructure, APIs and other technical components required to enable broad access to data assets. But it also meant improving the AI fluency of the whole organization – from the executive team to business users, he told “The Data Chief” podcast. To identify how the technology could help Hyatt deliver outstanding experiences to all its stakeholders, including hotel guests, owners and employees, Ray also brought experts together from across the enterprise.

“AI pulls the company a lot tighter together than even data did historically. So you've got to have great business leadership, you’ve got to have technology teams that are at the table in the right way … and then you’ve got to introduce data science and machine learning people in those groups … and it changes a lot of things about how people work,” Ray said.

Ray shared valuable advice to help other technology leaders use data to drive more engaging, personalized experiences for customers.

• Prioritize self-service: “People have to have the data, they have to have that information, they have to have it in a way that's flexible and quick and they can go do their work. Self-service is really at the cornerstone of that.” ‍
• ‍Work AI into existing business momentum: “We view data and AI more and more as an enabler. We want to look at those outcomes, look at those outputs, and think about where artificial intelligence and data should play a role, and work on the transformation of the business with that in mind.” ‍
• Establish outcomes early, and let them lead the way: “When you think about experimentation, being clear about the outcomes and being clear about how we are going to measure it allows that stuff as it's approved to be clear. And then, as the company drops it into the ‘go get it done’ cycle and those teams are working on the development of the data, the artificial intelligence services, plugging it into the tech stack and then launching, the goal is to look at it and see if we’re achieving those outcomes.”
• Bring the right people to the table: “Make sure the business is at the table, the technology team is at the table, all the applications the initiative will touch, the people who build out the artificial intelligence services are at the table, and all the data teams that need to go get the data to power this thing are at the table.”
• Data is a team game, and everyone has a role to play: “Velocity comes over time – as you build up the operating model and you've got the business playing their role correctly, the technology teams playing their role correctly, the data organization playing their role correctly, and the governance and security roles being at the table.”
• Work AI into existing business momentum: “We view data and AI more and more as an enabler. We want to look at those outcomes, look at those outputs, and think about where artificial intelligence and data should play a role, and work on the transformation of the business with that in mind.” ‍
• Find your champions: “We want to make sure we are building superusers around the world so that they can help people grow in a self-service way.”

Make sure to check out the full discussion for even more great advice from Ray.