Interview: Raymond Boyle, vice-president of data and analytics, Hyatt Hotels

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Interview: Raymond Boyle, vice-president of data and analytics, Hyatt Hotels

Raymond Boyle, vice-president of data and analytics at Hyatt Hotels, is an experienced executive who helps his business make the most of its information. He is responsible for Hyatt’s data strategy, governance, engineering, science and analytics capabilities. His team’s data-led insights boost customer and colleague experiences.

“I took the opportunity because I love the role,” says Boyle, who joined Hyatt at the start of 2020, having previously been vice-president for data and analytics at Walmart Labs.

“I was very excited about Hyatt as a company and its culture. It gives me everything I enjoyed doing within the data role, including leading the strategic insights and the governance areas.”

At Hyatt, Boyle reports to Amy Weinberg, senior vice-president for loyalty, brand marketing and consumer insights. He has spent his five years at the firm laying the foundations for a business strategy that puts data at the heart of organisational and operational processes.

“I love working in the travel industry,” he says. “It’s a complex business. As a data leader, you get all the stuff you would ever want in terms of delivering a customer and colleague experience and creating effective digital engagement.”

Boyle’s current role is the latest stop on a 30-year professional journey during which he has used data and analytics to fuel innovation and growth. He recognises the role of data chief has changed significantly during his time in the profession. The impact of emerging technologies, such as artificial intelligence (AI), brings even greater challenges.

“It has been a fascinating area for many years,” he says. “The field of data and AI is changing extremely quickly, including the types of things that we take on, the way technology is implemented, the way people engage with it and the cultures we build around it.”

Building data products

Boyle says much of his day-to-day leadership role at Hyatt involves ensuring people around the business are fluent in data and can engage with information assets. He says the work revolves around “the productisation of data” and developing self-service environments that make things easier for employees and customers.

“We think of data as a product, including all aspects around managing information, designing strategies and creating solutions,” he says. “That work covers the data engineering worlds that care for different parts of the business, the platform organisations that manage our foundations, and the data science and machine learning functions.”

Boyle says Hyatt’s data strategy centres on advancing care through insight-driven decisions and automation. The focal point of this strategy is cultivating the best people and evolving the organisation’s data culture.

“We’re working through how people lead in the organisation and thinking about data fluency and the stewardship of information within the business,” he says. “We focus a lot on customer personalisation and trust. We want to build the ability for the organisation to be perfect with every guest during every step of their journey and continue to personalise how we engage with our customers in a high-security, high-trust framework.”

Boyle is excited about some of the achievements so far. His team ensures the business has the right data capabilities and performance indicators. At the same time, they make sure people across Hyatt have a common understanding of data-led performance.

“That’s taken a lot of great work to automate and simplify the business from an operational perspective, and then a lot more work to ensure we’re growing with intent – that as we do new mergers and acquisitions as an enterprise, that we can connect data and the products into that system smoothly,” he says.

Innovating at pace

A key underlying technology for this approach is the Snowflake AI Data Cloud for Travel and Hospitality, a unified data platform that helps companies exploit their information. Boyle says Hyatt uses Snowflake technology to consolidate enterprise data into a single location.

The switch to Snowflake took two years to complete and was finished by the second quarter of 2024. Boyle says the move to the AI Data Cloud was an important transition. An ever-increasing number of people at Hyatt wanted to use information. However, the company’s legacy environment had capacity constraints.

“We needed to add a ton of compute to the system, and we had some hard decisions to make as we went through that work,” he says. “We had a massive growth in the amount of data people wanted to consume within the business.”

“We think of data as a product, including all aspects around managing information, designing strategies and creating solutions”

Raymond Boyle, Hyatt Hotels

Boyle’s data team approached the Snowflake implementation carefully and pushed components live incrementally. The switch to Snowflake involved some hard graft. Pipelines were refactored, and the security infrastructure was redesigned. He recognises the migration process was a significant technological and cultural challenge.

“You can’t stop running the business while you ******** the migration,” he says. “We had to manage the delivery of many new products and capabilities during the migration. There were times when we had to manage duplicate pipelines. A lot of folks had to be engaged in the migration process.”

The data team decommissioned Hyatt’s legacy environments in August. Snowflake is now the company’s scalable data platform. He says the technology allows people across the business to access data for their projects. The AI Data Cloud also cuts the time his team spends on information management.

“Snowflake allows us to innovate faster and drive those outcomes cleanly over time,” he says. “We’re launching more services, so we have more data applications coming into the system fairly quickly, and we’re also benefiting from Snowflake’s work to ensure that other software organisations are building natively on the platform.”

Supporting business growth

Boyle leads a 100-strong data team at Hyatt, including full-time staff and contractors. He says insight and analytics are at the core of the company’s decision-making processes.

“Data is at the heart of how the company functions,” he says. “Our CEO is engaged in data and has led the strategic work around how we think about AI. Data is now a big part of every domain and a core element of how people plan, build and ********.”

Boyle says one of the company’s data priorities right now is personalisation. “We’re focused on following the customer journey and making sure that AI and data drive the properties that we recommend and the search experience and the content people see,” he says. “We want to ensure our customers have a deeper relationship with Hyatt.”

In addition to its work on personalisation, Boyle says the company is rolling out modern pricing-optimisation capabilities globally. His team is also exploring the potential for generative AI capabilities within analytics. He says there’s no straightforward answer as to whether it’s better to build or buy AI technologies and models.

“It’s likely to be a mix, and the result will depend on what we’re trying to achieve at any given time,” he says. “We’ll look at the outcomes, the initiatives, the strategic investments that the company wants to make, and we’ll make decisions based on the speed and the impact that we want to have, and the architectural standards that we want to see within the organisation.”

Boyle says the data organisation he’d like to lead two years from now will use digital innovation to boost customer experiences and business operations. From self-service behind the scenes to fresh services at the front end, he wants Hyatt to continue transforming with data.

“I want our guests to experience Hyatt in a personalised manner and for us to take full advantage of the relationship we have with our customers. I want to push innovations that ensure our relationship with guests is deeper, more meaningful and more trusted across all the different interaction points we have with them,” he says.

“I’d also want our operations to be more efficient and automated. I want to help our organisation grow with intent. I want to ensure that the types of development we want to do as a business, and the growth the organisation wants to see globally, are better, faster and more efficient due to the data we provide.”

Defining the data chief’s role

Boyle has built his career leading data initiatives at major organisations. He understands successful data chiefs will play a key role in helping businesses to thrive in the digital age. However, they shouldn’t fulfil this role in isolation. Boyle says successful data stewardship is a team game that starts at the top of the enterprise.

“The CEO or the executive team should dictate the direction of travel for AI within the organisation,” he says. “When I think about the operating model, it’s about making sure we have clarity around our purpose and the areas the executives believe are the most important things to invest in. The business leaders for the domains must be aligned to that strategy and work to drive value creation in their functions.”

Boyle says the role of digital leaders, whether CDOs, CTOs or CIOs, is to ensure the hardware and software stack helps business leaders achieve their transformational objectives. Internal and external partners must ensure data is published and consumed effectively and safely.

“The tech stack is critical to your success,” he says. “Enterprise architecture plays a huge role, as does cyber security and the privacy and data governance specialists. If you get those things right, you’ll build out your AI services and the back-end data infrastructure to drive your business outcomes. You’ll be able to scale your initiatives at a faster pace.”

Boyle’s best-practice advice for other data leaders is to think of digital change as a team game. “You need to have fluent, transformational thinkers at all levels. You must have technology partners who are a big part of what you’re trying to do and creating high-quality data tooling,” he says.

“You need to get your product management, engineering, architecture, machine learning and science community functioning together, knowing their roles and delivering joined-up processes quickly and cleanly.”

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