Choice Hotels technologists gather at the company's Scottsdale office for the the annual Mastery ... [+]
Earlier this year, Choice Hotels CIO Brian Kirkland achieved a milestone many technology leaders dream about: he shut down the company’s last physical data center.
The move closed the door on a five-year shift to Amazon Web Services that included decommissioning more than 3,700 servers, phasing out 300 outdated software programs, and improving another 250 before moving them to the cloud.
Chief Information Officer Brian Kirkland
Today, Kirkland and his team are taking advantage of the speed and flexibility to scale up artificial intelligence initiatives and deliver new experiences for customers and franchisees across its portfolio of more than 7,500 properties.
“We had to do this because we don’t know what tomorrow looks like,” Kirkland said of the move to AWS. In an industry that increasingly relies on real-time data to deliver up-to-the-minute room pricing and personalized customer experiences, “being in a data center is not going to allow for a competitive advantage.”
Kirkland began his career at Choice in 2015 developing a cloud-based version of the company’s reservation and inventory management system, a big step for an industry not particularly known for being on tech’s cutting edge. When he became CIO in 2018, his focus shifted to bringing that agility to the entire company.
A focus on delivering value alongside strict governance and cost management has been key to the transition, Kirkland said. He worked closely with his peers in the C-suite to plan the transition, and his team established guardrails to monitor cloud consumption and keep a close eye on spending.
The benefits have begun to materialize in ways both big and small. For example, a shift to deploying software on a daily rather than monthly basis led to big changes to its website. During the first month of the pandemic, Choice launched more changes on its site than it had in the entire year prior.
In 2022, the company rolled out ChoiceMAX, a mobile- and cloud-first revenue management system that uses machine learning to give real-time pricing recommendations to franchisees. In addition to potentially boosting property revenue, the app also automated much of what was before a time-consuming manual process.
IT roles, tools and skills have also evolved as the company moved to cloud. Many employees who used to manage physical data centers shifted to cloud operations and engineering teams, working alongside AWS to build and manage networks and building tools to optimize cloud spend. Data science capabilities are becoming increasingly democratized, Kirkland said, and everyone is encouraged to explore how they can use AI and machine learning in their work.
Choice has a small “tiger team” focused on driving safe and efficient adoption of AI and generative AI. It ramped up tech-focused training initiatives for both employees and franchisees, and its Mastery innovation summit includes “make-a-thons” where teams can show off new projects to executives that could get fast-tracked into production.
A benefit of working closely with a large cloud provider like AWS is the chance to test new products and services as they become available, Kirkland said. Choice is a trial customer for Amazon Connect, a platform that uses AI to improve efficiency in customer call centers. It’s also testing an AI tool that aggregates customer data across multiple systems to create a unified profile, which ultimately can help deliver more personalized experiences.
On the generative AI front, Choice is testing Amazon’s CodeWhisperer developer productivity tools and Microsoft’s copilot solutions, among others. While not quite ready for prime time, teams are also testing genAI capabilities that could be used directly with customers.
No matter the AI technology, “when they are ready for employees to use in a safe way, rolling that out fast will be a focus,” Kirkland said.
The onslaught of new technologies offers a range of opportunities for Choice to leverage its data to drive growth and move more quickly. Looking ahead, Kirkland said he is focused on scaling up new AI use cases, getting reliable data into the hands of end users, and tying together knowledge and insights across disparate parts of the organization.
“We are the most advanced we’ve ever been, and the least advanced we’ll ever be,” Kirkland said. “The journey’s never over.”
