What does real ROI from AI and analytics actually look like in the fast-food industry?

At SAS Innovate, I sat down with David Gardner, Senior Director of Analytics at Boddie-Noell Enterprises, the largest franchise operator of Hardee's in the United States, to explore how a 60-year-old family business is transforming itself through data, forecasting, and AI. This is a company processing around 40 million transactional records every single day across more than 300 restaurants, where even shaving a few seconds off a drive-thru experience can have a measurable impact on customer satisfaction and revenue.

What makes this conversation so interesting is how grounded it is in operational reality. David shares how the company moved from relying on spreadsheets, summarized reports, and gut instinct toward real-time analytics powered by SAS. One of the standout stories involves extending breakfast hours. Operational teams initially resisted the idea, convinced it would create chaos in the kitchen. But once David dug into the transactional data, the numbers told a very different story. Breakfast sales during the extended hours were growing dramatically, proving the demand was real and helping the business make a decision based on evidence rather than instinct.

We also discuss how analytics is helping optimize labor scheduling, forecasting, payroll, inventory planning, and customer throughput at scale. David explains how his team can now analyze profitability hour by hour for every restaurant in the business, helping local managers make faster and more informed decisions. With forecasting accuracy improving to within fractions of a percentage point, the business can plan more effectively in an industry facing inflation, labor pressures, delivery app disruption, and shifting customer habits.

Another major theme is accessibility. David talks about the importance of data democratization and making analytics understandable for non-technical teams. Restaurant managers are not data scientists, and they should not need to be. The goal is to put insights directly into their hands in a way that is simple, actionable, and easy to understand. AI is now becoming part of that journey too, acting as what David describes as a mentor for newer managers, helping them identify opportunities, improve operations, and get up to speed faster.

We also explore how customer behavior has changed dramatically with the rise of delivery platforms like DoorDash and Uber Eats, creating entirely different purchasing patterns compared to traditional in-store diners. Through analytics, the company can better understand those differences and optimize everything from promotions to staffing and menu strategy.

What stood out most to me is that this is not a story about flashy AI demos or abstract transformation projects. It is about using analytics to solve practical business problems in real time while quietly improving the customer experience behind the scenes.

Because at the end of the day, customers do not care about dashboards or machine learning models. They care about getting good food quickly, accurately, and consistently. The technology only matters if it helps deliver that outcome.

So as businesses continue chasing AI opportunities, are they focusing on the use cases that actually move the needle, or getting distracted by the hype?

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