Latest / Franchise Conversations with Fexingo: Buying, Running, and Scaling Franchise Businesses / How Franchisees Use AI-Driven Labor Scheduling to Boost Profits
Transcript
- Lucas: So we've talked a lot about cutting costs on the supply side — group purchasing organizations, reverse auctions, lease audits. But there's one cost line that eats up 30 to 35 percent of revenue for most franchisees, and it's actually the biggest lever most operators aren't pulling hard enough: labor. Luna: And I bet you're not talking about just cutting hours. You mean smarter scheduling. Lucas: Exactly. I'm talking about ai driven labor scheduling. Not the old spreadsheet and gut feel method. I mean platforms that ingest your point of sale data, your foot traffic patterns, weather forecasts, local event calendars — even things like school holidays and hospital shift changes — and then spit out a schedule that matches staffing to predicted demand, often in fifteen-minute increments. Luna: I've heard of this in the context of big corporate chains, but are franchisees actually using it? I mean, the upfront cost must be a hurdle. Lucas: More than you'd think. I spoke with a franchisee who runs six quick-service restaurants in the Dallas metro area. He adopted a platform called ScheduleSmart — there are a bunch of them, 7shifts, Homebase, Legion — and he told me in the first year, he cut overtime by 18 percent and improved his customer satisfaction scores by 12 points. Luna: Overtime dropping makes sense — the algorithm catches when you're about to hit 40 hours and either shifts labor or alerts the manager. But how does scheduling raise customer satisfaction? Lucas: Because the biggest complaint in fast food and fast casual is wait time. And the biggest cause of wait time is having three people on the register at 2 PM on a Tuesday when you only need two, and then four people at 7 PM on Friday when you actually need six. The AI learns that pattern and reallocates hours to when customers are actually there. More staff when it's busy, fewer when it's slow. Customers get served faster, food is fresher, and you're not paying people to stand around. Luna: So it's a win-win in theory. But I imagine some franchisees push back because they think their store managers know best. Or they're worried about employee morale if schedules get too rigid. Lucas: That's the tension. The franchisee I spoke with said he had to do a lot of hand-holding in the first few months. His managers felt like the algorithm was second-guessing them. And employees — especially the Gen Z staff — actually liked it because they got more consistent hours and could request shift swaps through the app. But the managers needed to see that the algorithm's forecast was right before they trusted it. Luna: And was it right? How accurate are these things? Lucas: The platform he used claims 85 to 90 percent accuracy for next-week demand forecasting. But that's based on historical data. The first few weeks, the model is still learning your specific store's rhythms. So you have to give it a month or two before the real savings kick in. By month three, his labor cost as a percentage of sales dropped from 32 percent to 28.5 percent. That's three and a half points. On a store doing $1.2 million in annual revenue, that's $42,000 a year — per location. Luna: For a six-unit operator, that's over a quarter million dollars annualized. Not pocket change. Lucas: And that's just the direct savings. The franchisee also told me his turnover went down. Employees quit less when they get predictable schedules that match their availability. The platform let them enter preferred hours and block out times they couldn't work, and the algorithm respected that. So the scheduling process became more transparent. He said his annual crew turnover dropped from 130 percent to about 95 percent. Luna: That's a huge deal in QSR where turnover is often over 150 percent. Every percentage point of turnover saved is thousands in recruiting and training costs. Lucas: Right. And then there's the compliance piece. This is July 2026, and a lot of states — California, New York, Illinois, even some cities like Seattle and Chicago — have predictive scheduling laws that require employers to post schedules at least two weeks in advance and pay penalties for last-minute changes. These platforms automate compliance. They flag when a schedule is posted too late or when a shift change would trigger premium pay. That alone can save a franchise from fines and class-action lawsuits. Luna: I've seen those suits. They can run into the millions for a chain. So the ROI on the software — which is usually a monthly subscription of maybe $50 to $200 per location — is almost immediately positive. Lucas: Exactly. And yet, when I surveyed franchisees at a conference last spring, only about 25 percent said they were using any kind of AI scheduling. Most are still doing it manually or with a basic spreadsheet. So there's a huge gap between what's available and what's actually deployed. Luna: Why do you think that is? Is it just awareness, or is there a trust issue with the technology? Lucas: I think it's a mix. Some franchisees are intimidated by the word 'AI.' They think it means they have to overhaul their entire tech stack. But most of these platforms integrate with the POS systems they already use — whether it's Toast, Square, or NCR. It's really just plugging in an API. The bigger hurdle is cultural: convincing store managers that a machine can do part of their job better than they can. Luna: So what's the best way for a franchisee to get started without overwhelming their team? Lucas: Pilot one store. Pick your highest-volume location or the one with the most scheduling headaches. Run the AI scheduling alongside your manual process for two weeks — don't actually use the AI schedule, just compare it to what your manager created. See where the algorithm would have put more or fewer people. That builds confidence. Then flip the switch for real on that one store for a month. Measure labor percentage, overtime, and customer feedback. Once you see the numbers, you'll have the ammunition to roll it out to the rest. Luna: That's smart. Low risk, and it lets the manager save face if they're skeptical. Lucas: And by the way, franchisors are starting to mandate these tools. I've seen two major sandwich chains include AI scheduling in their updated operations manuals for 2026. They're telling franchisees: if you want to open a new location, you have to use our approved scheduling platform. So it's coming whether you adopt it now or later. Luna: Yeah, it reminds me of when they started requiring digital menu boards. Nobody wanted to spend the money upfront, but now you can't imagine running a store without them. Lucas: Exactly the same pattern. And look, I'll be honest — this kind of conversation is exactly why we do this show. We dig into the operational tactics that actually move the needle, and we share them so you don't have to figure it all out from scratch. We deliberately keep this podcast ad-free because we want the advice to be useful, not interrupted. If you've gotten value out of episodes like this one, and you want to support that choice, there's a link: buy me a coffee dot com slash fexingo. It's a simple way to help us keep doing what we do. Luna: Yeah, and we mean it — no pressure ever. But every little bit helps us stay independent and focused on what matters for franchisees. Lucas: So back to the scheduling piece. One more thing I want to highlight: these platforms also help with hiring. They can analyze your historical sales data to predict when you'll need to bring on seasonal staff, and even recommend how many people to hire based on projected growth. Luna: So instead of reacting to a sudden rush, you're proactively building a pipeline. That's smart. Lucas: Right. And the franchisee I mentioned, he used that feature to prepare for the back to school surge. He knew from the data that the first two weeks of August would see a 20 percent jump in lunch traffic. The algorithm told him he needed three extra crew members per store starting July 25th. He hired them early, trained them during the slower week, and then they were ramped up and ready. His competitor down the street was scrambling with 'help wanted' signs and overworking their existing staff. Luna: That's a tangible competitive advantage. And it's not just about saving money — it's about building a better operation. Lucas: Exactly. And that's what we're really after here. It's not about squeezing every nickel. It's about running a business that works for customers, employees, and the owner. AI scheduling is one tool that helps all three. Luna: Alright, so if a franchisee wants to explore this, what's the first step? What should they look for in a platform? Lucas: First, make sure it integrates with your POS. That's non-negotiable. Second, check if it supports the specific labor laws in your state or city. Third, look for a platform that offers shift-swapping and time-off requests through a mobile app — that's what drives employee buy-in. And fourth, ask about the accuracy of their demand forecasting. Some platforms use only historical data, but the best ones also pull in external factors like weather and local events. Try to get a free trial or a demo with your actual data. Luna: Good criteria. And start small, as you said. One store, one month. Lucas: Exactly. The data will speak for itself. And if you're listening and you've tried this — or if you have questions — we'd love to hear from you. We're thinking about doing a follow-up episode where we compare different platforms. So drop us a line. Luna: Sounds like a plan. Thanks, Lucas. Lucas: Thanks, Luna. That's it for this episode of Franchise Conversations. We'll see you next time.