Latest / Franchise Conversations with Fexingo: Buying, Running, and Scaling Franchise Businesses / How Franchisees Use Labor Scheduling Analytics to Lift Margins
Transcript
- Lucas: So, Luna, you know that regional burger franchise on the edge of town, the one with the drive-thru and the surprisingly good shakes? Luna: Yeah, I've been there. They always seem to have just enough staff, never too many, never too few. Lucas: Right. I sat down with the operator, a guy named Dave, and he told me something that stuck: last year he stopped scheduling by gut feel and started scheduling by number. Specifically, he started using labor scheduling analytics, and it cut his labor cost as a percentage of sales by eight percent over six months. Luna: Eight percent is huge on a franchise P&L. How did he actually do it? Was it some fancy AI system? Lucas: No, that's the thing. He didn't buy any new software. He used the reporting tools his franchise system already had, plus a basic spreadsheet. The key was shifting from reactive scheduling—you know, looking at last week's sales and guessing—to forward-looking scheduling based on historical patterns and local events. Lucas: He started tracking three numbers every single week: sales per labor hour, forecast accuracy, and customer satisfaction scores by shift. And he reviewed them at the same time every Friday, like a ritual. Luna: So what's the biggest insight he got from that first month? I bet there was some embarrassing discovery. Lucas: Oh, absolutely. He realized he was overstaffing the mid-afternoon lull by about forty percent. He had three people folding napkins when the drive-thru was dead. And he was understaffing the Friday night rush by about twenty percent, which meant longer wait times and lower ticket sizes. Luna: Ouch. So the fix wasn't just cutting staff, it was moving them from the slow times to the busy times. Lucas: Exactly. The data let him shift hours, not just slash them. And that's the thing that got his managers on board. He wasn't asking them to do more with less; he was asking them to do the same with smarter. Luna: What about the customer satisfaction side? You mentioned he tracked that too. How did that play into the scheduling decisions? Lucas: He found that his satisfaction scores were dipping on Tuesday afternoons, which he'd never noticed because that shift was considered 'slow.' Turns out the after-school crowd of kids and parents was bigger than he thought, and the understaffing was causing long waits at the counter. Lucas: A simple tweak—adding one person from three to five on Tuesdays—brought those scores back up. That's the kind of correlation you only see when you're actually looking at the numbers. Luna: That's so practical. So what would you say is the biggest barrier for most franchisees who aren't doing this? Is it the data being hard to get, or just not knowing what to look at? Lucas: I think it's the latter. Most franchisees have access to sales data, but they don't have a framework for turning it into a schedule. Dave said the hardest part was the first two weeks, just getting used to looking at the numbers in a structured way. Lucas: And let's be honest, there's a human tendency to cling to the way you've always done it. A lot of operators are 'hands-on' types who trust their instincts, and that's fine—but it's better when your instincts are backed by data. Luna: So you're saying it's a mindset shift as much as a process shift. How did Dave bring his managers along? I'd imagine they were pretty skeptical. Lucas: He didn't just hand them the spreadsheet and say 'do this.' He involved them in the Friday review. He'd ask, 'Why do you think Tuesday was off?' and let them dig into the numbers themselves. That way, the managers felt ownership over the decisions, not like they were being micromanaged by a computer. Lucas: He also gave them a small incentive: if the store hit its labor cost target and kept satisfaction above a certain score, the managers got a bonus. Suddenly, they were the ones asking for the data. Luna: That's a great example of aligning incentives. So what about the tech side? You said he used a spreadsheet, but are there affordable tools that do this automatically? Lucas: There are, and they're not as expensive as you'd think. Some of the popular scheduling platforms have built-in forecasting that uses historical sales data to predict labor needs. A lot of franchise systems even have preferred vendors that offer discounts. But Dave's point was that you don't need the fancy tools to start; you need the discipline to review and adjust. Luna: You know, it's funny you mention the discipline part, because that's actually one of the things I appreciate about what we do here. We don't have advertisers telling us to keep things flashy or short. We can take the time to get into the weeds on something like labor scheduling. Lucas: Exactly. And that's why we keep the show ad-free. If these conversations have moved your work forward in some small way, you can support that choice. The link is buy me a coffee dot com slash fexingo. No pressure, just a way to keep this going for people who find it useful. Luna: Yeah, we really appreciate those who do. It's a simple way to make sure we can keep these conversations deep and practical. Lucas: So back to Dave. After six months, his labor cost was down eight percent, but he noticed something unexpected: his turnover rate dropped too. He thinks it's because the schedule was more predictable, so employees could plan their lives. That's a huge side benefit. Luna: That makes sense. People stay when they feel respected, and a fair, predictable schedule is a big part of that. What's the one thing you'd tell a franchisee who wants to start this tomorrow? Lucas: Start with your last eight weeks of sales data, broken down by day and hour. Find the average sales per half-hour and plot them on a simple chart. You'll immediately see the peaks and valleys. Lucas: Then, for each shift, estimate what your ideal sales per labor hour should be—your franchise system probably has a benchmark. Compare that to what you're actually doing, and you'll spot the gaps. Luna: And then what? How do you turn that into a schedule without feeling like you're just guessing again? Lucas: You build a simple template in a spreadsheet: for each day, you input the forecasted sales and then adjust the number of staff per hour to hit your target sales per labor hour. It's a bit of back and forth, but after a few weeks, you'll have a rhythm. Lucas: Dave said the trick is to not overthink the first draft. Just get something down and then refine it as you see real results. The goal is to be better than last week, not perfect. Luna: What about the next level? After you've mastered the basics, is there a way to take it further with predictive analytics or AI? Lucas: Sure. Some of the more advanced scheduling tools use machine learning to factor in things like weather, local events, even holidays in other countries if you're in a tourist area. Dave is actually testing a pilot where the system suggests a schedule and he just approves it. Lucas: But he's careful to say the human still has the final say. You never want to alienate your best employees just because a model says you can save a few hours. Luna: That's the balance, right? Using data to inform decisions, not to overrule common sense. What do you think is the biggest mistake franchisees make when they first try this? Lucas: They look at labor as a cost to minimize, rather than a resource to optimize. If you cut too deep, your service suffers, your team gets burned out, and you end up losing money in the long run. The goal isn't the lowest possible labor number; it's the right number for the sales you're actually generating. Luna: That's a great point. So what's next for Dave? Is he going to roll this out to his other two locations? Lucas: He already has. And he told me the first store's numbers are holding steady, which is the real test. It's not a one-time win; it's a sustainable practice. He's now looking at using the same approach to optimize his inventory ordering, but that's a conversation for another day. Luna: Definitely. Well, this has been super practical. The idea that you can start with a spreadsheet and your existing sales data is really empowering. Thanks for bringing Dave's story in, Lucas. Lucas: Anytime. The key takeaway is just start small, be consistent, and let the data guide you. I hope listeners find it as useful as I did.