Franchise QB

Episode 73: Matt Forbush- Founder and CEO, Zignyl

• Mike Halpern • Season 1 • Episode 73

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In this episode of the Franchise QB Podcast, host Mike Halpern speaks with Matt Forbush, founder and CEO of Zignyl, about his journey in franchising and the innovative solutions his company provides to enhance business operations. 

They discuss the challenges faced by franchise owners, the importance of employee engagement, and how Zignyl's AI-driven platform helps streamline decision-making and improve business outcomes. 

The conversation also touches on the future of Zignyl and its commitment to evolving with technology to better serve the franchise community.

Takeaways

-Zignyl was created to address the chaos in labor management
-Employee engagement is crucial for driving business success
-AI technology can enhance operational efficiency in franchises
-Setting clear expectations helps employees perform better
-Incentive structures can significantly boost sales
-Zignyl aggregates data to provide actionable insights
-The platform is designed to be user-friendly and easy to implement
-Future innovations will focus on employee benefits and operational support
-Zignyl aims to expand beyond the QSR segment to other industries

https://zignyl.com/

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Mike Halpern, CAFC
mike@franchiseqb.com

This is the Franchise QB Podcast, where we empower entrepreneurs to win big in franchising. We huddle up weekly to educate our audience about the most successful small business model ever created. Franchise it! Welcome to the Franchise QB podcast. I'm your host, Mike Halpern, a 20-year industry veteran and entrepreneur. My mission is for listeners to achieve their American dreams of creating wealth and independence through franchise ownership. Every week we speak with franchisees, franchisors or vendors that support the industry. Thank you for joining us and let's get started. Joining us in the huddle today is Matt Forbush, founder and CEO of Zignyl. Welcome to the show, Hey Mike, thanks for having me on. We're excited to be here with you. Absolutely. Great to have you on the show. So you've spent 15 plus years operating multiple household name brand QSR franchises like Auntie Anne's and Cinnabon. I have to admit, I literally grew up on those brands in the nineties and early two thousands. and you recognize the struggle. and the chaos of labor costs, shifting forecasts, employee engagement. And your response was simple and groundbreaking. Don't read a chart, get an answer. So you took action. You didn't just sit around and say, we have a problem. You went ahead and solved it. So you built Zignyl, which is a digital platform that transforms how business owners and managers make decisions without burying them in endless charts. So looking forward to getting into the model. Before we do that, I'd for you to share a little bit about your background with the audience. So can you tell us a little bit about yourself, Matt? Yeah. So I, from a business perspective, I, they've done nothing but franchising my whole professional career. I played football, Clemson when I was there, I actually left practice and went work the Firehouse Subs down the street. My brother was into franchising, worked at the UPS, worked for him in high school. And, my first job out of college was working the drive through at Chick-fil-A. Always, you know, I wanted to get into franchising. That was the safe way to be my own, way to be your own entrepreneur or business owner. And through family ties got into Annie Anne's. As you mentioned, built Zignyl first and foremost for my stores. I went from one to three stores. This was five years, five plus years ago. As we began to scale, we, needed to be able to. get the intelligence from when I wasn't spending 50, 60, 70 hours in a store, because as I stepped away, I lost the minor details of what was going on there. So we a platform to start recording things digitally. And since, have been able to scale our company like crazy. I'm now silent in that group, but we're 45 locations. We did over $30 million last year, I believe, largely on the back of Zignyl and the way we're able to have a genuine understanding and insight of what's going on at the store, as well as engaged employees. Sometimes I ask about me personally, I've got triplet boys that are, they just actually today is their 10th birthday. happy birthday boys. Yeah. And then a baby girl who's a seven year old girl who's just as much as a handful of all three of them put together. That's awesome. I'd to talk more about, like to race cars, like we race cars professionally as well. that's cool. Sounds like you're busy guy, right? Between running the company and the four kids, you're, probably pretty busy. So, That's interesting comment you made about like when you personally went from one store to two store to three stores like that isn't talked about a lot, but there's like this exponential increase in Stuff that you have to manage and you don't you're not in the minutia of the details like you had been So I can see why you know, it's kind of neat that you created this platform based on your own experience Which I think is obviously very credible. So tell us a little bit for anyone that's listening. That's not familiar with your company. What is Zignyl? Yeah, so mean, it's a platform, now it's an AI platform that supports every level of the business, providing clarity on what's expected at the store. So task management at the store level, everything from there to sales and labor expectations that give you some genuine insights to the stores that ultimately the 90,000 foot is to to improve human behaviors to to out to increase business outcomes. What that means is all these insights are ultimately leading to setting goals for employees, clear expectations. And then from there on the back end, we can either see, did we achieve those goals? And if so, we're going to reward the employees with some automated reward systems, or if they feel short, there's some really great coaching opportunities to help them improve next time around. Okay. Very cool. So, I mean, you obviously like had the decision to make when you realized there was a gap in technology and you just went ahead and did it. So why did you? like decide that you're going to create this thing on your own? Well, quite honestly, I got tired of spreadsheets and going, you know, cross-eyed messing with spreadsheets. I built it and I enjoyed the brick and mortar component of the industry. However, I've always been kind of a creative man too and wanted to build a platform like this. I built it for my store first and foremost, made sure it worked as expected there and then kind of did a soft rollout with some other very close friends in the system. And then a couple of years ago, we decided to commercialize it. So kind of stripped it down, rebuilt it and took it to market. Okay. So, I I'd imagine there's other technology out there that does similar tasks. So like what problem are you solving in the food and beverage industry specifically? Yeah. So the biggest, I think, differentiator for us, I think there's two effectively, is there are a lot of really great, quite honestly, niche products out there, really tight on forecasting or scheduling or operational task, things of that nature. I'm really big on aggregating all that data and taking that siloed data and bringing it together to drive genuine insights for the business. And then we're also very heavily focused on the employee engagement component. We don't worry about processing payroll. do integrations for that or reports. We're really big on taking the information we've derived and passing that to the employees, again, to help either to drive engagement through either coaching or rewards. Yeah. Okay. Appreciate that. So tell us a little bit more about the solution. Like what makes Zignyl a one-stop shop? You said it's really important for it to be an aggregator. So how does this like really help owners and managers, kind of the key leaders that are at the unit level? Yeah, I think from that perspective we are big about again aggregating all the information so that this forecast leads into the schedule so you have to have an accurate forecast to lead into the schedule and you have to schedule accurately so you can then, so you know the worst thing you can do is pay out too many incentives to too many employees for example right so it all stacks on top of each other and if you're bringing these things in together from fragment and components it just makes it harder at every level. So yeah, we are big on, we have an in-house solution that we call either Zignyl management or actually transitioning that name to Zignyl Core, which has all of the core scheduling and forecasting functions. But I think what we really do a good job is bringing it all together and pumping it into our AI model that is what's helping bring the insights out. I could see how you can have a more effective cost per labor hour when you're like maximizing efficiencies with you know, just having fewer people that are able to handle the same amount of tasks. And maybe you can't see that when you're in the weeds, but when you're using this tool, it's like, wait a second, there's a better way to do this. Yeah, it's kind of that hundred pennies to make a dollar thing, right? There's not three or four shifts every day you're missing, but when you're copying and pasting a schedule, for example, from week to week, as opposed to looking at the hourly for a sales forecast projections, well, maybe somebody doesn't need to come in 30 minutes before they typically do, or they need to stay 30 minutes later. So we're not, we're not understaffed when we get that last rush. Taking things like weather into account and all kinds of stuff. It's just really looking at it on a very granular detail at the store level, which from a macro level obviously adds up pretty quickly to the bottom line. Yeah. So let's talk about specifics. Like, can you share any customer success stories with us? Yeah, I think the most impactful ones are, you know, we can, we really see it lot in the Auntie Anne's and Cinnabon's with the Impulse bias when people it's not uncommon at all to see a 15 % bump in sales through the employee engagement with our incentive structures. And that is literally as simple as if we're supposed to do $3,000 for the day and we do 3,500, let's say everybody that worked that day gets an extra dollar. I won't get too deep into the psychology of it, but the bottom line is it's human nature. And if there's something in it for the report, it makes the employees feel like gives him ownership, right? Kind of trains the employee to think like an owner. And the last thing I'll say on that, the most telling component of that is, is we have all the time customers will call me and tell me that their hourly, opening hourly employee in the morning is calling back in the evening to see what sales are at. And I don't know how much more of a testament you Yeah, that's pretty good. I think every owner wants that other employees to like an owner. It's the team. It's, it's, that, that's where we see the biggest improvements. And then we got So we obviously can save money too with labor savings, things like that. But what I like to promote is we are all about making money and driving business outcomes. That's the easiest way to lower a percentage is to raise the denominator, right? So that's everything that we're about. That's at the core of everything we try to put out there. Yeah. And you mentioned that obviously this Zignyl solves pain points for owners and managers. How does it help employees? Like I like the idea. I mean, it's like the industry adage, you're going to praise your employees publicly in front of their peers and you're going to coach them privately. Tell us a little bit more about how the solution helps the employees. Yeah. So, and especially with this new, with the AI component that we're bringing in, we're really going to be able to make that more robust. You know, at its core, what we're doing is we're giving them very clear expectations. And what I like to tell people is no employee wants to do a bad job. People don't come into work and they say, Hey, I'd love to do a bad job today. They don't know how to do a good one. They don't know what's expected of them. So number one, we're setting them up for success with that. And then from there, we're able to reward them more often than not monetarily with the incentive component of it. But going forward with the AI, we'll be able to be even more proactive with them on that. So, hey Mike, you've been late your last three shifts. Maybe you should leave 20 minutes early today instead of 15, right? And really be proactive and see where their areas for opportunity are or hey, you've been on time five times in a row this week, great. And so proactively, be that mediator for lack of a better term between the employee and the employer. And that will go both ways. Sometimes the employer may need to know that there's some, we're seeing some unhappy trends amongst the employees. So AI really allows you to kind of be a neutral, genuinely neutral mediator with all the endpoints we've got together. Yeah. I want to transition right into that topic. mean, I watched the video that you sent with Zigy, which is your AI co-pilot. And the demo was really cool. Like it was just really great flowing conversation. It was intuitive. It was interactive. And the actual data that Zigy sharing with you is like really powerful. So tell us a little bit more about Zigy. Yeah. So again, Zigy is, it's a natural progression from the Zignyl platform, the all in one kind of a SaaS platform, for lack of better term. And what we have learned from there and the, learnings we've derived from our customers there. And so what we've done is we've pulled all the information together and seen all the insights our customers can get the old school way by reading through it. And now we're able to automate that and let AI take that for us. And the beautiful thing about Zigy is we are now able to aggregate through multiple platforms. So for example, we're partnering up with Paychex right now. So maybe you don't have to use our scheduling system, you can use theirs. It's still going to aggregate all that information to bring it into an AI model that again is really genuinely centered around business outcomes. And there's a lot to that as far as how it is trained and what it's trained to think through. And so per your brand, it's all driven to drive outcomes through telling the owner what they need and telling the employee what they can do to help with it as well. Yeah, and it's nice that you have those integrations because I know people that really like a product don't want to leave it just to try something new. and the fact it can be integrated into your system is really, I think, meaningful to business owners. So Matt, when a franchise owner is evaluating Zignyl compared with other solutions providers, what are some of the key takeaways you want to convey today? Yeah, we have a very, with our new AI products especially, we have a very easy implementation process where there's no real operational changes needed. You don't need to bring in a different scheduling system. You just can hook up whatever you've got. everything is centered around boosting the bottom line, right? And business outcomes, job business outcomes. And we are, I believe, at the cutting edge of the AI generation that's coming right now, the AI shift that's coming. And so I feel really good about where we are being on the leading edge of that and will continue to be so in the future. Yeah, hey, you make it easy, you show people how to make more money, and that you guys are constantly evolving. Like those are Definitely key differentiators for the brand. So what's next for a Zignyl? Yeah, we will. mean, now that we have brought all the data together, we will. It really makes it an especially with AI. can get exponentially more intelligent and more sophisticated with the answers, you know, bringing in equipment manuals, right? So we know that you have a certain equipment set at your store. We know that you're how to make a pretzel, for example, if your dough is rising a certain way, right? We can bring in tons of operational components to this as well. we're going to really expand on what we're providing the workforce, so the hourly employee, and help them take their KPIs from their job from one job to the next. We're really big in helping them, for lack of a better term, go from blue collar to white collar. So we want to provide a lot of benefits for the employees as well. And obviously at some point we will expand beyond the QSR segment to other consumer facing businesses. That's what I consider the common denominator, is if you've got a customer and employee that their interaction can drive your business outcomes. That's kind of where we live. And I think there's a lot of room beyond the QSR franchise space to expand on that. And obviously the QSR space is very complex, a lot of moving parts. So if you're able to figure that out, I would imagine that the next batch of clients or segments you go into, you've already probably solved most of those problems. So this has been really cool, Matt. Anything else you want to add to the mix before we wrap up today? It's just been a pleasure to be with you and really enjoy the conversation. Yeah, absolutely. Well, if anyone listening would like to connect with Matt and his team to learn more about Zignyl, contact me at FranchiseQB.com or on x @QBFranchiseQB. I'll get you connected. Thank you so much, Matt, for taking the time to get in the huddle today and discuss Zignyl with us. Thank you, Mike. I really enjoyed it. You got it. Thank you for listening to the Franchise QB podcast where you're at the helm of your future as a franchise owner. If you enjoyed the content, please rate the show and recommend it to anyone that might be interested in franchising. Make sure to visit franchiseqb.com to subscribe to my newsletter and for an actionable playbook to go from walk-on to legend in your new business. Follow us on Twitter @QBFranchiseQB and join us every week for a new episode. See you next time. Visit FranchiseQB.com. take the next step of your journey towards wealth, independence, and franchise ownership. And remember, when working for the man gets old, you must do something bold. Thank you for listening.