Full transcript of The $30,000 Refund Nobody Caught: MachineQ’s Tom Woodbury — episode 347 of the Restaurant Technology Guys podcast, with Tom Woodbury, MachineQ. Speaker labels preserved; lightly edited for readability.
What this episode covers. Tom Woodbury of MachineQ, the IoT connectivity platform inside Comcast Business, on what restaurant sensor data is actually worth. The conversation starts with the R in ROI: managers spending 30 to 45 minutes a day walking around with a clipboard checking walk-in temperatures, and a catastrophic cooler failure costing roughly $10,000 of food. Tom covers labour reallocation, food waste, why a paper log is a liability rather than a record, how LoRaWAN deployments actually work, and what changes when the same data is digitised and compared across a fleet.
- In this transcript:
- Tom Woodbury and MachineQ
- Why Front-of-House Staff Should Not Be Doing This
- The R in ROI: Labour Reallocation
- The Paradigm Shift Operators Need to Make
- Where the Biggest Losses Actually Are
- Treating IoT as More Than Temperature Tracking
- How Sensor Technology Changed in 15 Years
- What a Good LoRaWAN Deployment Looks Like
- What to Actually Do With the Data
- Where This Goes Next
- How to Reach MachineQ
Jeremy Julian (0:01): Welcome back to the Restaurant Technology Guys podcast. I thank everyone out there for joining us. As I say, I think every single episode and my wife and children who sit outside the door of the podcast studio give me a hard time about it. I know that you guys got lots of choices. So thank you guys for hanging out this week with me because uh I’m grateful that we get to spend time each week uh on the podcast. Today is a really cool piece of technology and I’m excited to dig in uh with our guest, Tom. But Tom, before we jump into kind of what you get a chance to do professionally, Why don’t you give everybody a little bit of background? Who is Tom? Where is Tom come from? How did you get into restaurants? uh then we can talk about what you guys have been building over there.
Tom Woodbury (0:40): Thanks, Jeremy. Great to be with you today and to all of the listeners of this podcast. It’s a privilege to be here. One of my very first jobs was at 12 years old as a dishwasher in a local restaurant. And I came up the ranks. If you look at the traditional chef jacket, you’ve got all the different insignias and different. is C-U-T-T-R, came up through the ranks is my certification.
Jeremy Julian (0:51): Love it.
Tom Woodbury and MachineQ
Tom Woodbury (1:08): I worked in restaurants for years and about 15 years ago, recognized that there was an opportunity within the restaurant space to make technology more prevalent. And so I’ve been working with the fine folks of the restaurant industry for about 15 years now, figuring out ways to make their facilities more operationally efficient. Now that can be done by a variety of ways, which I’m sure we’ll talk about today, but the end goal. of what I do is to help restaurants become more profitable.
Jeremy Julian (1:41): I love that. I love that. I love I do say it on a lot of the shows that I think there’s uh I could probably be a multimillionaire and in another life if I if I had a therapy group for for extra strong people trying to get out, you know, because there’s so many of us, but I do believe in now all of my children, all three of my adult children have worked in restaurants at some point in their career. And I do believe it makes us a better society because uh at the end of the day, they are a lot of times where people go to celebrate, where people go to mourn, is in restaurants. And so the fact that they are such a vital part of our community. So talk to me a little bit about, because you gave us some really broad strokes there, Tom, of kind of making restaurants more efficient. Do you stand behind them with a cattle prod, just telling them to move faster? Obviously that’s not the case, but that’s a piece of technology. Are you creating dishwashers to make stuff faster? I guess talk me through, what does that look like for restaurants because there is a ton of tech within the restaurant brand. there’s a lot of things that even the last guest that I had on there’s she works in a company that makes oil management and fryer oil management restaurant technologies incorporated. Like that’s piece of technology and now being able to get IOT to be able to know when was the last time that got but I guess at a high level, where have you guys dug in and where where have you seen the biggest biggest penetration short term?
Why Front-of-House Staff Should Not Be Doing This
Tom Woodbury (3:02): That’s a great question, Jeremy. So, and by the way, RTI, they’ve got a great product. Not to shout out uh somebody, but uh there’s a lot of IoT that’s included in that solution. So IoT, Internet of Things. There’s all this equipment that exists in your restaurant. And Comcast Business has a brand called MachineQ. MachineQ is the Internet of Things connectivity platform. that restaurants use to track various things going on inside the restaurant. The goal is to eliminate and automate as many of the mundane tasks that a store manager or restaurant manager could be doing as part of their ongoing day. For example, uh the FDA has guidance that you should take temperature of your walk-in cooler, your reach-in cooler, your freezers. uh periodically throughout the day. Most restaurants do that at the start of every meal period or during every meal period. There’s no reason you can’t automate that. That is a mundane task that for the price of a single sensor and the network to support it, you can automate a task that most managers are spending 30 to 45 minutes a day doing. That 30 to 45 minutes a day then allows them to go and better take care of customers to make sure that the front
Jeremy Julian (4:03): Mm-hmm.
Tom Woodbury (4:23): front of house staff is trained to really do all the things that help ensure a better customer experience. But it starts with that sensor, that sensor that tells you what the temperature is every 15 minutes, which alerts if there’s a problem that’s going on in your restaurant that allows you to know, oh my gosh, my walk-in cooler is currently at 50 degrees and it’s been at over 50 degrees for 30 minutes. I probably had to go look over there and see what’s going on. Again, Automating those tasks that you really don’t need a human to do is the key way to promote operational efficiency.
Jeremy Julian (5:01): Yeah. And, and I guess for our listeners out there, Tom, that haven’t even considered this, because again, I’m one of those early adopter people. When you look at the adoption curves, I’ve got a, I’ve got a refrigerator that’s got a tablet on the front of it and I can look inside of it at my house. I’m the guy that my, my, my friends will come over. All of my lights automated automatically turn on at certain times and turn off at certain times. So I’m one of those guys that’s super early adopter on the residential side, but I think that there’s this misnomer that restaurants are so far behind and retail so far behind. But what I continue to find when I talk to people like you and the investments that are going into that is a lot of that same technology that might have been commercialized for residential is now moving to the enterprise level because the savings are that much more significant. The investment um opportunities are that much more um evident. And really the ROI point is It’s not just cool that I can do, you know, kind of the clapper for my bed and turn off my lights. It’s like, it’s, it’s real big savings that happens. So I’d love for you to kind of, guess, educate our listeners that haven’t really looked into this and say, where are you? Are you seeing it? Is everybody kind of talking about it? Is it, you know, the pressures to make money in restaurants are there across the board. Energy costs continue to increase, cost of labor continues to increase, food costs continue to increase. So we’ve got to be really efficient. So I’d love for you to kind of talk about where that investment’s at. um across the board as you’re talking to different people out there.
The R in ROI: Labour Reallocation
Tom Woodbury (6:28): So let’s talk about the first part of ROI, that’s the return, right? How does any money I invest into an IoT platform get returned to me as a restaurant owner or uh operator? So there’s a number of ways that we see the restaurant industry reduce their overall uh costs, thus creating a return. Number one is that you mentioned the time. 45 minutes a day on average is completely limited. It’s a task that that manager no longer has to do. uh You don’t necessarily see that as hard cost savings, because you’re not going to cut the manager’s salary by 45 minutes a day. But that is 45 minutes that can then be reallocated to go out and drive customer satisfaction, which does have return. Happier customers return more frequently, happier customers spend more money. The second area where we see that R in ROI, where we see that return, is in food waste reduction. First off, let’s talk about what happens if you have a catastrophic failure of your walk-in cooler and you have to throw every piece of food in that cooler out. On average, that’s about $10,000. Assume that your walk-in cooler fails once every five years, either because of mechanical, because of power, because of a door just being left open. That ends up being real savings. That’s about $2,000 a year in food waste. Not to mention the cost of replenishing the walk-in cooler, the time it takes to replenish the walk-in cooler, the downtime that your restaurant experiences, and the customer dissatisfaction that comes from not having food in your restaurant. And then finally, you mentioned energy. And this is something that blew me away. If you can tune your walk-in cooler to operate at food safe temperatures, if you go from let’s say 36 degrees Fahrenheit to 38 degrees Fahrenheit, on average, that’s gonna cut your cost of utilities for that individual device by about 9%. So you’re seeing energy reduction, you’re seeing food waste reduction, you’re seeing uh labor reallocation is how you drive that return.
Jeremy Julian (8:29): Wow. That’s incredible. I hadn’t even thought about just that small differential. I think, again, as you guys continue to dig into it, you see these values and it ends up being hard savings because a lot of times the idea is, oh, it’s too expensive. I can’t figure it out. But as you start to look at these things, as you stated, they end up paying for themselves. Let’s talk a little bit, Tom, about some of the other areas where you guys, guess, see opportunities as you guys are investing. We’ve got the refrigeration, but um you talked about the, I guess, the traditional way that people have done it has been a clipboard, right? Is that not how they go do these things? So digitizing that whole system, and I think it’s silly, but there’s a lot of listeners that are going to be out there going, yeah, I’m tired of carrying the clipboard around or using that cattle prod to ensure that somebody goes and does it. because not only does it need to be done for FDA standards, but then there’s the management time on top of that. Now somebody’s got to do something with those logs. They’ve got to store them somewhere to ensure that when the inspector comes in that, you know, they’ve got it there. So guess I’d love for you to kind of talk through all of those other areas that you didn’t even consider outside of the 45 minutes that you already just talked about.
The Paradigm Shift Operators Need to Make
Tom Woodbury (9:49): Well, there’s a paradigm shift that needs to happen with that clipboard. And here’s why. Traditionally, that clipboard, that paper gets put in a filing cabinet somewhere, never to be seen again. And then a period of time later, sometimes 90 days, sometimes 90 years, it feels like, uh someone will come back and clean all those files out of that clipboard and throw them away. And nothing gets done with them. The sole purpose of those files, those paper copies, is to satisfy a health inspector if and when they show up at the store. That’s it. But by taking that data, using that data, comparing that data, you’re able to get a lot of insights that you wouldn’t get any other way. For example, you can identify, okay, which of my walk-in cooler brands is the most efficient? If I’m looking at buying a new walk-in cooler, I have hard data that now tells me which of these do the best job. Which of these coolers is going to perform the best? Which of these coolers is going to have the longest meantime between failure?
Jeremy Julian (10:39): didn’t even think about that.
Tom Woodbury (10:47): based on what I’ve seen in my restaurant. I can extrapolate that data from a digital system where I can’t do that from a paper system. And then the real risk is, again, when it comes to customer risk, right? You want to make sure your customers are coming to your restaurant, getting safe, reliable food. If there’s data… on a clipboard, you don’t necessarily know if that food is safe and reliable. You don’t know that it’s been stored at an appropriate temperature. Not that it happens in the people that listen to this podcast, not in their stores, but I have seen other restaurants where the clipboard, the manager has filled it out all in the same pen, all in the exact same handwriting and always 38 degrees. In fact, this same manager can see the future because they know a week from now, that temperature is also going to be 38 degrees. Now, pardon the levity, but a lot of times that data isn’t as reliable as data that’s captured on an IoT device, an Internet of Things device in the restaurant. It provides a much higher level of reliability, which also, heaven forbid, if you ever have to prove legally that you’ve stored food at the safe temperature, If they put a manager on the stand and they ask, hey, have you ever written the wrong number in here? Have you ever forgotten to take a reading and went back and added the temperature? And they say, yes, suddenly every single paper log that you have in your restaurant is now suspect, right? But with an IoT device, you can’t fake it. It’s always there, it’s always on, it’s always recording. So you have the ultimate in protection for your store. Again, heaven forbid you ever get called into. due to an outbreak, due to a food safety outbreak.
Jeremy Julian (12:42): Yeah, no, and I want to dig in a little bit to the food safety side of things. But one of the other things that I know, at least for me, because I too grew up in the restaurant, 14 years old was my first job. rode my bike to go sling hot dogs at the local park for the adult men’s softball league. And then that turned into a sandwich job and the rest is history. But with that, I know that when I was working, the refrigeration would, I mean, even in my house, the kids will go slam the freezer and it. will get stuck and it won’t close all the way. I know they’ll be doing inventory and they’ll leave the door open and your temperature might rise. They’ll be receiving inventory of the back door, know, the walk-in cooler, walk-in freezer, and the temperature will rise, ultimately causing potential risk there. I guess I’d love for you to dig a little bit deeper into the behavioral times because that paper log is, you gotta check it pre-shift. But if you checked it at 11 before your lunch rush and you don’t check it again until four, and the door has been open that entire time. Now what happens? What happens to the food? What happens to the food safety? So I’d love for you to talk a little bit about that, Tom, and really the spoilage side, because it’s just a little freezer burn, but now you’re delivering bad quality and all of those kinds of things back to the guests. In my own house, no big deal, because it’s my kids that are eating those things.
Where the Biggest Losses Actually Are
Tom Woodbury (13:56): Yeah! Well, if you’ve got, you what are the biggest risks in any restaurant or things like leafy green, you know, cut leafy greens. Not only do they go bad the quickest if you have a temperature issue, but they’re also the one that’s most likely to support pathogen growth. And if you’ve got a refrigerator that’s been open for four hours, uh that’s going to open the door, pardon the pun, to food safety issues, to pathogen growth, which can cause… guests to get sick. at the end of it, that’s what we’re trying to prevent, right? We want people to come to our restaurant, have a confidence that they’re going to get a safe, delicious meal. And if someone performing a key drop at three in the morning when it’s unstaffed, opens the door, leaves it open for four hours while they’re bringing food in and out of the cooler, you have no way of knowing that. Because there’s no one there on site when that food is being delivered while that door is being propped open. So you could come in the next day, and you could have food that’s been stored unsafe for an extended period of time, and you’d have no way of knowing, which just elevates that risk.
Jeremy Julian (15:08): Yep, well, and I know quite a few brands that have had dilemmas with this and there’s brands in my career that have ultimately closed because of this challenge. it’s awful to say, but at the end of the day, as consumers, we all go to restaurants expecting them to have abided by the rules that the FDA put out about these things. And whether they do or they don’t, this is where the automation and the efficiency. Have you guys gone beyond kind of the walk-in and the IoT side of things? Because I know even at the… at the line at the cold case at the line. Have you guys gone there as well, Tom? I know I knew the back back of the house, but I didn’t know kind of the front of the house at the line side the refrigeration that’s up there. Have you guys started managing those things as well?
Tom Woodbury (15:47): We have. In fact, we’ve got clients that have sensors in every piece of refrigerated equipment they have, refrigerated or frozen equipment they have in their store. Everything from make lines, make tables. We even have a client that has a machine that dispenses a uh predetermined amount of milk or cream into coffee. And we figured out a way to track temperature inside that device as well. and it’s completely eliminated any manager responsibility for daily temperature taking. Now they get a dashboard that they pull up as part of their everyday check and they go, everything’s good. uh Time to move on and do else I can do to help make customers happy. It’s important to note that, especially with machine queue, and this is one of the things that sets us apart. We’re part of Comcast business, as I mentioned previously. So we look at
Jeremy Julian (16:16): That’s amazing.
Treating IoT as More Than Temperature Tracking
Tom Woodbury (16:45): an IoT implementation, not just as, hey, let’s track temperature. But we look at this as a complete uh enterprise level IoT implementation. So temperature is just the first thing that we do to help automate and create operational efficiency inside a restaurant. So we may start with temperature, but then we can go onto other use cases as well. Things like monitoring the the ice maker uh many of our customers ice is a very critical part of what they do and how they make their drinks and Not having enough ice not having the right ice uh Is a huge problem and so we’ll track that we’ve got another cost customer that found that they were having their uh Their trash empty twice a week we put sensors IOT sensors on their dumpster and they found out that at no point on with that trash being entered, did they ever exceed 70 % full on their trash? So they were able to move from from twice a week to once or three times every two weeks, which might not seem like much. But when you start adding up all these little micro improvements that you can automate in your restaurant, suddenly, you’ve got real savings and it might be $10 a month here and $50 a month there or $100 a month there or or even $500 a month here and there, but all that money adds up to make a much more profitable enterprise.
Jeremy Julian (18:17): Yeah. And I think across the board, everybody, especially in today’s day and age, we’re recording this in May of 2026, like, you know, cost savings for every dollar you save is another $10 you don’t have to do in the top line sales. Because at the end of the day, you know, all of us are working on, you know, high single digits, low, you know, low double digits margins. So for every dollar saved, it’s $10 worth of sales you don’t have to have. So it’s a pretty significant, significant opportunity to be able to do this. remember really early on, Tom, and I’d love to talk a little bit about before I do want to get into the network and kind of how you guys manage the network. But I remember super early on, everybody wanted to throw these devices out. And they were not nearly as reliable. They failed more often than they you know, they there were a lot of management. So I guess I’d love for you to kind of catch us up 10 or 15 years on to when IoT really started in these environments to where they are now. from a battery life perspective, how often are you needing to replace them? How often are needing to maintain them? Because whether it’s the thing on the trash dumpster, or it’s in the refrigeration, or it’s managing temperature in the back banquet room that you have air conditioned all summer long, but nobody’s had a banquet in there in six weeks, across the board. But if the sensor dies and it becomes as much of a headache to have to manage the sensor as it does savings, then it’s less worth it from an ROI perspective. So I’d love for you to talk a little bit about that.
How Sensor Technology Changed in 15 Years
Tom Woodbury (19:41): Oh, you’re absolutely right. So 15 years ago, our options for IoT sensors were Wi-Fi, Bluetooth, and Zigbee. Each of those have their own uh pros and cons. I’ll talk in just kind of broad strokes, but I will tell you that those are no longer considered a best practice in the restaurant space. And the reason being is for all the problems you pointed out. uh You might have to replace your battery every six to 12 months if you were lucky. There were issues with reliability of signal propagation inside a restaurant, particularly where you’ve got uh walk-in coolers that are nested inside walk-in or walk-in freezers nested inside walk-in coolers. All of those things created huge reliability issues. In fact, I sat down, this was about 10 years ago. with an individual that was an early adopter of IoT technology. And his comment to me was, if I’m lucky, at any point in time, I’ll have 75 % of my IoT sensors reporting in. Now, yes, yeah.
Jeremy Julian (20:48): I remember these conversations with people because I remember early days going, Hey, this looks amazing. And then the actual, you know, as our CTO likes to say, looks great on a whiteboard, but then when it gets into real life use, you run out of these opportunities. So sorry, I’ll let you catch us up, but I just, think it’s so true that anybody that’s listening to this, this, um, episode, listen to where it is today, not where they might have seen it 10 or 15 years ago. So I’ll let you keep going.
Tom Woodbury (21:15): It’s funny because I actually spoke with the VP of IT for another large chain the other day and he said, but my CIO won’t touch IoT because he tried it before. Michael, how long ago did he try it? About five years ago. Well, there’s your problem right there. There is a protocol that has rapidly become the best practice in food service space. It’s an open standard called LoRaWAN. uh It came out of Europe as a way to track the uh meters. So power metering, gas metering at your home, where they could put a single access point and it would cover a very large area. So some enterprising people realized that, that’s a great way, that would be a great way to implement IoT in the restaurant. So all those problems we talked about earlier, six month battery life, not. being able to get over 75 % of your sensors reporting in at any given time, those are gone, those are gone away. We’re talking battery life of up to 10 years between battery changes. We’re talking reporting in at 99.99%. In fact, we just finished a pilot and are now rolling out in a very large chain. And their requirement was we need 99 % of the sensors reporting in at any given time. And they’re like.
Jeremy Julian (22:37): Okay.
Tom Woodbury (22:40): That’s not a problem. can add two nines after that and still hit your metric. So those problems that used to exist in IoT have been eliminated with LoRaWAN. And all that does is that ultimately it reduces cost in managing the system and makes the system much more effective at supporting your enterprise. So with LoRaWAN, it’s become that cure, that panacea, if you will. uh with IoT in the restaurant space.
Jeremy Julian (23:12): Thank you for sharing that and again, I I recall talking to people 10 or 15 years ago and it was like this is great and you’re gonna have to replace it every six months so it’s like you’re on this constant cycle of uh you know um of having to continue to maintain it it’s But I’ll give you the sensors for free. It’s like well, but yeah, you’re gonna sell me batteries for you know, it’s it’s the Gillette, know, you’re gonna buy give me the razor the razor but the razor blades you’re having to pay for and so uh Talk to me a little bit about the network Tom, because this is obviously a division of a network company that delivers network to these businesses. You’ve talked about this new protocol, but how does it sit on top of, guess, you know, and manage all of these things? Because um again, as everything is connected, as more and more devices are getting IoT even built into them, dishwashers and washing machines and ovens and stoves and all of this. I can only imagine that the traffic continues to get more and more congested. so ensuring that you’ve got your four or five, nine uptime is critical to making sure not only is the network up and running, but that it can deal with the traffic that you guys have. I guess I’d love for you to talk a little bit about how much of an impact to the network does it have? If any, is it a separate network? Is it the same network? Is it right on top? And what does that look like for people?
What a Good LoRaWAN Deployment Looks Like
Tom Woodbury (24:27): That’s actually a easy question to answer. A good LoRaWAN network is going to use less than half a gig of data in a month. And that’s with hundreds of sensors being installed at the enterprise. It’s a very small packet size. And so the amount of data required to run the network is next to nothing. In fact, if you download a single song on Spotify, uh in a day, that’s more data than your network will use for that same day for IoT. It’s built with enterprise management in mind. It’s built with efficiency in mind. Therefore all is something that when we sit down with network managers and we tell them, okay, here’s the requirements, it’s going to be about a half a gig a month. It’s going to require this. It’s going to require that. They look at us like, why are you even coming to me with this? That is such a small amount of data for us to even worry about that. uh It’s a it’s a non-issue stamp it with approve move on the one other question we get a lot Jeremy and this is This is important is what about security? There was an issue a few years ago where an HVAC repairman plugged the USB drive into an air conditioner in a very large restaurant or not Sorry a very large retail chain that had malware on the USB which then worked its way through the network and got into their PCI, know, their payment card data to the point that they had to pay them hundreds of millions of dollars in settlement because an HVAC repairman plugged the USB in. uh Because each of those, because it had an IP address, it existed on the network. This is the beauty of Loroana and other reason why restaurants are making this their preferred protocol for IoT. The sensors themselves do not have an IP address. The sensors themselves, heaven forbid, if they’re ever compromised, each individual sensor has its own 128-bit encryption key. So if it’s ever compromised, you’re able to capture one point of data. uh Furthermore, there’s the access point where that data travels wirelessly from the sensor to the gateway, the access point. That data is encrypted, and then the data from the access point to… the public cloud is also encrypted. So it’s like if you took a car, changed the license plate on it, and then took that car and drove it into the back of a box truck to transport that car, number one, you don’t know what the license plate is, because if that’s been encrypted, then you put another layer of encryption around it in the form of a box truck to make sure that any data that travels to the public cloud is double encrypted. uh It makes it nearly impossible to take that data and do anything meaningful with it. And even if you were able to somehow figure out those two different layers of encryption, congratulations, you just found out the walk-in cooler at your store is at 38 degrees.
Jeremy Julian (27:32): Yeah. And what are you going to do with it? I guess in theory you could hack it to turn it up to 50 degrees and spoil the food. what else are you going to do there? Well, and Tom, you said it earlier, but the data is awesome, but I need to be able to make it actionable. So I’d love for you to talk about how do you make it actionable both at the store level and then at the enterprise level to be able to do, because we’re producing more data today than we’ve ever, ever have in the history of restaurants. So Being able to do something with the data to be able to solve business challenges is really why we exist, not just to go generate a bunch of data. And so I’d love for you to talk a little bit about how does that get up to the enterprise and what do we do with it as well as what happens within the store to ensure that they close that walk-in or that they go figure out what’s going on with the freezer or the walk-in cooler or whatnot.
What to Actually Do With the Data
Tom Woodbury (28:20): Well, that’s a great question that’s going to take a lot more than 30 minutes to cover in detail. So we’ll cover the very high level overview. uh What we’ll do is we’ll trigger actions to be completed at the store level. And that can be triggered a variety of ways. It could be an email to the store manager, hey, you’re walking coolers at 38 degrees, uh go shut the door. uh Hey, uh your fryer is currently… the total polar materials in your fryer is 24, you should probably change the oil. We even have some clients who will lock out the ability, they’ll warn you, they’ll warn you, they’ll warn you in the case of the fryer to do it, to do it, to do it, and if they haven’t done it by a certain period of time, they’ll actually shut off that piece of equipment so it can no longer operate. So. at a high level, and those are just some examples, but at a high level, it comes down to triggering alerts that go to the store manager or the staff at the store. It goes to triggering workflows that need to happen. uh Another example, this is one of my favorite ones. This one blew my mind. We had a client who has a rapid oven at their restaurant, and every so often, that oven would throw an error code. So what would happen is that error code, the store manager would go and get it. That store manager would go, oh, I don’t know what this error code is. So they would call it into their service desk. The service desk would then dispatch a technician. The technician would then go out and look at it and go, oh, I kid you not, the easiest way to fix this, this error code means you need to turn your oven off and turn it back on again. So they were paying hundreds of dollars. to send not only the downtime of the equipment, but sending somebody out to go flip a switch, unplug it, plug it back in. So some things we’ve done is we’ve automated that. So one of the first things that happens if there’s ever a uh trigger that says, hey, this piece of equipment is not working, then we’ll automatically trigger a power cycle as well. So some of the stuff we can automate in the case of the power cycle of the oven.
Jeremy Julian (30:20): Yeah.
Tom Woodbury (30:42): we will, other things we will trigger an alert. Now the cool thing about this, and I know AI is everywhere. It feels like you go to a trade show, a restaurant trade show, it’s a noun, it’s a verb, and it’s artificial intelligence. But by overlaying AI, by using and feeding this data into an AI engine, you have the ability to, in many cases, automate that. those responses. If it won’t be solved by a power cycling, you could automate the, use your AI engine to uh send recommendations on how to fix it to the store. You could make, you can send out a technician directly to the store without the store manager even knowing there’s a problem. You know, all this can be done. based on the quality of the data. that’s where this, if you could summarize why IoT, above and beyond all the great benefits we talked about before, your AI experience as a restaurant is only as good as the data that you put into the AI system. And… uh
Jeremy Julian (31:56): If I had, I so want to take that clip and I’m going to put it everywhere because it’s amazing how many of our customers are like, well, yeah, I was going to solve all of it. it’s not until you can get the proper data in here, which the thing that I love to remind people about this is you said it about this oven, this rapid cook oven that just needed to be reset. How many times could we preventatively have solved this problem or known that the fryer needed to get done? So it’s not how happening at the middle of the shift, but it’s getting done on the slow days or whatever those things might be. so the idea of preventatively fixing the HVAC, preventatively fixing the fryer, preventatively doing these things prior to it being, you don’t want your oven to die. your Marie Callender’s and you’re known for your pies right before Thanksgiving, you need to make sure that that’s your moneymaker. You’ve got to make sure that you’ve got that ready to go on the days that you’re there. knowing that there’s a potential challenge of potentially having it maintained real time without it being just somebody on a clipboard that should have called in the ticket and then they forgot because somebody called out sick and now they never got to doing that. Now having that preventative care happening automatically is, in my opinion, where the future is and it sounds like you guys are already there.
Tom Woodbury (33:15): uh It’s you nailed it. You absolutely nailed it. And there are so many things that indicate you’re about to have a problem in a restaurant that even the most observant manager isn’t going to see. A manager isn’t going to be able to see that their electric uh heating element is suddenly pulling a lot more energy than it has in the past. An indication, leading indicator of failure. That’s not something that anybody’s going to notice. But the right IoT device will. So using your example, if my oven is suddenly drawing significantly more power than it has in the past, that could trigger an alert, trigger a service call, trigger an element being replaced, a heating element being replaced, and I as a manager don’t even know that it’s a problem. Therefore, I’m reducing my equipment downtime, I’m reducing the impact on the customer, I’m reducing the impact on top line revenue, because I can’t sell pies because my oven’s down. uh in a way that allows me to run a much more profitable restaurant.
Jeremy Julian (34:18): I love it. Where are we going, Tom? guess, me a little look into the future. You get the chance to sit at the forefront of these things. uh Many of our listeners probably have none of these devices or are at the kind of precipice and maybe have a little bit of IOT within their brand, but where is it going? know, give me a little bit of a glimpse into the future. Where do you think that this industry and the ability to track and help keep guests safe, keep restaurants running profitably? ah Where do you see the biggest investment time and energy and money going in the next, know, I guess five to 10 years as, uh as you sit and look at it.
Where This Goes Next
Tom Woodbury (34:54): Yeah, that’s a great question. And I’m going to shift gears a little bit on this because where I think, number one, think IoT is going to be the critical path for profitability for restaurants over the next five years. Also, I think that restaurants have to be very careful about the way that they implement AI. I was at a show recently and a CIO of a large company said, listen, If you’re using AI to eliminate the customer interaction, you’re risking the differentiation of your restaurant versus somebody else. So it’s important to use the right type of AI. For example, uh you have cameras in your restaurant and those cameras are always on.
Jeremy Julian (35:35): 100%.
Tom Woodbury (35:49): But there’s not always somebody in the back room sitting here watching every camera looking for something, looking to see how long the queue is outside of your drive-in. They’re not looking to see, do I have a risk of a slip and fall somewhere in the store? They’re not watching to make sure that the person at the cash register is actually taking the same amount of cash as listed on the receipt. But by applying an AI overlay, we call it vision intelligence, by overlaying that, with IoT data, you’re able to get a solid snapshot of what’s truly going on in your store. Let me give you an example. And this blew me over. We have a partner that does vision intelligence. And they looked at how often customers were getting cash refunds, but there was no customer present in the store when that cash refund was applied. This company has 27,000 employees. In that analysis, they found four employees that were going back after the customer left the store, refunding the ticket, refunding it in cash. There was no customer there, so you know where that money was going. It wasn’t going to a customer, it was going to the employee. They found four people. That one example saved that store $30,000. in cash refunds that had been going out that were fraudulent refunds. So the point being is, in the future, smart restaurants are going to apply IoT. They’re going to apply IoT to so their managers and an organization can operate as efficiently as possible. They’re going to apply AI in a way that is going to allow them to track all those things that are currently going on. and do it in a way that will allow the staff to be as responsive to customer needs as possible.
Jeremy Julian (37:51): Yeah, and I love that thought because I do think we all need to be thinking about AI augmenting us so that we can do what we do best. Is it the best use of somebody’s time to go walk with a clipboard, look at a number in the walk-in and write 38 on it or 36 on it or 37 on it? Or is it to engage with that guest and then have the critical thinking skills to be able to go solve that problem if it’s at 40 degrees? And what do I do now? That’s where humans are really in the loop and the AI is just helping augment and make it faster, better, smarter. So Tom, thank you so much for what you guys do. I genuinely love this stuff. I feel like we could sit and talk all day about where it’s going and the future. How do people get in touch? What can they expect from you and your team if they do engage?
How to Reach MachineQ
Tom Woodbury (38:39): So machineq.com is our website. Again, we’re part of Comcast business. Go to the website and you can track us there. I’ll even give my email address, thomas underscore woodbury at comcast.com. If you have any questions, I’m happy to get you in touch with the right folks. uh Generally what we’ll do is we’ll evaluate where your restaurant is today. We’ll evaluate what where the weaknesses are and where IoT can help you specifically. uh As they say, uh a proof of concept is worth a thousand expert opinions. So we may do a small proof of concept to validate that what we think you’ll save is actually what you’ll save. And in our experience, it’s honestly, it’s usually more. We try to keep our uh pilot and proof of concept projections a little bit on the conservative side because we want to make sure that we’re we’re delivering and in almost all cases, there’s more value than we originally uh come up with. So we’ll do that. We’ll sit down, we’ll chat with you and we’ll figure out how to make your restaurant the most efficient possible. But again, reach out to me anytime and I’m happy to arrange that.
Jeremy Julian (39:54): Well, I appreciate that. And I had a former guest say, proof of value, not even a proof of concept of proof of value. And I was like, I’m going to steal that. And I’m going to be using that because I do love that idea that says it’s a proof of value. Let me prove to you the value and then you can sign up for it. One last thing on that point, and I’m pretty certain I know the answer to this, but you don’t have to take and bite the elephant all in one bite. It’s little bits at a time, right? You can take little pieces of the solution and continue to grow with it as time goes on. don’t have to…
Tom Woodbury (40:04): I love it.
Jeremy Julian (40:24): outfit every single device in your environment at day one, is that correct?
Tom Woodbury (40:28): Yeah, correct. And your analogy is spot on. Let’s find maybe just one use case or two or three use cases that are going to create the most value right out of the gate. And then once we’ve got that hero use case, can then that covers the cost of the network, any infrastructure that has to be brought in, any sort of expenses that may happen can be absorbed in that initial first foray. And then everything else becomes much cheaper to implement because you’ve got the network, you’ve got the infrastructure to support it. So we can add on as we move along.
Jeremy Julian (41:04): Love that. Tom, thank you so much for coming on. Thank you for educating me. Thank you for educating our listeners. I love what you guys are doing and it’s always so cool to kind of see where the technology was and where it’s at and then really where it’s going. So to our listeners guys, if you haven’t already subscribed, please do so. Favorite podcast player, YouTube. I also have a monthly newsletter that goes out. Tom, thank you for your time and to our listeners, make it a great day.
