Using AI and Analytics to (Actually) Manage Labor의 전체 녹취록

Video. Head over to margin edge.com chip again. Margin edge.com chip. As always, you'll find that link in the show notes. Okay, so my guest on today's show is a guy named Will Stewart. He is the founder and CEO of a piece of software called Right Work. It's an incredibly powerful piece of software. Can't wait for you to hear more about it. Also, I think Will's background is pretty interesting. I think you're going to appreciate that. Will, welcome to the show. 2 00:03:39.000 --> 00:03:42.000 Thanks, Chip. Yep. Happy to be here. 3 00:03:42.000 --> 00:04:11.000 I'm glad to have you. I'm really excited that we met. I'm really excited to be able to have this conversation and bring this to the audience really, really quickly to start us off so we understand what we're talking about. Talk about the system, the platform, the software that you built. What is right work? What does it do? And then. And I'm going to pause you there and we're going to go back and we're going to talk about your background after that. Because I think how you got here is incredibly interesting and I think the audience would definitely appreciate it. First, start off, tell me what right Work is. 4 00:04:11.000 --> 00:04:36.000 Yeah. So at the core, Right work, we call it a labor optimization software. So we help companies, restaurants, optimize their labor spend. And so at the core, it's. It's scheduling. But we have a ton of additional modules that help companies better understand their labor and better optimize and schedule for that labor. 5 00:04:36.000 --> 00:05:56.000 So anybody listening here, I have come across this software. I am incredibly impressed by this. Yes, we are going to talk about this. The why, though, is really important. It is our labor is our single biggest line item on our P and L every single month. Ours is a people industry. We feed people, we buy from people, we employ people to serve people. Everything is people. And so we need a way to manage our people, to manage what ends up being a massive cost and treating it not as a liability, but really as the asset is. It is. So that's why I talk about labor so much. That's why I talk about managing labor, not cutting labor, but managing labor so much it's why we're having this conversation. The power of having somebody like Will on the show is not so he can tell you all about his thing, but really. And I say this, I said this to Will before we hit record, and I say this over and over. Anybody who's been listening to this show for a while knows you've heard me say this. Is that the power of having somebody like Will on the show who works with hundreds of restaurants all over the country is he gets to peek behind the curtain at a lot of different operations and he sees all the connective tissue. He sees the common threads, the common mistakes, the speed bumps that everybody hits. He can see the trends as they're coming. And I think Will's background is particularly interesting. So we'll talk a little bit about

where you were at and what led you to build this thing that you built. 6 00:05:56.000 --> 00:07:55.000 Yeah, definitely. And, and thanks for kind of some of that context. And, and before I dive into the background a little bit, I'm, I'm glad just some of the language you use there around kind of labor as an investment. And when we talk about optimizing labor, we're, we're not just talking about cutting labor. Right. I think that's kind of a preconceived thing that people get. Like we want to help make sure restaurants are, are staffed up for their, their peaks and. Yeah, just not kind of overstaffed during those. L just kind of a note there and something we want to make sure we get clear to our customers 100%. But yeah. So my background, I spent a little over five years doing data science and analytics at Starbucks. So I have a background in analytics and optimization. And while I was at Starbucks, I built a lot of the, or some of the tools that Starbucks uses to manage and optimize labor across 10,000 plus stores. So being able to kind of see labor at that scale and understand how kind of small tweaks and adjustments can have a major impact on operations. Again, not just from a cost cutting perspective, but also being able to capture some of that for, for Starbucks, it's, it's mainly the, the morning rush. Right. And how do you understand and have visibility to that? But ultimately kind of saw that whole perspective, left Starbucks to start my own company and was approached by a number of former Starbucks operators, leaders that had left Starbucks and kind of wanted some similar tools to what we had at Starbucks in terms of the sophistication and data. And so ultimately a lot of the former Starbucks, yeah, people kind of left and those were Our first customers of right work. 7 00:07:55.000 --> 00:08:48.000 So talk to me about, because again you get to peek behind the curtain. You are behind a very heavy curtain that's difficult to look behind. I talk about the Starbucks service manual, that employee manual all the time and how they set up and basically their version of like figure eights and keeping people in position. I was talking with the folks at Big Be Coffee who modeled a lot of how they build their thing based on how Starbucks did their thing. It was basically like, well, we can't do any better. So let's just try to, you know, emulate it as much as, as much as possible and improve where we need to improve. So talk to me specifically about how Starbucks thinks about managing labor, about, you know, what is again this massive line item on the P and L and also one of the biggest opportunities. Talk to me about how they approached it and I guess you could speak to it in your time there. But. But how, how did they think about it? 8 00:08:48.000 --> 00:10:25.000 Yeah, so I think one of kind of the core things and you'll see this at a number of kind of enterprise like large companies that, that hasn't really been adopted by smaller companies, but we're helping to kind of change that is the concept of kind of a bottoms up labor model where you are able to forecast by a number of different kind of sales drivers or labor drivers and then understand how that's affecting the staffing levels needed to support that demand. So when you think about Starbucks, there are obviously a ton of different concepts and based off the markets that they live in, the product and channel mix is very different. Right. So especially with the advent in the growth of mobile order and pay and some of those different channels, those have different labor needs compared to the drive thru customers. Right. And so the first thing that kind of happens is breaking apart those kind of sales groups and understanding what actual labor is required. And so that a mobile order and pay heavy store in a city gets a different kind of labor model and staffing needs compared to the drive through stores that have different peaks and valleys. So that's kind of one of the important things to understand is how the channel mix and product mix can affect the, the labor needed to, to run the store. 9 00:10:25.000 --> 00:11:04.000 Yeah, it makes sense. It seems to me like this does translate to independence where we look at what the needs are for different day parts, different days of the week. And I think a lot about consumer behavior pre pandemic throughout the pandemic and now post pandemic where people are only in office two or three days a week, maybe in some markets or people aren't doing the happy hour, the nighttime, you know, the, the dinner's out, they're not entertaining clients in the same way. Maybe you know, once a quarter instead of just once a week or once a month, you know, and rethinking the operation based on those changes. Is that a, is that a fair analogy? 10 00:11:04.000 --> 00:11:55.000 Yeah, definitely. And, and I think one trap that, that restaurants fall into is just assuming last year is going to be the same or this year is going to be the same as last year. Right. And like starting at that from a investing perspective. But obviously the, the trends change, the, the recency and, and what's kind of happening around you is an important indicator for what you are going to do combined with last year. Right. And so helping to not not only kind of translate the expected sales into the labor needed, but also understand the, the forecast of it and understanding. Yeah. What, what you are going to be doing kind of based off the different seasonality, events and weather that impacts your business. 11 00:11:55.000 --> 00:12:42.000 So talk to me about, so talk to me about some of the things that you built into. Right. Work to specifically make this easier. I know we've spent a lot of time offline talking about forecasting because I think it's the hill that I'm going to die on. Right. When people say, oh yeah. I said, you know, so tell me about your budgets. They're like, oh yeah, I budgeted this and this and this. I said,

great. So talk to me about your modeling. How are you forecasting? They're like, oh, we don't really do that. I was like, well then how are you coming up with budgets? You just making them, picking them, you know, out of, out of thin air. I believe budgets have to be connected to forecasting. You have to be able to look into your crystal ball, predict the future and then build, you know, sort of a spending cap for the different areas of your business. But they go, they go hand in hand. So talk to me about how you guys approach that. 12 00:12:42.000 --> 00:15:17.000 Yeah. So we, we kind of think about the labor optimization kind of challeng challenge in, in kind of four buckets. There is obviously the, the forecasting that's, we feel like that's kind of the foundation. So outlining the different sales groups, kind of labor drivers of your business and being able to forecast accurately into the future what you're expected to sell. The second step is kind of how we help translate those forecasts into the staffing levels needed to meet that expected demand. And we have some, some pretty sophisticated kind labor modeling capabilities. Built directly into the tool. Some companies we work with already have kind of activity based time standards, but a lot don't. And so what we help do as kind of part of the onboarding and as part of working with companies is, is kind of build them an initial labor model that takes into account the things that they want to take into account, that is able to translate those forecast into okay, how many people do you actually need at this time period to support that demand? So that's kind of giving the, the managers the clear picture, the clear targets that, that they have when, when building out their schedule. And then the, the third piece is really like how do we evaluate a schedule based off how well it meets that expected demand? And you can do that at like the weekly level, you can do that at the daily level. But we also find it's important to get the labor right throughout the day. And so we have kind of what we call this grading system that is as a manager is writing a schedule, always evaluating that schedule for how well it kind of fits within the budget and some of those daily and weekly goals, as well as making sure you have enough coverage throughout the day. And those people are where you need them when you need them. So kind of being able to provide the, the managers with this grading concept for kind of accountability and, and having them kind of increase their confidence in the schedule and improve their kind of business acumen, if you will. And then the fourth step is like, okay, if we are able to evaluate a schedule, why don't we be making recommendations of how to improve it? And so that's where some of our auto scheduling comes in and makes adjustments and recommendations for how about if you kind of move these shifts around and this gives you a better peak demand kind of staffing and limits over staffing off peak. So those are kind of the four pieces. 13 00:15:17.000 --> 00:15:53.000 Great, I love that. I want to pull at that thread here because now we're talking about, you know, you talk about auto, now we're talking about AI. So we're talking about a built into that is a guardrail of sorts. The, the, the agent, the model, the whatever is looking at it and be like, actually have you thought about doing this or that? So talk to me about that piece to it because I think having a co pilot in this as you're building the schedule I think is, you know, another set of eyes is always, is always helpful. So talk to me, talk to me a little bit more specifically about that and the interface, you know, how a manager would work hand in hand with some of the recommendations there. 14 00:15:53.000 --> 00:17:37.000 Yeah. So as part of this whole process we've, we've tried to stay very close with the managers that are writing schedules and trying to understand how they normally schedule. And one thing we found with like auto scheduling is that it doesn't really work if you just give them a schedule and they can either accept or decline it. Right. Like it's hard for them to just completely trust those one things. That one thing that we have built into the system from those learnings is making it more of kind of an autocomplete where they are able to specify the shifts that they want. Sometimes it's their, their fixed staff that they want to make sure they have scheduled and then can lean on kind of the copilot recommendations to be more of an auto complete or an auto adjust. So we've tried to make these kind of algorithms as flexible as possible and give some of those controls to the manager because ultimately we don't want to like be overly rigid in how we are making recommendations. Like there are some things that they care about that maybe we don't have visibility to and so trying to, to make it so that they can be helpful for a wide variety and make sure that the managers still feel like they have ownership and are empowered to kind of write the best possible schedule for their team, but ultimately trying to help get to a schedule that, that works well for their team as well as for the, the business and, and making sure they kind of save time and aren't just spending hours moving shifts around. 15 00:17:37.000 --> 00:19:08.000 This episode is sponsored by Right Work, a labor optimization platform built specifically for restaurants. If you own up, if you own and operate multiple locations. The challenge isn't just making schedules. It's making sure every store is staffing to real demand. That every store is staying on budget and following the same operating standards without adding more work. For managers, Rightwork helps turn sales patterns and service models into smarter staffing plans. Then it gives the managers the tools to schedule accurately and efficiently. Restaurant strategy listeners can get free onboarding, a free labor model build out, and

three months free of write work usage. To claim the offer, visit Write Work chip. Again, Write Work Chip. And yes, that link is in the show notes. So talk to me about what you've learned as you launch this. Because it's different when you look at Starbucks. Yes, different markets, different sort of footprints for the stores and all of that. But here, when you release a tool like this to all kinds of different concepts. Quick service, fast casual, full service, fine dining, all different markets. Urban, suburban, rural, all of that what are the things? If you can make some sort of broad generalizations like what were the big learnings that you guys came up with? And by extension, you know, what were the big things, the big epiphanies that hit the different operators who started using these tools? 16 00:19:08.000 --> 00:21:01.000 Yeah, good question. So, yeah, I mean one of the things that is, is always a learning is that it is helpful to go from like the weekly budgeting obviously down to like the daily and then the intraday. Because ultimately that's what matters is like, okay, at what time are these employees working and how are they actually serving these guests in that day part. But the other thing is that we don't want to be like overly prescriptive or, or rigid in, in that labor model. And so there's this concept of separating out kind of the labor model into service standards that are like directly servicing customers that kind of need to be done in that specific time period. Then the concept of kind of support standards or work that is more flexible, which gives a manager the ability to kind of move some of that opening closing prep work around to better kind of level load. Because obviously you see kind of your optimal staffing levels and you think, okay, I'm not going to be able to schedule exactly to every perfect like 50 minute increment or half hour. And so there's this concept of kind of okay, how do we level load some of that so we can still have like the, these shifts. But we kind of know, okay, during this day part some of our, our staff is doing support work and then like the other people are servicing the customer. So it's, it's, it's starting to understand it and kind of of help managers learn. That's why I say like improve kind of the business acumen of okay, maybe in this time period we should be doing those support tasks while we have some additional capacity. And then obviously during peak, you're, you're exclusively focusing on the guests and servicing those. 17 00:21:01.000 --> 00:22:10.000 Yeah, for sure. I mean the, so much is changing in real time. You know, I always talk about, you know, forecasting and historical data. You know, we've got five years of data that just doesn't necessarily translate because you know, 2021, so we're recording this in the summer 2026. We look back to like 2021. Man, we were coming out of the pandemic. 2020 was not helpful for 20. And even 21 was sort of like all crazy. 22 was maybe the first real year we had. Right. 23. Then everybody was traveling again. All the trips that they put off and everything. 24 was an election year so we naturally always see a pullback in our industry. You know, 25 there was sort of like, you know, new administration, sort of geopolitical things going on. You know. 26, this has been a wacky year so far with sort of the Iran conflict and you know, the cost of gas and what that does to people's, you know, spending power and all of that. So like it feels like five years in a row. And the historical data isn't entirely usable because it doesn't translate. But how, I mean obviously you guys have had to make heads and tails of that. So how have, how have your, how do your models take that into account and how have you sort of navigated through the challenges? 18 00:22:10.000 --> 00:24:24.000 Yeah, so it's a good question. Obviously machine learning and AI kind of helps with some of that. Being able to obviously do all of the anomaly detection and you feed it a bunch of data and it's starting to kind of tease apart those patterns and understand kind of the confidence intervals of what's expected to happen moving forward. I mean there's some things that we, we do now with ingesting like reservation data as well and kind of the, the confidence of that moving forward for, for some of our full service customers. And obviously it's very dependent per location. Like even for a brand, obviously there's going to be a lot of different factors or like weights of these different variables. So like some are going to be more reliant on, yeah. Previous years, some are going to be pretty recency based. And so what we do is kind of we, we retrain the models every week on a per location basis. And then the other thing that we do is we help to kind of scrape local events and try to provide visibility to that in the tool. Some of that, some of that is a little bit noisy but we want to give visibility to it for managers to allow them to adjust the forecast as needed. So what we've really tried to do is like give them the information they need, like make it kind of as explainable as possible. Like these are some of the things that's taking into account. Here are some other like yeah, local events that may be a factor and then allow them to kind of make an additional adjustment if they believe that to potentially be impactful. And then we obviously are kind of tracking all of their historical adjustments, making sure they are becoming kind of more, more accurate and then starting to feed that, that into kind of the model moving forward. So there's, there's a lot you can do. There's not like a silver bullet, obviously. There's like a lot of kind of little things that go into getting you that additional kind of accuracy points on the model. But, yeah, I love it. 19 00:24:24.000 --> 00:25:10.000 Talk to me about some of the other features you guys have built, because I think one of the things that I loved about the very first

conversation we had, as you said, you know, a bunch of people who came from, you know, the previous organization came to you and said, you know, basically said, we want a tool like this. We want a tool like that. Hey, can you do this? He could do that. Hey. And you guys have been really sensitive about learning and listening to, you know, the other things that people needed. And so we're talking about how we manage labor. Right. You know, how we properly forecast and set our schedules to, you know, provide the right support for the business levels and how do we manage that in real time and all of that, which is right up my alley, which is exactly what I talk about. But then we talked about, you know, like, the learning models and, you know, the communication tools and all that. So talk to me about the other things that you've built into the platform and why they're important. 20 00:25:10.000 --> 00:27:45.000 Yeah, definitely. Yeah. I mean, one of the things that we've always aspired to do is stay as close to our customers as possible. Yeah. I mean, one of the joys of this job is just really getting to know a lot of these restaurant operators and kind of understanding their pain points and making them our own. So, yeah, obviously we started with. With scheduling kind of the. The labor optimization side of things, but we would always ask, like, what are you doing manually? Like, what is taking time of your gm? Like, what is. What do they need help kind of making decisions about? And we've started to kind of pull some of more of those things into. Right. Work, either that they were doing in another tool or very manually. So, yeah, some of those things, obviously chat and collaboration is just like. That helps people communicate more effectively. Training has been a big one recently where we would kind of look at some of these training processes that companies had, and maybe they had kind of a good approach, but weren't super organized or structured. So the managers were having to spend a bunch of time scheduling these training shifts and then kind of deciding what they should be doing on those training shifts. And so we. We found kind of enough synergy between some of these different things where not only is it is it helpful to just have one account where you can log into it and do all these things, but Also yeah, just kind of managing your roster and being able to see who can work what capable role because they have completed these trainings like some of those synergies have just been helpful for our customers. So we've kind of just been kept our ear to the ground and continued adding new things to be a little bit more of kind of an all in one operating system. But yeah, reporting is something we've leaned a lot more into trying to use analytics and data to help empower operators to help make better decisions. Ticketing is one that has seen some recent great adoption of being able to manage facilities and it ticketing, yeah, a number of contests is

something that we found and it all kind of has to do with this manager employee relationship and just helping to make sure people are operating efficiently and have the tools and the information needed to help make the best decisions possible. 21 00:27:45.000 --> 00:27:47.000 All right, talk to me about the contest tool. What do you mean? 22 00:27:47.000 --> 00:29:07.000 Yeah, so a lot of our customers are multi unit and they've, they found that competition is a very healthy way to incentivize behavior. And so you have the ability to create contests across locations. So labor contests, sales contests, you can have kind of a baseline target that they are going against. And we essentially have these like leaderboards that all companies or all locations can see that has like a race replay. So as the, the contest duration is progressing, you can see okay, who's in first like throughout the entire contest. And it's kind of this, this dynamically shifting leaderboard. And then the same thing applies within a location so you can make them employee specific contests as well. So if you're trying to incentivize the upselling of an LTO or a gift card contest, for example, there are a, a number of different metrics you can have that are associated with employees and then they can kind of see you can kind of. Yeah. Create rewards for top three, get, get something and it just kind of a way to gamify it and make things a little bit more interactive and a healthy competition. Yeah, I, I, I love as a, a former athlete. 23 00:29:07.000 --> 00:31:19.000 Yeah, I love all this because we talk. I really meant it what I said at the beginning. It's not about cutting labor, it's about managing labor. It's about getting the most out of the people who work for you. So it begins really at hiring. It's finding the best possible people you can and training them to do exactly what you want them to do, how you want them to do it, when they should do it, and making sure they understand why, holding them accountable Measuring their performance, you know, coaching in real time. I always talk about that. We hire for it, we train for it, we model a behavior and we coach it in real time. So it's giving feedback in real time. It's criticism and positive accolades. Right? Yes, thank you. That's exactly what we were talking about. Or, hey, I just watched you. Why didn't you do that thing? All of that is getting the most out of our people. It goes so far beyond, like, making sure people clock in on time, making sure, you know, that, that we, you know, we're not heavy on our daily labor so that we stay profitable. Because if we have people who are better and better trained and excited to be there, I promise you, any restaurant out there is able to run with less. Because when you've got better people, better trained people, more passionate, more excited people, they're just going to work harder and they're going to be able to do more for the operation. So it's, it's all, it's like, it's not any one thing. It's all of that together, you know, being able to forecast, being able to look at, you know, predict what's going to come in the front door so that we can make educated guesses about how much we should staff and who we should staff and when they're coming and going and all of that. But the other piece to that, all these other aspects is making sure communication is good and your teamwork is good. And again, that they're trained, developed, that they're incentivized, that, that they stay properly productive. And that is not just true for restaurants. It's, it's all kinds of businesses all over the place. Small, big, everything in between. Yeah, well, I appreciate your time. I want to be respectful of your time. Last words of wisdom. So you obviously have a captive audience here, a whole bunch of independent restaurant owners, operators, managers from all over. I think we're represented in like 50 some countries. So what did we get to talk about? What, what can you share with the, the audience while you got them? 24 00:31:19.000 --> 00:32:46.000 Yeah, I mean, I, I think, I mean, the, the number one thing I would say is just whatever tool you're using, whether it's, it's right work or something else, is just like developing your, your labor plan and being able to, to generate those forecasts moving forward and then being able to kind of report on those historically as well. So you can understand, okay, do I need to make adjustments? Just like creating that visibility and that transparency is always just the first step and then you can kind of tailor and hone in on that labor model, but in that labor plan. But just like getting serious about labor, because it is one of the most controllable things you can do, it affects top line, it affects bottom line. If you're really trying to kind of grow and get serious about operational discipline and making sure if you, if you grow ad locations, that each location is kind of operating profitably and you can have confidence that you can kind of continue growing and. And aren't gonna. Yeah. Look back and be negatively impacting the guest experience, the. The employee experience and diluting your. Your profit margins, obviously. So getting serious about labor. And yeah, we're, we're here to help, but yeah, we'd just advise that. To take it seriously as. As part of the business. 25 00:32:46.000 --> 00:33:53.000 Yeah, I mean, it's literally one of the biggest reasons why we created the P3 mastermind. So that's the group coaching program. For anybody listening if you haven't heard it, that's the coaching program I run. And we love to adopt and promote tools that are just helping our members do these things. I always say, you know, the. The best restaurant owners there, the best restaurateurs, best restaurant group. They don't have four restaurants. They have 24. They have 400. They have thousands. Right. Because once you figure it out, it's just like, oh, let's just do another one. Let's just do

it. If it's repeatable, it's replicable. If it's replicable, it's scalable. There's a reason there aren't 20 Taco Bells. They figured it out and they know how to just replicate it over and over again. There's a reason why Boca restaurant group has dozens of restaurants. Why Danny Meyer? Why Michael Mina? Why Thomas Keller? Like all the biggest restaurateurs out there, Whether you're talking about, you know, quick service, fast casual, fine dining, whatever. They don't have four restaurants. They have, again, 24, 400 thousands out there because they figured it out. So being really serious about it and understanding what your restaurant needs to be able to do it is crucial. 26 00:33:53.000 --> 00:34:06.000 Yeah. I mean, one of the goals is just reducing the uncertainty of possible outcomes. Right. And like, reducing that variance, like, allows you to have more confidence in the future and. And plan accordingly. Right. 27 00:34:06.000 --> 00:34:45.000 So boring numbers. We talk about it all the time. Boring numbers. I want the P L. I want, you know, the fiscal management of any business, especially restaurant business, to be boring. Because the industry, the day to day, is anything but boring. It's putting out fires, it's you know, people call out, somebody got sick some, you know, it's, there's so many things that can go wrong. So our fiscal management, you know, how we predict the future, how we set our modeling and our budgets based on that just like flat, boring, repeatable profit every single month. So I'm all for it. Keeping this business boring. Will, if people want to go learn more about Right Work, everything you guys are building, what are the, what are the next steps? Where do they go? 28 00:34:45.000 --> 00:35:12.000 Yeah, I would say visit our website at write dot work. Just write dot work. And that will allow you. Yeah, if you want to book time with me directly, I believe that you should be able to do that there. And, and yeah, we'd love to share Right Work with a whole host of other people and see if we can be a good solution to help run your business more profitably. 29 00:35:12.000 --> 00:36:15.000 Absolutely. And if you guys don't know. So Will is going to be on stage with me at the profitability summit in Minneapolis that happens in mid October. Really excited to have him there. They're a supporter of this podcast, they sponsor this podcast and so listeners of this show actually get three months free of the tool. So like it costs you like $0 to just try it out and see if you like it and see if it can help you do the job better than whatever you're currently using. So it's one of the things that I really try to do whenever we build relationships with partners like, like Will and Right Work is to come up with something that's ultimately really usable for you. So like you don't have to talk about switching costs or will my people like it or hate it or whatever. Like just try it out and see all it can do. So all of that, all of those

links will be in the show notes. So the link to, you know, book demos and to reach out to Will and to, you know, to look for this. So keep an eye out for that, the three months free deal as well. Well, I appreciate you taking the time. Thank you so much. 30 00:36:15.000 --> 00:37:23.000 Yeah, thanks Chip. I really appreciate it. See ya. Foreign. 31 00:37:23.000 --> 00:37:42.000 Okay, so my guest on today's show is a guy named Will Stewart. He is the founder and CEO of a piece of software called Right Work. It's an incredibly powerful piece of software. Can't wait for you to hear more about it. Also, I think Will's background is pretty interesting. I think you're going to appreciate that. Will, welcome to the show. 32 00:37:42.000 --> 00:37:44.000 Thanks Chip. Yep. Happy to be here. 33 00:37:44.000 --> 00:38:14.000 I'm glad to have you. I'm really excited that we Met. I'm really excited to be able to have this conversation, to bring this to the audience really quickly to start us off so we understand what we're talking about. Talk about the system, the platform, the software that you built. What is right work, what does it do? And then. And I'm going to pause you there and we're going to go back and we're going to talk about your background after that, because I think. Think how you got here is incredibly interesting, and I think the audience would definitely appreciate it. First, start off, tell me what right work is. 34 00:38:14.000 --> 00:38:40.000 Yeah. So at the core, right work, we. We call it a labor optimization software. So we help companies, restaurants, optimize their labor spend. And so at the core, it's. It's scheduling. But we have a ton of additional modules that help companies better understand their labor and better optimize and schedule for that labor. 35 00:38:40.000 --> 00:40:01.000 Love it. Okay, so anybody listening here? I have come across this software. I am incredibly impressed by this. Yes, we are going to talk about this. The why, though, is really important. It is our labor is our single biggest line item on our P and L every single month. Ours is a people industry. We feed people, we buy from people. We employ people to serve people. Everything is people. And so we need a way to manage our people, to manage. Manage what ends up being a massive cost and treating it not as a liability, but really as the asset as it is. So that's why I talk about labor so much. That's why I talk about managing labor. Not cutting labor, but managing labor so much. It's why we're having this conversation. The power of having somebody like Will on the show is not so he can tell you all about his thing, but really. And I say this. I said this to Will before we hit record, and I say this over and over. Anybody who's been listening to this show for a while knows you've heard me say this. This is that. The power of having somebody like Will on the show who works with hundreds of restaurants all over the country is he gets to peek behind the curtain at a lot of different operations, and he sees all the connective tissue. He sees the common threads, the. The common mistakes, the speed bumps that everybody hits. He can see the trends as they're coming. And I think Will's background is particularly interesting. So, Will, talk a little bit about where you were at and what led you to build this thing that you built. 36 00:40:01.000 --> 00:42:01.000 Yeah, definitely. And. And thanks for kind of some of that context. And. And before I dive into the background a little bit, I'M I'm glad. Just some of the language you use there around kind of labor as an investment. And when we talk about optimizing labor, we're. We're not just talking about cutting labor. Right. I think that's kind of a preconceived thing that people get. Like we want to help make sure restaurants are, are staffed up for their, their peaks and yeah, yeah. Just not kind of overstaffed during those lulls. So just kind of a note there and something we want to make sure we get clear to our customers 100%. But yeah. So my background, I spent a little over five years doing data science and analytics at Starbucks. So I have a background in analytics and optimization. And while I was at Starbucks I built a lot of the, or some of the tools that Starbucks uses to manage and optimize labor across 10,000 plus stores. So being able to kind of see labor at that scale and understand how kind of small tweaks and adjustments can have a major impact on operations. Again, not just from a cost cutting perspective, but also being able to capture some of that for Starbucks it's mainly the morning rush. Right. And understand and have visibility to that. But ultimately kind of saw that whole perspective, left Starbucks to start my own company and was approached by a number of former Starbucks operators, leaders that had left Starbucks and kind of wanted some similar tools to what we had at Starbucks in terms of the sophistication and data. And so ultimately a lot of the former Starbucks, yeah, people kind of left and those were our first customers of right work. 37 00:42:01.000 --> 00:42:54.000 So talk to me about, because again, you get to peek behind the curtain. You are behind a very heavy curtain that's difficult to look behind. I talk about the Starbucks service manual, that employee manual all the time and how they set up and basically their version of like figure eights and keeping people in position. I was talking with the folks at Bigby Coffee who modeled a lot of how they build their thing based on how Starbucks did their thing. It was basically like, well, we can't do any better. So let's just try to emulate it as much as possible and improve where we need to improve. So talk to me specifically about how Starbucks things about managing labor, about, you know, what is again this massive line item on the P L and also one of the biggest opportunities. Talk to me about how they approached it and I guess you could speak to it in your time

there, but how did they think about it? 38 00:42:54.000 --> 00:44:32.000 Yeah, so I think one of kind of the core things and you'll see this at A number of kind of enterprise like large companies that hasn't really been adopted by smaller companies, but we're helping to kind of change that is the concept of kind of a bottoms up labor model where you are able to forecast by a number of different kind of sales drivers or labor drivers and then understand how that's affecting the staffing levels needed to support that demand. So when you think about Starbucks, there are obviously a ton of different concepts and based off the markets that they live in, the product and channel mix is very different. Right. So especially with the advent in the growth of mobile order and pay and some of those different channels, those have different labor needs compared to the drive thru customers. Right. And so the first thing that kind of happens happens is breaking apart those kind of sales groups and understanding what actual labor is required. And so that a mobile order and pay heavy store in a city gets a different kind of labor model and staffing needs compared to the drive through stores that have different peaks and valleys. So that's kind of one of the important things to understand is how the channel mix and product mix can affect the, the labor needed to, to run the store. 39 00:44:32.000 --> 00:45:11.000 Yeah, I make sense. It seems to me like this does translate to independence where we look at what the needs are for different day parts, different days of the week. And I think a lot about consumer behavior pre pandemic, throughout the pandemic and now post pandemic where people are only in office two or three days a week, maybe in some markets or people aren't doing the happy hour, the nighttime, you know, the dinner is out, they're not entertaining clients in the same way. Maybe you know, once a quarter instead of just once a week or once a month, you know, and rethinking the operation based on those changes. Is that a, is that a fair analogy? 40 00:45:11.000 --> 00:46:03.000 Yeah, definitely. And I think one trap that restaurants fall into is just assuming last year is going to be the same or this year is going to be the same as last year. Right. And like starting at that from a forecasting perspective. But obviously the, the trends change. The, the, the recency and, and what's kind of happening around you is an important indicator for what you are going to do combined with last year. Right. And so helping to not not only kind of translate the expected sales into the labor needed, but also understand the forecast of it and understanding. Yeah. What you are going to be doing kind of based off the different seasonality, events and weather that impacts your business. 41 00:46:03.000 --> 00:46:49.000 So talk to me about, talk to me about some of the things that you built into right work to specifically make this easier. I know we've spent a lot of time offline talking about forecasting because I think it's the hill that I'm going to die on. And people say, oh yeah. I said, so tell me about your budgets. They're like, oh yeah, I budgeted this and this and this. I said, great. So talk to me about your modeling. How are you forecasting? They're like, oh, we don't really do that. I was like, well, then how are you coming up with budgets? You're just making them, picking them out of thin air. I believe budgets have to be connected to forecasting. You have to be able to look into your crystal ball, predict the future, and then build sort of a spending cap for the different areas of your business. But they go hand in hand. So talk to me about how you guys approach that. 42 00:46:49.000 --> 00:49:25.000 Yeah, so we, we kind of think about the labor optimization kind of challenge in, in kind of four buckets. There is obviously the, the forecasting that's, we feel like that's kind of the foundation. So outlining the different sales groups, kind of labor drivers of your business, and being able to forecast accurately into the future what you're expected to sell. The second step is kind of how we help translate those forecasts into the staffing levels needed to meet that expected demand. And we have some, some pretty sophisticated kind of labor modeling capabilities built directly into the tool. Some companies we work with already have kind of activity based time standards, but a lot don't. And so what we help do as kind of part of the onboarding and as part of working with companies is kind of build them an initial labor model that takes into account the things that they want to take into account, that is able to translate those forecasts into, okay, how many people do you actually need at this time period to support that demand? So that's kind of giving the managers the clear picture, the clear targets that, that they have when, when building out their schedule. And then the, the third piece is really like, how do we evaluate a schedule based off how well it meets that expected demand? And you can do that at like the weekly level, you can do that at the daily level. But we also find it's important to get the labor right throughout the day. And so we have kind of what we call this grading system that is as a manager is writing a schedule, always evaluating that schedule for how well it kind of fits within the budget and some of those daily and weekly goals, as well as making sure you have enough coverage throughout the day and those people are where you need them when you need them. So kind of being able to provide the managers with this grading concept for kind of accountability and having them kind of increase their confidence in the schedule and improve their business acumen, if you will. And then the fourth step is like, okay, if we are able to evaluate a schedule, why don't we be making recommendations of how to improve it? And so that's where some of our auto scheduling comes in and it makes

adjustments and recommendations for how about if you kind of move these shifts around and this gives you a better peak demand kind of staffing and limits overstaffing off peak. So those are kind of the four pieces. 43 00:49:25.000 --> 00:50:01.000 Great, I love that I want to pull at that thread here because now we're talking about, you know, you talk about auto, now we're talking about AI. So we're talking about a built into that is a guardrail of sorts. The agent, the model, the whatever is looking at it and being like actually have you thought about doing this or that? So talk to me about that piece to it because I think having a copilot in this as you're building the schedule I think is, you know, another set of eyes is always, is always helpful. So talk to me a little bit more specifically about that in the interface. You know, how a manager would work hand in hand with some of the recommendations there. 44 00:50:01.000 --> 00:51:44.000 Yeah. So as part of this whole process, we've tried to stay very close with the managers that are writing schedules and trying to understand how they normally schedule. And one thing we found with like auto scheduling is that it doesn't really work if you just give them a schedule and they can either accept or decline it. Right. Like it's hard for them to just completely trust those one things. That one thing that we have built into the system from those learnings is making it more of kind of an autocomplete where they are able to specify the shifts that they want. Sometimes it's their, their fixed staff that they want to make sure they have scheduled and then can lean on kind of the, the copilot recommendations to be more of an auto complete or an auto adjust. So we've tried to make these kind of algorithms as flexible as possible and give some of those controls to the manager. Because ultimately we don't want to like be overly rigid in how we are making recommendations. Like there are some things that they care about that maybe we don't have visibility to and so trying to, to make it so they can be helpful for a wide variety and make sure that the managers still feel like they have ownership and are empowered to kind of write the best possible schedule for their team, but ultimately trying to help get to a schedule that, that works well for their team as well as for the business and making sure they kind of save time and aren't just spending hours moving shifts around. 45 00:51:44.000 --> 00:52:22.000 So talk to me about what you've learned as you launch this. Because it's different when you look at Starbucks. Yes, different markets, different sort of footprints for the stores and all of that. But here, when you release a tool like this to all kinds of different concepts. Quick service, fast casual, full service, fine dining, all different markets, urban, suburban, rural, all of that, what are the things? If you can make some sort of broad generalizations, like what were the big learnings that you guys came

up with? And by extension, you know, what were the big things, the big epiphanies that hit the different operators who started using these tools? 46 00:52:22.000 --> 00:54:15.000 Yeah, good question. So, yeah, I mean, one of the things that is always learning is that it is helpful to go from like the weekly budgeting, obviously down to like the daily and then the intraday because ultimately that's what matters is like, okay, at what time are these employees working and how are they actually serving these guests in that day part? But the other thing is that we don't want to be like overly prescriptive or rigid in, in that labor model. And so there's this concept of separating out kind of the labor model into service standards that are like directly servicing customers that kind of need to be done in that specific time period. And the concept of kind of support standards or work that is more flexible, which gives a manager the ability to kind of move some of that opening closing prep work around to better kind of level load. Because obviously you see kind of your optimal staffing levels and you think, okay, I'm not going to be able to schedule exactly to every perfect, yeah, 50 minute increment or half hour. And so there's this concept of kind of, okay, how do we level load some of that? So we can still have like the, these shifts, but we kind of kind of know, okay, during this day part, some of our, our staff is doing support work and then like the other people are servicing the customer. So it's, it's, it's starting to understand and kind of help managers learn. That's why I say like improve kind of the business acumen of, okay, maybe in this time period we should be doing those support tasks while we have some additional capacity. And then obviously during peak you're, you're exclusively focusing on the guests and servicing those. 47 00:54:15.000 --> 00:55:25.000 Yeah, for sure. I mean, so much is changing in real time. You know, I was talking about, you know, forecasting and historical data. You know, we've got five years of data that just doesn't necessarily translate because, you know, 2021. So we're recording this in the summer 2026. We look back to like 2021. Man, we were coming out of the pandemic. 2020 was not helpful for 20. And even 21 was sort of like all crazy. 22 was maybe the first real year we had. Right. 23, then everybody was traveling again, all the trips that they put off and everything. 24 was an election year. So we naturally always see a pullback in our industry. 25, there was sort of like new administrations or geopolitical things going on. 26. This has been a wacky year so far with sort of the Iran conflict and the cost of gas and what that does to people's spending, power and all of that. So it feels like five years in a row. And the historical data isn't entirely usable because it doesn't translate. But how, I mean, obviously you guys have had to make heads and tails of that. So how have, how have your, how do your models take that into account and how have you sort of navigated through the challenges? 48 00:55:25.000 --> 00:57:38.000 Yeah, so it's a good question. Obviously machine learning and, and AI kind of helps with some of that. Being able to obviously do all of the anomaly detection and you feed it a bunch of data and it's starting to kind of tease apart those patterns and understand kind of the confidence intervals of what's expected to happen moving forward. I mean, there's some things that we do now with ingesting reservation data as well and kind of the confidence of that moving forward for some of our full service customers. And obviously it's very dependent per location. Like even for a brand. Obviously there's going to be a lot of different factors or like weights of these different variables. So like some are going to be more reliant on previous years, some are going to be pretty recency based. And so what we do is kind of we retrain the models every week on a per location basis. And then the other thing that we do is we help to kind of scrape local events and try to provide visibility to that in the tool. Some of that is a little bit noisy, but we want to give visibility to it for managers to allow them to adjust the forecast as needed. So what we've really tried to do is, like, give them the information they need, like, make it kind of as explainable as possible. Like, these are some of the things it's taking into account. Here are some other, like, yeah, local events that may be a factor, and then allow them to kind of make an additional adjustment if they believe that to potentially be impactful. And then we obviously are kind of tracking all of their historical adjustments, making sure that they are becoming kind of more. More accurate, and then starting to feed that. That into kind of the model moving forward. So there's. There's a lot you can do. There's not like a silver bullet, obviously. There's like a lot of kind of little things that go into getting you that additional kind of accuracy points on the model. 49 00:57:38.000 --> 00:58:26.000 But, yeah, I love it. Talk to me about some of the other features you guys have built, because I think one of the things that I loved about the very first conversation we had, as you said, a bunch of people who came from the previous organization came to you and said, basically said, we want a tool like this. We want a tool like that. Hey, can you do this? Hey. And you guys have been really sensitive about learning and listening to the other things that people needed. And so we're talking about how we manage labor, how we properly forecast and set our schedules to provide the right support for the business levels, and how do we manage that in real time and all of that, which is right up my alley, which is exactly what I talk about. But then we talked about, you know, like, the learning models and, you know, the communication tools and all that. So talk to me about the other things that you've

built into the platform and why they're important. 50 00:58:26.000 --> 01:01:02.000 Yeah, definitely. Yeah. I mean, one of the things that we've always aspired to do is stay as close to our customers as possible. Yeah, I mean, one of the joys of this job is just really getting to know a lot of these restaurant operators and kind of understanding their pain points and making them our own. So, yeah, obviously we started with scheduling, kind of the labor optimization side of things. But we would always ask, like, what are you doing manually? Like, what is taking time of your gm? Like, what is. What do they need help kind of making decisions about? And we've started to kind of pull some of more of those things into. Right. Work, either that they were doing in another tool or very manually. So, yeah, some of those things, obviously chat and collaboration is just like, that helps people communicate more effectively. Training has been a big one recently where we would kind of look at some of these Training processes that companies had and, and maybe they had kind of a good approach but weren't super organized or structured. So the managers were having to spend a bunch of time scheduling these training shifts and then kind of deciding what they should be doing on those training shifts. Yeah, we found kind of enough synergy between some of these different things where not only is it is it helpful to just have one account where you can log into it and do all these things, but also yeah, just kind of managing your roster and being able to see who can work what capable role because they have completed these trainings like some of those synergies have just been helpful for our customers. So we've kind of just been kept our ear to the ground and continued adding new things to be a little bit bit more of kind of an all in one operating system. But yeah, reporting is something we've leaned a lot more into trying to use analytics and data to help empower operators to help make better decisions. Ticketing is, is one that has, has seen some recent great adoption of being able to manage facilities and it ticketing. Yeah. A number of contests is something that we found and it all kind of has to do with yeah, this like manager employee relationship and just helping to make sure yeah. People are operating efficiently and have the tools and the information needed to help make the best decisions possible. 51 01:01:02.000 --> 01:01:05.000 All right, talk to me about the contest tool. What do you mean? Explain it. 52 01:01:05.000 --> 01:02:26.000 Yeah, so a lot of our customers are multi unit and they found that competition is a very healthy way to incentivize behavior. And so you have the ability to create contests across locations. So labor contests, sales contests, you can have kind of a baseline target that they are going against. And we essentially have these like leaderboards that all companies or all locations can see that has like a race nice replay. So as the, the contest duration is progressing, you can see okay, who's in first like throughout the entire contest. And it's kind of this, this dynamically shifting leaderboard and then the same thing applies within a location. So you can make them employee specific contests as well. So if you're trying to incentivize the upselling of an LTO or a gift card contest, for example, there are a number of different metrics you can have that are associated with employees and then they can kind of see you can kind of create rewards for top three get, get something and just kind of a way to gamify it and make things a little bit more interactive and a healthy competition. Yeah, I love as a former athlete, 53 01:02:26.000 --> 01:04:39.000 yeah, I love all this, because we talk. I really meant it when I said at the beginning, it's not about cutting labor, it's about managing labor. It's about getting the most out of the people who work for you. So it begins really at hiring. It's finding the best possible people you can and training them to do exactly what you want them to do, how you want them to do it, when they should do it, and making sure they understand why, holding them accountable, measuring their performance. You know, coaching in real time. I always talk about that. We hire for it, we train for it, we model a behavior, we coach it in real time. So it's giving feedback in real time. It's criticism and positive accolades. Right? Yes, thank you. That's exactly what we were talking about. Or, hey, I just watched you. Why didn't you do that thing? All of that is getting the most out of our people. It goes so far beyond, like, making sure people clock in on time, making sure, you know, that, that, you know, we're not heavy on our daily labors, that we stay profitable. Because if we got people who are better and better trained and excited to be there, I promise you, any restaurant out there is able to run with less. Because when you've got better people, better trained people, more passionate, more excited people, they're just going to work harder and they're going to be able to do more for the operation. So it's, it's all, it's like, it's not any one thing. It's. It's all of that together. You know, being able to forecast, being able to look at, you know, or predict what's going to come in the front door so that we can make educated guesses about how much we should staff and who we should staff and when they're coming and going and all of that. But the other piece to that, all these other aspects, is making sure communication is good and your teamwork is good. And again, that they're trained, developed, that they're incentivized, that they stay properly productive. And that is not just true for restaurants. It's all kinds of businesses all over the place. Small, big, everything in between. Well, I appreciate your time. I want to be respectful of your time. Last words of wisdom. So you obviously have a captive audience here. A whole bunch of independent restaurant

owners, operators, managers from all over. I think we're represented in like 50 some countries. So what did we get to talk about? What, what can you share with the, the audience while you got them? 54 01:04:39.000 --> 01:06:06.000 Yeah, I mean, I, I think, I mean, the, the Number one thing I would say is just whatever tool you're using, whether it's. It's right work or something else, is just like developing your labor plan and being able to generate those forecasts moving forward and then being able to kind of report on those historically as well. So you can understand, okay, do I need to make adjustments? Just like creating that visibility and that transparency is always just the first step. And then you can kind of tailor and hone in on that labor model, but in that labor plan. But just like getting serious about labor, because it is one of the most controllable things you can do, it affects top line, it affects bottom line. If you're really trying to kind of grow and get serious about operational discipline and making sure, if you. If you grow at locations, that each location is kind of operating profitably and you can have confidence that you can kind of continue growing and aren't gonna. Yeah. Look back and be negatively. That impacting the guest experience, the. The employee experience, and diluting your. Your profit margins, obviously. So getting serious about labor and yeah, we're. We're here to help, but, yeah, we just advise that. To take it seriously as part of the business. 55 01:06:06.000 --> 01:07:14.000 Yeah. I mean, it's literally one of the biggest reasons why we created the P3 mastermind. So that's the group coaching program. For anybody listening, if you haven't heard it, that's the coaching program I run. And we love to adopt and promote tools that are just helping our members do these things. I always say, you know, the best restaurant owners out there, the best restaurateurs, best restaurant groups, they don't have four restaurants. They have 24. They have 400, they have thousands. Right. Because once you figure it out, it's just like, oh, let's just do another one. Let's do it. If it's repeatable, it's replicable. If it's replicable, it's scalable. There's a reason there aren't 20 Taco Bells. They figured it out, and they know how to just replicate it over and over again. There's a reason why Boca Restaurant Group has dozens of restaurants. Why Danny Meyer? Why Michael Mina? Why Thomas Keller? Like all the biggest restaurant tourists out there, whether you're talking about, you know, quick service, fast casual, fine dining, whatever. They don't have four restaurants. They have, again, 24, 400 thousands out there because they've figured it out. So being really serious about it and understanding what your restaurant needs to be able to do it is crucial. 56 01:07:14.000 --> 01:07:27.000 Yeah. I mean, one of the goals is just reducing the uncertainty of possible outcomes. Right. And like reducing that very like allows you to have more confidence in the future and, and plan accordingly. Right. 57 01:07:27.000 --> 01:08:06.000 So boring numbers. We talk about it all the time. Boring numbers. I want the P L. I want, you know, the fiscal management of any business, especially restaurant business, to be boring. Because the industry, the day to day is anything but boring. It's, it's putting out fires. It's, you know, people call out, somebody got sick some, you know, it's. There's so many things that can go wrong. So our fiscal management, you know, how we predict the future, how we set our modeling and our budgets based on that just like flat, boring, repeatable profit every single month. So I'm all for it. Keeping this business boring. Will, if people want to go learn more about right work, everything you guys are building, what are the, what are the next steps? Where do they go? 58 01:08:06.000 --> 01:08:33.000 Yeah, I would say visit our website at right dot work. Just write dot work and that will allow you. Yeah. If you want to book time with me directly, I believe that you should be able to do that there. And yeah, would love to share. Right Work with a whole host of other people and see if we can be a good solution to help run your business more profitably. 59 01:08:33.000 --> 01:09:36.000 Absolutely. And if you guys don't know. So Will is going to be on stage with me at the profitability summit in Minneapolis that happens in mid October. Really excited to have him there. They're a supporter of this podcast, they sponsor this podcast and so listeners of this show actually get three months free of the tool. So like it costs you like $0 to just try it out and see if you like it and see if it can help you do the job better than whatever you're currently using. So it's one of the things that I really try to do whenever we build relationships with partners like Will and Right work is to come up with something that's ultimately really usable for you. So like you don't have to talk about switching costs or will my people like it or hate it or whatever. Like just try it out and see all it can do. So all of that, all of those links will be in the show notes. So the link to, you know, book demos and to reach out to Will and to, you know, to look for this. So keep an eye out for that, the three months free deal as well. Will, I appreciate you taking the time. Thank you so much. 60 01:09:36.000 --> 01:09:39.000 Yep, thanks Chip. I really appreciate it. 61 01:09:39.000 --> 01:09:41.000 See ya. Bye. 62 01:09:41.000 --> 01:09:43.000 Bye.