Discover why experienced restaurant managers override scheduling systems and how to build trust, improve adoption, and reduce manual schedule edits.
If you’ve rolled out a labor scheduling system across multiple locations, you’ve likely seen the same pattern play out. The system generates a schedule, your managers open it, and then they start making changes. By the time the schedule is published, it often looks very different from what the system originally produced.
This isn’t a training issue, and it’s not because your managers don’t care. In many cases, it’s your most experienced operators, the ones you rely on to run your highest-performing locations, who are making the most adjustments.
If your goal is to move toward fully automated scheduling, this is the behavior you need to understand and address.
In one of Fourth’s webinars on why restaurant technology rollouts fail, former Red Lobster Executive Vice President and Chief Information Officer, Shawn Harrs, emphasized that most failures aren’t driven by bad technology. They happen because operators don’t trust the system they’ve been given.
Labor scheduling is one of the clearest examples of this dynamic. Managers are ultimately accountable for labor cost, service levels, and the guest experience. If a schedule doesn’t match demand, they’re the ones dealing with the consequences in real time. When a system-generated schedule doesn’t align with their expectations, stepping in to adjust it feels less like resistance and more like responsible decision-making.
Most general managers didn’t learn scheduling through software. They learned it through years of experience in running shifts, reacting to demand, and adjusting in real time.
Over time, they build instincts around their business: when sales tend to spike, where staffing gaps usually occur, and how their team actually performs during different dayparts.
When a system-generated schedule doesn’t reflect those patterns, the natural reaction is to step in and “fix” it. At an individual store level, that behavior can seem reasonable. But across dozens or hundreds of locations, those manual adjustments introduce inconsistency. Some stores overstaff, others understaff, and it becomes difficult to scale a repeatable, data-driven approach to labor.
One of the most important insights from the webinar is deceptively simple: when there are two ways to complete the same task, operators will choose the one with less friction, even if it isn’t the most effective approach.
In practice, that means managers are often deciding between using the system-generated schedule or modifying it based on their own preferences. If both options are available, the system becomes optional. Over time, this turns what should be an automated process into a manual one with extra steps layered on top.
At a smaller scale, these adjustments may not create noticeable issues. But as an organization grows, the impact compounds quickly. Small, store-level changes made across 100 or more locations can result in thousands of unnecessary labor hours, increased overtime risk, and significant variability in performance.
Because these decisions are made locally, they’re also difficult to track and standardize. What looks like a minor adjustment in one store becomes a systemic issue across the business. This is where many operators find themselves stuck, having invested in technology, but not seeing the expected improvement in labor performance.
Adoption doesn’t come from additional training sessions or repeated reminders. It comes from proving to operators that the system consistently produces better outcomes than manual decision-making.
One of the most effective approaches discussed in the webinar is to show a clear comparison between what the system generated, what the manager ultimately published, and what actually happened once the shift played out. When managers can see how the system’s recommendations align with real demand, and how their manual adjustments impact results, they begin to build confidence in the system.
Over time, that confidence reduces the need to intervene. Managers start to rely on the system not because they’re told to, but because they’ve seen that it works.
There’s a common misconception that automation removes control from managers. In reality, it should do the opposite. The goal of automated scheduling is not to eliminate oversight, but to reduce unnecessary effort and variability.
If managers are still rebuilding schedules each week, adjusting every shift, or second-guessing forecasts, the system is only acting as a starting point. True automation happens when the system produces a schedule that managers trust enough to accept with minimal changes, making adjustments only when conditions actually require it.
If your managers are consistently overriding the system, the solution isn’t to force compliance. It’s to identify where trust is breaking down and address it directly.
Start by making performance more visible. Regularly compare system-generated schedules to actual results so managers can see how well the system aligns with demand. Look closely at where manual edits are happening, as those are often the clearest indicators of where the system isn’t meeting expectations. Instead of trying to change everything at once, focus on one or two specific behaviors that will move the needle, such as reducing manual overrides or following system-generated labor targets more closely.
Finally, highlight the locations that are successfully using the system and achieving better outcomes. When operators see their peers benefiting from a different approach, it creates a level of credibility that top-down directives often can’t achieve.
If your best managers are ignoring your labor scheduling system, it’s not because they’re unwilling to change. It’s because they haven’t yet seen enough evidence that the system will help them run a better operation.
Fully automated scheduling doesn’t start with technology. It starts with trust. When operators believe the system reflects the reality of their business, they stop rebuilding schedules and start relying on them. That’s when you begin to see real gains in consistency, efficiency, and profitability.
If you’d like to hear more from Shawn Harrs on how to build trust with operators, drive adoption, and avoid the common pitfalls that derail technology rollouts, you can watch the full webinar on-demand.
If you’re looking to reduce manual schedule edits, improve adoption across your locations, and ensure your schedules actually reflect real demand, Fourth can help.
Our AI-powered forecasting and workforce management platform connects demand, scheduling, compliance, and payroll into a single, continuous workflow, giving operators the visibility, guardrails, and confidence they need to rely on the system, not override it.
Christina Lau: Hello everyone, thank you so much for joining our webinar today and welcome to everyone tuning in. I’m Christina from the Fourth team. I’ll be your webinar host for today’s session, and today we are covering the topic of why most restaurant technology rollouts fail and what actually works.
Before we get started, I’ll go over a couple of housekeeping notes. The first is that this is being recorded in case you want to rewatch it, share it with someone who might be interested, or if you have to step away at any point during the webinar — we will be emailing you the recording afterwards. Second, if you have questions at any point, you can definitely ask those. If you’re joining us live, you’ll see an option to submit a question towards the bottom right of your screen. And if you’re watching this at a later time, you can always email us and reach out with any questions you have as well.
Now, to get into the webinar, we have an exciting guest joining us and this is going to be a great conversation. I would love to officially introduce our guest speaker, Shawn Harrs. Shawn is a seasoned technology leader with more than 20 years of experience leading digital transformation at global organizations. Most recently, Shawn was the EVP and CIO at Red Lobster, where he oversaw restaurant technology strategy and support across more than 690 restaurants, with a focus on driving operational performance through technology and data.
Joining Shawn, we have Jay Altizer, Fourth’s Chief Operations Officer, who will be moderating today’s discussion. Jay partners closely with restaurant operators and brings a very practical, operations-first perspective on how technology is helping teams improve labor efficiency, control costs, and scale more consistently. Thank you so much to both of you for being here with us today. Jay, I think this is a great time to lead us into the discussion.
Jay Altizer: Thank you so much, Christina. And mainly, thank you to Shawn — a true pro. You’ve got incredible experience as a CIO and in driving business change, and I learn something every time we talk. It’s very kind of you to take the time to talk to us and to our audience today.
Let me set this up for us. I’ll cover our topics and then we’ll get into it. What we’ll spend time talking about today is, first, the challenge of driving performance at large scale — what driving performance looks like and how you think about it across hundreds of locations instead of maybe a few, and how that’s different. Second, we’re going to spend some time talking about building trust with operators — in particular, how do you get the trust, the buy-in, and ultimately the commitment from the field operations organization. We’ll then talk about what makes a good technology partner in the context of driving restaurant performance and building trust — what do you look for in partners? And where I’d like to take it at the end is how you think about ultimately driving adoption. There are a lot of tools out there, a lot of suppliers running at different problems in multi-unit operations, and ultimately you’ve got to get adoption of those tools and the processes nested in them to get the benefit. That doesn’t always come easy. So we’ll wrap up on adoption and then maybe leave our audience with a takeaway or two. Does that sound like a plan?
Shawn Harrs: Sounds great. Great conversation topics.
Jay Altizer: Fantastic. So let’s start with the question of scale. You’ve overseen technology and operations across fairly large-scale restaurant chains — cruise ships, some time at Disney. Let’s start from: what makes performance improvement or getting business impact different in a scaled or multi-unit organization than perhaps a smaller one?
Shawn Harrs: One of the big things that’s different at scale is the frequency of when issues arise. No matter what you attempt to do or try to predict, things that would seemingly not happen as frequently, given the scale, are going to happen more frequently. But even more so is the unpredictable — things you really could not have thought of. And I have to say, it’s not just about the technology — it’s the end user. Users are going to find ways to use that technology in ways that you could not have predicted. From good or from not-so-good, they’re going to use it. There are some interesting things that happen when you get technology into the hands of thousands and thousands of users. As you’re working on a scale-up, things that weren’t anticipated can come up, and you have to have the ability to respond to them. That makes for sometimes very curious uses of the technology — ones that you can look at and say, wow, I could never have thought that would have happened. You have to be prepared for the unprepared.
Jay Altizer: Right — the edge case cometh in a large-scale rollout. So how do you think about, if not preparation for that, how you communicate, anticipate, or handle it? How do you like to see that handled in the teams you work with?
Shawn Harrs: It’s definitely a hands-on approach. When you’re back at the evaluation stage — especially in a larger organization — you have to evaluate edge cases, because larger organizations are going to have more of them. So in the evaluation phase, begin with conversations out in the operation. Talk to operators, talk to people in the field, understand their pain points, and involve them in the requirements. What do we need this technology to do? How do we need it to function?
I can run a strong IT organization that understands technology and the restaurant business, and I have a lot of insight into what other operators are doing and what best practices look like. But all of that gets put aside when you have a conversation with an operator who really understands their business. They’ve been doing it for a long time, and they bring expertise that gives you insights into things you didn’t think of. So that preparation, beginning at the evaluation phase — thinking about whether there are capabilities or solutions that will really fit the company’s needs — that’s where you have to start.
That’s also what companies will struggle with the most when they’ve started out at 20 or 50 units using mid-enterprise-size technology solutions that worked okay, and then they’re getting into that 100-plus-unit size. The variations — especially in certain restaurant segments — around regional menus, regional regulatory requirements, and certainly regional labor requirements start to come up. Those tend to be new for the organization. That’s when you’re moving into being a large restaurant business and you have to begin to have that enterprise thought process.
Jay Altizer: Right — the organization is just starting to hit scenarios and operating environments they haven’t seen before. I really liked what you said about listening and getting out with local teams. When I used to work in CPG, we called it getting into market. Any tips, or any do’s and don’ts for technology teams in terms of how to get that knowledge and experience?
Shawn Harrs: You definitely want to start by ensuring that the operator sees you as a partner and an ally. Really convey that you’re from the support center and you’re here to help. Give them examples and show them how the support center has been helping them in the past. And when it comes to a technology change at large scale, there’s no rolling back once you’ve rolled these things out. So what operators are going to be cautious of is: I’m going to be stuck with this thing if I don’t like it.
Having them on board and building that trust out in the field — using examples from the past where you can show them, “listen, we heard you, we listened to you” — and making clear that we are doing this not as a corporate mandate, but in service of you as an operator. We plan to make it easier for you. We plan to help with your prime cost, your labor cost, your COGS — whatever the initiative is, we’re going to help their P&L with it.
We’re not adding a burden to them. The change is disruptive — they’ve got a business to run day in and day out, and there’s some legitimate concern about what that could mean for their business. So putting myself in their shoes, thinking about the concerns they have, and addressing them up front — starting with why. Here’s why we’re doing this, and not because it’s a support center mandate, but because this is going to be in service of you, the operator. Getting them really comfortable seeing and believing that is the most important, most critical place to start. It’s not a technology initiative. It’s a people initiative.
Jay Altizer: I think that is extremely well said. Something you just said reminds me that a lot of times when we’re working with larger organizations, our reason for being is to drive operational improvements and enable better P&L results. But there’s a lot of focus up front on the risk of the downside — if the store doesn’t run, you don’t have to have too many problems at a location before you have a significant financial problem if you’re not taking care of guests. My suspicion is that it’s wise to invest in those relationships and in listening up front.
So we’re on our operator trust topic. How do you know it’s going well? From the perspective of the technology organization or the technology leader — how do you know you’re really building trust here? What behaviors come along with that, versus just following the steps because you have to?
Shawn Harrs: The process has to involve an operator-involved pilot. Take the time necessary — at the support center or with your technology partner — to pilot in as close to a real-world scenario as possible. You’ve done all the due diligence and design up front, and you time how it’s going to integrate and what the process changes look like for the team, from the GM on down. Really put this into the real world, and have an operator involved who doesn’t have qualms about telling you what they really think.
Everyone listening knows who I’m talking about — those GMs or CSMs who are going to tell you if it’s working or not. Find that group and work with them. Provide a dedicated team to be on site to support it, and gather and record as much data and information as you can through observations. Record people interacting with the technology if you’re allowed to. Things like: where do they pause? Is the layout of the screen right? Is the device working as expected? Gather as much rich, real data as you can.
Then come back and make sure it’s understood that this is not just a rollout pilot — this is about gathering information on the feasibility. Is this the right solution? Come back to the operator and restate what you heard. Say to them: “You gave us a lot of your time and a lot of insight. Here’s what we observed and here’s what we saw.
Here’s what we believe worked, and here’s what we believe wasn’t working. Are we right?”
Give them the opportunity to validate that. Because when they feel heard, you can say: “Before we take a single step further, we’re going to address these things. Of the ten things that didn’t work, these five are the showstoppers.” Make sure those can be addressed, because otherwise you can’t move forward and have any real shot at success.
Jay Altizer: Getting detailed feedback, writing it down, and then playing it back — “we heard you, we made the change, here’s how it works” — I’m sure that builds a ton of credibility. Have you seen situations where you had good tech and good solutions, but struggled to get users or operators around it because of challenges with the human side?
Shawn Harrs: Yes. It was simply a dislike for introducing a new technology — it wasn’t even about the technology itself. And that’s more so where it tends to happen. It certainly happens on replacements. Every restaurant operator out there, or anyone in the hospitality tech world, is looking at AI enablement and different capabilities.
Generally, they’re replacing existing things. But when you’re looking at introducing new capabilities that didn’t exist before — a new piece of hardware or a new piece of technology — the human element has to come first. Where does the guest fit into the experience, or where does the employee fit, or if it’s a joint guest-and-server piece of technology, what role do they each play? What are we expecting of them?
If the expectation is 100% adoption — say, we’re putting a new online ordering experience in place, and that is the way every customer is going to order — it had better work. Because that entire segment of your to-go business, that entire revenue stream, flows through that one piece of technology. What I’ve seen is a big drop-off in revenue or a big drop-off on the dine-in or carry-out side because one thing didn’t work and it was part of the entire guest experience.
I’ll give a tangible example of one where it did work because we were very careful to test it out — and that is voice AI ordering. For years, we’ve been talking about using voice to interact with our phones or smart home devices, and it just never was quite there. If you’re calling into a restaurant and it’s not a human, and it has a hiccup, that’s a guaranteed loss of a customer. The widely known concept is the Turing test — it has to pass that. It has to be human. It’s got to understand the stuttering, the mumbling, different accents, and changing your order mid-sentence. If that doesn’t work, you’re 100% guaranteed to lose that customer. And every time that issue occurs, you lose that customer, and loyalty is really hard to regain.
That is a specific situation where I’ve seen it go very wrong and I’ve seen it go exceptionally well. It’s an area that is now working well enough that I’ve evaluated it and said, yes, this is good enough to put in front of our customers. It’s got to be as good as the plate of food we put in front of them. Otherwise, we shouldn’t do it.
Jay Altizer: I really like your framework — if it’s a new process, there’s going to be more friction, or maybe there’s an existing process you can revert to if the new one doesn’t work. You really have to address the human element and any incentives to get it right.
In the hospitality space, I’ve seen situations where what I call “throwing the org chart at the customer” happens — where solutions are built up around P&Ls. If you want to interact with a single brand, you want to buy this product one way, but if you want to buy a different product, you go somewhere else, and if you want both together, you go somewhere else again. They get funded, implemented, executed, and rolled out completely independently of one another.
It doesn’t matter what age group we’re talking about — people have a different expectation of what that experience should look like. How does that extend to a restaurant? If I call in and place an order to pick up myself, or if I come into the restaurant to sit down, all of the experiences and the ways a customer interacts with your brand should be the same. You should get the same level of service, the same level of experience. If you’re going to introduce some new revenue channel or opportunity, and it adds friction or creates a disjointed experience — online versus on-site, or whatever it is — don’t do it.
Shawn Harrs: That’s right.
Jay Altizer: “Throwing the org chart at the customer” makes me grin because it’s hard for businesses, I think, to start with the customer and then think backwards. I’ve caught myself saying around here that the customer is like the honey badger — the customer doesn’t care. You’ve got to start with what the customer needs.
All right — let’s shift gears and talk about partners a little bit. I loved what you had to say about change and trust. Your partners have a role in that. Talk to me about what good partnership looks like, and what you’re hoping to see — or hoping not to see — out of your technology partners and suppliers.
Shawn Harrs: Focusing on partners that are suppliers of technology — a good partner understands my business. I might be a restaurant from one category, regional or national, or a specialty food category within a segment of the restaurant business. Having a great technology solution for the restaurant industry does nothing if the partner doesn’t understand whether they have a great technology solution for my restaurant.
Understanding my business really matters. Know what the drivers of cost are, what my cost structure looks like — we mentioned labor, for example. What is my labor cost structure compared to other restaurants in my segment? What is my service model? Front of house, bar or no bar — there can be a lot to it. There are a lot of ways to do that research and gather that intelligence. Don’t lead with how great your technology is — lead with how well you understand my business and how you can solve problems for me.
Great partners will also tell me when they’re not the best fit for something. I value that highly. They’ll say, “I’d rather not try to force a square peg in a round hole, because I understand your business. But if you ever have a need for X, I can guarantee we’re the best at that — give us a call when you’re ready.” I guarantee you I will call them. That really is a mark of partnership — knowing your wheelhouse and being candid. Nobody wants to be on the other end of a force fit.
Now once we’re working together — building trust is important. I have to build trust with the operator, and my vendor partners are an extension of myself. I can’t hide behind “well, our partner…” — I’m the person showing up and talking to my customer, which is the operator. Building trust means follow-through on the things you’ve committed to.
Going around me and reaching out directly to the CFO during the pre-sales phase — things like that don’t build trust. Understand the organization. And if you need help with the business case, be frank about it: “We’re happy to help you build a business case for your CFO.” Things like that build trust.
We also talked about scale — restaurant businesses with 100-plus units have different sales cycles. High seasons and busy windows are going to drive the sales cycle, and there are times when you’re simply not going to be doing anything. If you understand my business, you know that. Don’t be impatient and try to say, “Hey, we’ve got an incentive if you sign this month” — clearly, you don’t understand my business. For most businesses, certainly at year-end — and for fish restaurants in Lent, for example — knowing the business cycle, the annual planning cycle, the budgeting cycle — those are all things a good partner knows. Trying to sidestep them doesn’t build trust.
And the third thing: once we’ve started an engagement or completed an implementation, the same way I’m the face of technology or leadership to the operator, whoever I engage with primarily from the sales team — companies will often hand off to a post-sales customer success team, and as long as that transition is clear and clean, that’s fine. But you can’t just sign a deal and walk away. Bringing my success is the third criteria.
Being a true partner also means investing in the kinds of pilots and field tests we talked about earlier — not just booking the revenue this quarter and moving on to the next thing. That is the kind of technology vendor that becomes a good, enduring partner, because you’re investing in the technology not just for the life of one agreement. I don’t want to have to replace it again in three years. I want to be leveraging the innovation that this partner is putting into their product on an ongoing basis — being part of their customer advisory board, having input into their product roadmap, hearing the voice of other customers. That way the platform I’ve invested in doesn’t require me to disrupt operations again in three years with a replacement.
Jay Altizer: Well said. Part of it is honoring the relationship you’ve built during the sales process. And personally, how else are you going to learn, get feedback, and improve if you’re not showing up and continuing to engage? Maintaining those relationships is paramount — that’s where the feedback comes from, that’s where the innovation ideas come from.
All right — I think we’ve covered most of our topics through partnership. Let’s spend a few minutes on adoption, and then I think we’ll be in a good place to take some questions.
For any tool, there’s a period where you go through evaluation, get some early wins, get some buy-in, and at some point you’re scaling out — trying to get not just the technology, but the processes represented in it, replicated and in use across hundreds or thousands of different locations. It’s always classically difficult to get communication through the funnel down to the management team at the location level. What are some do’s and don’ts for not just getting people to log in, but really getting them to adopt a better way to run a process that creates better cost control or a better employee experience?
Shawn Harrs: Adoption happens most reliably when it’s a capability that has to be used as part of a revenue process — there’s no way to sidestep it. Adoption can fail when it’s not part of a core process. In the example of payments, if there are two ways to take payments and you start to see the percentage uptake not moving the way you hypothesized, you’ve got to be looking at that data every day — almost maniacally. Because the operator just isn’t telling you why. They’re busy, and they’re getting their payments processed.
Using labor as another example — if there are two ways to publish a schedule and you’re not seeing the adoption you expected, and after the fact you’re seeing high variances to plan, that’s a lagging indicator. What you should be looking at in real time is the system-generated schedules: why is there such a high variance between what the system produced and what’s actually getting published? You’ve got to be looking at that data in real time. That’s how you understand what adoption is actually looking like.
Because given the ability to go two routes, the operator is not necessarily going to go the route that is faster, more beneficial to their EBITDA, or better for their prime cost. They’re going to go the route that they like, or the one with fewer steps, or less friction at that particular time of day. There’s something there that you haven’t caught yet.
It can’t be one and done. You’ve got to partner with operations — whether it’s operations or HR handling communications out to operators — to maintain those drum beats. Have the use of that particular technology come up regularly. Something like: “Last month we rolled out Technology X — great job, everyone. We’re still in the learning curve and we’re 50% there in terms of adoption. Here are the key things to focus on this week.” Just hit the two or three things the data is telling you the operators could do to increase adoption.
Jay Altizer: Yes — something we see a lot is: just do this one thing. Here’s why, here’s the impact, just do the one thing. If you can break what you need done into bite-size chunks like that — there may be 20 things you need them to do, but if you’re looking at the data well, that one action can really move the needle. And once that one action becomes muscle memory, you move to the next.
Operators have so many things to focus on every day — product recalls, menu changes, and so on. Earning your time in the operator communication cadence and asking for that one behavior change to help continue improving adoption is really valuable. Gamify it if you can — recognize performance at a regional leader level. “Here’s the regional leaderboard — Region X is at 85%, they’re trailblazers.” Use the positive peer pressure — if it can be measured, lean on that measurement.
A colleague of mine in another webinar talked about a growth goal that was really opaque when you got down to the store level. They simplified it to: how many cars have been through the drive-thru today? They put it up so every location could see how others were doing, and he said you could walk through any hour of the day and see them say, “They’ve got 80 cars — we need 20 more.” They made it easy to understand, created a healthy, positive element of competition, and made it achievable.
Let’s wrap up. You’ve given us a ton to chew on and a ton of practical tips. Let me try to restate a few summary points and then you can tell me what I missed or add any closing thoughts.
A few themes I heard: engage the operations team early and get ground-level information. A lot of transparency — whether that’s piloting the technology or setting it up in a way where your operations teams can understand it. Having partners who will help you create that change, who will listen, and who won’t get in your way as you’re trying to run programs. And I really like the way you think about doing one thing at a time — just do the next right thing.
Anything I missed that our audience should have in mind as a takeaway?
Shawn Harrs: You restated the things we covered well. A couple of additional things I’d leave with the audience:
Since we’re talking about labor — one of the things that is very valuable, with the data and capabilities we have today to drive adoption around a labor system in a large organization, is to show operators the comparison. This is what the system produced. You published your schedule this way, but here’s what the system suggested. Then, after the fact — once guests have come in, labor has run, and payroll is in — compare what actually happened to what the system produced as the labor forecast. Show just how accurate these capabilities are today.
Twenty years ago, when I built one of these systems from the ground up manually, capabilities like that weren’t available off the shelf. The Software-as-a-Service capabilities for labor planning and scheduling today are so sophisticated and so much easier to turn on. They provide the operator with the ability to see, week after week, that the system is producing forecasts that come right in line with what the actual demand was. Showing that, and building that trust — getting the operator to say, “I can trust this, I can let go” — is really one of those key things.
Another thing I’d leave your audience with: in the upfront conversations with the operator, consider where your technology initiative actually ranks on their priority list. As technologists, we’re so close to the technology that we can’t always see the forest for the trees. How does this rank against a store build-out, new equipment in the kitchen, a staffing challenge? Operators and brands that are thoughtful about this will try to get the change calendar and the communication calendar for what’s going down to the store — because there’s technology stuff, menu stuff, safety stuff, labor stuff, regulatory stuff. The windows to communicate with operators are noisy. Does your initiative rank in the top five things on the operator’s mind right now? Or is it the dishwasher that keeps breaking, or the ice cream machine? That’s good insight to have. When you understand where your initiative — which requires a lot of change, a lot of resources, and capital to make happen, especially in a 100-plus-unit business — actually ranks for the operator, a little humility goes a long way.
Jay Altizer: Absolutely. Those are the two other things I’d add — super helpful. Shawn, this was absolutely fantastic. I learned a ton as always, and it’s always great to catch up and hear your perspectives. Thank you so much for making time.
Shawn Harrs: I was very happy to. I appreciate the opportunity to share some insights.
Jay Altizer: Christina, you want to come back on and maybe take a question or two before we wrap?
Christina Lau: Absolutely — we probably have time for one question, so I’m looking through and I’ll pick from the list. The question for today is: What is the toughest habit to standardize across stores?
Shawn Harrs: From the CIO seat, the toughest habit is getting adoption of the processes that new technology brings about. We talked about this a bit — with labor scheduling, if schedules are built using new sources of data and new scheduling parameters and rules, breaking those old habits, especially in a restaurant chain that’s been in business for a while with operators who have a lot of experience, is a tough nut to crack sometimes.
Jay Altizer: Fantastic. Well, let’s leave it there. Shawn, I owe you yet another favor — this was great.
Shawn Harrs: I appreciate the opportunity.
Christina Lau: Thank you to all of our audience for tuning in today. We host webinars every month here at Fourth, so we hope to see you at the next one. Have a lovely rest of your day, everyone.
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