Geoff Seper from Teamcore joins Mike to discuss the role that Algorithms play in OSA measurement and alerting.

Geoff shares how algorithms can be used by retailers and suppliers to measure OSA without having individuals perform audits. Algorithms have become a powerful tool to measure OSA especially for higher velocity items and alert retail employees and third party providers of the OSA issues.

Donnie Williams 0:04

Welcome to Season Two of the SCMRC Lead podcast featuring epic supply chain lessons from our industry partners. My name is Donnie Williams and I am the Executive Director of the Supply Chain Management Research Center in the Walton College at the University of Arkansas. Season Two of the podcast will be hosted by Mike Graen. Mike is the director of the retail supply chain initiative, and this is a strategic partnership within the SCMRC. The goal of this initiative is to surface the challenges and opportunities of on shelf availability or OSA, focusing on the concepts tools and technologies driving retail OSA. Season Two will feature a dynamic guest list of retailers, CPG suppliers, solution providers and industry leaders to drive collaborative efforts and advance learning within the industry. Thank you for joining and enjoy the podcast.

Mike Graen 1:02

Geoff Seper 1:41

Good afternoon, Mike. Great to be here.

Mike Graen 1:43

Awesome. Hey, we're really interested in the topic that you have to share with us today. An important part of on shelf availability is algorithms that allow you to alert you when things are not on the shelf the way they're supposed to. And that's really what we're going to spend some time doing. Before we do that, we're going to introduce Kiara to us. Kiara is a junior at the University of Arkansas as part of the supply chain. Kiara, why don't you go ahead and introduce yourself for us.

Kiara 2:09

Hello, Mike, I'm so glad to be here. I'm glad to take this opportunity to learn more from professionals about you know, the supply chain issues because it is such a big deal right now in our society. And I'm just glad to be here and learn from you guys.

Mike Graen 2:23

Awesome, welcome. It's great to have you. And we want you to be part of this conversation, we may even put you on the spot and have you ask a question or two during this time. So Geoff, I want to I want to kind of open it up to you the whole idea that we have tried to build this platform on is getting product on the shelf for either a customer to come into a brick and mortar store and buy or to order online and pick it up in store. And we've all been to stores before. And we've seen really bad things situations where you've gone in and tried to buy something I use an example in a class this week at the university about where I tried to go in and buy something, they didn't have it, I got so frustrated, I pulled out my phone and I ordered it from Amazon, they use their Wi Fi signal to orders from Amazon, which is kind of hilarious. So before we get into the the algorithmic solution, have you personally had a situation where you went in to try to buy something and you thought they had it and they didn't? And what kind of reaction you had of that?

Geoff Seper 3:24

Yeah, you know, it happens all the time. And I think what ends up happening, though, is the disappointment you experience varies by person, and that's going to drive their subsequent actions. You know, for example, if I'm incredibly loyal to a brand, I may not buy a different product, you know, and I may end up going somewhere else, I may leave the store and like you said, you know, I'm gonna shop from a different retailer. Or if I can only buy a certain version of a product. For example, if I'm gluten intolerant, I can't switch, I can't go to another bread that's in the store. And so if I'm in either one of those situations, it's possible that both the retailer and the supplier have lost the sale. And not only that, but you know, retailers and suppliers talk about the lifetime value of customers. And so you may not just lose today's sale, you may lose all those downstream future sales as well. And, you know, you talk about your Amazon experience, I've got a retailer, it's about a mile and a half from my house or a big box and they're in stocks are consistently bad across almost every category. And they've been that way, even before COVID. So we never go there. And that sometimes means us driving, you know, two, three times as far to go to a competitor, but we'll do it because we know they'll have the products in stock.

Mike Graen 4:28

Gotcha. Gotcha. So it impacts everybody.

Geoff Seper 4:31

Yeah

Mike Graen 4:31

and that's what's fun about that. And every time I've asked that question, it hasn't take somebody very long to go. Yep, that happens all the time. And it's pretty frustrating for sure so. So you've got a unique career and unique background. You are with a retailer before I believe you were, you started was a Target or did you have an experience in retail before that, Target?

Geoff Seper 4:50

I was with Target.

Mike Graen 4:51

And then so you had some experience as a retailer and then you sort of looks like kind of switched into the solution provider business. And a lot of that seemed to be like algorithmic kind of providers that provide alerts based upon data and algorithms to alert people when there's out of stocks. We talked to Field Agent at an earlier podcast, and they have a pretty good model of set up a job, go and do a physical, put your eyes on it. That works pretty well, if we're talking about things like cosmetics or razor blades, or something that's a little lower velocity. That's pretty hard to do. And pretty expensive if you're going to try and do that for detergents or cereal, etc. So to walk us through the role algorithms play in terms of trying to identify where you have issues?

Geoff Seper 5:40

Yeah, it's a great question. And like you said, there isn't a one size fits all for how to solve out of stock situations certain, like you said, certain categories are better for certain solutions, traditional store audits, putting cameras on things, etc. But, you know, I'm throwing up a slide here that, you know, helps walk you through, you know, how the algorithmic approach works. And so everything is predicated on the data, okay. And so, you know, if, if we got good data, and we got the data we need, then everything flows nicely. And so we just got to start there. So you know, what we do is we collect, and by item, by store, by day basis, the following information, we got to know what kind of inventory, the situation is, you know, so is it at the distribution center, or if it's a direct store model, then you know, what is going into the distribution center, what's going into the store, we got to know that, and then we got to know what is going out of the store, okay. And so we get by item by store by day inventory and sales data, we take two years of that information, and we start to create forecasts. And so what that enables us to do is when we continually get the future data, like tomorrow's data, and Saturday and Sunday, and you know, et cetera, we can then match up like what we expected to have happen versus what's actually happening. And now throw up some flags. Okay, so we do these daily comparisons, what that ends up doing is it enables us and using machine learning and learning and artificial intelligence, you know, it enables us to develop what we believe the situation is and what the root cause is and then generate recommendations for the actions to take. And so that information, you know, those actions then get sent out to the people that need to take those actions, you know, and those could be maybe at a headquarters role, it could be a supply chain group, it could be a retail operations team, etc, in house, you know, more of a replenishment team, it can also be sent out to the stores. And what I mean by that is some of these issues you can fix outside the store, you can ship more product to a store that's maybe got a low on hand position. But some situations, you got to go into the store to fix it, right, you might have a phantom inventory situation. So you got to send somebody in to the store to figure out what's going on with that situation. So they can then correct that. So these alerts, these actions, then get sent out to both sides of the equation. And that's what we believe really enables you to solve for some of those out of stock situations. Then finally, and this is really mission critical is that you've got a closed loop process, it can't just be sending information out into the atmosphere and the universe, and then not knowing what's happening. What we end up doing is we then get feedback back from those groups to say, yeah, you gave me this action to take and yeah, I took it, okay. Because if they didn't take the action, you shouldn't see a change, right? If they took the action, then we know there should be a change, you should start to see we'll start to see sales start flowing again. So that allows us to measure, you know, are we being accurate with what we think is happening, and then feeds the information back into our algorithm algorithm that makes it smarter. It says I thought it was the situation you took you went into the store, he saw it was that situation? Great. And then it allows us to, you know, then start to recap, recapture those sales and report on that. So we can measure, basically ROI by activity.

Mike Graen 8:48

So fascinating. So so help me understand that. I think number one, and number two, make sense. Help me understand number three. So I have an item that normally sells two to three to four a day. That's it, and it has consistently for the last 30 days. At what point in time do you go, I think we have a problem. Because if it just sells 0 1 day, I would assume that could be it just didn't sell that day. So how do you know when to raise the alarm? And does the volume of that item help to predict when that alert would you generate it?

Geoff Seper 9:22

Yeah, I mean, the old way of doing things was I would do prediction for the entire store chain, I would I would look across and I'd say okay, well, here's an anomaly with this particular store. Okay, that's not helpful because, you know, some stores have higher velocity than others. Okay. And I may be doing it more of a category level. Okay, well, that's not helpful either. Okay. You may be a new candy bar, you know, it's a new product introduction. And so that's going to behave very differently than you know that you know, one that's been out there for 30 years. And so what we end up doing is creating a forecast at that again by item by store by day level. Now that should tell us that okay, historically, I'm going to be selling this many products on a daily basis. What it'll do is it'll flag it and say, Okay, I think there's an issue with this particular situation. It may take a couple of days for that to say, yeah, it truly is that situation. So it may, may not be, you know, okay, well, I sold on Monday, I didn't sell on Tuesday, oh, going to store on Wednesday, gotta fix it. It may not be that unless, we've got enough history that says, You know what, yeah, if you're not selling on Tuesday, there's something wrong. Okay. Cuz you know, you should be selling as many units every single day, every single week, again, for that specific SKU, for that particular store, on that particular day. That's the level that has been enabled based on the technology that exists today. And that's what's been so exciting in my career is all these things that people have talked about wanting to be able to do get that granular. You can do it now, you know?

Yeah, that's awesome. What percentage of the time in step number five, when that person, I'm assuming it's a store associate goes to the shelf? Does it actually give them a situation where there really is a problem? Are there times they go to the shelf. and, hey, everything's there, and it's fine? And is that a real high percentage, a low percentage? How do you think through that?

So, I mean, it's continually evolved over time. And so it's gotten to the point now, where, at least for the company that I'm working for right now, we're about 90% accurate on that. And so, now, that may seem like okay, well, you know, I'd love to be 100%. How come you're not 100%? I'll tell you, you know, in the past, you know, 60% was good enough. And so things have come a long way in the past three, five years, where, you know, you're not sending people a check on things that aren't true, right. And I'll tell you just, in general, you know, this, the whole evolution of this, the old way of doing things was somebody would go into a store with a static sheet of paper and say, All right, now I gotta go check. If this is in, you know, in stock, I gotta check if there's phantom inventory, I gotta check if the price is right, I gotta check, you know, et cetera, et cetera. And they just goin through, and they're just doing the same thing every single day, right. So even a 60%, you know, rate was good back in the day, because then you'd be checking on things more frequently, that were truly issues versus checking on things that were there wasn't a problem, everything was fine, you know, and you're wasting your time going to this store and trying to check on stuff. Because that store is absolutely fine. Move on to the next store and fix the next store's problems. So

Yeah, and you can get it up to probably 100%, you just have to wait three or four weeks to make sure absolutely, positively sure you're not seeing it sell anymore. But then you'd lost a month for the sale. So there's a balance between valid alerts, and waiting so long that you've lost sales and disappointed customers in the past. And I don't know how you measure that part of it. But that's a real part. So you got to balance, I need to be pretty sure that this is a root cause. Because if you send a bunch of alerts in step five, and 90% of them are false alerts, and they're invalid. People just start pencil up and go, Yeah, you know, these are all fine. And you don't want that either. So

Now absolutely. And in one way that we try to get around that too, is again, it's all predicated on the data being available. But what you can do, I mean, because when you think about it to your point, it could be out of stock right now. And in two days, there could be a shipment showing up and it could be fixed just through your standard replenishment process. Right?

Right.

And so what you need to be able to do is also have those data points. Okay, so I need to know what's in transit. And so if I've got that data, I can pull that out and go, you know, what, it's an alert looks like we're out of stock. Oh, well, you know what, I'm not going to send somebody in the store, because that shipments just about to arrive. And, you know, it should be on shelf in the next 24, 48 hours, you know.

Or you know, especially given COVID, you look at the supply chain, there's no supply chain, there's no products in the pipeline. You may be absolutely right, there's an out of stock, but there's not a thing they can do about it. So, yeah, I alert them. Right. Kind of thing.

Right. Yeah. And that's, I mean COVIDs been a great example that too, because when it's really done, it's pressure tested the entire system. So you got some cities, for example, that went you know, through the first round of COVID. And they did stock up, okay, great, they cleaned out, they clean house in some areas didn't do that. They might have had excess inventory. But when you can look at your system in real time, you can say, Okay, well, great. I don't need to be centered anymore to those overstock stores. I want to get it out to the other ones, you know, and then you can then start to forecast when you start to see another like, Okay, I got omnicron coming down the pike, I'm probably going to see the similar behaviors. I can then start to make adjustments in advance of those things happening and getting the product to the right stores in advance of the spikes that you believe are going to happen. Right.

Gotcha, gotcha. So what is the people in step number five in this, is that always the store associate, the Night Stalker, the department manager or are there outside parties that actually take care of this kind of work as well?

Sure. Yeah, it varies. I would say the three groups that are the most common would be the retailer team, if, if they've got people that want that are getting these alerts, they're going in, and they're making those changes. So that would be one. Two would be if a supplier has their own field teams. So there are some manufacturers out there that have their own teams that go out and check on products merchandise, and then finally, our brokers or sometimes referred to as sales agents. And that would be a third party that would be hired either by this buyer most often or in some cases, retailers. And that group is basically the arms and legs of the their client. So if it's supplier X, they're saying, Look, you know, supplier X might be getting the alerts, and they're sending them on to their broker partner to say, Hey, these are the issues that I'm experiencing, I need you to go into store and fix these issues. So those three parties could all use, you know, these solutions. And even in conjunction, I mean, if everybody has the same information, then you can say, look, the store teams are gonna be doing these types of changes, and, you know, the broker or my field team, are gonna do these type of changes. So you're not all looking at the same issues. Right?

Got it. So give us a success story, I'm sure you've got some. Tell us about a situation they, you had a retailer and you had a CPG company, using your tools and kind of what a result you get, you don't have to disclose who they are for confidentiality reasons. But so give us a reasonably what kind of what kind of a business benefit should we expect if we invest in this kind of a solution?

Yeah, that is incredible point. I've seen more than enough blind reviews where items get discontinued and that's why I'm sorry, we have dogs barking in the background. Kiara, you got a question for Jeff?

Yeah, I do. So we have talked a lot about shelf availability, and you know, things being out of stock and stuff like that, but with the way COVID has affected, you know how consumers shop and the supply chain, does this algorithmic approach apply to like online shelving like online like when you need to tell those customers that's out of stock? Or tell customers that may have already purchased it like we don't actually have this product for you? So like, what's your approach for the online traffic in the online shopping that we've shifted to?

Yeah, it is a great question. And so when I mentioned earlier on shelf availability, you know, it's abbreviated OSA, OSA, the online version is OLA, online availability. And that is starting to pick up momentum in the industry. And what's most important, I mean, unless you're a pure play, like an Amazon, and that's all you're doing is online, if you're gonna, if you if you want to do it and do it right, you really have to look at both of them. If you're brick and mortar and ecommerce, you have to look at the entire picture, because your customer is shopping that way, to your point. And so if you don't have your arms around the entire ecosystem of what's going on with your products, both in store brick and mortar and online, you're gonna be you're gonna have gaps in bad customer experiences that you don't even know about. So, for example, if you're saying, Look, I'm gonna buy online, and I'm gonna shop from store to my house, which some of the retailers do that's going to, that's you're now down on one product in store, right? Well, what if you know Kiara, you went in at the same time that I purchased that product, and it was just pulled off the shelf to ship, and now you're in there, and now there's a hole in the shelf? Well, okay, that means that the retailer and or the supplier didn't have their arms around the entire situation to understand exactly the entire inventory position, and all the activities that are going on, you know, to create those out of stock situations. So yeah, I mean, the way that companies are looking at it is the same way brick and mortar is online. So they they're looking at the online inventory, and can I fulfill all that? Am I what is going on with my in store? And then what all do I need to you know, monitor and manage both of those simultaneously? It's not easy, but it's doable.

Okay, yeah, I was just with COVID, I feel like, I hear a lot of people saying, like, when are we going to go back to normal, but honestly, like, this is our new normal, you know, we've all had to adjust. And so it's something that, honestly, I didn't really know how much it was going to affect us. But things are out of stock a lot more often now than they ever have been, which is also a part of like panic buying and things like that, but, and even the way I shop, I shifted that and so I'm, you know, going into this supply chain, you know, the supply chain major, like, I just want to see how things are changing in my time in real time, and how I can, you know, find new ways and innovative ways to, you know, to work on this new normal and these issues that are occurring right now.

There was an interesting study that came out chain store rage, and I'll send this to you guys outside of this. But there's a study done in November that they reported on, it said two thirds of shoppers plan to return to brick and mortar. Okay, so there is a new normal. And I believe that we've been basically accelerated, I think COVID basically accelerated what ecomm was going to be doing to retail eventually, right. But that being said, there are some categories I think, are going to be more effective than others. Right? You know, some people, you know, put maybe toilet paper on subscription buy, they're going to have that thing shipped out every two months, or whatever it is, and so they're never going to go back into store to buy that toilet paper. But certain products, you know, they're probably still gonna go to the store to get those things, right. So it's that the new normal is going to be different by category. And it's really important to understand what category you're in and what that's gonna mean for your business. Right.

Right.

Yeah, Kiara, my response to that would be, I don't think anything's going to be normal in the future. I think we are now experiencing the new normal. And here's the good news, brick and mortar stores are still there. Not all being shipped to you via Amazon. So all the retail stores go away. It will be a constant balance between a brick and mortar store and omni channel, where seamlessly from a customer perspective, I can secure products both ways whatever is most convenient for you. Now, as we talked the other day, if the accuracy of inventory in my store is 50 to 60%, I now have to potentially create a brand new set of inventory which is what does that inventory in the store that I'm going to pick for a customer that will never be on the shelf? Well, if I'm already struggling to get my inventory accuracy of what I've got on the shelf versus what I have in the backroom, now I'm adding a third one, I guarantee you it's not going to get better, it's gonna get more confusing and wrong. But here's the other thing is Geoff's got an algorithm that he could run on both brick and mortar sales separate from online sales and tell you exactly why things are slowing down from an online sales perspective and give you the exact same alert you got before. So it's a, it's a pretty thing. Now, Geoff, they do have other things like Neil picks and substitutions etc, which obviously would feed that algorithm. But no matter what sending arms and legs to look at something on a shelf is not the most effective way to see if you've got product on the shelf or not, it's gotta have a, for a lot of the items, if we've got 125,000 items in the store, we cannot go to that level of detail, because we'll have people all day long just looking at shelves. And that's not an effective way of doing it.

Well, I mean, going back to the COVID comment, too, I mean, that that has impacted the ability to even send bodies into stores. I mean, because retailers, brokers, supplier teams, they're, they're all they got people that are sick, and they can't even go into the store. So you got to take your remaining resources and make those even more efficient. So the last thing you need is people going into stores where there aren't problems, you know, and trying to check on things that aren't issues, you want to have that dynamic intelligence given to them every single day that I need to go to this store and do this, you know, these two things when I'm in that store, and then move on, you know, so it's trying to make existing resources as efficient as possible.

So help me understand step five, and your process here. Because here's what I've heard. I think I can do 1, 2, 3. I think when the alert gets to step number five, too easy for people to go. I'm already busy. Yes, there. Yes, there. Yes, there. Yes, there. Yeah, pencil whipit, we call that pencil pencil whipin. So when we use an algorithmic approach, how do we how do we make sure if we're going to do all this work, the person who's getting the alert actually takes the time to do it right. And is there any kind of KPIs to make sure they're just not going, I did it. I did it. I did it. I did it, even though they haven't touched a thing.

Sure. Yeah. There. That's, that's not uncommon. And there are basically, alerts that you'll put in place. So for example, we do like geofencing. Right. So first of all, you want to make sure that person is even in the darn store, right? They can't just be sitting on their couch going, Yeah, I went into store, I checked on these things. Like, Okay, number one, we verify they're in the store. Yeah, no,

Kiara, Kiara, put your phone down. Quit, quit responding, in all those alerts, you can't do it. Doesn't work that way.

Then number two is the what ends up happening again, this is just the beauty of the data and using artificial intelligence is you start to then understand what real is right. And so as you start to see, you know, person, you know, ABC go into a store, yeah, they're in store, but they just said, Yep, everything looks good, move on, everything looks good. All of a sudden, that just throws up a flag. I mean, day one, that is just a warning flag, that we got to keep an eye on the situation, if we keep seeing these types of things. We know it's the person, it's not the alerts. And so I mean, it's those types of safeguards that are in place that just, you know, it allows you to evaluate not just, you know, fixing the issues, but evaluate your team as well, you know, and were they following the protocols? Do they, you know, the, the algorithm told them to go to a store, you know, C first instead of a, they normally go to A, then they go to B, then they go to C, the algorithm says, You know what, go to C first because C has the biggest issues, and it's gonna get us the biggest return on investment, if you go there and fix those issues. If they went to a first, okay, look, you're not following, you know, what the algorithm is telling you to do. Go to C, do these things. And so it allows the people that are managing those retail resources to, you know, do training, you know, to help coach their teams, or if they can't, if they're not coachable, then they can make the decisions, you know, they need to make, but it helps you evaluate that, as well as are they taking the right actions and being efficient in store? So for example, it might take me, you know, a half hour to resolve an issue that might it might take you 10 minutes, and you're the average, right, and I'm an anomaly. It's just taking me forever. Okay. Well, Geoff, why is it taking you 30 minutes but everybody else is only taking 10. So I mean, you can get down to that level of of information. So you know, what's going on, and are these people being as efficient as they could be.

Yep, great point. Yeah, I shared I shared this if you'll let me share real quick, Geoff, I shared this screen for the class at the University of Arkansas yesterday. So we talked about this one, this is a this is an algorithmic approach. It's not your slide, but it's something I think it's very relevant where I'm literally got two items, and I'm selling 15, 14, 16 And they both dropped to zero. And then we send an alert and going, Hey, we think we have a problem. We send two alerts both of them say, yep, we fix the alert. And the recovered sales suddenly takes off for the green one, but it stays flat for the red one. Guess what, you may have said you did something but I don't believe the red one changed anything I believe, and by the way, suppliers are starting to look at their business of recovered sales, as some of the biggest brand initiatives and new item launches they could do is just getting recovered sales, it's changing the paradigm, I don't have to introduce a new brand, I just have to be measuring that recovered sales, not incremental. It's not like I'm adding a new flavor form or whatever. I'm just saying, this is a situation where 55 units were sold, recovered sales, because somebody got an alert from you guys reacted to the alert said they took care of it. And we see the resulting sales over the over the next several days. So I think there's there's other KPIs. Because if it was really selling 11, 12, etc, and it went out of stock, and then you get back on the shelf, it should start taking off again.

Absolutely. Absolutely. And I mean, if I could just throw a one other slide too I mean when you talked about the recaptured sales, what we've been talking about almost exclusively is the the availability of the product. Right. And that is that is part of it. The other thing that we've also uncovered along the way, is the fact that okay, is that you've got the situation here, right, we've talked about the product number one isn't on the shelf, or like I described earlier, it's been phased over there, you know, there's something in there that it shouldn't be there, it's blocked by another that was that was brought by another product, you got phantom inventory. These are all your traditional on shelf issues. And those are all precluding sales, right? Now, let's take that even farther, these are all sorts of other issues that go on in store, got the wrong planogram, you got an out of date promotion, wrong price, displays not executed or accurate, incorrect or missing tag, all of those things impede sales as well. So it's informing the all the other activities that should be happening while you're in store as well. Now, that may not be included in an OSA metric per se. But I'll tell you right now, it's still a big chunk of sales. And so if you've got somebody in and it's being able to make these other changes, send them in and get them even more efficient by knocking on all these other things, too. So that that recaptured sales that you mentioned, restarted sales, it's critically important. There's a lot of things that can impact it.

That's a good, that's a great slide you got there too. That's a good slide to share with all your friends and family when they go why aren't we on the shelf? Is it those boats out the ocean that aren't being unloaded? Is that the reason? Because that's, that's what I hear all the time. Oh, you're in supply chain? Can you figure out how to get those container ships unloaded, that we're not getting bread, milk and cheese from container ships, folks, we're just not, I'm sorry. This has been extremely helpful. Kiara, do you have any other any last questions before we kind of wrap this up?

I don't think so. I'm just, it's just awesome to see, you know, hear from you guys. And to just see this shift in supply chain and how you know that the people like you guys are doing something about it. And that, you know, we're gonna get back to making sure that consumers get what they need when they want it. So

You know if we if we fix all the problems Kiara, we won't have a job anymore. So we got to leave a few straggles back there. Geoff, I gave her and her classmates the opportunity to go to four or five retailers over the weekend and check out on shelf availability of razor blades. And they're going to come back and they're going to present it back to the Procter and Gamble leadership. So this will be very interesting to get their perspective of Okay, how's Walmart versus Target versus Walgreens versus who's the other one I got Harps. How in the world if you're going to shop for razor blades, which one would you go in? Why? What kind of out of stocks they were, because again, at the end of the day, if you have any confusion about this stuff, go to the shelf and look at the shelf, because that tells a huge story.

You know what, and to just tag on to that I was talking about lifetime value before. I mean, that razor blade model is front and center. I mean, they talked about how if you can get somebody that feels the need to start shaving in their teens, if you can get them to buy your brand. They're almost loyal from day one, it's really hard to break them from that. So if that product is not available when they're, you know, even 15, 16, 17 years old, you could be costing yourself 60 years worth of sales. So I mean, it is it's an incredibly impactful situation. You know, it's much bigger than just that single sale.

Great point. Great point. Geoff, thank you so much. This has been incredibly insightful. I really do appreciate. And I certainly we will we will link the Team Core LinkedIn profiles, so people want to contact you for any follow up stuff. Great. And Kiara, guess what, here's the here's the good news for you. Job security, you will have job security in the supply chain because Geoff and I are not taking on a responsibility to fixin all these problems. We just are trying to have our time and work every single day. So

It takes an army.

More than an army I don't know. Hey, thank you both very, very much. I'm really really excited about some of the stuff we've talked about and we look forward to to share another news later. So thank you and take care.

Thank you guys.

Thank you for taking the time for this epic discussion and special thanks to Mike Graen for leading the retail supply chain initiative. On behalf of the Walton SCMRC, we are delighted to lead with you as we learn, engage, address and develop all things supply chain to lead the world of commerce from Northwest Arkansas. Have a great day.

Transcribed by https://otter.ai