Lisa Johnston: Hello everyone and welcome to “Dodge Data's Blind Spots and Unlock the Power of Effective Retail Execution.” My name's Lisa Johnston and I'm senior editor at CGT. I'm looking forward to diving into today's topic, which explores why retail execution has become a top priority for today's consumer goods companies. We're going to share how some of the key players are winning in the marketplace by getting this right, and we're going to get into why it's become so challenging.
Of course, we're going to look at the role that technology plays in successful retail execution and how it can be leveraged to gain that crucial competitive edge. Today's event is centered around the findings of a whitepaper we recently published, called “Unlock the Power of Smart, Effective Retail Execution.”
Joining us today is Cheryl Perkins, CEO of Innovationedge, Pete Billante, CPO of Repsly, and Andy Walter, strategic advisor and retired P&G executive. Lastly, moderating today’s event we have Joe Skorupa, editor at large of RIS News, CGT’s sister publication. With that, Joe, the floor is yours.
Joe Skorupa: Thank you, Lisa. One of the things I'm very excited about for this webinar, in addition to having the speakers that we have lined up for a great panel, is that optimizing retail execution capabilities is one of the unsung and under emphasized operations in the CG business. It's always been considered a key component for growing sales and profits for CG companies, always been a complicated operation with numerous moving parts.
Demanding consumers are pressuring CG companies to ramp up retail execution strategies, while, at the same time, two huge challenges have recently entered the world: the global health crisis and massive supply disruptions, or supply pain disruptions, as some people call it now.
These have certainly become more important in helping CG companies solve them. To stay competitive, CG companies must create and capture value in retail execution operations, and the best way to do this is by using a nimble set of technology solutions. That's part of the key topic and things we are discussing today.
Let's turn to Andy Walter to get our discussion started. Andy, what makes retail execution so challenging for CG companies to do well? What are some of the key moving parts that CG companies need to focus on to make retail execution operations more effective?
Andy Walter: Well, Joe, you hit on it. Obviously, this area is super critical to companies. At P&G, I was leading all of our commercial services. This was one of the areas that I was accountable for end-to-end for the company. Really, it's three things that make this so difficult:
1. You're really coordinating a team, both inside the company and outside the company. You've got distributors. You've got merchandisers. The partnership with the retailers and the like.
2. There's lots of moving parts as you think about the different countries, the number of stores that we're talking about, the number of SKUs.
3. The supply chain is always a challenge. How do we get the right product in the right place, clustered in the right stores and all that, and have transparency across that?
Now, all of that was difficult to do two or three years ago. Then, add in the health crisis and all the challenges that companies are facing now, and it got exponentially more difficult. At the same time, you're seeing an incredible acceleration of e-commerce, direct-to-consumer and the like. Now CPG companies are faced with managing that whole complex area in a more challenging environment. That's why this is one thing you've really got to get clear on your strategy, and this technology is going to be key for the success.
Skorupa: Andy, that's why this is an unsung part of the CG world. You mentioned you were in charge of this aspect of it end-to-end at P&G, it's certainly true that they're one of the best at it. However, there are a lot of players that have to rise up to that level.
Cheryl, let's turn it over to you. Why is the challenge being more complicated by demanding consumers, who are challenging CG companies to raise the ante and the retail execution operations? Why is this component so important for CG companies to focus on today?
Cheryl Perkins: Today’s consumers are no longer content with average store experiences. We're looking for that store experience to be a winning experience. Even all of us on this virtual webinar right now are inspired, engaged, and want to feel safe and comfortable in a retail setting. That is really hard right now, especially during the pandemic. Consumers are seeking an immersive experience and still convenience. Convenience was always a driver in the past. It's not going away, that's an ante, but the difference now is that we want to seek those immersive experiences that are way beyond what we ever expected before.
The challenge is, beyond what Andy mentioned of all the challenges we have now, that there's so many online platforms and delivery methods available. It's important that consumer goods companies start listening to these consumers and look for new ways to engage them and improve that shopping experience. We spend a lot of time with companies trying to help them demystify what the consumer says and wants. Consumer goods companies need to be nimble. They look for those opportunities, but they have to improve the overall execution.
I'm excited to be here with this panel talking about automating tasks, integrating AI, and how we're going to improve efficiency. It's also how the right software and technology solutions are needed to improve the performance, maximize the sales, and remain competitive. It has to deliver a winning experience for those consumers, right now. Because if not, then why don't they just go online and do it directly online, right? How are we going to differentiate ourselves? We've got to listen to those demanding consumers, and we're all one of them, so we should know.
Skorupa: That's a good way to shift the conversation from the challenges that are very important to understand, to begin to talk about the solutions that we can recommend to CG companies today. Pete, there are challenges, but how do you take more control of the challenges in retail execution operations. A lot of discussions we've had in preparation for this, is doing little tweaks and capturing low hanging fruit, it’s just small potatoes. Pete, what should companies think about as they seek to update their retail execution operation in your recommendation.
Pete Billante: Sure, just a quick intro on me. I'm Pete Billante, chief product officer here at Repsly, a retail execution platform. I'm going to be talking a bit about some of those things that CG companies should be thinking about. My background though, is actually – I, too, started my career at P&G and then worked for a number of supply chain software companies throughout the years including SAP and others, creating platforms to help provide value in getting products to market. Specifically, on retail execution operations, there's some really hard problems to tackle. When you're making this decision about upgrading the services you're going to use, you have to take a long term mindset going into this process.
This retail execution is called the last mile of the retail supply chain. The data is not well organized there, for instance it might be upstream in a manufacturing system. CPG manufacturers need to think about what kind of information is needed to make better decisions about new product intros on-shelf availability, promotion events, etc. Then, what tasks they want teams to perform when they're in stores that are going to make that impact and create uplift. This is what a lot of CG companies are looking for. There needs to be a plan to embed that in the system and not leave it up to your reps to figure out when they're making a visit. The go to market plan for each store has to be in there so that the reps can follow and execute it.
Once you have some results, you can start to look at the data from the programs and see how it is impacting sales, or a new product introduction, based on the actual sales data. The bonus sales scan data at the store level, allowing you to answer questions like, "Can I reallocate my team to the highest priorities in programs," or "Can I demonstrate the results of my programs to my stakeholders inside the company."
As Andy mentioned, this shows the impact that we're having. If you take the pandemic, or the global health crisis, as you said, "as an example," the best manufacturer teams had that data about on-shelf availability across all the channels as things progressed over time. What they were doing was changing the way that their teams planned things, such as routes, to have the most impact.
Instead of just scheduling the same visits on the same regular route every day, they adjusted where to deploy field teams based on risks of lost sales or where they could get the best uplift, and prioritized allocations of which stores to visit and inventory was available based on that. That’s the baseline.
The other part of it is the ecosystem. It's a given that, today, the retail execution platform has to fit into the tech stack. If you're a CG manufacturer, there’s a CRM system of record, an ERP and other planning systems, and all that information should be synchronized flawlessly. What’s needed is an updated platform that's all already built with connectivity in mind. I don't just mean APIs, where you can make your own connections, but even going as far as pre-built connectors, so that you can plug into the other major platforms and keep that data flowing. Now, you can make those changes and adjustments to be nimble.
Skorupa: Andy, Pete brought up the concept of teams. I mentioned the concept of moving parts, but those moving parts are handled by teams. He also brought up the concept of data, and data plays an important role here. How do you get all those relevant teams to work together, centralize data, and get this activity in an end-to-end view – a dashboard, or some web service – a key component of making that happen?
Walter: I'm not sure if I like the term centralized data, but you're hitting on transparency across all the data. It's funny, before we did an intervention in this space, people struggled to get their arms around retail execution and understanding what's happening in distributors, in warehouses, in the merchandisers, and warehouses, on the shelf – things like that. To get that transparency is that first step, but then, once you have it you can start bringing that data together. You want to be able to bring that data together with other sources of data, such as ERP data and things like that, that's when some real magic can start happening.
When you can combine internal data and external data all the way down through consumption of the product, that's when the magic starts to happen. That's when you start thinking about advanced analytics and AI to start doing things: what SKU should I put into this store, or cluster of stores, that's going to drive the greatest penetration and growth for my business?
If that foundation of transparency across the end-to-end isn’t there first, with bringing the data together, you never really get to that point. Cheryl made some great points because it's not only about eliminating friction for the consumer, but in many markets eliminating friction for the store owner, as well. That's what we're talking about when we're talking about retail execution in Latin America, India, or China. It's small store owners, as well. They're part of this ecosystem with us and what we found is when they have end-to-end transparency on their business and can see how to grow their business, they really get behind it. That's the power of that.
Skorupa: Cheryl, I'm going to do something that could make some people nervous, but I'm going to read a quote from you that I'm hoping you can unpack for us here today. It's a good quote, "Technology plays a huge role in connecting consumers, retailers, and retail teams to capture value in the ecosystem." Can you unpack that for us, about what you mean by that?
Perkins: Sure, I'll build off of where Andy stopped. It is end-to-end – the consumer, the retailer, the store owner, the execution team – it's not any one function or one part of the ecosystem. If technology's implemented correctly, it can develop effective teams and enhance the overall shopping experience, but also get better results.
To unpack this, it's really figuring out which part of the ecosystems have to be engaged, what technology can be used, what data needs to be used to actually get to the better experience, and the better results. The best way to unpack this is through examples.
A lot of retailers are using new ways to automate shelf space auditing. It used to be people out there auditing the shelf, seeing if the shelves were full and the products were in the right location. There's technologies that can do that, image analysis captured from a smartphone or an internet connected camera. They're identifying not just out-of-stocks, but what SKUs are out-of-date, what products are in the wrong place. Using these types of technologies reduces the burden on the store owner, the retailer, and the employee – it reduces human error.
Of course, it's a better experience because the store shelves are filled with the right products and the retailers can align to their planogram. Technology is improving every part of the ecosystem, making it easier to find the product you want. Think about loyal customers, they're loyal to the point where they can't find the product or the product's not where they expect it to be – what are they going to do, they're going to purchase another brand.It’s important that they have that technology to do it.
Another example that’s really exciting is Giant Eagle. Right now they’re using smart coolers. They're in the frozen or refrigerated section, you walk up and see a high resolution digital screen as you go to open that refrigerator door – these screens are amazing. They can be used for advertising, to monitor product flow in the store, but what's really cool is getting real-time information on how consumers browse. It's pretty interesting because you learn a lot about the customer's interaction with the products, and you can see exactly what they grab, what they pick up, if they look at it and put it back.
Are we tracking inventory this way? Absolutely. Is that helping the supply chain? For sure. Are we measuring traffic? Yes, again that's helping other functions. Are we detecting what consumers are doing? In real life, how do they interact with the product? That can help product development. Of course, it's creating a better customer or consumer experience. All around, these are ways that technology is helping everyone in the ecosystem and capturing that value. That’s why it's really cool. Not only is the consumer on one end getting it, the store owner, retailer, but we're getting the performance and increased sales.
Skorupa: That’s a great way to understand it. We've certainly nailed down the challenges, we've nailed down that there are many operations, teams that need to be coordinated. We've talked about data that needs to come from lots of sources, partners, and ecosystem, and honestly, to accomplish all of that. Don’t think you can do it without a future-forward approach to technology. Pete, we're talking about future-forward technology to accomplish all of these tasks we're going to ask of it. What kind of future-forward technology are we talking about here? What kind of platform can do all of this?
Billante: I’ll start by building on something. Cheryl made a great point about the experience for the consumer and also for the brand in-store. The problem of an out-of-stock is that it’s not just limited to the sales of that one item. Many retailers are concerned about out-of-stocks because they look at a consumer visiting a store as a basket of a transaction. There might be that one thing that they were going in there for – maybe a new parent is going in to buy diapers – if those are not on the shelf, not only did they lose the sale of that one unit, but everything else that they were going to buy on that trip too, which might have been food and other items along with that.
There's a lot at stake in getting this right and making that experience really good. It benefits both the CG manufacturer and the retailer.
Back to your question about the future for technology that can support it. Building on the connections to the rest of your sales and marketing tech stack, there's a few important elements to focus on. CPGs, if they haven't already, should be thinking about a 100% cloud-based approach. Things like availability and uptime, those problems have been solved. A platform that's working with a top-tier cloud provider is going to have those kinds of things built into it.
There will be high availability to rely on the data anytime you need it, anywhere in the world. It will have best-in-class security infrastructure because it's important to keep your data safe. You could be collecting a lot of information about what's happening in stores and the supply chain. Things like that are the first stop on future-forward, where you want to make the right choices. Then, we mentioned how this is a complex data set, it's unstructured because of the nature of retail stores and shelves. CPGs need to ensure the platforms have ways of analyzing that information to provide immediate insights into problems to correct or opportunities to impact and increase sales.
Systems that have built-in business intelligence, along with the capabilities for machine learning, are table stakes. That's going to be the things that people expect going into the future. The days of email and Excel spreadsheets to analyze what's happening are not going to be able to scale in the same way. You need that business intelligence layer built in. Then, adaptability and usability come to mind for the future. What I mean by that is, the needs in retail are changing quickly and dramatically. For example, what we saw during the pandemic where teams were completely reorganized to address on-shelf availability issues or other supply chain problems that related to keeping products on the shelf.
A rigid platform and rigid set of tools that doesn't allow for making easy configuration changes and getting reports that business users can act on instantly, without engaging for custom development or custom coding, that adaptability is going to be core to speed to market and speed to correct issues. Usability is more important than ever.
Time in-store is valuable; teams shouldn’t be struggling with mobile user interfaces that are outdated or get in the way of doing their job. When they're in-store they can impact sales or most of the value-added activities, not the things that are on the app. Things including talking to the store manager about new SKUs, placements, promotions, and pre-sales activities for upcoming events. What you want is an experience that's consumerized, fast, and easy. That visit time in-store goes towards those sorts of things, instead of just working on the mobile device.
Skorupa: Andy, you said earlier that, "centralizing data was important, but more important was having it transparent so that you could see it." That brings us to a point about that’s been debated for a long time. How do you do it? How do you make it work? That's real-time, or we're near real-time data. The problem has always been that there are many databases, many applications, and these things often exist in silos, but technology has moved beyond that, of course. Pete mentioned web services and API-based technology. In retail execution, we have that future ability to do real-time execution. How important is that real-time or near real-time retail execution?
Walter: Well, obviously during the pandemic it became critical because not only were we trying to figure out on-shelf availability, we had to decide what SKUs to keep making. A lot of companies had to take that data and decide if they were going to keep making all the SKUs they were making. Obviously, most of them decided not to. So, which SKUs are selling the best, in which stores, and the like.
I can't reiterate Pete's comments enough on having an agile future-forward software as a service cloud-based capability. What Pete didn't allude to was when we worked together at P&G, we were stuck with big monolithic systems that were very inflexible. The fact that these things can now be layered on top of monolithic things is very powerful because the investment that’s already made in the ERPs, etc. isn’t lost – we can put these breakthrough capabilities on top.
This transparency has been critical, but I'm going to bring up another aspect of it too. What we were able to do once we had that transparency – and also had the ability to start looking at analytics and AI – is to then bring in retail partners and say, "let us show you what we're doing, what we're looking at, and what we're able to do with the business because we now have this transparency and we can start doing these advanced analytics." We hosted the leadership of Walmart, Tesco, Target, Kroger, and showed the analytics we had built as a result of this. It was a complete breakthrough.
It was funny because my chief sales officer, Bob Fregolle – one of the top chief sales officers, he's retired now and runs the Daytona Tortuga's baseball team – was very skeptical of this whole transparency and analytics, and said, "Andy, I'm not getting it." Then, suddenly when the retail partners came in and said, "Andy, what else do you need?" I said, "Well, we would love to have this data source and this data source." The number two person at Walmart says, "We'll make it happen." When we walked out of that meeting Bob said to me, "Andy, you've turned analytics into a currency.
That’s what we're talking about here. How do you turn data and analytics, not only into helping operationally or when challenges arise, for instance the health crisis and things like that. But, how do you turn it into a currency that is as valuable to your business as trade funds or other elements of execution are? All the things we've been talking about, that's what you're really trying to get to, something that becomes a strategic, competitive advantage to your business.
Skorupa: I'm going to make you a little pun here, "it probably increases the value of the currency if the data is very current."
Cheryl, on the analytics theme. Andy did allude to it, machine learning is playing an increasing role. What is that role? Is it optional? Is it essential? Is it part of this future-forward technology platform we're talking about? And if so, why?
Perkins: I think it's absolutely essential. AI and machine learning help transform large amounts of data into actionable insights with the ability to prioritize and go after the things that give economic value. There's so many things that we're learning, the question is: which ones are actionable and which ones should you act on? That’s the key and machine learning helps with that. Another example, I started early on saying it's about the consumer experience, and convenience. I think Pete’s words were, "make it fast and easy."
Right now, Walmart’s doing all the things they can for store pickup programs. They’re asking customers to check-in when they leave their location to even head to the store. Based on the app and all that, they use that consumer's location to estimate the time of arrival. When you arrive, your order's ready. How cool is that, to be able to get it on time and ready. We're still delivering on convenience and creating a better consumer experience.
The other thing that I love, if you're a Walmart+ member, you can scan and pay as you go. Who wants to stand in line at the register and wait to check out anymore? Do all your scanning and pay as you go, and then just leave. It's a great incentive to see how AI and machine learning can help create this experience and provide convenience at the same time.
I don't want to talk about only Walmart. Look at Target and what they're doing to elevate the shopper experience. For years – again, I’m a Target shopper – they had all these different apps. Finally, after a decade, they’re all combined: coupons, loyalty rewards, bridal or baby registry, prescription, and whatever else is now in this super app. That app continues to create a more convenient shopping experience. Of course, they're gathering information and tracking consumer data, but it's allowing it to be customized to you. They give opportunities and offers that are related to how you shop and what you do.
From my perspective, where things are going, it's absolutely critical to use AI and machine learning to get that convenience and experience all the time. Again, you are at the store to get what you need, at the time you need it. It’s enjoyable, faster, and smarter and that's all based on technology and what technology can do.
Skorupa: Consumers are definitely going to love super apps that are faster, smarter, and more convenient. But interestingly, super apps require super architecture and super technology to happen.
This is where we bring Pete back in. We're talking about advanced elements, which can make a big difference in optimizing modern retail execution operations through platforms such as machine learning that's cropped up in our discussions. Pete, you've also brought up API-based, web services-based templates, and other advanced technologies. Can you dive into that topic a little bit for us here, Pete?
Billante: Sure, it seems like every year we're hearing about advances and the capabilities specifically in machine learning and AI applications in retail. Whether it's the ability to analyze large data sets and provide insights into patterns, which is what machine learning models are really good at, or the ways machine vision or image recognition can be used to detect problems, like on the physical shelf, in-store.
For example, taking a photo of a shelf with a mobile phone and then, nearly instantly knowing which products are out-of-stock, determining your share of shelf versus your competitors, or even things like price tag audits. Cheryl mentioned a few great examples of things you can do. Then, imagine trending this data week-over-week to find patterns, that's now more possible than ever with some of the advances.
What we're seeing in this phase is where the core tech of those types of image recognition models have been proven in standalone pilots. Many CPGs have run these and proven the applications where it works really well and figured out the best ways to use it. Now, this kind of capability can be brought into your platform and made part of the workflow for a broader rollout. It’s more like turning on a switch to enable a new service without a lengthy custom development project and data scientists to create machine learning models. It's something that you can just add on to the workflows that you already have. You can enable these automated image recognition systems, workflows for your teams, things that they're already doing now.
That gives you another stream of data into your analytics to help plan and execute better. For example, getting that week over re-trending data compared to your competitors, overlaying that with scan data at the point-of-sale and then, matching those things up to understand how that impacts what you're seeing in terms of sell-through. Those things are now evermore available. What you're going to see in the next few years is that those will be quickly adopted because that gives you two things:
1. Speed. You're spending less time on data collection activities in store and more time on selling activities.
2. A whole new stream of data. This data can be added into the mix as part of your planning process to optimize where you're going to allocate teams and resources.
The future is very bright for those sorts of technology.
Skorupa: Those capabilities are very advanced. Andy, one thing that CG executives love to hear about is best practices in the marketplace. As a deeply involved person in making some of these things happen, you don't have to name any companies if you don't want to, but what are some elevated best practices you've seen that CG companies are capable of doing today?
Walter: Well, the nice thing about my role is I have no legal department and no communications department, I can say whatever I want to say. So, I'll name names, and name companies with no problem. Obviously, I talk P&G a lot. The Jeff Goldmans of the world, one of their chief data scientists and what they're doing to bring all that data together by SKU, by store recommendation is driving the business phenomenally. I can't share all the metrics, but these things are growing the business. Being able to bring that data together and then bring together a team with top leaders is critical.
Corrado Azzarita, CIO at Kraft Heinz, was my technology guy on our analytics transformation at P&G. Not surprisingly, he's embracing the cloud, figuring out how to class capability and the like. Sandeep Dadlani at Mars is literally holding an entire company-wide AI internal conference. Cheryl mentioned Giant Eagle, Kirk Ball and his team are doing phenomenal things over there, as well. There’s three things that leading CG people are doing in this space. I won’t get into the technology, Pete and others are more well versed than I am, but what are these leaders doing?
First, they're influencing and raising this up to a leadership discussion. This is part of the strategy of the company, not just a technology project.
Second, they are making this part of their data strategy and AI strategy. Retail execution is where the rubber hits the road. If this is not part of data or AI strategy, you're missing the boat. Guess what, all three of those examples are doing that.
Lastly, they realize they can't go at this alone. They’re finding the right strategic partners to create a hybrid model of best-in-class internal and best-in-class external. The value is they're not just seeing P&G, they're seeing what everybody's doing. If you're not taking advantage of the investment of external people that are focused in this space, you're missing the ball.
Those best-in-class players, that's what they're doing. They're doing those things. They're playing to win, they're not playing not to lose. They're not making this a technology transition or things like that. They're making this a business strategy. That's really powerful.
Perkins: To build off what Andy said, it's the companies that are walking the talk. They pull leaders in, they've got the internal and external ecosystem, and they also have a focus on the consumer.
One example I’d like to bring up that wasn't yet is Safeway. Everything they're doing is based on smart retail to reward shoppers and discounts to those. Once you buy something in-store, you register, they give you additional rewards. Again, you have individualized people's beliefs, personalized coupons, and deals based around that. Within the addition to what Andy talked about, the internal and external ecosystem, bringing those consumers in, and giving them a way to get engaged in what they're trying to do.
Smart retail methods, gathering the information, understanding the habits, yes, it's going to be positive for inventory tracking. It's going to give the best selling products, having the placement at the right place. But, what this comes down to is the ecosystem. Like a well-oiled machine, if it's working well and everyone within the ecosystem is walking the talk, the profitability is maximized for each of the participants in the ecosystem. Fill those internal and external partnerships, and the engagement with consumers and as many touch points as possible is what's going to create the win for all.
Skorupa: I love your consumer focus, Cheryl, and all the other points, too. Pete, can you sum up, if modern technology companies achieved this goal, you've already mentioned quite a few of them, but just the final set of comments.
Billante: If I had to put into a catchphrase for the problem, I'd say, "it's all about the data." Maybe you've heard that before, but how quickly can you capture it, organize it, and integrate it with the rest of your sales and marketing platforms. Then, use those insights to make an impact on sales with the resources available on field teams or merchandisers. Isn't that what those teams are there for after all.
The companies that are the best at gaming and actioning insights from all these sources, those that have this data-first strategy – some of the companies that we were just talking about, Andy and Cheryl had mentioned a few – those are the ones that are going to be the winners in the long-term. It will be used for competitive advantage in their categories. They're going to outperform competitors at the shelf. Retailer customers are going to notice too, and are going to reward them for it with better placements and better opportunities for promotions, and things like that. So, back to that phrase again, "it's all about the data," and how you use it.
Skorupa: Thanks a lot, Pete. Lisa, let's turn it over to you for audience Q&A.
Johnston: Great, thank you, Joe, Pete, Andy, and Cheryl, for all that insight. It was a great conversation and I certainly appreciated all of the data puns you were all able to squeeze in. As each of you referenced, there's some amazing innovations occurring right now. Thank you for breaking that all down and sharing those examples.
The first question is: What is a realistic scenario where effective retail execution, or specifically field merchandising visits, can actually make a difference and especially an impact on changing the direction of a promotion going south?
Billante: Actually, I'll tell a story from an experience we had here with one of our largest customers, a large CPG manufacturer. Trade promotions and trade funds are a significant, if not the largest, budget item on a consumer packages company's marketing budget. This particular company had one promotion that was their largest of the year, and it was the majority of their trade funds that they spent on that. The stakes were extremely high. It was in all of their largest retailer channels and had elaborate displays and product placements that went along with it. There was time drawn to a specific date. And so, the promotion launched, or at least the date came by when the promotion was launching.
One of the key account managers for the largest retailer wanted to know how it was going because he was expecting to see a lot of sales uplift. In prior years, before he had a retail execution platform, he would make calls to the sales team, but it depends on how many reps could be reached in a day. He would say, "Well, in three weeks, I might know the answer."
In this particular situation, for this event that was just launched on a Monday, by Tuesday, he realized that the event was only at about 40% execution, when they were expecting it to be at 85%. Immediately, there was a problem. There wasn't all this marketing that had been done to send people into stores, they weren't seeing the promotion or the displays that were there.
He was able to immediately task the non-executing stores with the coverage, with the reps that were in those regions, to go out and make sure that the shelves were reset and the displays in place. By Thursday, they'd actually reached the execution goal of 85%. Now, it's a great story of taking real-time data, actioning it, and getting it done within four days, which would've otherwise taken potentially three weeks, and the promotion would've been over. This company said with the stakes as high as they were in terms of what they would've seen for lost sales, that alone was a positive ROI on the entire program for the year.
These kinds of things happen a lot. The ability to actually look at what's happening live in the field, near real-time and actually take action on it, and correct those lost sales outage opportunities has positive benefits. That's just one story, but there's many like that from among many of our customer bases.
Walter: Pete shares a great success story, so I'll share a great failure because no one ever shares the failures. We launched the Tide Stain Pen in 2005. I remember it well because I was running digital marketing in eBusiness for Fabric and Home Care. I was told to stop selling it online because we were selling too many of them and we wouldn't have enough for the stores.
Then, we launched it in stores and no one could find it. We had no way of knowing that though, and no way to correct it. It was a great example of not having the capabilities we've been talking about over the last 45 minutes and what can happen. If we would've had that capability to realize we were putting it in the wrong place in the store, we’d know consumers weren't finding it, all those types of things. This type of capability can absolutely sell, save, or kill a promotion if you don't have the capability, for sure.
Johnston: That leads very nicely into the next question. There seems to be a disconnect between the technology and how store managers actually work. How much training is necessary to translate the data to the last mile?
Billante: I'm happy to take that one, too. A couple things. A lot of times when we're talking about retail execution, at least from a Repsly perspective and certainly some of the points that Andy brought up, we're talking about the perspective of the manufacturer who has the field sales team or merchandisers in various local markets. It's not necessarily the retail store manager, although the meeting that team has with the retail store manager, especially a Walmart, that’s a big meeting.
It's not so much that the store manager themselves is the user, it's certainly the team that's bringing that information to them to say, "Hey, I noticed there’s an opportunity to set up an end cap here," or "I'd like to introduce these three or four SKUs, because I noticed you have an opportunity on the planning end to do a reset to bring these new products out."
That conversation isn’t a training conversation, it’s a sales conversation. What we want to do is make sure that the people in the store having that conversation are equipped with the best information, data at their fingertips, sales and selling assets to actually have an impact in that very brief time they have with the store manager during that visit.
Johnston: What are some of the must-have criteria that you want to have when starting the evaluation process?
Walter: Obviously, you need something that has a modern architecture. You're looking at the technology: how’s it going to integrate with other investments you've already made, is it cloud enabled, those types of things to allow you to take advantage of the data for analytics. You're going to look at the partner and if they are going to innovate with you. Will they co-invest with you? What does that look like?
You're looking for that maturity, as well as how to simplify your architecture. If I can find a player that can add all those values and help me get rid of some of the legacy stuff as well, that's incredibly powerful. As we evaluated players in this space over time, these were some of the key factors we were looking for.
Perkins: I'll build on that a little. That partner choice discussion and vetting them as a partner is critical. A lot of times we rely too much on vetting the technology, the application of the technology, and not how do the cultures match?
Again, are they aligned on the same objective? Are the goals aligned? Where technology has failed in the post assessment, it's typically based on the lack of assessment of that partner to know if that partner choice was aligned to the same end goal as the company was aligned to. That partnership piece as a criteria is often missed.
Billante: It is. I'll add onto that and combine some of the points you've both made. In the very beginning, Lisa talked about the whitepaper that's around modernization of the technology stack. The concepts in there when looking at a partner and trying to make that decision, the partners that are talking about the most current technology and how it can be applied, that tells you about the kind of company that they are in terms of how quickly they're going to be able to help you get results and how willing they're going to be to work with you. They're trying to create the absolute best experience possible for you.
They don't want you to have to spend extra time dealing with out-of-date technology or things that aren't going to work in your ecosystem. It's a good indicator, if your partner has a modern tech stack, that they're going to be a great partner to work with because they're already thinking about the future. Without stealing too much of the whitepaper punchline, you're going to find those themes in there. It’s going to be super important as a must-have criteria.
Johnston: What's a key use case of a consumer goods company that felt their retail solution helped modernize the way their team is working, right now? The emphasis is "right now" because of such a changing landscape.
Billante: I'm going to pick a word to emphasize in that phrase. The "right now" part is interesting because right now is a strange time. We have supply chain disruption. Andy talked about manufacturers doing things like SKU rationalization, so some products aren't even available because they're not being made.
There's a lot of challenges in figuring out what is supposed to be in the store. What are my consumers looking for, and what should be on the shelf? That's the use case, on-shelf availability right now is more important than ever. If I was to plot a trend – Repsly has about 800 customers using the platform around the world and the changes from a few years ago versus now – the biggest increase is solving problems with on-shelf availability. That's been the biggest pain and the most obvious thing we've all seen.
Everyone, not so much anymore, but not too many months ago, there were pictures of empty shelves of different products and things like that. That got everyone's attention. Teams are being deployed to solve those situations as best they can given the challenges in the supply chain and an agile retail execution platform is an absolute must to get that done.
Johnston: Great, thank you very much. I'd like to thank our speakers for giving us their time and subject matter expertise today. I'd also like to thank Repsly for sponsoring today's webinar. Finally, thank you to our attendees for giving us your time today, we hope you found it worthwhile.