How does PepsiCo support their retail partners through insights? In this episode of the podcast, host Ian Cook sits down with Kate Garner, the SVP of Demand Accelerator at PepsiCo. Kate outlines how they’ve worked with retailers to help them grow their category and attract customers down the store aisle.
How does PepsiCo support their retail partners through insights? In this episode of the podcast, host Ian Cook sits down with Kate Garner, the SVP of Demand Accelerator at PepsiCo. Kate outlines how they’ve worked with retailers to help them grow their category and attract consumers down the store aisle. Ian and Kate also discuss how PepsiCo’s “matrix” organization helps business and data stakeholders collaborate.
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Key Quotes:
“Don't ever chase something unless you know somebody's lying awake at night waiting for that information.”
“I invest behind ideas that get stakeholders excited and waiting with bated breath for the information…That's when you know that you have it, when somebody's emailing you and asking you the status and seeking to understand where the product is at.”
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Show Timestamps:
(00:47) Kate’s day as SVP for Demand Accelerator at Pepsico
(01:36) How Kate defines an insight
(03:03) What goes into making an insight?
(05:18) Data science and business stakeholder “matrix”
(06:32) Example of a valuable insight
(09:20) Using data to attract customers down the store aisle
(12:17) Bringing the data together in an efficient way
(13:13) How is PepsiCo thinking about generative AI?
(16:06) Looking at data in four pillars
(17:50) Working with retailers and sharing data
(19:32) Example of sharing an insight with a retailer
(23:45) Pepviz, PepsiCo’s data and analytics platform
(27:04) What data does Kate wish she had?
(29:01) Final recommendations for companies navigating data challenges
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Sponsor:
This podcast is proudly sponsored by Seek, the leader in cloud-based creation and delivery of industry-focused insights.
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Links:
Connect with Kate Garner on LinkedIn
Connect with Host, Ian Cook, on LinkedIn
Follow Seek on LinkedIn
Ian Cook: [00:00:00] Some days, it feels like we're drowning in data, but data isn't knowledge. Data without context or the expertise to understand it is just something taking up space in your warehouse. That's where being insights driven comes in. Insights driven organizations focus on generating actionable insights rather than just collecting and munging data.
Ian Cook: Insights drive better decisions. Welcome to the Insights Factor.
Ian Cook: My name is Ian Cook. I am your host and the CTO at Seek. I am thrilled to be joined today by Kate Garner. She is the Senior Vice President Demand Accelerator at PepsiCo. Kate, thank you so much for joining us today.
Kate Garner: Ian, it's great to be here. Thanks for having
Ian Cook: me. Excellent. Let's just start very quickly. So give me a description of the day of the Senior Vice President for Demand Accelerator. Oh,
Kate Garner: gosh. Um, you know, it's a [00:01:00] great day. I get the opportunity to interact with our commercial functions. So I spend a lot of times with our sales leadership, our marketing leadership, um, as well as our strategy and transformation.
Kate Garner: Uh, certainly, you know, the, the insights and data and analytics, uh, it's at a crux of, of impact for corporate America.
Ian Cook: Fantastic. I have read, uh, things that you've been quoted in. I've listened to podcasts that you've been on and you just said for me, what is the magic word insights? I want to start off kind of a high level.
Ian Cook: One of the things we talk a lot about at Seek and on this podcast is the question of an insight itself. As distinct from, say, some data or just a dashboard that you're looking at or a number or a metric. What constitutes for you a true insight?
Kate Garner: Sure. So certainly it comes from all the things you just said.
Kate Garner: But the insight to me is when I can go to those stakeholders that I mentioned. So whether that's sales or marketing or Strategy team and inform them on a new [00:02:00] way of thinking that really influences how we go to market. Uh, how are we going to deliver differently in the marketplace to accelerate growth?
Kate Garner: And it is such a fascinating topic when, you know, having had the opportunity to lead sales teams as well as insights teams. And there is such a distinction, right, in, in job responsibility and areas of interest. And so all that data and analytics that we gather to find that insight. Um, it's a real passion point for our insights leaders, but getting to it's, it's often the iceberg analogy, right?
Kate Garner: It's that big piece that sits below that's so critical to get that little piece on top. That's that piece of the iceberg that sits out. That's the insight that informs our, our senior leaders on where we need to behave differently or take different action in the marketplace. And so it's not only whittling down to that way of influence, but it's also ensuring that we don't get caught up.
Kate Garner: And what's below the water, right? Because our commercial leaders, they just want to go create that action. And so how do we distill it and really get [00:03:00] clarity
Ian Cook: for them? When you say there's the part peaking above the top and then all of the things underneath that you need to, to not be distracted by what goes into making an insight for you, is it working just with the data or is it a group effort?
Ian Cook: How does that come about?
Kate Garner: I remind the team, there's two things. There's, there's two important insights. So the first, both are headlined by the common theme of. Don't ever chase something unless you know somebody's laying awake at night waiting for that information. And so that can come in two ways. It can come in, somebody knows they have a problem to solve, and so you are seeking for how can I help inform them to create solutions for the challenges they're facing in the marketplace.
Kate Garner: The second area is somebody may not recognize that they have a challenge or an opportunity, but they're, you're, you're helping inform how to plan their business strategy. And so you're looking for what's that next growth enabler. It's the hidden piece. And so that often is a deeper dive into the analytics to figure [00:04:00] out how you're going to unlock that
Ian Cook: granular growth.
Ian Cook: But both of those are really dependent on knowing or understanding sort of the business problem at hand. Are the people who are working on the data working hand in hand with those business folks to know, Oh, Kate's lying awake at night trying to solve this problem. I need to get it to her. Or, I know this business problem exists and it seems like I've got something to answer it.
Ian Cook: Maybe I need to raise it. How does that kind of Yeah, certainly
Kate Garner: there are areas where people will uncover opportunities unexpected. Um, and we at PepsiCo, one of our ways of working in our culture is about speaking fearlessly. So people always feel comfortable coming to the table and really saying, Hey, I think there's a new opportunity.
Kate Garner: I want to talk about how we can make this happen in the marketplace. Um, and then the other action is from a problems to solve our. You know, it's interesting. We are a very matrix organization at PepsiCo. But specifically for our team, right, we sit across both our food and beverage, um, North American sectors, and our teams are embedded.
Kate Garner: So my team [00:05:00] spends 90 percent of their time with those stakeholder partners. So in terms of truly understanding what those opportunities are, that's where they spend their time every day. Um, they sit on those leadership teams and work hand in hand. Our job is to help them support them functionally. So how do we ensure that we're leveraging, um, our functional knowledge across the businesses?
Ian Cook: That's terrific. There's always this debate, at least in the data science projects I've been on and the teams I've helped build is, do you embed them with the business side and so that they are working hand in hand with those folks? Or do you centralize that they're working close to each other and have the sort of technical expertise in one place that people can come to?
Ian Cook: So PepsiCo has chosen to embed them and sort of matrix them out. So you have people. that are going to be working on different business problems all of the time, um, is that all within sort of like a marketing area or does it cover marketing sales, maybe logistics and all of those?
Kate Garner: It is. So it's interesting.
Kate Garner: We're almost, as I said, matrix. So functionally they do sit cohesively [00:06:00] together. So we have a. We have a retail marketing team that sits under my team. We have a category leadership team that sits within my organization, a space planning, as well as analytics and insights, our data and advanced analytics team.
Kate Garner: And our, our marketing team and our, Um, category team, they sit direct on those retail partnerships. And so they work hand in hand with our retail teams, um, as well as then coordinate with the marketing teams. And then our analytics teams, uh, they're, they're what I call the zone or the consulting team. So they're not one to one, but they are taking in the projects and really managing priorities across them.
Ian Cook: I'd love to hear an example of when you found, or when the team has found an insight that truly turned into action that maybe, let's go with your first case, answered somebody's need that they were lying awake at night worrying about, and that you helped find this terrific answer. Do you have like a good example that you can remember?
Ian Cook: Sure.
Kate Garner: Yeah. Um, so one of our retail partners were their [00:07:00] category, their snacks category was really struggling and they came to us and they were seeking ideas on how to generate growth. And when I say struggling, it was lower than the category, right? So they wanted the goal of the project was how do I get to category or better?
Kate Garner: What's happening in my retail footprint? That's creating this different dynamic. I don't mean to
Ian Cook: interrupt. Just a quick thing for some of our listeners. When you say at or above or below category, can you dive a little bit more and give people a little more context for exactly what that is? We might have a lot of people who listen to work with data, but aren't as close to the CPG world.
Kate Garner: Sure. So from a CPG perspective, just the syndicated data that we leverage across retailers that Let's them know, hey, across the board, this is snacks growing in the marketplace. So, this is the amount of snacks growth that it grows within the grocery retail outlets. But this was a specific retailer in comparing themselves to the marketplace, right?
Kate Garner: They saw that they were below, below market, and they were looking for ways to improve that. And so, with that, then, we're able to bring our insights. Specific to their footprint and help them [00:08:00] understand here's what we know about the industry and the category. And here's how we would translate that into action then.
Kate Garner: And so we were able to identify space planning opportunities. So how do you actually, uh, place the product within the aisle to create different types of. Um, mobility up and down the aisle, what attracts them, what brings them down the aisle, as well
Ian Cook: as a store. In terms of action, the thing they could do is specifically like where to put this in the store.
Ian Cook: I'm walking down the aisle. I look to the right, look to the left, and you can change sort of how people behave or at least what they see and how they respond purely by moving things around. Do I get that right?
Kate Garner: Certainly, what, what invites them into the aisle versus brings them down the aisle in terms of the products that they're seeking, um, as well as ensuring the assortment.
Kate Garner: So as we think about, um, how our marketplace is changing from a consumer standpoint, whether that's just the variance in age, demographics, just taste profiles overall, you see a great variability. What we're able to do, [00:09:00] though, is start to isolate what that looks like on a store by store basis. So it's not only the flow of the aisle, how do you flow the snacks down that aisle, as well as what are the specific products that you want to make sure are available in a specific store.
Kate Garner: Is the store profile somebody who is seeking, um, what we would call some of our more permissible snacks, or are they seeking some of our really, um, high intensity flavor snacks? Talk to
Ian Cook: me a little bit about that in a concrete way. So, the flow down an aisle, I'm heading into an aisle. And do I first see, like, what would be permissible?
Ian Cook: A little bit healthier, a little bit more, um, typical flavors, or what is,
Kate Garner: what's permissible in this case? Yeah, so some of our SunChips products, or perhaps you've seen our Popcorners, we have that on. I sure have. The
Ian Cook: SuperBowl app. I have an eight year old daughter, so I'm very familiar
Kate Garner: with those. You're familiar, that's awesome.
Kate Garner: So we, um, just ensuring that we have the flow that brings that Consumer down and which products they're looking for to invite them in and then which products that they're [00:10:00] seeking as they walk down the aisle.
Ian Cook: So will that, like you said, sort of the high intensity ones, will those be at the other end of an aisle?
Ian Cook: Do you sort of come to a crescendo in the middle of an aisle? Um, I'm trying to think because like at my grocery store, you can enter an aisle in two directions. So I'm trying to think of like what the flow is from. Both directions and how people think about that. This type of psychology is just fascinating to me.
Ian Cook: Well, and
Kate Garner: oftentimes it's what's at the other end of the aisle, right? So if you're at an aisle, um, that may match up against perhaps the deli area where there's sandwich meats and other things, you might put, uh, the multi pack products that we have there because mom's in the mind that she's looking for things that are going to fit into.
Kate Garner: The lunch boxes for her family that week, and so just having it there to help her shop more efficiently, um, is one way to think about what you might have at an, at an aisle depending on what else is at that spot in the rest of the grocery store. Um, with our flavored products he asked about some of our, um, Heat products, right?
Kate Garner: Those products, they sit across a multiple, um, of our products. Some people have a preference [00:11:00] for Cheetos, but they love that heat. Others have a preference for some of our potato chips. And so you'll see it across, um, that space. You know, one area we do concentrate in some of our convenience stores is ensuring that we're, um, we have those products put together as you're coming in the store from an impulse standpoint.
Ian Cook: That is a lot of really interesting data. And one of the things that we do at Seek is trying to bring all this data together for people who are trying to work on understanding not only their own product and or product range, but also where they sit and how to work with retailers. Is this broad variety of data something that, um, your folks are trained to work with every day?
Ian Cook: So to me, um, I am, you know, just as a quick background, I come from a data science, machine learning, AI background, not CPG. So a lot of this is brand new to me, which is making all of these conversations so much fun. The idea that there is like understanding of where everything is placed within a store, but doing that across so many stores, do you have to have specialized abilities to work with that?
Ian Cook: Do you mesh it all together to see [00:12:00] things in conjunction? Who's working with that to, to make sort of sense of it all?
Kate Garner: Yeah. And I think like so many industries, the data proliferation is just on fire, right? And so it is, you know, it's a challenge we face. It's a challenge many industry faces face. And for us, it is about.
Kate Garner: The process of ensuring that we can bring the data together in an efficient way. Um, so as I look to the future, it is data consolidation, so you're able to access that data and combine, integrate the data, um, in a way that has fewer human touches, right? And so the, um, That's a process that we've been focused on the last five years to ensure we can actually then lay over the AI and the ML on top of that, which is then what goes into our space planning capabilities.
Kate Garner: So it's been a journey, and certainly it starts with the data consolidation that you referenced. As well as then putting some of the, um, AI as well as ML on top of that.
Ian Cook: Well, you opened the [00:13:00] door and I don't think I'd be, uh, allowed to keep going if I didn't ask about generative AI, the, uh, thing that every even remotely tech related podcast is asking about.
Ian Cook: Has this obviously shown up on your radar, but has this started to become a topic of active work within PepsiCo and how are you going about that? Sure. Um.
Kate Garner: So I think any, any industry, any organization is looking at that, right? It's a hot topic. Um, and I, I would say moving forward with a level of responsibility, right?
Kate Garner: So looking at it from a marketing standpoint, and there's a lot of great opportunities in a world where we can be so granular and customized, it can allow that at a, at a, at a cost that's scalable, correct? The, um, and then in other places, as we think about generation, and so I would Processing and generation, right?
Kate Garner: So for me, it's jumping to generation, um, before processing and some of our advanced analytics. How do I get to that processing piece [00:14:00] first? So in a world where we're bringing data sets together, so we're getting that common base. Now I have an opportunity to actually process some of that in a way That can be automated and really allowing our associates then to focus on where, where we need their focus, which is the top of the iceberg, right?
Kate Garner: If I take this back to the beginning of our conversation, a lot of that, uh, data and information that sits below the water. Can be, um, automated from an analytics and, you know, we, we have a process that we use internally to do a category or business analytics teardowns, um, that we can use to train, to train the data or to train the AI as well to do that in an automated way, which would then allow our associates to focus on the top of the iceberg, which is where we need them.
Ian Cook: Just quickly to jump in, when you say teardowns, what does that entail? So,
Kate Garner: so it's about understanding the various pieces of analytics. So the various key performance indicators and ensuring that we, um, look at each of them [00:15:00] in a very systematic fashion. In a business as broad as PepsiCo's, we've got different subcategories, we've got different retailers.
Kate Garner: And we want to have a level of consistency in our approach. And you can imagine as you do that across a lot of associates, there's um, different learnings and there's, uh, you know, different depths of history and experience, but if you can create more automation around that and get a level of consistency and allow that, um, creativity and that strategic insight to again, come at the top, um, that will just create a lot of great growth
Ian Cook: for us.
Ian Cook: Absolutely love that you mentioned creativity. I think that's a huge part of the data world that people often don't quite appreciate that it does get very, very creative that you mentioned all of these things that have to get built back up again. I'm really interested in how you interact with that data.
Ian Cook: Lots of people and that is a lot of data. Do you, are you day to day Getting up, looking at a dashboard, saying, all right, here's some things that are trends that are going on and where I need to make some changes. [00:16:00] Are they part of everybody's kind of day to day or do you deliver them at set points? Just sort of give me an idea of like how you kind of work with all of that data for right now, or at least seeing the insights that you're
Kate Garner: generating.
Kate Garner: Yeah. And so I think about our data and the So, um, we look at it in four pillars. And so there's absolutely a day to day marketplace performance aspect of that. What is our performance last week? How are we going to optimize anything going forward? Um, all the way to we need data and analytics when we're doing our.
Kate Garner: Three to five year old strategic planning. And so we leverage it in that case, right? So there, there's that type of planning. And then there's the spaces in the middle where, um, maybe two years out where we're building business cases against innovation that might be transformative in product. So food and beverage product innovation, how are we going to bring that to life?
Kate Garner: And then how are we building next year's plan? So those four different pillars create different time horizons, but data is actually, you know, it's a critical component with each of them. [00:17:00]
Ian Cook: PepsiCo has been very active in using data to make these plans for a long time. You've had a great career with PepsiCo.
Ian Cook: Have you seen the use of data grow, or have you always just been a very data focused company?
Kate Garner: You know, I have seen the use of data and advanced analytics grow. Um, so, you know, we just mentioned the... You know, the AI and ML. And if we looked at the number of hits that mentions that's getting in social media and other things today, right, we'd see that huge spike.
Kate Garner: And I'd say our growth is very consistent with that spike. Um, they're really fortunate to see the transformation journey that are, that, you know, the senior leadership has in place to, to drive for that. And so we're definitely leaning in and engaging in data in a way that can create the future.
Ian Cook: One of the things you've mentioned is working with the actual place, the retail space, where your products get shown.
Ian Cook: That data is something that can help inform the retailers. How do you go about working with them to help them understand the data that you have collected about their space? [00:18:00]
Kate Garner: So it is an interesting. Base, um, particularly as people become more comfortable working with data and what they want to share, our retail partners, we always re you know, respect that they know the shopper in their store at that granular level like nobody else.
Kate Garner: I, that, that's not information that I have unless we get into a data sharing, um, area. What we do though is we look more broadly across the landscape. And with an understanding of what we call their shopper circuit. So where are all the places that they shop? What percentage of their dollars are they shopping in those outlets?
Kate Garner: And then how does that inform what they, what, what they're shopping or what the implications are? And so oftentimes it's just that recognition of the differences in our data. And then how do we use that data then to inform joint business growth? With obviously the category at our, you know, the front of our context, um, making sure we're creating health for the overall categories that we
Ian Cook: Do you find that you're [00:19:00] generally ahead of or behind some of the retailers and understanding the people who actually show up at those spaces?
Ian Cook: Um,
Kate Garner: I think it's a combination of both. And I would say where, you know, we work with a lot of very sophisticated retail partners and that's where they have that information at their fingertips for what's happening in store. Um, the question becomes, how do we... What we have is visibility to success in other places, right?
Kate Garner: And so we all get biases depending upon the seat in which we sit. And what I would say is we get the opportunity and an example, if I'll use an example to drive the case, um, we had a retail partner who wanted to generate category growth and they were. Working with us to say, Hey, we're just not, we're looking at who our shopper is.
Kate Garner: We know who they are very granularly. And they, they shared with us a lot of great insights about that shopper. Um, but we had a, we said, let us, let us think about this and come back. And we had a thought that they looked across [00:20:00] their whole footprint and perceived it to be very consistent with that shopper.
Kate Garner: And so we took a twist on it and said, Hey, we're actually going to say. Do you have some differentiated shoppers? You, and what we found is the, the shopper they had profiled represented about 75 percent of their shopper, their shoppers, but it also represented about 66 percent of their stores. And so it was a really important shopper to them.
Kate Garner: But this other third of stores, there was another shopper and it was specifically a Hispanic shopper and that was not the types of products they were bringing to market and other things. And so. What we observed is, hey, you have good growth in your strategies working in these, this part of your footprint.
Kate Garner: We think it's actually a more focused, not an overarching, uh, every store shift and change. But if we could shift some of the products that you're bringing, um, forward to this shopper, we think you could create more relevancy, um, for them. And so that's an, that's an area to say how we can partner together to look at their challenges they're facing and the things [00:21:00] they want to solve and bring ideas that might not just have been on the forefront of the data that they had.
Ian Cook: Really interesting. I'd like to dig into that a little bit. Were you able to get to that insight? And it's probably a combination of both, but more about, did you have data that the retailer didn't have access to? Or was it more about that you understood a little bit more about some specific data that even if the two of you had, you had spent more time looking at or just had been more, um, focused on and had time to dig into?
Kate Garner: Um, so it was some data that we, it was some third party data that we had access to, um, it, it, it was also, you know, internally, right, as part of our overall looking at the national footprint. We recognize the shift in the demographics of the country, and so we spend a lot of time thinking about how are we managing our portfolio against the breadth of shoppers that are in the marketplace today, and ensure that we don't have a one size fits all approach, [00:22:00] and I think just bringing that strategic Perspective to the table is part of why we looked at that as an opportunity when they said, Hey, we want to really unlock some growth, recognizing that they hadn't implemented a Hispanic strategy.
Kate Garner: That was one of the filters that we looked at in evaluating what might be the opportunities for them.
Ian Cook: So to make sure I'm following, they wanted to grow category, which as we talked before, keeping up with category means the whole category is moving and you're either at above or below that trend.
Ian Cook: Growing category is trying to affect and shift the curve of the whole category. So helping people say like, there's more of all of these that we could be selling. So you're working not only with, Hey, I want this one product to sell a little bit more because it's keeping under category, you're helping retailers in general.
Ian Cook: Lift up an entire category by saying there are people out there that you may not be focusing on that constitute a significant portion of your shoppers, but aren't necessarily the ones that you've profiled because you've taken the [00:23:00] time to say, you know what, we understand some national trends. We're taking a different sort of look at this.
Ian Cook: We have some data where we can, um, group things differently. We can categorize shopping behavior a little bit differently. There's another way to look at this and you can present that back to them and you. Both benefit from that, meaning category goes up, the retailers sell more in general. But if you're part of that category, you're selling more of whatever products you have in that category.
Ian Cook: Is that a, did I follow along appropriately?
Kate Garner: Yes, and opening that dialogue, it really generates two way conversation. And we get great feedback from our retail partners as well in terms of ways that we can think differently about our business growth.
Ian Cook: So when we think about working with this data, and I've, again, been doing some reading, been doing some listening.
Ian Cook: I heard a bit that I would like to dig in a little bit more on, which is PepViz, your data analysis platform. Do I have that correct? Terrific. So is this something you're in and working with all the time? Is this the company wide platform for doing data analysis or is it [00:24:00] specific to particular groups that do like the data science and machine learning?
Ian Cook: You know, it's
Kate Garner: a, it's the way we approach our overall commercial planning function. And so when we think about how we go have conversations with our retail partners, so for example, the National Association of Convenience Stores will be having their big industry event in a few weeks and my team will be there.
Kate Garner: At the PepsiCo booth and have this context to really start showcasing how we do some of the analytics that we've talked about today. Do you use
Ian Cook: that to deliver analytics to some of the retailers? Will they, is it a platform that people sign into and go, Hey, you are from this particular convenience store.
Ian Cook: We'll show you how things are going at those stores that you can share. Or is it much more of an internally focused tool? It's an
Kate Garner: internal focus, and it's more about, um, talking about our overall practice. So talking. Yes, there's data. There's also people, there's industry depth of experience and knowledge, and bringing all of that together in a practice in a way that says, Hey, we want to talk to you about what your opportunities are.[00:25:00]
Kate Garner: Um, right. Oftentimes we can build certain advanced analytic models and do other things. Um, and that, that can create an environment where people start selling ideas or what I call shiny objects. And I think that oftentimes it's keeping those things, you know, in the drawer and pulling them out when they're needed.
Kate Garner: The most important thing is really listening and understanding. Right. Is kind of going back. Is there a problem to
Ian Cook: solve if there's somebody staying up late at
Kate Garner: night? Yeah. And so making sure you're really listening to that is
Ian Cook: key. That's interesting. It's hard, I think, sometimes to differentiate between what is the shiny object that everybody could could run after.
Ian Cook: And one of the ones that meet what you called your sort of second criteria, which was I think I have an insight here that this group needs to know about and they've not really asked this question, but it truly informs and could help them make choices. Is there a way that you help your team figure out which ones are the, the shiny objects that that's terrific?
Ian Cook: We'll bring that out when we need to, to come up with Braden. Totally new [00:26:00] brainstorming or to say, Aha, I think you have a real issue there that you should bring up to whomever.
Kate Garner: I invest behind ideas that get people, that get stakeholders excited and waiting with bated breath for the information. That's what I always tell them.
Kate Garner: That's when you know that you have it. When somebody's emailing you and asking you the status and seeking to understand where the... Where the product is at.
Ian Cook: Uh, that's a great way to tell if people really desperately need it, then it's clearly something that somebody wants. I think that's largely how we also figure out if a startup is successful or not.
Ian Cook: Is somebody actually out there eager to start working with it? Am I solving a real problem? Tons of things are really neat to look at, but if it's not solving a real pain point, I just don't have the time and effort and money to, to expend on that. So we've talked a bit about the data that you have, the data that you work with in terms of retailers.
Ian Cook: One of the things I like to talk to people who. work with data all the time about is if you could just have data on something, forget about how it actually comes into the system. If you have data on something, what would that be? [00:27:00]
Kate Garner: If I could have data on something, I feel like we're making so many advancements that I'm excited about.
Kate Garner: The one that I would love to have that I've been challenging our team on is data on how our organization. is leveraging existing data. So it's data on the data. As we look to prioritize, as we look to create what's delivering the most value for us, right? You asked, does everyone work with everything? How do we manage that?
Kate Garner: Right. And at some point that is a management process, right? Managing the robustness of the data. And so that's a place where, um, that I think about a lot. What, how do I want to help our team prioritize and focus?
Ian Cook: So it's something the scale and breadth of PepsiCo, there has to be a lot of time and effort putting put into.
Ian Cook: Purchasing data, collecting, like, normalizing, standardizing [00:28:00] the data, getting it into some storage, making the, uh, accessible to people, getting it in the systems. A lot of the things you talked about is being part of the submersion, part of the iceberg that can be automated, but it still requires a lot of time and a lot of cost.
Ian Cook: So what you're talking about, it sounds to me like understanding Are we using all of that? Is the cost going to something useful at that point? Do we have a good idea of how we're using the data and what might be vital versus what might be less important at any one time?
Kate Garner: Yeah, and we have an awesome team of experts internally that helps us there, um, to manage that.
Kate Garner: The, um, but it's always, you know, as we seek to manage the team's time, it's a, it's a question I always have. When is, when is a date? When is there a sufficient amount of data? And when do we pencils down as business decisions? Because business owners make some business decisions.
Ian Cook: Kate, I want to say thank you so much for your time, for the thoughts.
Ian Cook: It's been a fascinating conversation. Before we go, are there any final thoughts or recommendations you have for even some of the smaller companies facing [00:29:00] the kind of need for data that you have and how best to navigate it?
Kate Garner: You know, for me, it's just. Start someplace and recognize depending on the size of the organization, um, what your user user base looks like.
Kate Garner: So you may have a lot of young associates who are ready to jump on the data train. You may have older associates who there is more change management required. But how do you recognize and reward everyone for leaning in and really focusing on transformation?
Ian Cook: I think that's sound advice. I appreciate the time.
Ian Cook: Again, Kate, all the best. Hope to talk to you again soon and maybe see you around one of these conferences sometime. Thank you, Ian.
Ian Cook: This podcast is proudly sponsored by SEEK, the leader in cloud based creation and delivery of industry focused insights. Thank you for listening. If you liked it, please feel free to rate and subscribe wherever you get your podcasts.[00:30:00]