This is a special episode, featuring a wrap up of insights from top data leaders across the retail and consumer packaged goods industries. They dive deep into topics like being consumer-centric with your data, navigating the pandemic supply chain, improving products and much more.
This is a special episode, featuring a wrap up of insights from top data leaders across the retail and consumer packaged goods industries. They dive deep into topics like being consumer-centric with your data, navigating the pandemic supply chain, improving products and much more.
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Narrator: Hello and welcome to The Data Cloud Podcast. Today we have a very special episode. We’re going to do a deep dive into the retail and consumer packaged goods industry. With insights from some of our top experts. We’ll tackle some of the biggest data challenges facing retail today. Topics like: being consumer-centric with your data, navigating the pandemic supply chain, improving products and much more.
First, Graeme McVie, who’s the Managing Director of Data Science and Analytics at Logic Information Systems., will break down what retail is, and how data impacts it.
Graeme McVie: at its simplest level, retail is about people buying stuff. So those people, the shop was, and that stuff. And when retailers are making the decisions, they want to understand as much as he can about those people, the shoppers, and about the products that are being demanded by the marketplace.
So they can work out what products to buy at what quantities to buy them and try to move those products for the supply chain and then high to sell the customers in the stores. So if you've got a lot of different systems that don't talk to each other, that whole end to end process becomes very complex.
So what we found. Retail is I have three key areas that need to address from this perspective, if they need to have a data platform that brings all of that information together. And snowflake is a great solution for that. though, you need a data model to make everything consistent.
And that's where Robling comes in. Now, before I started working in retail, some of the challenges that all retail data will not at all obvious to me, one that I find, which was surprising, but then made sense to me is around the area of costs. Now you'd think that when a retailer buys an item from a supplier, it has a cost associated with it.
And that would be the end of it. You'd be able to take that cost of goods. You'd be able to work out what your gross margin is. And that will be simple. The problem is retail is oftentimes multiple cost elements and then Telmo systems. So sometimes it was only until I worked with the hide a list cost.
Then they had a net. Uh, net net cost and a dead net cost. So if you have different people in different parts of the organization, not using the same cost to calculate gross modeling, you have people that are talking past each other. So that's one example where the Roebling standardize all of that. You have all the standardized hierarchies of all the standardized metrics.
There's the time that I timeframes. So everybody's talking about the same thing in the same way. So decisions can get made consistently. Then once you're finished with the data model, You then need to make that information available to the business decision makers. So you need a reporting solution on top of it.
You give the business decision makers, access to the insights and information that they need on a very timely basis. So I think of it that I was putting the data and the insights, uh, the fingertips of business decision makers in a way that enables them to make the best possible decision on the shortest possible amount of time.
So you need solutions across those three different areas in order to be effective across all your different functional areas and the high paced, changing environment that is retail.
Narrator: Mani Gopalakrishnan, VP of Digital Transformation at KraftHeinz, knows that once you get those three key areas lined up—you’re set up to create a better product for your customer.
Mani Gopalakrish: At the, at the heart of this is us creating a total understanding of our consumers. We're, we're living in this interesting time where we have a lot of data and that data comes a great responsibility. We take our consumer data and Nona minds and do aggregate analysis on, on that particular data. So, so I may not know that Joe down the street brought our catch-up, but I would know that people in Chicago, Illinois area with such a demographic demographic brought such and such product, that could be our product , our, our, our consumer, our competitor's product.
We are also able to decompose. The ingredient levels in our products. And we are able to not only use that for building enterprise cost drivers, but also Al part research and development teams on how to think about creating new products. So we're able to bring in consumer three 60 , um, to life by not only our own data, but also working with several partners and bring it to life in a very anonymous and aggregate way.
We are also, and I may use this word more generously called competent or three 60, which is where we are looking at our products, decomposing our products , uh, and then matching it up against our competent or products and saying where and how we can continuously improve our products. Right. And then maybe I will take that even further and say insights three 60 and how we're able to clean.
Everything that's publicly available and identify the demand landscape and the trends even before they are here. Now, all of that are in various stages of maturity in the journey as we speak. And, and , um, I faced the consumer three 60 journey that we have started an accelerated, gives me confidence and hope that we can help. We can create a data platform that can help the entire company be more consumer obsessed,
Narrator: Vaibha Kulkarni, VP of Engineering and Data Science at PepsiCo, knows that being customer obsessed is more important now than ever.
Vaibha Kulkarni: Definitely as the world adapts to new ways of living and working , uh, being consumer centric is more important than ever. Uh, consumers are increasingly turning online for their food and beverages needs. Uh, we launched this initiative, Patrick shop.com our direct to consumer initiative. Where a shoppers can quickly and easily order their favorite products and get it delivered to their doorstep.
We developed the site. Within less than 30 days in response to consumer evolving needs. During these uncertain times last year from data perspective , uh, we do some user level analytics to better serve our consumers. Uh, at the same time, we mainly use this data for forecasting and supply chain planning purposes.
Narrator: As we use data to learn more about our customers, that naturally leads into creating a more personalized product. Which data plays a crucial role in facilitating. Arnie Leap,CIO of 1-800-FLOWERS.COM Inc. has the unique perspective of using data to understand personalization when the end-user isn’t always your customer.
Arnie Leap: The gifting paradigm, as it relates to personalization is a very complicated process to go through because we engage with our customers. Sometimes it's self-consumption other times it's a gift. And what makes the gifting portion. More challenging for us is we allow our customers to express themselves to their friends and loved ones directly from our platform.
Meaning you can fill out a greeting card and we can send it our, the gift directly to. It doesn't have to come to your house first. You don't have to wrap it and then put a card on it and then put it back in a box and then send it off to the, to them. So the convenience of being able to gift directly is an important one for any retailer data, as it relates to being once removed. Is even harder to manage because you have to manage some level of context, some level of, of relationship between the parties, meaning customer. Their wife or their spouse, their husband, their daughter, their son, daughter-in-law aunts, uncles. Right. So all of a sudden you get a managed relationships and to a whole bunch of other things within the datas that. And what eventually happens is, is you still need that at your fingertips, right? You're at the Beck and call at the time that the customer or consumer decides that they want to express themselves. an awful amount of data that needs to be available and readily available at our fingertips to help personalize the engagement of our platform and whether it be by mobile device, by tablet, by desktop, by chat messages.
Or voice with a customer service agent. All of those channels all need to be fulfilled with the right data at the right time with the proper context and snowflake provides because it's, cloud-based gives us the ability to morph the edges of the cloud to each one of those channels differently while providing a reasonably seamless experience.
For our customers, snowflake has made some great technological advances in the last year or so by launching their node JS, uh, interface. So our headless commerce platform, which is. Got that has and supports no JS or developers can actually access data directly from the snowflake warehouse.
Um, and from the cloud directly in a secure manner, providing context. To our website and our presentation layers to the different devices that are available. Um, and, and what that, what does that do actually? I mean, what it does is it just changes the paradigm in the equation of how we deliver data to the front side, to be able to present some level of engaging interface for our customers to express themselves.
It is, it is. Amazing to be able to actually sit here and say that versus where we were 5, 7, 8 years.
Narrator: Jeff Buck, CEO of Robling, has seen how all of these technological developments in personalization have impacted targeted advertising.
Jeff Buck: A the environment for retail gets more complex, the need for analytics and data management as a result of that becomes greater and greater because there's no really one system that's going to, uh, handle all of this complexity.
There is. There are all these different ways that, uh, that retailers have adapted to the changing world. And one of those ways is to implement new systems for, for that. So when they have questions about what to do next, with all of the change that happens, they need something that, that answers those, those questions.
And what's also been so interesting, especially in, in COVID is the increase in an advertising digitally. So because of the information that's available, And you were able to target your advertising much, much more finely than ever before. And so, uh, that could be time of day, day of week, but then also who and what you deliver to them in a personalized experience becomes also possible.
So. I think that maybe the target advertising is a little bit creepy and it's good to change with, uh, with all of the regulations around cookies and that kind of thing. However, I think it adds value to our experience when retailers know us better. And so retailers are now adding in that. [00:33:00] That component to the way that they merchandise the two, the way that they stock their stores to the way that they talk to you.
And I think that that's actually getting us closer to where we should be, um, which is a very personal experience with our retailers.
Narrator: COVID hasn’t just impacted how we advertise. Headlines over the past few years have been dominated by supply chain issues impacting retailers of every size. Patrick Duroseau, Vice President of Enterprise Data Management at Under Armour, has seen firsthand what data and analytics can do to help stabilize your supply chain.
Patrick Duroseau: This whole concept of supply chain has come to the forefront of everybody's mind, I think is fantastic and not unique to us. So that, that is where we are and really trying to. Work our way through the, the challenges that that COVID has brought with being able to not only produce, but deliver our products to our consumers.
I think the other thing that, that COVID actually probably brought to the forefront, not directly, but also as a result is the concept and the sustainability. So just really, how do we really draw a circle, clarity around our products as well, and ensure we know where they're being sourced from, how they're being sourced and everything else.
And to answer your question on a data and analytics. And really to drive efficiency and improve the operations of those things. It requires data. It really requires data. And receiving that data closer from our, our sourcing partners are our entire logistics and distribution all the way up to when we actually sell that product.
So data, data, and analytics is played a huge part in that entire life cycle.
Narrator: Sheila Jordan, the Chief Digital Technology Officer at Honeywell, shares how she tackled how the supply chain issues and inflation impacted real time pricing challenges.
Sheila Jordan: We have over 4 million sellable stews. So the other thing of Honeywell is the volume is just significant. So now we're pricing those 4 million sellable fuels in near real time. So that's really exciting. And then as you know, the supply chain with COVID and where we are right now has become a significant challenge for most businesses.
And especially those in that have inventory has become a significant issue in supply chain. So what we're trying to do is to figure out, okay, what does all this mean? And understand the challenges that this is offering us and every industrial company is dealing with this. So we started to see these increases in inflation.
So we're like, okay, these increases where inflation came really last minute and they were pretty significant. So during a discussion, we said, well, why can't we tie inflation to our pricing? Sure. So why can't we link that together? So that's a really significant thing we put into, into play, like the fall of last year.
The same with surcharge. You know, we basically were in some businesses, we were charging surcharge and others, we weren't. So we said, well, why let's look at what the reasonable fair market value is for surcharge, Amazon charges, that's all, all shipping, right? So yes, what's the surcharge we could apply are shipping.
We could charge that's reasonable and responsible, but also we're consistent. So there's a whole bunch of things. Again, the value of the enterprise data warehouse is to. Those pieces of data together that normally sit in a transactional system, but now you have an opportunity to link those together, to deliver this kind of value.
Narrator: When tech leaders in retail are making these kinds of decisions, the customer is directly impacted. Graeme is no stranger to seeing how high the stakes are firsthand.
Graeme Mcvie: So when retailers make, uh, assortment decisions, oftentimes they'll do what they call stacking rank and they'll rank color items based on sales. And they'll cut off. So the ones that are in the bottom that don't sell a lot. What we oftentimes find though, is the one thing the bottom of don't tell are oftentimes very important to your most loyal customers and does not another item in the assortment that they would substitute in for that option.
We oftentimes find items somewhere in the. Of the stack that I actually do have other items that will be substitutable for a customer. So you're oftentimes better keeping those ones on the bottom that are more valuable to your most loyal customers and substitutes and making some changes in the middle of the section where they've got high substitutability and Omnicell important to your most loyal customers, because to what you injectable saying, you know, I, I have a belief that the, the retail.
The best satisfy customer needs will win in the market. You know, if you'll do a really good job of satisfying your customer needs, why would they go somewhere else? But those two fundamental components to underpin that the first is you actually have to understand what your customer needs are. So you need to customer data to be able to do that analysis.
And then secondly, you actually have failed to take actions so you can consistently satisfy those customer needs. So if you don't have the data platform, the most. Um, upon what you can build the analytics, you won't get to that level of understanding. And unless you can actually get to actionable and executable insights to satisfy customer needs, you won't be able to win in the marketplace with shoppers.
So you can continue to end the loyalty and grow your business in a profitable way. So in some regards, there's a personal example I had recently, which I don't know if any of you will be able to relate to that. My kids. Uh, the holidays, when they were going back to school, they actually had to have a, a COVID test, um, you know, before they went back to school.
So I went online to one of the big drug chains to see who had the online at home test kits online. And I found my local store that had it. And I was like, great. And there was some other stores that were stopped, but that's to go home. So I drove up to the store and when I go up to the store, there was a handwritten note, had been stuck to the door saying we are.
Of at-home test kits. And I was like, well, that's frustrating. And the problem with that is the retailer didn't have the systems in place to update the data in real time and then connect it to the inventory that then connected to the website. So they would tell me that it was a stock. So that's why you need these data platforms.
You need them to be real time and need them, all the systems be connected. So you can get that experience to be what your customers want it to be.
Narrator: Giving our customers what they want is our ultimate goal. And using the data-backed decision making skills we’ve covered today is the surest way to get there. We’ll close out with Arnie sharing what he thinks is the ultimate secret to using your data in the best way possible.
Arnie Leap: The challenges about processing data will haunt man forever. The human race, the human race will forever be challenged by processing data. The question is, is how good are you at using certain tools and how creative can you be? For example, not everybody's a carpenter and there are certain people I would not trust, swinging a hammer.
There are also certain people that know how to draw a wonderful picture of their family and loved ones and hanging on a wall that I wouldn't necessarily trust certain people with a pencil. So what tools are available and what skills do you have? And this gets back to the notion of. How do I, as a CIO, enable enough of the team at the right times with the right tools to make them successful in what they do. Right. And four years ago, we made the conscious decision to ramp down some of the investments in the data warehouse. And because we knew we were going to shift gears, we built up a war chest. We started looking at different tools and different capabilities, understanding roadmaps of certain companies that in their tool sets and how they work.
And so. Then as we, you know, all of a sudden we have this wonderful pool of assets that we can go acquire tools at the right time, at the right place when the team's ready to actually approach that problem or solve that specific challenge. And then take advantage of it appropriately. Um, and it is timing.
Timing's a big piece of it. it's one thing to have the data.
It's another to be able to leverage it. And then it's even more important to be able to take advantage of it at the right time.
Narrator: As we learned today, the world of retail is as ever changing as the world of data. Luckily, we have a ton of experts to help us navigate the ever changing landscape.
We hope you enjoyed this special episode of The Data Cloud Podcast. Until next time.