00:00:09
Speaker 1: ESG is constantly evolving. Over the years. It is shifted from socially responsible investing to impact to sustainable finance. While the terminology continues to change, what hasn't changed are the underlying science, market pressures, and tangible physical and financial impacts of the Kimic crisis. We aim to filter out the noise by speaking with industry experts to identify what is really driving value. Welcome to ESG Kurrentz. I am Andy Stevenson, Senior climate analyst and your host for today's episode. Today we are talking about using weather patterns to forecast consumption trends with Fred Fox, who is CEO of Planalytics, will discuss how shifts and temperature, rain and snow can lead consumers to make different choices going forward. Thanks for joining Fred, Thank you, and I had to be here with you guys great. Can you explain what Planet Linx does for us, what types of customers you engage with, that kind of thing that would be really helpful.
00:01:12
Speaker 2: Sure. So, I think I have one of the most fun jobs on the planet because we get to help businesses understand how weather influences consumer demand and purchasing be behavior all around weather. So if you start and ue with weather is one of the largest external drivers of consumer purchasing decisions. So it affects everything that we decide as consumers the win, where, what, and how much to buy. Yeah, it's the least understood, the least measured, and really the least utilized a factor that's out there. Weather is driving consumers to purchases goods and services. So what we do with Planalytics is we've built a capability, a technology that inculs all types of client data and creates a climate model for the business on the demands side exactly how weather's driving consumer purchases at the level of purchase, which is the store or on the e commerce side that they can you know the when, where, and how much the weather is driving them?
00:02:32
Speaker 1: Gotcha? Can you give us a sense of the scale of what you're talking about here? Obviously we have a US economy is absolutely massive when it comes to consumer spending, many trillions of dollars. Is this how much of the needle is moving with respect to climate? Can you just give us a weather patterns? Can you just give us a sense of the scale of it? Sure?
00:02:53
Speaker 2: So weather drives about three percent of retail sales globally. So in retailing is the world's largest industry and it drives three percent of that. So if if you think of it, that that equates to about a trillion dollars any given time of weather based sales swings on a annual basis. So whether can change consumer purchasing enough that you're going to get about a trillion dollars of swings in purchasing year to year due to weather.
00:03:34
Speaker 1: That's a phenomenally large amount of money that, as you say, is very under recognized as a driving force in terms of sales patterns and shifts. Do you want to, like, maybe give us an example of where you of one of these patterns and how it kind of played out in terms of you know, what the consumer ended up not buying or buying. And I know that your data is very regional or even city specific, maybe highlight how that plays relative to another city, you know, just to keep just to make give some comparison.
00:04:08
Speaker 2: Sure, So we are engulfing data from some of the world's largest retailers and consumer packaged goods businesses, and we're doing it every day, trillions and trillions of bits of data on purchasing exactly everything they're selling in every location, in every day, so we have a view on how weather's affecting the entire assume economy. So when you think of weather, weather affects people differently based on several key factors. One where you are, I mean, sixty degrees let's say in Miami is going to drive consumer purchasing different than sixty degrees in Minneapolis. You know, if you take a product like long underwear, which is a very warm weather product, they sell it in Minneapolis, but temperatures have to get down to sort of the low twenties before people start to feel the need to buy it. In Miami, it gets below sixty and you'll start to see long underwear Staye'll start to spike, you know, So people get used to the weather of where they are, and something like cold is an example time of year place part two. So if you look at like, sixty degrees in October is different than sixty degrees in February. In October it's starting to feel a built chili. In February it's feeling warm, and so you know, it depends on when those temperatures hit the I would say too that the specific products matter. So if you think of something like ice cream for instance, you know ice ice cream can sell and the NOVELI, which is the handheld, it can sell in the pine, it can sell in a gallon. In a place like Europe, they sell a lot more novelies extremely weather affected, like fifteen eighteen percent swings week to week in sales due to weather. Pints are affected about maybe eight to twelve percent swings and sales due to weather. Gallons which we buy in dates and we've now spread to other parts of the world. We put in our freezer there about three to four percent weather affected because it's more of a staple product, So that matters. If you look at things like you like, you know, water, I mean a six pack is different than a single bottle where their soul matters. Convenience stores are much more weather effected than a mess merchant because a convenience store we are going in there. Age matters. You know, older people are influenced differently than the younger people to weather, so older people may be more sensitive to weather than let's say a younger person. Pricing and fashion matters. You know, weather drives needs versus one When you think of it, weather is driving our need to buy a product, not our want to buy a product. As you go up in price scale, you move from the need to more than one. So high fashion boots you don't need to buy high fashion boots. You want to buy high fashion boots and may cost one thousand dollars, but those one hundred and fifty dollars pair of boots, it's more on a need basis, can be much more weather effected. Gender matters men versus women's So I can go on and on on this.
00:07:56
Speaker 1: No I want you to go on and on. I just want to break up a little bit. And you made me think of because I just came from living in Florida and when it was sixty degrees, the ugs came out, like you can't believe. So you had all these you know, women dressed in kind of the summer kind of where but they are wearing ugs as a compliment. So it just obviously very winter friendly and well, a lot of what you're pointing to sounds like logistics is a huge component of what you're describing as well, right, I mean you're talking about not only are how people are changing their consumption functions, but but the wear is very very important. So if you are a retailer for in particular, you need to get those goods to where they need where they're going to be sold, right, I mean, that's that seems like one of the functions that you probably are one of the most successful things your company does, is allow for better logistics. And how that kind of plays maybe if you talk a little bit about that, because let's say air conditioners for example, you know, like the demand for air conditioners, you want more where they're needed, right, So I'm just curious if that plays a role at all.
00:09:13
Speaker 2: Yes, So companies use us for logistics, inventory management, planning, marketing, effectiveness, labor as well as just financial reporting and planning. So whether affects every part of a retailer or consumer packaged goods business because it affects the consumer, so it flows throughout how they use weather analytics, so in each part is very different. So a grosser, we can model anywhere from twenty to seventy thousand items a day that goes into their replenishment system, adjust their system according to what goods are going to be selling a over the next week, and they're shipping into that the man where there is weather driven d man and they're not shipping as much into those stores that there's not going to be that demand, So that drives things like waste savings because they're not do you waste as much goods on shelf availability. There's all types of metrics as well as labor, and that adds up to huge, huge dollar savings for these businesses that all can be measured other businesses uses for marketing. So those same analytics we may build for a inventory model can also be used to drive a marketing model because you want to fish where the fish are if you're into fishing, and what that means is that you want to market your product when and where the consumer is mentally in the mood to buy those goods based on whether so they're going to buy those goods and you want them to go into your funnel versus your competitors tunnel.
00:11:10
Speaker 1: Wow, And I just wanted to go back to what you mentioned on labor because that's a very interesting component that I think is harder for people to get their heads around because you think about, Okay, I understand that there's going to be different actual purchases, but can you talk a little bit about the labor implications of that, because that's a pretty interesting thread. Sure.
00:11:30
Speaker 2: So you know, labor is very much based on the amount of anticipated demand into a store. Most labor systems today just look at the payass sales and do some average of the type of foot traffic you would expect in a certain part of the day as a certain day day of the week, and then adjust and you make sure you have enough people there. What it doesn't account for so well is really how much weather is affecting store traffic. So when we model data, we know exactly how much traffic you're going to get all based on weather. That use for labor scheduling allows these companies to do a much more effect a job of both the front end of the store as well as well as to the back end having enough people or having less people to really support that type of traffic.
00:12:32
Speaker 1: Can you just get a sense of, like how much the impact is on labor. So let's say it's gonna let's say there's a storm coming, like a major storm or something along those lines, or you know, giant a freeze. It doesn't really matter how much of a swing in labor is. Can that be.
00:12:50
Speaker 2: Well, a storm, whether it's a hurricane or let's say a snowstorm, you know, can both add huge opportunity and risk for a retill how the opportunity is of course before that storm hits, because you have a weather driven traffic in anticipation of that storm. So knowing how much they need to ship into those areas is part of what we model based on how these storms will drive traffic. And because we are analyzing years and years of their sales data against similar types of weather, we know exactly how many sales are going to have based on an incoming storm. But then there's the adverse effect, what is a lag factor after the storm. Because the lag of these storms can also drive traffic, it can also depressed traffic because people have bought a head of the storm. The best type of storm that our retailers love is one of the forecasts but never hits because you get all the sales and none of none of the cleanup mets here.
00:13:58
Speaker 1: That makes sense, no downside. They just keep on spending. But you think about I mean, obviously retail and restaurants and things like that, people will either you know, they'll they'll pick up that pace and then you can't replace those days. Right if the storm closes your street or something along those lines. That's sort of the end of it for the label.
00:14:17
Speaker 2: Well, I mean live factors in retail due to weather are a big part of what we model now. Certain parts of retail, such as a restaurant, there is no makeup. I mean, you're not going to go out to a restaurant and double down two three times a day to make up for the fact that you didn't go the day before because it was heavy rain or snow. So lost sales do the weather is really lost sales. If you look at a parel yes, there's time to make it up. So in this last season is really a great case. I had a pretty rough May in apparel, and I would say that it was much clothing last year, and about the eastern half of the nation sales were down. You had some economic headwinds as well. It was a pretty good storm. By mid June the weather totally changed. Summer came in. We sort of missed spring and we saw a big sales job. The same was true in the DIY sector. A lot of consumers were putting off purchases due to unfavable weather for many outdoor products, and some of that was made up in the latter part of the June and July period, so you know you can make these up if the weather turns, you never make up all of it. The other thing that I'll mention too, is that making up sales later in the season, you may be making up top line sales, but you're not making up margin because you know the highest margin is always going to be at the start of the season. That's why we're here in labor day. It's feeling like fall. It's great selling weather, especially for the soft line retail just because they will sell a lot more products at full price, which is their best way to sell. If those things sit on the shelves and don't sell and they have to start to discount prices, as all these retailers do, then they can sell them later in the season, but they can sell at a much tighter margin.
00:16:18
Speaker 1: And would you say this, so, is this an average year or this is an atypical year just out of curiosity.
00:16:24
Speaker 2: Well, in weather, there's no thing as normal, even though there is normal. So the weather's always warmer, colder, wet, or dryer. That's really the beauty of it for us is that it's always changing. And therefore companies that don't incorporate that knowledge into the way they operate, are really going out into every season a little bit blind. They've done everything else right, they've planned it, they've spent multiple amounts of time on the right products, the right fashion, the right pricing. But if they're not incorporating weather, then they're leaving a big part of what they do to chance. If you look at some of the quotes from this last spring, you look at Low's, you look at oh Riley, you had a really rough May, and Marvin Ellis from Low's said that weather is their number one one of the number one drivers, and their business aligns heavily with weather, and that was to explain that they were having a rough, fairly start to spring. Now they had a great second half of spring weather eyes, and they were able to make a lot of that up. It's hard to say how much was left on the table because they weren't really planning ahead and anticipating that type of weather. And versely, the same wet cold weather that was hurting Low's helped oh'illy auto sales because when you get cold, wet weather in the spring, it means more accidents, more breakdowns, more traffic into to get to their stores.
00:18:10
Speaker 1: It's just a revolving ricocheted bullet rickcheting bullets. That's where you're discovering, yes, and I mean obviously from a trading perspective, just to go into the financial you know, case of this, like knowing that they had a soft and acknowledge soft early part of the season, but seeing the weather kind of pick up, knowing that there is scope for them to make that up right, because there's there's sort of people kind of always promised to make it up, but you know, like the weather needs to help you make that up right. So the weather needs to behave in a way that allows that to happen. So that's also kind of an interesting insight that you're able to glean from some of your work, is that not only are you seeing what's going on as it's happening, but the kind of downness of the market relative you know, because of statements like that you just described from the CEO of Lows, there is sort of a ray of hope there, you know, like that's that's not necessarily the end of the size. You say, the spring didn't end. You know, they were able to make that up. So that's a pretty interesting insight. I think, you know, from a financial standard standpoint.
00:19:19
Speaker 2: Yeah, they were able to make it up from from an operational standpoint. But if they're not incorporating weather analytics, how much are they leaving during on the table? And numbers are quite large. So now weather can hurt and help and all these companies are operationally set up to deal with that. But whether and whether analytics present an opportunity into day's world of a cloud based scalable analytics incorporating AI, there's the ability to model mask of amounts of data and to not guess, but to know. So so you know, these companies should know what's going to be hitting them and they should know how to act because they do not even know what it's hitting them. But what is going to come around the corner. That's massive, massive knowledge. So at least we talk to the market about. Now we've been doing this a number of years, I am still surprised in twenty twenty five how few companies incorporate these types of weather analytics. Very very few. It's it's rare we show up and someone is doing something about it. There's a lot of people now that are throw weather into an AI system. But you know, raw weather data into a AI system doesn't really give give the answers, so you know, it's it's it's one of those things that what we do is we put our pre engineered numbers into these systems, and it's like a turbocharger.
00:21:05
Speaker 1: Gotcha? And how far out are you when you're describing whether is this a month forward? What's the forward? How far out do you look when you look at for these patterns, like where your confidence level you feel comfortable making, you know, assessments because the weather does shift.
00:21:22
Speaker 2: Well, weather forecasting, the state of the the state of the science today, the state of the art is really about two weeks out. I mean that's that's how much weather modelor is out. But we can strip whether out of last year's data and allow companies to to plan from a more normalized, clean base base one. So by by doing that from an analytical point of view, you automatically raise their ability to hit plan because you're not planning off last year. If you're not taking last year's weather out of the data, you're assuming last year's whether what would occur next year, which may happen twenty some percent of the time. So by taking it out, you're really upping your odds quite a bit. You're flipping those odds.
00:22:17
Speaker 1: Yeah. The only the industry that comes to mind that actually does that is the utility sector. Like they actually publish every quarter. I mean, you could probably get it even daily if you want it, if you have that much time on your hands. But they report you know, weather related impacts, right, because they try to make sure that that is separated out as not a factor of growth or you know, it does not reflect positively or negatively because it obviously swings both ways on you know, customer demand, right, because that's what they're trying to at least from an investors standpoint. They're trying to highlight the piece that doesn't include the weather patterns, right, right.
00:23:00
Speaker 2: Like you get that, we all get that in our bills, are right, it's exactly what those normalized us are. So that's a sense we're doing for a very complex industry, which you know, thousands and thousands of different to products categories sold through different locations. We take that complexity and we work through it and provide it back in very useful ways to to our clients.
00:23:27
Speaker 1: That's great, And you mentioned that you do this globally. Is that that's correct, we do it globally, and would you say the US because from a damages standpoint, and particularly this year, I mean not that this is necessarily the norm, but ninety percent of the insured losses in the first half the year. We're in the US as an example for a client from a climate perspective, and you know, obviously we've had great floods this year. Severe storms were a feature of the summer. Well, not necessary like never before, but certainly unusually high relative to the history. Does the US stand out as being the more one of the most dynamic users of you know, I'm just saying from an application standpoint, clients in the US, are they like they really should be looking at what you're talking about? Or is it or is it similar in other places?
00:24:20
Speaker 2: Well, weather affects consumers globally, in every place on the planet, even in the San Diego which doesn't really have weather. I like to joke with my friends that live there it's always seventy. But one of the really fascinating things about the US that we have one of the most violent, one of the most violent weather on the planet, the most changeable, and most people here don't realize that. We just take it for granted that we had weather that swings so much. That's not true in the rest of the world. And the reason is is because we're almost like an island nation. We have this warm pool of water sitting at our south called the Golf and we have, of course the polar to the north, and our mountain ranges run north to south. So unlike Europe which has the Alps, because the US have a warm body, where do they have the Mediterranean as how, polar air coming down, but there the Apps sort of stops those patterns from coming together. A lot. We don't have that. I mean the Rockies and really really the Appalachians run north south. We have the planes in the middle, and so you have this cold air and the warm tropical air are always fighting each other and so they're always moving up and down and that creates tremendous volatility that most places on this planet don't really have.
00:25:49
Speaker 1: Yeah, I can believe that. And imagine is Canada close or is Canada not even close? Like from a just from a volatility perspective.
00:26:00
Speaker 2: I mean they have some you know, the southern part of Canada, you have the changeable weather, uh quite a lot. I mean if you look at the you know, if you look at the southern part, which is really along the US border, that that changed as much as our cities like Detroit, UH Andicago.
00:26:21
Speaker 1: Sure, Minneapolis and places like that. That makes sense. I wanted to spend a little time on supply chains because I think this is obviously when you were talking about forecasting, and you know, you're looking at history, you're getting some sense of what the impacts could be. But just from a goods production standpoint, is this is are you seeing shifts in because of the work that you do? You know, like, are you seeing manufacturing actually being affected in places like lows? You know, are they more reserved about having, you know, leaf blowers in July or something like that because of what they've been seeing historically, or is it doesn't reach that far back.
00:27:04
Speaker 2: Well, it really depends on the use. We have five different use products. I mean, we have the financial reporting and planning, which is from a finance point of view, it's a top down view. We have merchandise planning and allocation. We also have marketing, and we have operations which is extreme weather. And then we have inventory. So when companies are using us for inventory and we've modeled all their weather affected products, which can be anywhere. It's that said twenty thirty forty thousand items a day, it's going into their systems. That's in adjusting their systems on a regular basis to ship into their stores from their warehouse. So in those cases, we're having a very meaningful bottom line effect. It's we're making sure using that old added so that they're having the right product the right place at the right time. When we affect the planning side, most companies aren't using us for the buy because that's a whole different area, but they are using us to plan their overall sales. They're using us to what parts of but the States are going to load load up more than others where we think they're going to have a better opportunity from a preseason standpoint. And then the marketing area is is to a very measurable area. I mean, we were generating about thirty percent increased row ads due to aligning their marketing activities with greater lift. So you know, it really depends where and how they're using us, gotcha.
00:28:50
Speaker 1: Yeah, And the marketing side sounds like a pretty fascinating area because you are you kind of have for knowledge, you know, like you're as try everything kind of is built on some kind of in and this is this is the instinct that we don't know we have, you know, which is that these weather patterns are actually making informing us as we go along about what we think we need on a kind of constant basis, shall we say, Right, So there's there's certainly that. Well we're kind of winding down towards the end here. What I did want to give you some time to talk about where you see your business kind of growing and maybe you know, like you opportunities you think for Planeltics going forward, Like what excites you about I mean obviously you're you're in a space where not many people are playing, you know, and in such an impactful way, And just was curious if what what was sort of next for Planelytics.
00:29:43
Speaker 2: Well, you know, our our mission has never changed, but our means of achieving that just has changed radically. And so it's it's for us, it's always fresh and it's always using new technology. To get to the bottom line is how is weather d driving the consumer and how can these companies apply that knowledge to make better the decisions, whether the decisions are through their four kiss engines, whether they're through a management team sitting in a Monday morning meeting, all can be used. So what a psyche sets is the ability to help more and more companies at tree mendous scale. And we are always finding new ways. I total client the other day in Europe that if they have questions that we can't answer, or if we come across something that we haven't yet looked at, we just automatically analyze that. We don't charge it for it because we want to get to the bottom of it. We want to see how is weather driving a consumer And it gets complex with these multi national businesses. How they operate, how they plan, it depends on their data. So you know, it's really sifting through that and it's become in some ways much easier to do because we've built this engine that can take any type of data. So we're always pushing the bounds of what we can do to look at these impacts. You know, if I look at what's on our exciting lists right now. Other than building new automation through our AI tools, you know, we're just building these lag factors after a major storm passes, so you know, what will consumers buy after the storm? Some clients asked us that we'd have an answer, and we're harder. We're getting it, but you know, it takes a lot of modeling to make that happen, and then we have to put that into a galible engine. Yeah.
00:31:53
Speaker 1: Yeah, yeah, we're at Blomberg. We're looking at smoke days, you know, the wildfire effects on consumption and labor at the moment and putting out a piece next week or putting out a piece related to how the twenty twenty three events, which were kind of a factor of five in terms of smoke days relative to history, you know, because of the Canadian wildfires, was very impactful to wages period like it had you talk about three trillion in the kind of front facing sectors which includes retail, but wholesale and others. And you find that, you know, some of these impacts were up to five to fifteen percent of the wage bill was being negatively impacted by this. So it's several hundred billions of dollars and if you're looking at in one year, historically it's been very very small relative to that. But that obviously also means people aren't going to restaurants and people aren't doing you know, I'm saying there's a whole cascading effect that affects retail and wholesale and other areas that are kind of on the front lines construction Obviously, construction sale are difficult. In construction building, it slows down, even cement slows down, which is so it's a there's a yeah, it's a lot to absorb, and you need very very good data modelers to come up with the actual smoke, you know, pulling the smoke out of that. We have pollution period, right, you know, air pollution is a thing hasn't gone away. It's pretty good. You know, the air is pretty good, but we're kind of crawling the other direction because of the smoke, and it's having a pretty interesting impact on you know, the economy period. Which because we've used to be very localized on the West coast, we're seeing this really significant drift east of these impacts. And so what was kind of a California problem, you know that maybe or Oregon problem, is now a problem Minnesota as you just mentioned Minnesota. But you know, the the biggest impacts were in like Tennessee and North Carolina, surprisingly relative to history. So just just as if you're looking for something to do. You can you can look at that one as well if you want to throw that in the in the mix.
00:34:10
Speaker 2: But I'll well, I can't wait to read your article. But that that that sounds really a fascinating and anything you'd like us to look at.
00:34:20
Speaker 1: Okay, okay, yeah, we're I mean I this, as you know, this is not a very well pursued area of expertise, so unfortunately, I would argue for for people's consciousness of what actually is going on. But anyway, but thank you, thank you very very much. This was great, Fred. I learned a ton. I hope this was helpful to others really understanding the power of what you're talking about here. And these are you know, three percent on thirty three trillion is a is a trillion, you know, so that's a that's a massive amount of money, right, So there's no no denying that this is this is already well established as a as a driver of consumer preference, and obviously from a financial perspective that makes a lot of difference. But thank you again for your time. This was great.
00:35:09
Speaker 2: Thanks for having me.
00:35:11
Speaker 1: You can find more information on topics like climate damages and impacts by going to the Blomberg function BI Carbon and then the Climate Damages tracker on the Bloomberg terminal. If you have an ESG quandary or burning question you would like to ask bi's expert analysts, please send us an email at A Stevenson seventy eight at bloomberg dot com or ESG Currents at Bloomberg dot net
Speaker 1: ESG is constantly evolving. Over the years. It is shifted from socially responsible investing to impact to sustainable finance. While the terminology continues to change, what hasn't changed are the underlying science, market pressures, and tangible physical and financial impacts of the Kimic crisis. We aim to filter out the noise by speaking with industry experts to identify what is really driving value. Welcome to ESG Kurrentz. I am Andy Stevenson, Senior climate analyst and your host for today's episode. Today we are talking about using weather patterns to forecast consumption trends with Fred Fox, who is CEO of Planalytics, will discuss how shifts and temperature, rain and snow can lead consumers to make different choices going forward. Thanks for joining Fred, Thank you, and I had to be here with you guys great. Can you explain what Planet Linx does for us, what types of customers you engage with, that kind of thing that would be really helpful.
00:01:12
Speaker 2: Sure. So, I think I have one of the most fun jobs on the planet because we get to help businesses understand how weather influences consumer demand and purchasing be behavior all around weather. So if you start and ue with weather is one of the largest external drivers of consumer purchasing decisions. So it affects everything that we decide as consumers the win, where, what, and how much to buy. Yeah, it's the least understood, the least measured, and really the least utilized a factor that's out there. Weather is driving consumers to purchases goods and services. So what we do with Planalytics is we've built a capability, a technology that inculs all types of client data and creates a climate model for the business on the demands side exactly how weather's driving consumer purchases at the level of purchase, which is the store or on the e commerce side that they can you know the when, where, and how much the weather is driving them?
00:02:32
Speaker 1: Gotcha? Can you give us a sense of the scale of what you're talking about here? Obviously we have a US economy is absolutely massive when it comes to consumer spending, many trillions of dollars. Is this how much of the needle is moving with respect to climate? Can you just give us a weather patterns? Can you just give us a sense of the scale of it? Sure?
00:02:53
Speaker 2: So weather drives about three percent of retail sales globally. So in retailing is the world's largest industry and it drives three percent of that. So if if you think of it, that that equates to about a trillion dollars any given time of weather based sales swings on a annual basis. So whether can change consumer purchasing enough that you're going to get about a trillion dollars of swings in purchasing year to year due to weather.
00:03:34
Speaker 1: That's a phenomenally large amount of money that, as you say, is very under recognized as a driving force in terms of sales patterns and shifts. Do you want to, like, maybe give us an example of where you of one of these patterns and how it kind of played out in terms of you know, what the consumer ended up not buying or buying. And I know that your data is very regional or even city specific, maybe highlight how that plays relative to another city, you know, just to keep just to make give some comparison.
00:04:08
Speaker 2: Sure, So we are engulfing data from some of the world's largest retailers and consumer packaged goods businesses, and we're doing it every day, trillions and trillions of bits of data on purchasing exactly everything they're selling in every location, in every day, so we have a view on how weather's affecting the entire assume economy. So when you think of weather, weather affects people differently based on several key factors. One where you are, I mean, sixty degrees let's say in Miami is going to drive consumer purchasing different than sixty degrees in Minneapolis. You know, if you take a product like long underwear, which is a very warm weather product, they sell it in Minneapolis, but temperatures have to get down to sort of the low twenties before people start to feel the need to buy it. In Miami, it gets below sixty and you'll start to see long underwear Staye'll start to spike, you know, So people get used to the weather of where they are, and something like cold is an example time of year place part two. So if you look at like, sixty degrees in October is different than sixty degrees in February. In October it's starting to feel a built chili. In February it's feeling warm, and so you know, it depends on when those temperatures hit the I would say too that the specific products matter. So if you think of something like ice cream for instance, you know ice ice cream can sell and the NOVELI, which is the handheld, it can sell in the pine, it can sell in a gallon. In a place like Europe, they sell a lot more novelies extremely weather affected, like fifteen eighteen percent swings week to week in sales due to weather. Pints are affected about maybe eight to twelve percent swings and sales due to weather. Gallons which we buy in dates and we've now spread to other parts of the world. We put in our freezer there about three to four percent weather affected because it's more of a staple product, So that matters. If you look at things like you like, you know, water, I mean a six pack is different than a single bottle where their soul matters. Convenience stores are much more weather effected than a mess merchant because a convenience store we are going in there. Age matters. You know, older people are influenced differently than the younger people to weather, so older people may be more sensitive to weather than let's say a younger person. Pricing and fashion matters. You know, weather drives needs versus one When you think of it, weather is driving our need to buy a product, not our want to buy a product. As you go up in price scale, you move from the need to more than one. So high fashion boots you don't need to buy high fashion boots. You want to buy high fashion boots and may cost one thousand dollars, but those one hundred and fifty dollars pair of boots, it's more on a need basis, can be much more weather effected. Gender matters men versus women's So I can go on and on on this.
00:07:56
Speaker 1: No I want you to go on and on. I just want to break up a little bit. And you made me think of because I just came from living in Florida and when it was sixty degrees, the ugs came out, like you can't believe. So you had all these you know, women dressed in kind of the summer kind of where but they are wearing ugs as a compliment. So it just obviously very winter friendly and well, a lot of what you're pointing to sounds like logistics is a huge component of what you're describing as well, right, I mean you're talking about not only are how people are changing their consumption functions, but but the wear is very very important. So if you are a retailer for in particular, you need to get those goods to where they need where they're going to be sold, right, I mean, that's that seems like one of the functions that you probably are one of the most successful things your company does, is allow for better logistics. And how that kind of plays maybe if you talk a little bit about that, because let's say air conditioners for example, you know, like the demand for air conditioners, you want more where they're needed, right, So I'm just curious if that plays a role at all.
00:09:13
Speaker 2: Yes, So companies use us for logistics, inventory management, planning, marketing, effectiveness, labor as well as just financial reporting and planning. So whether affects every part of a retailer or consumer packaged goods business because it affects the consumer, so it flows throughout how they use weather analytics, so in each part is very different. So a grosser, we can model anywhere from twenty to seventy thousand items a day that goes into their replenishment system, adjust their system according to what goods are going to be selling a over the next week, and they're shipping into that the man where there is weather driven d man and they're not shipping as much into those stores that there's not going to be that demand, So that drives things like waste savings because they're not do you waste as much goods on shelf availability. There's all types of metrics as well as labor, and that adds up to huge, huge dollar savings for these businesses that all can be measured other businesses uses for marketing. So those same analytics we may build for a inventory model can also be used to drive a marketing model because you want to fish where the fish are if you're into fishing, and what that means is that you want to market your product when and where the consumer is mentally in the mood to buy those goods based on whether so they're going to buy those goods and you want them to go into your funnel versus your competitors tunnel.
00:11:10
Speaker 1: Wow, And I just wanted to go back to what you mentioned on labor because that's a very interesting component that I think is harder for people to get their heads around because you think about, Okay, I understand that there's going to be different actual purchases, but can you talk a little bit about the labor implications of that, because that's a pretty interesting thread. Sure.
00:11:30
Speaker 2: So you know, labor is very much based on the amount of anticipated demand into a store. Most labor systems today just look at the payass sales and do some average of the type of foot traffic you would expect in a certain part of the day as a certain day day of the week, and then adjust and you make sure you have enough people there. What it doesn't account for so well is really how much weather is affecting store traffic. So when we model data, we know exactly how much traffic you're going to get all based on weather. That use for labor scheduling allows these companies to do a much more effect a job of both the front end of the store as well as well as to the back end having enough people or having less people to really support that type of traffic.
00:12:32
Speaker 1: Can you just get a sense of, like how much the impact is on labor. So let's say it's gonna let's say there's a storm coming, like a major storm or something along those lines, or you know, giant a freeze. It doesn't really matter how much of a swing in labor is. Can that be.
00:12:50
Speaker 2: Well, a storm, whether it's a hurricane or let's say a snowstorm, you know, can both add huge opportunity and risk for a retill how the opportunity is of course before that storm hits, because you have a weather driven traffic in anticipation of that storm. So knowing how much they need to ship into those areas is part of what we model based on how these storms will drive traffic. And because we are analyzing years and years of their sales data against similar types of weather, we know exactly how many sales are going to have based on an incoming storm. But then there's the adverse effect, what is a lag factor after the storm. Because the lag of these storms can also drive traffic, it can also depressed traffic because people have bought a head of the storm. The best type of storm that our retailers love is one of the forecasts but never hits because you get all the sales and none of none of the cleanup mets here.
00:13:58
Speaker 1: That makes sense, no downside. They just keep on spending. But you think about I mean, obviously retail and restaurants and things like that, people will either you know, they'll they'll pick up that pace and then you can't replace those days. Right if the storm closes your street or something along those lines. That's sort of the end of it for the label.
00:14:17
Speaker 2: Well, I mean live factors in retail due to weather are a big part of what we model now. Certain parts of retail, such as a restaurant, there is no makeup. I mean, you're not going to go out to a restaurant and double down two three times a day to make up for the fact that you didn't go the day before because it was heavy rain or snow. So lost sales do the weather is really lost sales. If you look at a parel yes, there's time to make it up. So in this last season is really a great case. I had a pretty rough May in apparel, and I would say that it was much clothing last year, and about the eastern half of the nation sales were down. You had some economic headwinds as well. It was a pretty good storm. By mid June the weather totally changed. Summer came in. We sort of missed spring and we saw a big sales job. The same was true in the DIY sector. A lot of consumers were putting off purchases due to unfavable weather for many outdoor products, and some of that was made up in the latter part of the June and July period, so you know you can make these up if the weather turns, you never make up all of it. The other thing that I'll mention too, is that making up sales later in the season, you may be making up top line sales, but you're not making up margin because you know the highest margin is always going to be at the start of the season. That's why we're here in labor day. It's feeling like fall. It's great selling weather, especially for the soft line retail just because they will sell a lot more products at full price, which is their best way to sell. If those things sit on the shelves and don't sell and they have to start to discount prices, as all these retailers do, then they can sell them later in the season, but they can sell at a much tighter margin.
00:16:18
Speaker 1: And would you say this, so, is this an average year or this is an atypical year just out of curiosity.
00:16:24
Speaker 2: Well, in weather, there's no thing as normal, even though there is normal. So the weather's always warmer, colder, wet, or dryer. That's really the beauty of it for us is that it's always changing. And therefore companies that don't incorporate that knowledge into the way they operate, are really going out into every season a little bit blind. They've done everything else right, they've planned it, they've spent multiple amounts of time on the right products, the right fashion, the right pricing. But if they're not incorporating weather, then they're leaving a big part of what they do to chance. If you look at some of the quotes from this last spring, you look at Low's, you look at oh Riley, you had a really rough May, and Marvin Ellis from Low's said that weather is their number one one of the number one drivers, and their business aligns heavily with weather, and that was to explain that they were having a rough, fairly start to spring. Now they had a great second half of spring weather eyes, and they were able to make a lot of that up. It's hard to say how much was left on the table because they weren't really planning ahead and anticipating that type of weather. And versely, the same wet cold weather that was hurting Low's helped oh'illy auto sales because when you get cold, wet weather in the spring, it means more accidents, more breakdowns, more traffic into to get to their stores.
00:18:10
Speaker 1: It's just a revolving ricocheted bullet rickcheting bullets. That's where you're discovering, yes, and I mean obviously from a trading perspective, just to go into the financial you know, case of this, like knowing that they had a soft and acknowledge soft early part of the season, but seeing the weather kind of pick up, knowing that there is scope for them to make that up right, because there's there's sort of people kind of always promised to make it up, but you know, like the weather needs to help you make that up right. So the weather needs to behave in a way that allows that to happen. So that's also kind of an interesting insight that you're able to glean from some of your work, is that not only are you seeing what's going on as it's happening, but the kind of downness of the market relative you know, because of statements like that you just described from the CEO of Lows, there is sort of a ray of hope there, you know, like that's that's not necessarily the end of the size. You say, the spring didn't end. You know, they were able to make that up. So that's a pretty interesting insight. I think, you know, from a financial standard standpoint.
00:19:19
Speaker 2: Yeah, they were able to make it up from from an operational standpoint. But if they're not incorporating weather analytics, how much are they leaving during on the table? And numbers are quite large. So now weather can hurt and help and all these companies are operationally set up to deal with that. But whether and whether analytics present an opportunity into day's world of a cloud based scalable analytics incorporating AI, there's the ability to model mask of amounts of data and to not guess, but to know. So so you know, these companies should know what's going to be hitting them and they should know how to act because they do not even know what it's hitting them. But what is going to come around the corner. That's massive, massive knowledge. So at least we talk to the market about. Now we've been doing this a number of years, I am still surprised in twenty twenty five how few companies incorporate these types of weather analytics. Very very few. It's it's rare we show up and someone is doing something about it. There's a lot of people now that are throw weather into an AI system. But you know, raw weather data into a AI system doesn't really give give the answers, so you know, it's it's it's one of those things that what we do is we put our pre engineered numbers into these systems, and it's like a turbocharger.
00:21:05
Speaker 1: Gotcha? And how far out are you when you're describing whether is this a month forward? What's the forward? How far out do you look when you look at for these patterns, like where your confidence level you feel comfortable making, you know, assessments because the weather does shift.
00:21:22
Speaker 2: Well, weather forecasting, the state of the the state of the science today, the state of the art is really about two weeks out. I mean that's that's how much weather modelor is out. But we can strip whether out of last year's data and allow companies to to plan from a more normalized, clean base base one. So by by doing that from an analytical point of view, you automatically raise their ability to hit plan because you're not planning off last year. If you're not taking last year's weather out of the data, you're assuming last year's whether what would occur next year, which may happen twenty some percent of the time. So by taking it out, you're really upping your odds quite a bit. You're flipping those odds.
00:22:17
Speaker 1: Yeah. The only the industry that comes to mind that actually does that is the utility sector. Like they actually publish every quarter. I mean, you could probably get it even daily if you want it, if you have that much time on your hands. But they report you know, weather related impacts, right, because they try to make sure that that is separated out as not a factor of growth or you know, it does not reflect positively or negatively because it obviously swings both ways on you know, customer demand, right, because that's what they're trying to at least from an investors standpoint. They're trying to highlight the piece that doesn't include the weather patterns, right, right.
00:23:00
Speaker 2: Like you get that, we all get that in our bills, are right, it's exactly what those normalized us are. So that's a sense we're doing for a very complex industry, which you know, thousands and thousands of different to products categories sold through different locations. We take that complexity and we work through it and provide it back in very useful ways to to our clients.
00:23:27
Speaker 1: That's great, And you mentioned that you do this globally. Is that that's correct, we do it globally, and would you say the US because from a damages standpoint, and particularly this year, I mean not that this is necessarily the norm, but ninety percent of the insured losses in the first half the year. We're in the US as an example for a client from a climate perspective, and you know, obviously we've had great floods this year. Severe storms were a feature of the summer. Well, not necessary like never before, but certainly unusually high relative to the history. Does the US stand out as being the more one of the most dynamic users of you know, I'm just saying from an application standpoint, clients in the US, are they like they really should be looking at what you're talking about? Or is it or is it similar in other places?
00:24:20
Speaker 2: Well, weather affects consumers globally, in every place on the planet, even in the San Diego which doesn't really have weather. I like to joke with my friends that live there it's always seventy. But one of the really fascinating things about the US that we have one of the most violent, one of the most violent weather on the planet, the most changeable, and most people here don't realize that. We just take it for granted that we had weather that swings so much. That's not true in the rest of the world. And the reason is is because we're almost like an island nation. We have this warm pool of water sitting at our south called the Golf and we have, of course the polar to the north, and our mountain ranges run north to south. So unlike Europe which has the Alps, because the US have a warm body, where do they have the Mediterranean as how, polar air coming down, but there the Apps sort of stops those patterns from coming together. A lot. We don't have that. I mean the Rockies and really really the Appalachians run north south. We have the planes in the middle, and so you have this cold air and the warm tropical air are always fighting each other and so they're always moving up and down and that creates tremendous volatility that most places on this planet don't really have.
00:25:49
Speaker 1: Yeah, I can believe that. And imagine is Canada close or is Canada not even close? Like from a just from a volatility perspective.
00:26:00
Speaker 2: I mean they have some you know, the southern part of Canada, you have the changeable weather, uh quite a lot. I mean if you look at the you know, if you look at the southern part, which is really along the US border, that that changed as much as our cities like Detroit, UH Andicago.
00:26:21
Speaker 1: Sure, Minneapolis and places like that. That makes sense. I wanted to spend a little time on supply chains because I think this is obviously when you were talking about forecasting, and you know, you're looking at history, you're getting some sense of what the impacts could be. But just from a goods production standpoint, is this is are you seeing shifts in because of the work that you do? You know, like, are you seeing manufacturing actually being affected in places like lows? You know, are they more reserved about having, you know, leaf blowers in July or something like that because of what they've been seeing historically, or is it doesn't reach that far back.
00:27:04
Speaker 2: Well, it really depends on the use. We have five different use products. I mean, we have the financial reporting and planning, which is from a finance point of view, it's a top down view. We have merchandise planning and allocation. We also have marketing, and we have operations which is extreme weather. And then we have inventory. So when companies are using us for inventory and we've modeled all their weather affected products, which can be anywhere. It's that said twenty thirty forty thousand items a day, it's going into their systems. That's in adjusting their systems on a regular basis to ship into their stores from their warehouse. So in those cases, we're having a very meaningful bottom line effect. It's we're making sure using that old added so that they're having the right product the right place at the right time. When we affect the planning side, most companies aren't using us for the buy because that's a whole different area, but they are using us to plan their overall sales. They're using us to what parts of but the States are going to load load up more than others where we think they're going to have a better opportunity from a preseason standpoint. And then the marketing area is is to a very measurable area. I mean, we were generating about thirty percent increased row ads due to aligning their marketing activities with greater lift. So you know, it really depends where and how they're using us, gotcha.
00:28:50
Speaker 1: Yeah, And the marketing side sounds like a pretty fascinating area because you are you kind of have for knowledge, you know, like you're as try everything kind of is built on some kind of in and this is this is the instinct that we don't know we have, you know, which is that these weather patterns are actually making informing us as we go along about what we think we need on a kind of constant basis, shall we say, Right, So there's there's certainly that. Well we're kind of winding down towards the end here. What I did want to give you some time to talk about where you see your business kind of growing and maybe you know, like you opportunities you think for Planeltics going forward, Like what excites you about I mean obviously you're you're in a space where not many people are playing, you know, and in such an impactful way, And just was curious if what what was sort of next for Planelytics.
00:29:43
Speaker 2: Well, you know, our our mission has never changed, but our means of achieving that just has changed radically. And so it's it's for us, it's always fresh and it's always using new technology. To get to the bottom line is how is weather d driving the consumer and how can these companies apply that knowledge to make better the decisions, whether the decisions are through their four kiss engines, whether they're through a management team sitting in a Monday morning meeting, all can be used. So what a psyche sets is the ability to help more and more companies at tree mendous scale. And we are always finding new ways. I total client the other day in Europe that if they have questions that we can't answer, or if we come across something that we haven't yet looked at, we just automatically analyze that. We don't charge it for it because we want to get to the bottom of it. We want to see how is weather driving a consumer And it gets complex with these multi national businesses. How they operate, how they plan, it depends on their data. So you know, it's really sifting through that and it's become in some ways much easier to do because we've built this engine that can take any type of data. So we're always pushing the bounds of what we can do to look at these impacts. You know, if I look at what's on our exciting lists right now. Other than building new automation through our AI tools, you know, we're just building these lag factors after a major storm passes, so you know, what will consumers buy after the storm? Some clients asked us that we'd have an answer, and we're harder. We're getting it, but you know, it takes a lot of modeling to make that happen, and then we have to put that into a galible engine. Yeah.
00:31:53
Speaker 1: Yeah, yeah, we're at Blomberg. We're looking at smoke days, you know, the wildfire effects on consumption and labor at the moment and putting out a piece next week or putting out a piece related to how the twenty twenty three events, which were kind of a factor of five in terms of smoke days relative to history, you know, because of the Canadian wildfires, was very impactful to wages period like it had you talk about three trillion in the kind of front facing sectors which includes retail, but wholesale and others. And you find that, you know, some of these impacts were up to five to fifteen percent of the wage bill was being negatively impacted by this. So it's several hundred billions of dollars and if you're looking at in one year, historically it's been very very small relative to that. But that obviously also means people aren't going to restaurants and people aren't doing you know, I'm saying there's a whole cascading effect that affects retail and wholesale and other areas that are kind of on the front lines construction Obviously, construction sale are difficult. In construction building, it slows down, even cement slows down, which is so it's a there's a yeah, it's a lot to absorb, and you need very very good data modelers to come up with the actual smoke, you know, pulling the smoke out of that. We have pollution period, right, you know, air pollution is a thing hasn't gone away. It's pretty good. You know, the air is pretty good, but we're kind of crawling the other direction because of the smoke, and it's having a pretty interesting impact on you know, the economy period. Which because we've used to be very localized on the West coast, we're seeing this really significant drift east of these impacts. And so what was kind of a California problem, you know that maybe or Oregon problem, is now a problem Minnesota as you just mentioned Minnesota. But you know, the the biggest impacts were in like Tennessee and North Carolina, surprisingly relative to history. So just just as if you're looking for something to do. You can you can look at that one as well if you want to throw that in the in the mix.
00:34:10
Speaker 2: But I'll well, I can't wait to read your article. But that that that sounds really a fascinating and anything you'd like us to look at.
00:34:20
Speaker 1: Okay, okay, yeah, we're I mean I this, as you know, this is not a very well pursued area of expertise, so unfortunately, I would argue for for people's consciousness of what actually is going on. But anyway, but thank you, thank you very very much. This was great, Fred. I learned a ton. I hope this was helpful to others really understanding the power of what you're talking about here. And these are you know, three percent on thirty three trillion is a is a trillion, you know, so that's a that's a massive amount of money, right, So there's no no denying that this is this is already well established as a as a driver of consumer preference, and obviously from a financial perspective that makes a lot of difference. But thank you again for your time. This was great.
00:35:09
Speaker 2: Thanks for having me.
00:35:11
Speaker 1: You can find more information on topics like climate damages and impacts by going to the Blomberg function BI Carbon and then the Climate Damages tracker on the Bloomberg terminal. If you have an ESG quandary or burning question you would like to ask bi's expert analysts, please send us an email at A Stevenson seventy eight at bloomberg dot com or ESG Currents at Bloomberg dot net
