Evan: Hello and welcome to the Mining Your Own Business podcast. I’m your host, Evan Wimpey, and today I am very excited to introduce a very exclusive guest. Today we’ve got Elf on the show. Elf is the Head of Data and Analytics at Santa’s Workshop at the North Pole. Welcome to the show, Elf.
Elf: Evan. Thanks so much for having me here today. I’m a big fan of the podcast. I’m avid listener. I love what you’re doing here and I appreciate you having me on the show.
Evan: Absolutely. Well, hey, thank you so much for being here. We’re recording this in December, which I know is a very busy time of year for you there at the North Pole, so really appreciate you carving out time for us today. Elf, really curious about your background, how you got into data and analytics. You know, usually we think of elves, we think of making toys. We don’t think of conducting data and analytics. So can you give us a little bit of flavor?
Elf: Yes, well certainly. You know, I was in toys for a long time. I did Barbie Dolls, guitars, doll houses. A lot of Jack in the Box. You know, I worked in toys for decades here. And you know, for a very long time it was sort of, these are the toys and these are the quantities that you make them.
But you know, in recent decades taste, consumer taste, the child’s taste has started to change. There’s a much wider variety of toys that are available and that kids are wanting, and those demands are changing more quickly. I say demands – they’re not really demanding them. They’re requesting them very kindly through the list. Most children, right? Very nicely. Lots of please’s and thank you’s, but their tastes are certainly changing. And as we collected some of that data, it became more obvious to us here at the North Pole that we need to actually use this data to make better decisions on the types of toys that we’re manufacturing and how we deliver those toys.
And so I’ve always had a hankering for math and numbers. And, you know, in a place where I was in toys, this was something that I was on the front lines that I was seeing day in and day out. And so I started out sort of as a data analyst. You know, that title maybe didn’t even really exist, but I just contributed as I looked at these changing patterns this was an area where I really wanted to explore.
And then we sort of grew this capability organically. It started out in toys, and it’s moved to really the entirety of the Santa Workshop here. We’ve got a pretty big team, and it’s only in the last couple of years that I’ve actually been in charge of all of data and analytics here. And so I consider myself very fortunate.
Most of the skills that we’ve got here are from elves that have been in toy manufacturing or in logistics at, you know, various parts of Santa’s Workshop. And we’ve just sort of grown this capability organically, and now it is really an integral part of what we do and how we plan for a successful and magical Christmas every year.
Evan: That’s great. That’s super interesting. And you know, it makes perfect sense. Tastes are changing, you know, kids these days. Ah. So you’re head of data and analytics. I’m curious, what all is under your purview? So when we think about traditional business, you know, you’re looking at things like operations and logistics, but also finance and sales, HR, marketing. Do you oversee all of these functions?
Elf: Yeah. Well that’s a great question, Evan. Very thoughtful and insightful question. The thing is, we give our product away, so we don’t worry about sales at all. We also don’t really worry about marketing at all. With the only competitor in this space, nobody else is delivering Christmas presents for free across the entire world.
And our brand awareness is superb. Everybody knows Santa and his workshop. We’ve got a hundred percent market share there. Finance, we actually don’t touch finance at all either. We use Magic Elf money here at the North Pole. We are facing some inflationary pressures. It’s really not spared the North Pole from that either. But as of now, you know, we don’t have a big footprint in finance. Really our bread and butter and the data that we use and where we try to improve our decisions is in the logistics side. So making the toys, manufacturing toys, and getting the toys down the chimney to the children on Christmas. Manufacturing I think is relatively straightforward.
We’ve got a similar process to what you see around the world, so we can borrow a lot of best practices there. We do some outsourcing. We have a lot of partners, especially for some of the brand name stuff that we’re using.
Evan: You mean like maybe Carter’s for kids’ clothes? You know, we had Selma Dogic on the show recently from Carter’s.
Elf: Oh, that’s right. Yes. I know Selma well. She’s been on the Nice List every single year. Selma’s great. And I, well say, we’re not supposed to mention specific brands that we partner with, but it’s no real leap of logic. You see what’s under the tree every year. You can see what’s on the tag. You can see which brands that we partner with.
But that’s really the manufacturing and sourcing side. And the logistics is very difficult too. We’ve got roughly 2 billion children on the planet that we try to deliver to every year, delivering to every boy and girl in a 24-hour span is very difficult. And as you, as you might imagine, that’s where we spend a lot of our time trying to use data to help make better delivery decisions.
Evan: That does make perfect sense. But I’m curious, you know, your team’s been delivering to the entire world for centuries, right? So, I mean, is this a new problem? Are you just trying to maintain your current capabilities?
Elf: Yeah. Well that’s a great question and certainly we’ve been solving this problem. Evan, the thing is that the problem itself and the nature of the problem is changing. So the demographics around the world are changing. You see populations that are aging. You’ve got a lot of children that are aging out of Santa’s delivery age groups, and you’ve got different populations that are growing, and so that really changes. We can’t just run the same route that we ran in 1950 because we’re not spending enough time in the high child-density areas. So the demographic is changing also. Of note, I think, is that the architecture is changing. You know, in a single-family home with a chimney, the delivery is very straightforward. Santa goes down the chimney and delivers the presents. Now you’ve got all different kinds of units. Chimneys are going outta style. We’ve gotta rely on a lot more magic to get Santa into the home and under the Christmas tree. And so that’s not something that Santa can just do on the fly and hope to have a lot of success. If we’re going to plan out a good route and a good way to deliver all of these presents, we have to know where’s the high-density areas, where’s the suburban areas? Where are there chimneys? Where are we going in windows? And you know, I don’t want to give away all the ways that Santa can deliver into a house, but it’s very important that we try to map those out so that Santa can have a successful delivery.
And it’s really the data that we collect year over year and understanding we also do some third-party data acquisitions to understand some of these changing trends, but the data is really helping to drive those delivery decisions.
Evan: Great. Yeah. And that makes perfect sense. Yep. Thanks Elf. Down here on Earth are, I mean, they got, I guess you’re on Earth too. I just mean like down in more traditional organizations, some of the big challenges that data and analytics teams face are getting some initiative into production, into practice to have a real impact. Is that a challenge for you? You know, you’ve got, you’ve been delivering for centuries, so I think folks would tend to get set in their ways.
Elf: Yeah. Yes Evan. That’s a very fair point. And it’s a challenge here at the North Pole as well. I think we’ve got some general approaches and I think it would help if I walk through an example. So I led an initiative in the last few years about really overhauling our route optimization. And I will say that this problem didn’t start in the data and analytics team. We didn’t just sit behind a computer and try to improve some route optimization. It started with talking to the stakeholders and so, you know, we think certainly the big man himself Santa Clause is a stakeholder there. And also the reindeer, a lot of people don’t think about this, but the reindeer, they’re the end users. They’re the ones who are driving these routes and so, you know, things don’t go well if they’ve been doing a route a certain way, and then one December we go and hand them, “Hey, here’s your new map. Follow this.” You know, they’re gonna snort and stomp their hooves on the ground and they get very upset, you know. We want buy-in from the reindeers.
So the very first step in this process in scoping a problem is to talk to those stakeholders. So talking to the reindeer and to Santa Claus. And you know, we learn a lot from that too. We think we are just gonna use the data to optimize this route, but really we are learning. It’s not just the overall delivery time that matters. There are a lot of constraints that we need to make sure we are aware of. The reindeer, you know, they’re not machines, they’re animals and they do get tired. If they’ve just crossed the Mediterranean, then we don’t want to put them at a rural outpost where they’re going hundreds of meters between each home. They just crossed the Mediterranean. They need to rest. We need to put them in a high-density area or put them in Alexandria or Cairo next so that they can rest on top of a condominium while Santa does a lot of the movement and work. So these are things that we don’t really know offhand until we’re engaging those stakeholders. And it’s not just one time at the front of this. This is something – we really like to follow an agile process here at the North Pole. And so this is something that as we’re going, as we’re developing, as we’re getting some potential outputs, these are things that we go back to Santa Claus and go back to the reindeer and say, here’s some potential route here. Here are a few sequences of homes that you could visit. Does this look good? Does this look to be a challenge? And so getting that regular feedback from the stakeholders, and it’s tough to do, but making sure they’re bought into that process. And the way that we do that is we have some measurements. If we’re not able to measure some improvement in what the data and analytics is able to do, then it’s really hard to get that buy-in from the stakeholders.
So we’ve certainly got some key measurements. And I won’t be able to get into the specifics here, but it’s more than overall delivery time. And as we’re able to show Santa that these measurements are improving, as we’re iterating on this route optimization, then Santa becomes engaged. He becomes enthusiastic, he becomes a champion of the problem. And so this certainly is more time for Santa than him just saying, okay, come deliver me a solution next year. But the time invested for him ensures that he gets delivered something that is useful and usable and that he can trust.
Evan: That’s great, building champions there. So it seems like things at the North Pole aren’t so different than things here in the more temperate climates and actually speaking of the climate and the weather, we had Gus Kaeding on the show a few weeks ago. He’s head of data for U.S. Ski and Snowboard, and he talked about the challenges of trying to collect data on the slopes because the battery life is so low because it’s so cold, and I’m curious if you run into that challenge at all. It’s quite cold at the North Pole, I suspect.
Elf: Evan. No kidding. It’s cold. It’s very cold here. And I do know Gus well. He’s a great guy. Nice List, I think every year, I’ll go back to some years that were close, but I think he’s Nice List every year. And look, I’ll just say we’re not supposed to pull for our favorite countries up here, but I will just say personally I’m a fan, I’m excited about U.S. Ski and Snowboard and where they’re going in the future. Yeah, certainly a challenge for Gus, but I would say here, the cold is actually a benefit for us because we don’t use any external cloud resourcing for storage or computing. We do in-house. We have a lot of GPUs on site here and we do a lot of complex computing and we generate a lot of heat. So we’re actually able to use that heat. It gets very cold here at the North Pole, especially in the wintertime. And some of these processes, you know, we’re running compute over. And the nights are very long here. In fact, it’s night all the time. So when we run it overnight, it could last for several days. And we use that heat, you know, we’ve got a series of efficient heat capture and we route that heat. Not so much here in the workshop, stays actually quite chill. Here’s why I have to keep my sweater on. But the big man and Mrs. Claus certainly likes to keep the house warm and a lot of that heat that’s generated from those GPUs gets routed through the home to keep Santa’s home warm. It’s actually a real benefit to what we do here.
Evan: Oh, that’s, that’s great. Who would’ve thought you guys are able to find a lot of efficiencies. So I really appreciate your time today. I do wanna ask you one more question before you get back to it. So, imagine you’re completely unconstrained. You’ve got all of the resources you can think of, the talent, the hardware, the time, everything you need, and you can point your team’s analytic efforts at one problem. Then what is it you would want to try to focus that on?
Elf: Yeah, let’s say it’s a tough question. How about trying to source coal more efficiently, or – I’m just kidding there. We actually use very little coal. We’ve got almost all good kids. It’s very great to see the good kids. In fact, I think that’s sort of where my focus would be. We’ve got roughly 2 billion children around the planet. You know, not all celebrate Christmas or send a list have some hope of Santa delivering. But a lot of those do. And for the most part, we do a very good job of getting deliveries out and trying to follow the kids wish list as best we can, but if I were going to point our data and analytics we could scale that up as big as we could, I would really focus on that last mile. You know, some kids’ homes pose a real challenge. Maybe they’re in the midst of a move or they’re in an area that’s maybe difficult to get to. You know, these children may have difficult lives and Christmas may mean more to them than to the average child anyways. And these are the hardest deliveries for us to make. And while we do our best, there’s sometimes there’s children that don’t get a delivery, even though they’re hopeful for one. So I would really like to focus on that last mile, the most difficult children to deliver to, to make sure that every child that is hopeful of a Christmas gets something under their Christmas tree, something that they can open to have a little bit of magic there on Christmas morning.
Evan: Wow. Wow, Elf, that’s a great, what a noble answer.
You know, I’m afraid that is all the time that we have here on the show today.
Elf: Well, actually Evan, do you mind maybe, would it be okay if I ask you a question quickly?
Evan: Oh sure. Yeah. Turntables here.
Elf: What do you want for Christmas this year? I haven’t received a wish list from you.
Evan: Well, yeah, I appreciate you asking. I, you know, I thought it was just for children, but I guess I act enough like a child that I can submit one. If I could wish for anything, I guess I would wish that this podcast could reach all of the data professionals in the entire world. What do you think?
Elf: Well goodness, Evan. We do have some magic here at the North Pole. We deliver the 2 billion houses in, you know, under 24 hours, but we don’t have that much magic, I’m afraid. That’s not something that we can deliver on.
Evan: Well, that’s a shame. I appreciate your honesty, Elf. So that is all the time we have. Elf has a very busy time and needs to get back to it. Elf, thank you so much for being on the show today. Thanks, everyone out there for listening. Make sure to subscribe to get our next episode.
Elf: Thanks so much, Evan. Merry Christmas everyone.
Evan: Thanks so much Elf. Have a very merry Christmas. Have a wonderful holiday season, everyone.