Evan Wimpey: Hello, and welcome to the Mining Your Own Business podcast. I’m your host, Evan Wimpey. And today I’m very excited to introduce John Cook. John is the senior director for data science and reporting at Marriott International. You’ve probably heard of them. You’ve probably stayed at some of those hotels.
And if you have, you’ve got John to thank and John and presumably other people as well. But I think …
John Cook: Yeah, there’s a couple of other folks, no, super, super happy to be here, and that’s exciting. So excited to be joining you.
Evan Wimpey: Perfect. Well, thanks so much, John, to get started. Can you just tell us a little bit about your background and how you got into the role you’re in today?
John Cook: Yeah, sure. So, I graduated with a degree in history. I was a history major at UMD and like many other history majors, I had no idea what I was going to do with it. I was in, it was a way of finishing school. So I went to work in sales. I worked for Enterprise Rent-A-Car for several years and I found as I was sort of working through that, that I was much more comfortable looking at the statements that I was going out and selling coverage and insurance and going to body shops and things like that.
So I had a friend who’d gone to work in revenue management for Marriott. So she was nice enough to get me an interview. I started off in one of our remote revenue management groups. So we work with all of our limited service hotels around the country. I’ve had hotels, I’ve worked with hotels everywhere from Pennsylvania to Wisconsin to Illinois. I had some in the Midwest and all over. And from there I graduated into a role in analytics. So I spent some time supporting that remote group. I spent some time supporting our revenue management system. So a couple of years doing user analytics on that.
And then, transition into a few other roles supporting the Western region and eventually into what I do now, which is leading the data science and reporting team. So I’ve done quite a bit. I’ve seen quite a few areas of the business from a, from a revenue management perspective. My role now supports sales and marketing as well.
So I’ve got a bit of experience in those areas, and it’s been an interesting transition. I don’t know how much revenue management translates into like other parts of the business world. But it’s really sort of the gatekeeper like the intersection of all the demand coming into hotels and.
Then us picking the best bits of demand to, to sort of place in the hotel. So really interesting place to work and a really good place to get a sort of holistic view of what happens in the business, which is really exciting.
Evan Wimpey: Yeah, that’s, that’s, that’s very cool. And yeah, you, so you gave like the one sentence around revenue management.
I don’t know if there’s a—If there’s a one paragraph or two, a lot of the audience, hopefully some hotel years there, but a lot of folks probably in the data and analytics space that revenue management sounds sales is that demand forecasting, like what exactly does revenue management mean?
John Cook: Yeah, no, it’s a great question.
So revenue management deals with—it sort of comes up in industries where you have something called a perishable inventory. So what that means is if my hotel has a hundred rooms, I can only sell those hundred rooms for tonight, for tonight, like I can’t sell a room that I have for tonight, tomorrow.
Because it’s already gone. And so unlike in a lot of industries where you’re you trying to sell as much as possible within the hotel industry, within airlines, within rental cars, you have this concept where you want to price everything so that you sell out all the time. And if there’s excess demand, you want to try and control that demand so that you can are filling the hotel or selling the flights at the optimal price point or at the optimal to the optimal customer, right?
One of my old bosses put it really well. It was you want to sell the right product to the right customer at the right time. And that works in both directions, right? So we want to find the people who are willing to pay for the rooms, but also at the price they’re willing to pay for the mat. So it’s a really, it’s a really interesting discipline.
I mean, obviously on the demand side, there’s a heavy forecasting aspect to it to understand what’s coming in. And then on the pricing side of it, right, there’s a lot of strategy that goes into pricing the rates, right? So that we’re at the right place, like on the demand curve to make sure that we’re selling all of our rooms, but we’re not, we don’t have a lot of excess demand that we could have sold rooms to.
And also that we’re not pricing ourselves out and leaving rooms to sell. So it’s a really interesting and unusual discipline that sort of sits in the space, in a lot of travel companies, but really in that space where you have, inventory and the only lever that you have to control it is, is the price really primarily.
Evan Wimpey: Sure. Yeah. As a background in economics, it’s price elasticities all the way down. Perfect. Yeah. So you’ve, your background sounds like a lot of background in revenue management in Marriott, your role now, broader sales marketing is there. Is that a challenge for you to balance maybe the areas where you have more experience in revenue management versus areas where you’re reporting on where you didn’t come up in Marriott and sales or marketing?
John Cook: I think that’s a great question. And it is sometimes a challenge, right? I come into a lot of things with the revenue management mindset. The nice thing is that revenue management is a fairly data heavy discipline. You know, we recruit a lot of people from revenue management because they have that sort of, you know, It’s like a data first mindset.
But the way that we look at the business is very different across the three disciplines. It’s one of the things that I find most interesting about looking across it, right? Is revenue management really cares about what’s in the hotel? Like, what do I have? on the books. How many rooms have I sold? And if somebody cancels, right, that’s another room I have to sell.
Sales really cares about, Hey, what did we put on the books for some point in the future? Right. I have a running joke that I give during an internal presentation where it’s like, you know, revenue management can come in and say, Oh man, we had a really tough month and sales can come in and say, we had a great month, best month ever.
And both can be right because we’re looking at things in a, in a different way. And so that bridging that gap when I first started, the role was really challenging because I’m coming from a place where we look at everything by state eight. And that’s not the way that other disciplines look at the business.
And that’s stepping into those roles that I found really challenging to start with. But I think it’s a more, I have a more well-rounded way of looking at the business, right? Because you begin to understand there’s a reason they look at it that way. And there’s a reason marketing looks, you know, marketing doesn’t really look too much at cancellations, right?
They’re just looking at how many rooms do we sell versus you’re what we expected to sell with a particular promotion or something like that. And there’s good reasons for looking at it that way. And a lot of them come down to the data and data comparability. So I’ve learned a lot over the years about how to approach things and how to talk to stakeholders in different disciplines based on their backgrounds.
Yeah, it’s challenging, but it’s really interesting.
Evan Wimpey: Yeah, that’s great. Maybe, maybe we can talk about sort of how, how you’re talking with those stakeholders, part of data science and reporting is in your title. You do reporting is this. Sort of a, a given check a box. Here’s a metric, here’s what it was for the last month or the last quarter.
Or are you, do you have some flexibility there in the, what you report on how you craft a story or context behind it?
John Cook: Yeah. So we do a couple of different things. My team’s one of four analytics teams that support the U.S. and Canada. So we have sister teams that partner with each of the disciplines and my team sort of sits across all three disciplines. So we have a team that supports sales team that supports marketing and seen the sports revenue management. And the way the organization as a whole is structured is that my team does a lot of the cross-discipline work and we do a lot of the data work behind the scenes. We’re really heavy on the technical side.
And we do a lot of standardized reporting. So you might call it self-service reporting in some situations, but it’s reporting that our stakeholders go to understand what’s going on in there. Okay. And our sister teams do a lot of the work. They do a little bit of reporting too. There’s obviously, I mean, as in any big organization, right?
Nobody’s, nobody’s got the perfect swim lane, but they do a lot of the work directly with the discipline. So, you know, they’re working on presentations for business reviews. They’re helping people dig into specific problems. My team does a bit of that more on the reporting and on the data science side to try and we, so we intentionally disconnected my team a little bit from the business in order to give us that space, right?
If I’m sure a lot of people watching work in analytics roles that are really close to the business. And it’s like, Hey, I need something. And I need it yesterday. Like, give me an answer to this question. Give me an answer to this question. And the challenge when you’re doing that is that you’re moving so quickly from project to project to project.
You don’t have time to step back and say, okay, well, this is a common problem. Let’s solve this. You know, it might take us six months to solve this, but let’s step back and take six months to solve this problem. And so that’s a lot of what my team does. And we do that with like different data products and some modeling and things.
So to circle back to your question, which I’ve gone way around the houses to get to we do a lot of standard reporting, a lot of self-service reporting. We also do a little bit of building the story. So we take that. We take those reports. We help our partner teams either build them into decks or we have a few big presentations that we’re a part of as well, where we’re using the information that we put together in the self-service reports in order to help tell the story of what happened in the business or inform what we think is going to happen in the business going forward.
So there’s a little bit of everything is the sort of thing. Like everything from like heavy software engineering to, to storytelling, but, but a lot of it really in that, that middle phase of sort of delivering self-service reporting. Perfect. Gotcha.
Evan Wimpey: And so it sounds like certainly with, with sort of the latter case building a story around what happened in the business to, you know, generate this data or this report, the way it is, you’re communicating this to folks, you know, not an analytics crowd, not a business intelligence crowd, but to the actual business?
John Cook: Right, right. So yeah, so the teams that we partner with, and I don’t want to take all the credit for all these decks because there’s a lot of work that goes into them. I’m sure someone’s going to see this and be like, John doesn’t do that. But no, we partner with several of the other teams and we’re presenting to people outside of the data strategy realm.
So leaders within the U.S. And Canada. We’re heavily involved as a group in the investor relations process. So a lot of the comments in the investor relations calls and things like that will come from work that was done in the U.S. and Canada. We’re obviously Marriott’s biggest continent. So we get some billing during those.
And yeah, those are almost always to people outside of the data realm. So people who are working on the business, the strategy, working with individual hotels, working with our franchisees. So all different aspects of the business.
Evan Wimpey: You come from a revenue management background into your role. You mentioned that a lot of folks. In the data science reporting space come from revenue management is, is that something when you’re hiring?
So you have a team that works with you. Do you hire mostly internal? Are you looking mostly revenue management folks with sort of that data bent? Or are you looking across the across the business?
John Cook: I’m happy to look anywhere for anyone who’s interested in data. That’s really what it is inside the business, outside the business.
You know, we’ve had great hires come from inside the business. We’ve had great hires come from revenue management. We’ve had great hires come from sales. We’ve had great hires come from outside the business. What I really like, there’s, there’s sort of two parts to the job. Right. That we do.
The first one is the communication, like the data and the answering questions with data and digging into stuff aspect, which is great. We want people who are curious. We want people who love solving problems. The other part is that there’s obviously a technical aspect to what we do where people are working in sequel.
They’re building reports in Tableau. They’re building reports in Power BI. And they’re writing code in Python or in Sequel or in something else in order to pull the data together behind the scenes. So I look for some level of technical aptitude. So for our entry level roles, I don’t care whether somebody knows python or sequel.
What I do care is that they’ve, they’ve demonstrated enough knowledge in some sort of programming language that they’re not going to hate that part of the job. That’s, that’s really my biggest worry, right? Is if I hire, I hire somebody who’s never coded before and they’re like, I can do it, I can learn it.
And then four weeks in they’re like, Oh my God, this sucks. Like it’s really tough. I don’t want them to feel terrible every day coming to work. So I look for some level of technical aptitude. A lot of people have done great work in Excel, done great work with VBA. We get a lot more people now that Python so much more accessible.
We get a lot of people who’ve done work with Python. So anything, anything like that for the entry level roles, as long as you’ve done a bit and you’ve proved that you don’t hate it. I’m cool with it. And then on the other side, I love people who are enthusiastic about the business and just enthusiastic about solving problems and enthusiastic about learning, you know, the data space. People post the funniest job descriptions on LinkedIn, right? Because you need a little bit of experience or like five years of experience in everything in order to be hired. And it’s just, it seems crazy to me because you don’t, yeah. You know, everything’s moving so quickly.
But a lot of the problems that we have in business can be solved with relatively simple tools. Like nobody needs a deep learning model to understand a lot of what we do. It’s, it’s basic stuff. And so not having a huge amount of technical credentials is great. What I want is somebody who’s willing to learn how to use them in the right ways and how to do things.
In a way that impact the business, you know, that’s one of the things that, that I’ve become passionate about over the years. And it started when I was working on the systems within our systems team is translating what we do in data into something that, that normal people can understand because where we really get action and where we really get good results from data is when people are able to understand it and then use it to do something.
If we are just sending out complicated data presentations that nobody can use. Right. It’s great. You might have a fantastic R squared and a brilliant model, but it’s useless if nobody can do anything with it. And it’s certainly not helping the business. So yeah, that the real unicorns that we have on the teams are the ones who are, who are great on the technical and the investigative side, and then also able to translate that into what it means for the business and how that can make an impact to our hotels or somebody else’s hotels or the business as a whole.
Evan Wimpey: Perfect. Yeah. I think that’s spot on. That’s, that’s great. That’s harder, harder to capture on a resume than saying Python, scikit learn, whatever it is, but yeah, I mean, ultimately that’s what, that’s what we’re in the business for, or else we’d be in academia. Right. Exactly. We’ve talked quite a bit about the reporting data science, of course, in your title to certainly the focus on being able to have an impact, but is there any sort of the 10 percent of the picturesque data science. Is there the predictive model building? Is there the deep learning, the generative AI, the newest, coolest tools in data science?
John Cook: So we don’t do, we do a better machine learning, quite a bit of machine learning and predictive modeling. We don’t do a lot with like the latest and greatest cutting-edge tools, just because.
There’s so much for us to do with tools that were available five years ago. We haven’t, like, we haven’t maxed that out yet. Yeah. So when we max that out, I’m sure we’ll move to the, to the latest and greatest, but we do a lot. Yeah, we have a lot of data. We have a lot of hotels. We have a huge variety of hotels.
And so we do a lot to sort of deconstruct. What’s happening and what’s working across different areas. We have, again, a lot of hotels. So there’s a lot of—one of the most common questions that we’re asked, right? Is everybody’s short of time. How do we help people focus on what the right thing to do is.
So a lot of the machine learning that we do goes into what’s helping, whether it’s our sales team or our revenue management team or our marketing team, you know, where can they focus their efforts to get where is it going to help out Marriott as a whole, regardless of whether it’s managed or franchised?
Why don’t they focus their efforts in order to have that big, that big impact? And so that’s where we spend a lot of our time working through the complex. And for us, I think that’s a, you know, there’s, there’s a meaningful benefit to us doing that. I mean, we’re, you know, we’re helping out everybody equally.
That’s the goal that we go for is, is to, you know, how can we have the biggest ROI on what we do?
Evan Wimpey: Perfect. Yeah. I think, I think that’s such a useful way to phrase a question and not put the emphasis on the tooling or the techniques. So that’s, That’s, that’s great to hear. John, I want to shift gears just a little bit for those folks that are watching, in addition to listening, that we’ll see some, some behind you.
I’ve tried not to distract myself with it for the entire, entire time we’ve been chatting, but can you talk at, at the same time? Presumably you’ve got a background in music and then I would love it if, if there’s, are there any lessons in the music world or the creative world that you can bring to the data science?
John Cook: I’ve had an interesting life so far. I’ve done, I’ve done a lot of really interesting things. And, so yeah, so I do I play guitar. I have a piano. I don’t know if you can see it on the thing. It’s over to the side there. So I played in bands all the way through college. I was obviously completely convinced that I was going to be a rock star.
That’s why I graduated just about by the skin of my teeth with a history degree. Obviously, that didn’t work out quite as well, but I did continue to play on and off and in the time since. So I spent quite a bit of time off to college performing and I wrote songs and things like that. So it’s always nice to go to the, there’s a hospitality data conference that’s in Nashville every year that I try and go to as often as I can because I love to get down there and sometimes play a little bit, a lot of listening to other people play, which is really cool. But it’s funny, I think there is—playing music has always made me comfortable in front of people, which I think is a huge advantage when it comes to presenting data.
Just being able to be comfortable in front of a group of people who are going to ask you difficult questions and judge the hell out of you. You know, that’s what happens when you play every time you get on stage, right? There’s a whole bunch of people in the audience judging the hell out of you. So it’s made me a lot more comfortable getting up in front of executives and talking about things that may or may not agree with what they’re looking for.
So that’s been tremendously helpful throughout my career. And within the data space, I wish we had more people who were more comfortable getting up and talking about this stuff because it’s a lot of what we do is, is really critical and really impactful. And unless we do a great job communicating, it doesn’t necessarily have the impact that we would want it to have.
So that’s good. And I think there’s a lot of crossover in the way you structure songs and the way you structure like data projects. I find that writing music and writing code have a lot more parallels than you might think, right? You’re trying to do something within this very small box of rules that you have to fit into, which.
I find it activates the same part of my brain when I’m doing that sort of stuff, which I would never have known until I learned to code, which is long after I learned to play music. So yeah, it’s interesting. I don’t know how many direct crossovers there are, but there’s certainly some complimentary stuff that I’ve enjoyed.
Evan Wimpey: I mean, yeah, that’s more than I would have guessed.
Yeah, it’s my only experience. I picked up a guitar about a month into COVID like probably half of the rest of the United States and I realized it was, it was pretty bad at it and I thought this can’t be anything like coding, but now I’m thinking maybe it, maybe it is. And I don’t want to, I don’t want to say what that implies.
Yeah, very cool. That’s, that’s exciting. Yeah. And I think sort of the. The comfort, the ability to, like, put yourself out there and show, this is what I have done. This is what my team has been able to do. And it’s a scary proposition in music and in, you know, communicating your, your, your analytics.
John Cook: Yeah. And now that I think about it, I think like between learning and insight, Instrument and learning music and learning to code like there’s a, there’s a level of self hatred that really goes into both of those where you have to be determined to sit down and I am going to do this thing, even if it takes me a thousand errors to get there. So similar mindset, maybe.
Evan Wimpey: That’s good. And maybe a similar smile it puts on your face. I know if I go back and look at code that I wrote 10 years ago, I just shake my head. And, you know, I feel like a terrible coder today. If I go back and look 10 years, I’ve gotten better. At least it’s probably the same as a musician.
Absolutely. Yeah, absolutely, absolutely. Awesome. John, I want to ask you one last question. You’ve got a team there. You’ve got a lot of complicated parts at Marriott. We’re trying to serve the business. Let’s simplify it a lot. Let’s say it’s the John Cook show. John gets to decide the next data priority, whatever it is.
Everybody’s on board with, with your vision and you and your team can dedicate your time and your resources to it. So one particular thing, where is it that you want to put those resources?
John Cook: That’s such, that’s such a great question that I, when you sent me the list beforehand, I was like, Oh man, there’s so many things that I would love to do.
But I think the thing that I would—the thing that more and more I’m in the data world, right? The more and more passionate I am about actually giving people things that they could use, and I’m not even sure that what I would do is a data thing at all. I would love to have a way for us to simplify all of the complicated stuff that we do so that there’s a place where a hotel can go and be like, this is my situation.
They can, you know, their metrics are right there. Here are the strategies that you could use to maximize whatever situation you’re in. We do a reasonable job of, of supplying strategies, but it’s that, you know, it’s really hard for people to find what’s going on. Does this apply to me? You know, what was it like for other hotels that were in this situation?
And just to be able to provide. place where a hotel could just pull themselves up and we could say, Hey, look, here’s three strategies that we think are going to help you pick one and here’s how to execute it. I would love to be able to do that. I think in a sort of greater sense than that, right?
The more people understand data, whether it’s in a work environment or whether it’s in a home environment or whatever it is, like the better off we are as a society, because the less, the People are going to be able to feed you BS from a political perspective. And then, you know, people are going to be able to spot when there’s weird logical leaps in, in things that people are saying, and we’re going to be able to hold people accountable for doing the right thing.
And data tells us that, and we live in a complicated world. I mean, there’s so much going on, even within you just running a hotel is a complicated thing to do. and we can’t expect somebody to be an expert in everything, but we have the data and we have the tools and now with gen AI and things like that, we have a process where we can distill all of this information down into something that makes it meaningful for someone.
And we can help people make better choices by providing them information in the right way. So, I mean, if it wouldn’t, I’m not even sure that has anything to do with data. It just has to do with the way we deliver data to people. That, I think, could be so impactful because. We don’t need complicated tools to fix a lot of the issues or to find things.
What we mostly need is a way to get the right information to the right people when they need it.
Evan Wimpey: Spot on. Yeah, I think that’s, that’s such a great endeavor. I would love to see it. Let’s, let’s simplify what we are able to deliver to people. Very cool. John, you’ve got a YouTube channel. We don’t, we don’t have too much time left on the show.
You do have a YouTube channel, Penguin Analytics.
John Cook: I do. Penguin Analytics. So we’ve done, I used to make Tableau videos. I teach data, I teach part of the data science program at the university of Maryland global campus. So shout out to the program. That’s a great program. But one of the things I found frustrating is that it was really hard to give people like, Hey, you need to go to this video.
Just watch this for this one thing that you’re struggling with. So I started off with these really short snippets of how to do stuff in Tableau because that was the stuff I was directing people to find. And, yeah, I haven’t done a lot with it the last few years, but I’ve been gradually pivoting it and to be a bit more about like data science in general and you had to work with data, how to get people to take action with data.
Yeah, it’s a great place. It’s on Penguin Analytics is on LinkedIn too. So we share all of the new stuff there. There’s some insights and, you obviously know I’m on LinkedIn as well. So I’d love to connect with folks that want to learn more about how we can communicate with data. And I’d love to learn from some of the other folks too, about what people are doing and what works because it seems to be sort of this big unexplored space between, yeah, we’ve got all this great information on how to do data or this great information on how to do business, but not much on how to connect the two together. So, yeah, really interested in learning what other folks are doing and what’s working.
Evan Wimpey: Perfect. Thank you so much, John. Our guest today has been John Cook from Marriott International. John, thanks so much for coming on the show.
John Cook: Thanks so much, Evan. I really appreciate it.
In this episode of Mining Your Own Business, John Cook shares his unconventional journey to leading a data science team at one of the world’s largest hospitality companies. As Senior Director of Data Science and Reporting at Marriott International, John guides a talented team supporting U.S. and Canada sales, marketing, and revenue management for Marriott.
Evan Wimpey | Host