Rob Winters, Senior Director of Data at TripActions, speaks with Jesse about how data shapes the customer experience at TripActions, the travel, corporate card, and expense management company. He shares the importance of having a team that is cross-trained and a few honest truths about working across international borders and cultures, and explains why, even with those challenges, he prizes his team’s diversity and works hard to ensure they never become just an echo chamber.
Rob is a hands-on practitioner with experience building data teams around the world. He has expertise in nearly every aspect of the data space, from BI to data engineering and data science.
Welcome to the Soda Podcast. We're talking about the Data Dream Team with Jesse Anderson. There's a new approach needed to align how the organization, the team, the people are structured and organized around data. New roles, shifted accountability, breaking silos, and forging new channels of collaboration. The lineup of guests is fantastic. We're excited for everyone to listen, learn, and like. Without further ado, here's your host, Jesse Anderson.
Hello, and welcome to the Data Dream Team podcast. My name is Jesse Anderson. With me today is Rob Winters. Rob Winters has been doing, basically, data since 2006, and then he started doing management of teams since 2008. Rob, would you mind introducing yourself a little bit more?
Absolutely. It's my pleasure. I'm super happy to be here, by the way. My name's Rob Winters. I am currently the senior director of data at TripActions. We're a business travel company and expense management company. As Jesse mentioned, I've been doing this for a while. I've worked on pretty much every aspect of the data space from BI to data engineering, data science, both as a hands-on practitioner as well as building and growing teams around the world, really. And in my current position, I'm leading a group of about 30 people spread out all around the globe to basically drive data competency and capability at TripActions, and build what we believe is best in class infrastructure to empower our entire company to use data to make better decisions.
Awesome. So tell me about TripActions. What does TripActions do?
So TripActions - you're gonna hear me refer to it as TA a bunch throughout this podcast - is a business travel company. It's Silicon Valley based, started in 2015. Jesse, have you ever used a business travel application?
TripIt. Yes.
Okay. They're often quite clunky, and it's difficult for the end user to know what they can use. And it's difficult for the admin to manage the expenses and manage the policies and everything else. TA really tries to take away the stress and the challenge out of business travel, to make it really as convenient as you would expect from a consumer product. So we've designed what we believe are best in class application and admin tooling and everything to drive and bring this capability into the business travel world. That's one side of the company, one side of the problem space we're tackling. We believe we're doing quite well in that area.
The other side of it is something we introduced last year, which is our Liquid product. Expense management is also kind of often very challenging and difficult for businesses. It's just, it's not optimized for the end user. And so Liquid really tries to make the experience of expense management painless and easy and simple. In an ideal world, you can just use your card, and you automatically know what policies apply and how to use it appropriately or effectively. And you don't have to think about it, can I buy this? Can I expense this? Can I have this meal with this person? And Liquid tries to basically take all that stress of expense management away.
As you were talking about that, it reminded me of the problems of dealing with Concur. Not that Concur in itself was bad. Just the terrible, terrible time I had to deal with Concur. That was not fun at all.
The other side of it, I would argue, and this is another strength that TA really brings is, we care about our users and we invest heavily in customer experience and customer service. That is actually one of the things we've built our entire company foundation on, which is, business travel, often, you're gonna have situations, right? Last minute, you need to change your flight. You need to stay an extra day to meet with a client or something like that. In a perfect world, that's really easy for you to do yourself, but we know that we're not in a perfect world. So our service organization is also a key part of what we offer, which is, how do we make sure that we have the best agents available who can quickly solve not just your current problem but the next one you might encounter?
Oh, interesting. So when you were introducing yourself, you mentioned that you have 30 members of your data team all over the world. Tell me more about this overall data team structure.
We break down our data team into a couple of areas of focus. The first area that I think is interesting is business intelligence and analytics. And what that means for us is maybe a bit broader than it means for a lot of organizations. So when we talk about BI, we don't just talk about building reporting. We talk about guiding the business through making better decisions through data. So our analysts work as insight generators and experts on how data relates to different business domains and problem areas.
It's also about how we empower other people. So our analysts are also heavily focused on building self-service tooling, and building documentation, and even building training courses that can be the followed synchronously or asynchronously for customer service or for customer success or for product managers, to understand how to self serve in data and how to use data to make better decisions every day. That's one big vertical that we've got.
The second major vertical that we have is data science. We look at both machine learning - so, how do we take machine learning algorithms and build them into the product to make it personal, to make it accurate, to make it effective, to solve problems like what's in your receipt and what policies apply - that's machine learning algorithms our team builds, but also to create expert systems to guide decisions. We firmly believe, I firmly believe, that AI or ML or whatever you wanna call it, it's never gonna replace entirely human decision making, but it can help make people make better decisions. And to do that, we want to use expert systems to guide customer success to be aware of what accounts might churn, and why they might churn, so that they can know how to reach out and how to manage it. Or customer service agents to know what article might be relevant for them so they can solve the customer's problem faster, so we will make a knowledge-based recommendation. So that's the second major area that we tackle on our team.
The third major area is the foundation that all that sits on. The data infrastructure, the engineering, the data warehousing. Basically, how do we get data together? How do we store it, manage it safely and securely, and how do we integrate it and then put it back out into the world so that people can use it effectively? And so those are the three major areas of the team, and those folks are spread out all around the globe. We have people in California, in Seattle, in New York City, in Rennes France, in Amsterdam, in Tel Aviv, all over the place.
Those people are spread all over the world. How do you deal with the time zones? I know that can be difficult.
It's quite honestly a nightmare sometimes. So the time zone is a real challenge. There's a couple of ways we've tried to tackle this problem. Number one, we focus as much as we can on asynchronous communication. So write everything down, over communicate, over document, make sure that it's easy for people to find information that they might need.
The second is a really high emphasis on agency and autonomy. There are very few decisions that happen in the team that require my tacit approval. I believe that if I help people understand where we're trying to get to and what constitutes the right and the wrong way to do it, let's say that they'll make the same decision 80% of the time. And the 20% of the time that they don't, they'll make a better decision than I would've, because they have more information than I do at the moment. So very high agency means that no one is blocked most of the time waiting for someone else.
The third thing is really focused on building, we always talk about T-shaped people and we believe that's really fundamental. So there's no one in my team who doesn't understand CIS/CD. So even the most junior analyst is gonna be taught. How do we do deployments, and why does it matter? And what that allows is, everyone, even if it's not their area of expertise, can operate across the entire problem space so that they don't have to wait for an expert to help them. Now, that's not always the case, obviously. There's situations that emerge that lead to limitations. But I think this probably covers 95% of the general day to day problems that might emerge in trying to manage a global asynchronous group or a global team that has expertise spread out all over the different time zones.
And in a similar way, are your data teams, your data engineering, data science, are those cross-trained as well, or how are they handling the interactions between them?
Everyone is cross-trained. Basically, we've got a technical competency matrix that we use. And we say, look, everyone should know these things. So everyone in the team has good, solid knowledge of data modeling and deployments and basic data visualization. So obviously, it's not their day to day job, but every engineer knows how to make a dashboard in Tableau, even if it's a kind of crappy one, so that they can get what they need without needing to wait.
We’ve tried to distribute people with different expertise around the globe so that there is, you know, an engineer in the United States in case they need an engineer's background or experience to help them with a problem. We have engineers in Amsterdam. We've got data scientists in California, Tel Aviv, and Amsterdam, as well. So basically, what we look at is, you should have a very deep vertical knowledge in your discipline, but you should understand and be able to operate at least with some degree of proficiency in all the relevant side disciplines or other disciplines you might touch on.
Interesting. And so, let's say there's a management person listening to this thinking, oh, I want that. How long did that take? And how much did this cost in terms of time?
It is an investment. It is a constant investment, and it starts at the top and it goes down. I can tell you, our onboarding probably takes a bit longer, right? Because we have to train people in a bit more technical skills, but we've put a lot of structure into that to make it very efficient. But we also invest every single week into training and development. So I've got two standing global meetings with my team. Of those two meetings, the longest one is a weekly training session where we basically spend time investing on developing people's understanding of different aspects of how to be a successful data professional.
So it's not easy. It does require a commitment. It does require a tolerance for risk and failure as well, because you're basically giving people more freedom and offering them the ability to work in stuff that is not their area of expertise. So you take that risk, but you take it knowing that they will be stronger in their careers, and your team will be stronger by giving them that chance and investing in that development.
No, that's really interesting. That's a decent amount of commitment, but it sounds like it's paying off. Now, although we're focused on the technical side, how does the business side interact with the data team?
So, we've got two core models that we interact with them on. The one that I would focus on first is basically, how does our core data team interact with the business? And this might be the engagement we use with say, our customer service group or our product team. Our analysts are expected to be subject matter experts in the discipline and the domain that they work in.
So I have analysts who focus on product, I have analysts who focus on customer success, I have data scientists who focus on product. And they're expected to engage directly and consistently and frequently with the PMs, with the engineers, with the designers, and really almost be part of that team. Go to stand ups, go to weekly meetings. And they're supposed to not take requirements and deliver reports - that mentality in that model doesn't work at TA, and it doesn't work in my team - their job is to sit there and think with the PM, let's say, okay, what is the big problem you've got in your business today? And how can we use data to better solve that problem?
And that might be by getting a dashboard or report in place, it might be by building an algorithm that can underlie a piece of the product, it might be by doing some analytics and finding out which widget we should build next, based on how people are using the product. So that's the main engagement model that we use within the core data team.
There are parts of the business that actually use embedded analysts, where they've said, "Look, we really want people just focused on our business. We wanna manage them, we wanna manage their pipeline, we wanna have focus." And that's amazing. We're super happy to work with them and support those people as well. And in that case, we look at them as, I always say they're like brothers from another mother. They're doing the same thing we are, they're effectively part of our team, we fold them in as much as we can. The only thing we don't do is manage what they're working on day-to-day, but they use the same tools, the same processes, the same understanding. They have access to the same information in meetings. They're in the exact same collaborative flow as a data scientist or an analyst in the data team might be.
And do those people actually go to the training that you do? Or are they apart from those trainings?
Absolutely. They join in, they're participating in our team meetings, they're participating in our training, we do their onboarding. We actually, a lot of times, even do the hiring. Oftentimes, we will run the hiring pipeline. For example, for finance, they wanted to hire data scientists over the last couple of months. We ran the hiring pipeline. We did all the screening. We gave the interview case. We did all that. And then we trained and onboarded the new data scientists on data science specific pieces, so that they would be able to be successful in TripActions as a data scientist.
Oh, that's interesting. I've talked to a lot of people trying to do that, but at varying degrees of success. It sounds like you've done that pretty well. What do you think was the key there that the finance team actually went to you to do this? Is there some sort of buy-in that you had to get? Was it a mandate? What was that?
It's a product of close partnership, actually. And I think it highlights that the issue that we had was basically, resourcing and capacity. And that was basically where we got to, finance needed to hire their own data scientists. But it was actually discussed with me, with our DS managers, well in advance, and they were really excited to have us help them through the entire process, but it was because they trusted us that we would be partners and invest in this person, bringing them on board and helping them get up to speed.
As we prepared for this interview, we talked a little bit about diversity, and I was able to see how important diversity is to you. Personally, diversity is really important to me as well. So I wanted to dedicate some time to talking about that. I can say it's part of your values, part of your belief system. So tell me more about how you bring that belief in diversity and that value for diversity into your work life.
Diversity is, I think it's very much a buzzword these days, and everyone is paying lip service and has been for a few years. And I find it enormously frustrating, quite honestly. I think, and this is my experience and what I've found over the years, is that working with people who have a different set of backgrounds, different experiences, different life paths that brought them along but a common set of values, intentions, how they look at relationships with other people, how they look at their own personal development and growth, so, different experiences but common values, that makes an incredibly strong team. Because it doesn't just avoid an echo chamber. It essentially creates a virtuous chamber, I don't know what you would call it, of people bringing different ideas together and growing and developing the group as a whole and sharing in that experience. I think that's one piece that you get really out of building a diverse group.
The other piece is, if everyone is, okay, so I'm a mid thirties white guy from Seattle. If you only have a team of mid thirties white guys from Seattle, you never get a chance to create a culture in the team. Because you bring common culture together. It's implicit. You don't even think about it. You just all have the same experiences and education and backgrounds and everything, and so you speak the same language. When you all come from different places or all come from different experiences, you're forced to build culture together and define it as, okay, when we work together as a group, this is how we want our culture to be. This is the environment we wanna be in and we wanna work in, and it forces you to reflect and to question why you behave in certain ways and why you like or dislike those things, and ultimately creates something that harmonizes for people from all over the world. At least that's what we've tried to do, or that's been my experience over the years.
So as you look at diversity, for example, I'll talk a little bit about my side, since I think this is the first time we've ever talked about it in the show. Diversity's been incredibly important to me. I've had a scholarship for people in the US who are part of underrepresented groups. I really want them. I really want to see this change. And the importance for me was looking at teams, now that I've traveled the world and I've seen all around the US, there were teams that were either monocultures or had two cultures. And that was it.
And then, as I looked at teams and worked with teams that were much more diverse, USAA was one of the most diverse companies that I dealt with, where there were people from all different backgrounds. And there was a quantifiable difference between how those teams not just interacted, but how productive they were. What I saw was similar to what you were talking about. Everybody had the same life experience, so whenever you weren't down the line of that life experience, it was just a miss. But if you have all these people with complementary life experiences, they were able to help each other in ways I had never seen before. I just sat there and I watched it. Have you experienced that as well, Rob?
Oh yeah, absolutely. I mean, I see it every day, and it boils down to, I can give you some sort of more general examples. I can also get very specific from recent days. So more generally, we get to learn about each other. We get to share, we do Dutch lunch, for example. So I have a team in Amsterdam. Many of them are immigrants like me, you know, obviously it's helpful to learn language. So our Dutch call lakes host a Dutch lunch and we speak Dutch together and we practice regardless of level. And one of our colleagues just moved to Barcelona. And so we're gonna start a Spanish lunch. And so that way he can practice his Spanish with friends in a safe environment.
I mean, that's a really basic example of just helping people outside of work as a result of having this multicultural team that we've built up. But I mean, it also gets more personal. We have a colleague who is Ukrainian and her parents were just able to escape the war that's going on there. And she was trying to find places for her parents to go in Europe, effectively. We have colleagues who are also Eastern European. They were able to connect her with resources in Bulgaria, for example, for housing so that her parents would have a really nice place to stay. And that's, I think, the supportive nature you can get, or some of the benefits you can get outside of work of having a diverse team. Don’t know if that answers your question.
It does. And there's another part that we talked about that I'd like to talk about. And that is in Europe, there are a different number of cultures. So when we get into a team there's often, far more, not just languages, but cultures that are in there. Could you talk a little bit more about that and expand on that?
Yeah, so I think it's interesting. I have never worked in a team while I've been in the Netherlands where the dominant culture, let's say, the culture of the most number of people made up more than 30%. In my current group, I'm working in, we have 27 people. We represent, I think, 18 different nationalities today in my last team. I think every single person of seven was from a different background, spoke a different native tongue. So it really forces you to work in an environment where everyone is coming from a different background. And also, I think importantly, everyone is speaking English as a second language. It's not the language that they naturally think in. And that really also changes the dynamic, I think, in the team as well.
That's interesting. So now we've been mostly talking about established teams. People are already there. Now we have to expand that out to how do we create a diverse team? How are you incorporating that into your hiring process?
I think it's really important. So we all come in with biases, some very strong, some weak, some explicit, some known, some unknown in an ideal world. You're gonna basically find ways constantly to lower those biases and allow people to demonstrate their capability. So we've taken a number of steps in our hiring process to try and maximize the ability for everyone who we interview to succeed or on their own merit and their own competency. I mean, the starting point is CV screening, right? So it's very common.
CV being resume or curriculum vitae for, for people who don’t know that.
Thanks. Sorry, Jesse. So CV screening, I saw this at a company I worked with in the past, not TA, that recruiters, for example, would throw out everyone who didn't have an MBA in an analytics role. Well, that automatically discounts anyone who didn't have the money to get an MBA, but also people from most of the world who didn't go through the US educational system. And I've seen this a lot with different sorts of, these are examples of rules. So one of the things that we do is there's only one person who reads CVS in our entire team before they're selected for screening.
And that's me, I have my own biases. I'm aware of it, but at least then I can manage my own sort of biases. I would love to actually anonymize all the PII, the person identifiable information, name, etc., out of the CV, but unfortunately that's not possible within our recruiting application. So this way, at least I can kind of say, I know what I'm looking for in terms of potential skill set. And I'm gonna talk to as many people as I can who might be able to demonstrate that skill set, every person I select goes through a screening interview. In some cases that might mean reading 2000, 3000 CVs in a month on top of my day job, but it's worthwhile to make sure that no one is discriminated against, based on not having gone to the right school or not having the traditional sort of CS to master education as an analyst.
Second piece is how we train our interviewers. So all interviewing is done internally within the data team. Every interviewer is trained. We actually train everyone on communication styles, on biases, on interviewing, on what's allowed, what’s not allowed, why you don't ask certain questions, and basically how to adapt the interview to match the candidate’s communication style and pattern. Next, we always follow standard templates on interviewing. So all the questions are structured. In some cases, we even give examples. Actually, I would say always.
We give candidates examples of the questions we'll ask in advance to make sure that people who are second language speakers, for example, are not gonna be discriminated against because they're having to think through how to interpret or translate the question on the fly. So we use a very standard interview template in every interview we do, and we have a standardized rubric, scoring rubric we follow. Every interview is conducted by two people, ideally two people from different offices. So one person from California and one person from Amsterdam, to make sure that there's a maximum exposure of interviewees.
And the last thing we do is actually we ask candidates during the interview process about diversity, about their experiences in a diverse environment, and how they've worked to cultivate it. These are part of our standard screening process to make sure that when we talk to people, there are people who have thought about diversity and they weigh it as a value as much as we weigh it as a team. We actually have a team value where we say authentic diversity is our core strength. It's fundamental to us. And we believe that by applying all of these different guidelines and all these different rules and structures, we can create the most opportunity for any person who's qualified for the role to be able to succeed.
There's one thing about the European hiring process - I should say, specifically German - that I've went through with clients. And that is, there are certain questions that you could never ever ask in the US. For example, in Germany, marital status, actual age down to the year. Also they'll tell how many kids they have. Do you block out that information or how do you deal with that part of it?
So we do hiring in the US. All of those are absolutely illegal in the US as well. Quite frankly, it's very hard to remove that from CVs that are loaded as PDFs into our system. This is more of a technical limitation than anything else. The data is available. We've told everyone and trained everyone not to share, not to care, but it's hard to avoid that, because sometimes candidates do present that in advance. I will say that no one's personal situation weighs in the slightest in terms of how we do our interviews.
That resulted in a fairly diverse group. I think our youngest person is 25. Our oldest is in their late 50s. We're 45% female, 53% of our seniors and leads are female. Like I've mentioned, the nationality. We have people of every sexual orientation and marital status. It doesn't matter. What matters is, do they share the same values as what you're looking for in a team member? And do they have the competency to perform effectively in the role that you're hiring them for?
Was there a particular person or entity that influenced your views on diversity?
I don't think there's a particular entity. I think, again, I'm an immigrant. And one of the observations that I've had as an immigrant here in the Netherlands is that I am incredibly privileged, and the longer I've been in technology, the longer I've been in the data space, and the longer I've been an immigrant around the world, the more I've seen my own privilege that I had. And based on that, quite honestly, it started to bother me as I worked with people who didn't have the same privilege. And I saw them, whether overtly or subtly, unintentionally discriminated against, people who were more capable than me in so many ways, it really started to bother me. And I just started to feel that I had this obligation, this responsibility, because I am a head of data. I am in a position of power within the organization and within the team. I have an obligation to make sure that everyone has the same opportunity that I have. So I think that's probably the foundation of why I feel this way.
That's interesting. We were talking about what music you'd listen to. And for some reason, I thought that you would listen to a lot of Public Enemy, fight the power, but you listen to something different.
I do have a strong anti-authoritarian streak. It's very hypocritical given my role, and I acknowledge that. But no, I think it's a social obligation thing. If you ever read the work of John Rawl's, they did this thought experiment about what society would you define? If you had to define it and you knew you were gonna be one of these different people, but you didn't know who you'd be. And what they ultimately came up with was the measurement of society is not measured by how much the best off person has or even the top echelon or whatever, but how far can the person with the least advantage go in society? Whether it's about welfare or achievement or whatever else.
And I think that might play heavily into how I think about designing and building teams. I have this responsibility and this capability to make sure that everyone, regardless of where they're starting from, has this possibility to go to whatever level they strive for. And it's my job as a manager to build that environment that allows them to join and then to excel in the team in that capacity.
Excellent. So, just to kind of sum up this conversation, there's people around the world. And one of the things I would stress here is, diversity is really important, diversity will help you, but there are some countries where there just isn't any diversity, quite honestly. So the parts there I would stress would be the economic diversity that Rob was just talking about, that diversity means several different things, and if everybody lived a privileged life and you have somebody who came from poor, I came from a poor background, so I have a different outlook on certain things. I'm not thinking about how you pay for this, I'm thinking about why I can't pay for that. So there's a lot of diversity that's part of that. So it's really important to think about, and as you look around your team, that they can complement each other, even if you're in a country where there isn't a lot of diversity there. Getting back to more technology parts, why do you think it's so important to have self-service analytics?
Because quite frankly, no one wants to work with the data team. I mean, let's be honest, no one wants to have to make a request and then get a dashboard made, wait two weeks, get it, find out that it's not quite what they want, give some feedback, get it back again. Nobody working in the business, or at least, most people, want to be able to get answers to the questions that they have today. And their questions are gonna be varied, and their questions are not something you can necessarily put in a structured dashboard.
The best way to empower people with data is not to build a lot of reporting; it's to give them access to data and give them the tooling and the understanding and the capability so that they can use it effectively to make their own decisions. And that's what really empowers people. I remember I was sitting in one meeting at one point, there were several C level folks and we were just carrying on this conversation. And someone was like, yeah, blah, blah, blah, what do you think about this particular problem? And one of the execs, she's like, oh, I don't know, but let me just look it up real quick. And she went into Tableau and she did an edit. She opened up a data source and did a quick little graph, and she's like, oh look, this is actually the answer to the thing we're talking about. And she carried on.
And that, for me, was proof that self-service is not just something you can make accessible, but it's something that can really empower the organization. This is the highest level of decision making, and in the moment, they needed a data point that didn't exist in any reporting, but they were like, I feel comfortable doing my analysis to find this information on the fly to be able to answer this question and make a better decision as an executive.
As you mentioned, you're American. So, I'll point this out. When we first met, I thought Rob was Canadian. He actually had to pull his birth certificate out to show me that yes, he was born in the US, lived in Seattle. He has the most Canadian accent, except for not saying, sorry all the time, that I've ever heard.
Sorry about that.
Very. So since you're American, I'm American, what do you think Americans should imitate from Europeans and vice versa?
So I always tell people, regardless of where they work, that we are a European team with European values. And for me, what that means is, work is a job. It is not a life that you sacrifice your family, your friends, your kids, whatever else for. There are boundaries, and your work begins and ends at a fixed point in time. And that attitude, I think, is not always common. I think in, whether it's big companies in the US or tech companies, I think there's this mentality of working all hours and we want to celebrate 80 hour work weeks. That for me is not something I would ever want to celebrate.
I celebrate getting to share our lives together. And so that's something with our team we share. We celebrate the birth of kids, and we share photos of kids and holidays and people taking sabbaticals. That's something we actually, we take pride in that people take time off. And I think that's a very much more European than American model. And I think that's something really valuable, and really it makes the work environment better, and it makes people more productive, and it makes companies more successful when they allow people to put a strong boundary between this is what I'm doing professionally and then this is my life outside of it. I think it's one piece that was beneficial.
The second is, and maybe this is more, I've been in the Netherlands for a long time, and the Dutch are famously direct. There's an aspect to communication that happens when, take Dutch directness but combine it with the fact that everyone is a second language speaker. We are much more direct, and we say what we think here in Europe. And we don't tiptoe around topics, because you run such a high risk of losing the message. And so I think that's a very strong benefit to running a team, because then everyone is just gonna say exactly what they mean, rather than obfuscating information to avoid hurting people's feelings or to be sensitive to what you have.
And what about the vice versa? What do you think Europeans should imitate?
The one thing I, and I have this conversation with my wife often, the one thing I do really appreciate about my growing up in the United States and my background: H. L. Mencken once said, "There are no poor people in America. There are only temporarily disadvantaged millionaires." I think that's reflective not of economic mobility - we know that's not true actually, but that's a totally different conversation - but that's reflective of attitude. This attitude of I can try and I can fail, and I can try and I can fail, and I need to keep trying and failing, because eventually I'm gonna have this opportunity to find success. And I think that's historically been lacking in especially, like, startup culture here in Europe. I do see it really heavily emerging much more in the last say, three to five years, but I think that's that American mentality that I'd love to see and I would love to see continue to blossom here.
I would love to see that as well. That would be one of the things I would share. And I do share that with my European friends. What is the greatest data story that you've never told?
I'm gonna call you out, Jesse, a little bit on this, because the question was, "What's the greatest data team story you've never told?" In the prep question. Because the greatest story on my data team I've never told is nothing to do with data and everything to do with the data team. So, in the last company I worked with, we had some financial troubles. It was a travel company as well. And towards the end, the company was really running hard towards bankruptcy.
Now in data, we had information that would allow us to kind of hail mary, if you will. We were working with all potential last minute investors who might buy the company, whatever else. Because our focus was, how do we save jobs? The day before we went bankrupt, the team got one last opportunity to try and come up with some last opportunities for investing, and they showed up and we just started diving in, but there was a lot of other stuff that had to happen, because this had a 20% chance of success. And so we started working on okay, gathering the data for this potential investment or this potential sort of, saving financials. But the team jumped in, and there were a lot of other problems we saw.
So we knew we needed to communicate. And a lot of other people had already started quitting the company, because this was very clear at the moment. So the team jumped in, and they were writing messages to customers and travelers in their native tongues that we didn't have people ready to go on. They knew that there were folks who were gonna be impacted, so my data engineer who barely knew Excel - hi Niels, if you listen to this - was working on how to track people who were in travel so that if we did go bankrupt that day, we'd be able to reach out to people. And he was working through records in Excel.
And the reason this is so great is, you're facing such a horrible situation. You know, companies going bankrupt, you're gonna lose your job, you don't know what's gonna happen. And everyone jumped in, they did everything they could in whatever capacity they could to help try to prevent that but try to make sure that there was success. And we actually had a ton of fun during the day, and we made it into a really enjoyable circumstance for us as a team. So even as we're working on this terrible situation, we had fun. And I think that's the greatest story for having a team working together and collaborating together.
That is a good story. Thank you for sharing that. One thing I will say about this episode is, so far, this has been the most touchy-feely episode. Lots of feelings, lots of emotions on this one. And I want to tell everybody that, especially individual contributors and managers, what eventually becomes the gating factor in your ability to grow is your emotional intelligence. It's not going to be how well do you know Spark, how well do you know this other thing, or how well can you run an agile/scrum meeting. It eventually becomes your emotional intelligence. So it looks like Rob's worked a lot on that. So I would encourage everybody to do that as well. Let me ask you one final question, Rob. What do you never compromise on?
People. And I hope that might have come through throughout the day or throughout the recording. Whether it's the relationships that I build with people, it's really important for me to always be honest and genuine. Whether it's the commitment I make to people, I have talked to four former team members in the last 24 hours. Whether it's about what work they're doing or new jobs and how to work with their new managers. I'm on this podcast, actually, because of a former team member. Hi, Bastian. Whether it's about making sure they can trust me and being transparent, it's always about the relationship with the people on the team. That is the one thing I will never be willing to compromise on.
Thank you so much, Rob, for coming on the show. I really appreciate the sort of things that you shared.
Thank you for having me. It's been a pleasure talking about all things team and diversity and relationship building.
Another great story, another perspective shared on data, and the tools, technologies, methodologies, and people that use it every day. I loved it. It was informative, refreshing, and just the right dose of inspiration. Remember to check dreamteam.soda.io for additional resources and more great episodes. We’ll meet you back here soon at the Soda Podcast.
