 Hello and welcome to Data for City Talks, a podcast where we discuss with industry leaders and experts how they have built their careers around data. I'm your host Shannon Kemp and today we're talking to Erin Rulker, the Senior Manager of Data Strategy and Governance at Carhartt. Ready to share your knowledge and network with your data peers? Join us in San Diego this June for the Data Governance and Information Quality Conference. Five days packed full of new perspectives, new colleagues and new approaches are yours when you register at dgiq 2023 west dot dataversity dot net. Lock in early bird savings when you register by May 5th. We'll see you there. Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Officer at Data for City and this is my career in data, a Data for City Talks podcast dedicated to learning from those who have careers in data management to understand how they got there and to be talking with people who help make those careers a little bit easier to keep up to date in the latest in data management education. Go to dataversity.net forward slash subscribe. And today we are joined by Erin Wilkerson, the Senior Manager of Data Strategy and Governance at Carhartt. And normally this is where a podcast host would read a short bio of the guests. But in this podcast, your bio is what we're here to talk about. Erin, hello and welcome. Hello, Shannon. Thanks for having me. Pleasure to be here. Happy to be involved with this. I'm so excited. So you're the Senior Manager of Data Strategy and Governance at Carhartt. So what is Carhartt for those who don't know and what is it that you do? Yeah, so the mission statement of Carhartt is that we exist to serve and protect hardworking people. So we are an apparel fashion and retail brand headquartered in Dearborn, Michigan. We have about 5,500 associates worldwide. We have our company has a very proud history. We're a family company. So the original founder founded the company back, I believe in 1889. You know, still kind of housed within the family, definitely a private company. So we essentially we're a maker of work wear plus a lot of people know the Carhartt jacket, the Carhartt overalls, you know, the brown duck coats and things like that. So we also have the hats. I think that's one of the most popular hats. I think I've heard that the t-shirt. So the Carhartt t-shirt, a little pocket t-shirt, I think is the most popular t-shirt in America. It's a lot of different products that people have known us for, I think, you know, over 130 plus years. So definitely it's a pretty cool company to work for, you know, I'm based out of just outside of Detroit, Michigan. So I'm a lifelong Michigander. So the company is also, you know, very close, very close to me where I live at. So I've always liked working for local companies. So, you know, very awesome mission for the company plus local Michigan company is kind of what attracted me to the role. So I've been with the company for about six months now. So my range of responsibility is really around governance. So trying to help establish a lot of governance practices for the company and also, you know, have some responsibilities in the, you know, data architecture space and kind of, you know, bring about some data strategy as well. So very fun job, you know, still very new to the company, but, you know, being able to kind of dig around and kind of figure out where I can make a benefit impact. Well, I love it. And with the company that old, I'm guessing you deal with a lot of legacy systems and legacy practices that you're working to move forward. Yeah. I mean, the beauty of it is like it's there's a true love of the brand by the associates here. So you have people have been here for a very long time. You know, some people have been here 20 plus years. So people have that history. But there's also a good amount of people similar to me that just arrived when in the past, you know, six months to one year. So a lot of new energy. I would say that the company has faced a lot of growth. So, you know, going from, you know, continuing to grow in size and kind of, you know, revenue, you know, year over year decade over decade. You know, that kind of brings about new opportunities because, of course, you can't know when you go over a billion dollars, you know, at company size, you know, there's a difference in kind of how you run a half billion dollar company versus a billion dollar company. So definitely a lot of change in terms of our systems processing. That's why I'm here to kind of help with governance just because as you continue to grow and grow, you know, there's some different structures and systems and processes that to be in place to kind of help with that growth. So definitely, you know, a lot of kind of, you know, older, different things in place that we're trying to freshen and make new, you know, one of our mantras is power, the seamless customer experience just to kind of make sure we keep the customers in front of mind and make sure that we're kind of doing things to make it easier for our customers to work with Carhartt. Very nice. So tell me, Erin, when you were very young in elementary school, was this the dream I'm going to grow up and be a senior manager of data strategy and governance? No, of course not. But I think back to when I was, you know, a fifth grade, I think I put like a baseball player, like a computer programmer. So, you know, definitely in the baseball, I kind of max out of that, I think in the 11th grade. So I guess I'm kind of sort of a computer programmer since I kind of work in the in the data space. So yeah, definitely kind of didn't really imagine this coming. I was very much into kind of engineering and, you know, robotics, even like thinking about high school. So definitely a big shift kind of getting to the data space that I have my whole career. I love it. So so tell me, so as you were growing up then, you know, so staying into sounds like a lot of computers is growing up in high school. And what was the focus? Where did where did you go from there? What where did your passion start taking you? I mean, I would say that, you know, I even put this in my LinkedIn profile. Curiosity, I would say, is a big part of my journey. So I would say that I've always kind of leaned on the STEM fields, because I was always very good at kind of math. So I know I did I did some kind of engineering programs back when I was in high school. So kind of follow engineering just because I feel like that was kind of a good thing for Curiosity because you're always kind of building and tinkering around with things to kind of follow the engineering path. So actually that's what I got. My bachelor's degree was kind of electrical engineering. But then I realized that I wasn't going to be an engineer. Like I, you know, I had a lot of peers who were big into kind of engineering. I realized I didn't want to do that. So I ended up kind of working for Accenture as in the consulting world. So my first job that I got when I joined Accenture out of college was in IT. So I joined kind of a data like service desk or help desk at a client right out of college and learn kind of everything on the job. So learned about, you know, IT and servers. And, you know, this was back when it was all like physical machines when we got into virtual before cloud. So like how to, you know, how to build out, you know, security structures on servers and how to build out software and install software. So definitely just curious, right? Just learning, just constantly learning, constantly being challenged is kind of finding like digging in more into the wise, right? So, you know, why are we doing it this way? Like, okay, why, why are we doing it this way? No, are there different opportunities to do that? So I was just saying that the curiosity just been a natural progression along with my career just kind of taking the next level more and more to understand more and to kind of work more in front of office. Because I totally like to work with people, like, you know, engaging, problem solving, talking with people, understanding their challenges, solutioning, so coming up with solutions to their problems. I've been very much more front office versus back office. So it's kind of like, how do I get in front of people and problem solve and kind of continue kind of the curiosity journey. So that's kind of led me for the past, going on 16 years of my career. Very nice. So tell me a little bit more about that journey. So you started off at Accenture and almost immediately got into data, it sounds like. And even though in some IT support fashion, right? So, but, so tell me a little bit more about your data journey. Where'd you go from there? Yeah. So, so back when I started, luckily I've been in data my entire career. So that was like my first job. So I was in more of a service desk. So now it's on SAP, but before SAP bought it, I was very much involved with business objects. So very much into reporting. So I was on a team that was more of a service desk, where like when people had security issues, we were like trying to fix their security access because they can access reports. Also, we had like all these jobs. We were running all these different like reporting jobs. We were kind of making sure that our reporting queue was going anytime there was an error, we were kind of rebooting software reinstalling. So learned a lot about, you know, how to install applications, how to configure applications. Cause this is before everything was more cloud based with actually like installing applications on a server, clustering applications together. Cause you always wanted like the fail, the tolerance. So you want to make sure that the servers are all connected to each other. So a lot of that. So I really dug into the business object side of it, but then the recession happened in 2008. So I was consulting, so they let a lot of the consultants go. So then I took those specialized skills and business objects and that got me into a different consulting gig. So I ended up traveling for about six months to a company in Boston, like, you know, leave Monday morning and then kind of come back home Thursday and do it. So I did that for about six months, like still focus on business objects as a technology. And then, you know, met my soon to be wife, we got engaged and I didn't want to travel anymore. So then ended up kind of taking that business objects and working for a hospital. So a local hospital, I ended up kind of being their kind of business objects administrator. So keep, so taking that kind of same tech stack that I learned from my first job to different roles. And then at the time my director came to me said, hey, do you want to work on ETL? I never heard of ETL. At that time I was just all about like business objects, like data and reporting administration. I had not really done anything like actual like movement of data. So then I learned on the job about ETL and data warehousing. So I had some pretty cool managers that were my mentors. So learned a lot about ETL and data warehousing, what data warehouse was. So then kind of merged my role into kind of more data warehousing. So learned more about ETL, became kind of an ETL developer, then kind of got more curious and learned about the architecture side of it. So then kind of leaned more into data architecture and ETL architecture because I was wondering like why are we creating queries this way? Why are we kind of, why is the database structured this way? Why are tables and indexes built this way? So it kind of like took the curiosity team more of the architecture. Then kind of kind of bounced around and ended up kind of getting into leadership because I found that usually architects kind of lead itself into leadership. So then started to take on manager roles. About 90 years ago, kind of had my first manager role. So still kind of had part architecture, part people management side of it. So still taking the data route into data warehousing and like the more of the front end reporting. So kind of did a couple of roles on the data leadership side for a couple of years. Then got an opportunity at my current company to come here. So then it was more of a, I've done the data warehousing, done the business intelligence for a long time. What about like governance? I've done some governance in my entire career, but never like more like that was my core role is like governance and then more of the strategy. So I realized that even as we build the backend data warehouse and BI reporting, there's still like a level of governance and strategy that needs to be there too. Because I think a lot of the challenges we have in our space is just kind of, people don't really understand the end to end parts around how they put data into a system that comes out on the backend side or the strategy around like, how does this align to the business or how do we providing business value with these things? So I've worked on the backend side where I've created these data warehouses reports, but then connect like, why does the business need this? Are there better ways to do this? So kind of really kind of follow the strategy kind of around through curiosity, just kind of getting in front of it. So that's kind of like my journey from kind of really back in administration to like data warehousing through architecture, through manager and leadership and kind of where I am now. So kind of still on the curiosity side of just like being curious and wanting to address problems and finding new solutions to things. I love that. So let me just back it up a little bit because so many of our listeners are new to the space and they're looking to get into these kind of roles. So business objects, how do you define that? What are, how are you defining that when you talk to by getting into that? So that was, so that was a reporting tool. So, you know, in data, like if you, there's different roles within data. So, you know, you have kind of your, the people who kind of create the database is typically reporting on top of a data set. Usually those data sets are you're pulling data from different applications and you're storing them in a database, but people want access to see the data. So a lot of people use Excel, but there are formal tools. Like you've heard of Tableau, you've heard of Power BI. So business objects was a reporting tool. It was eventually acquired by SAP and they renamed it, but it was a reporting tool that since you sat on top of a database where you have a data model and then you kind of created a report on top of that. So it was kind of a tool that helped people easily create reports that you can go on, give off to like your leader, different business, people in the business. So it's kind of like a more of a reporting tool to kind of provide. So the things that you do in Excel, it allowed you to kind of do that a little bit faster at scale when you had kind of like more of a backend database to expose data to. Then ETL, you said you didn't know what an ETL is and then using your curiosity, discovered what that was in a data warehouse. Correct. Yep. So ETL stands for extract, transformer, load. So it's interesting how you build the database, right? So you have data sitting in different databases, you need to extract that, right? So you have to pull the data out, you have to transform it, you have to load it into your target like in result because you don't want to have reports sitting on top of the data where it came from. You want to move that data from one place to the next one. So that essentially is the ETL is kind of the movement from data from one place to the next place so that people can analyze it. Because typically like you don't want people touching like the actual application because they could break it, there's performance issues. So you typically want to move it somewhere else then let them create reports on top of that because you won't break it, it's usually going to have faster performance. So that was part of that is just kind of moving data from one place to the next. And the architecture is like trying to design how that structure should be made. So while it's kind of like the engineer versus kind of the construction worker where the engineer is going to design what the building should look like but you actually have the construction work to actually build a date. They're laying down the cement, they're putting up the framing, they're putting up the drywalls with someone kind of architects. It says like, here's the layout and here's the plans. Now someone has to actually go build that so they know they kind of change the name, right? So now I think you hear more about like data engineers. When I was there it was kind of more ETL developers or database developers but now it's kind of called data engineers. So we've kind of rebranded it but it's the same kind of concept where you're moving data from one place to the next and you may kind of transform it in some way. I love it. More and more companies are considering investing in data literacy education but still have questions about its value, purpose and how to get the ball rolling. Introducing the newest monthly webinar series from Dataversity, Elevating Enterprise Data Literacy where we discuss the landscape of data literacy and answer your burning questions. Learn more about this new series and register for free at dataversity.net. Lots of things for me to come back to there but also, so what is your definition of data and how do you work with it? Yeah, that was actually just a topic on LinkedIn. The data is, it's the thing that kind of describes our business, right? So it describes our products, right? So if we make a t-shirt, it gives you like, it's a t-shirt, it's this length, I lift this length, it weighs this much, it has this color, it costs this much. It's also kind of the output of our processes, right? So if we're going to ship a t-shirt to my house, you know that it came from this location, it got put on this truck, it took this many days, it ended up in my house. So it's all those different kind of, it's the information about a process that you get to follow along with, right? So you know where it came from, where it sat at, how long it took. So it's kind of like the information is the context about our business, about our customers. They know that my name, first name, last name, address, like so you know that information. So it's kind of that information that is moved, is that's about our companies, about our business, about our services. So it's really like that actual, no tangible thing that you can use to track, you know, your company, the value you provide, the product services, the relationships, like is that kind of information that you can use to understand our business or understand a product or understand something else like that? And I love to ask people who are especially in data governance. So you know, what is data governance too? We've had so many people come to us and say data governance is such a dirty word. We don't want data governance. It's all about adhering to laws and this and that. So what is data governance to you and how do you implement it? I mean, to me, to your point, it really depends on your industry. I think it's typically those kind of, it's kind of, it's people process technology, right? It's those type of people and process of technology around how we utilize data, right? So every company has data. The question is like, how do you use it? You know, where does it come from? Where does it go to? Who has access to it? How do we, you know, know what the guidelines around? Like how are we supposed to handle it? You know, are there certain business specific rules around how we should name things? So it's kind of like the structure and kind of the framework around which we use data because if you view it as like a true asset, it's really like, how do you treat that asset within your company? So governance is really just kind of that is the people process and technology that's wrapped around how we utilize data. Now there's, you know, we can talk about policies. You can talk about security. You can talk about regulations, compliance, but those are just more different shades of it. But it's just like, it's more of the, like how do we use data and like, how do we think about how it's managed and used around the organization? I really like that answer. And tell me a little bit about data strategy. You know, what are you thinking about when you're working on a data strategy for the Carhart? So I would say data strategy kind of gets into, like the, it's kind of interesting. The strategy I think is more like, how do you leverage a strength against a weakness? So it's kind of like, you know, what's our approach to leveraging data to benefit the organization? So we believe that data has value. So it's like, what are those different opportunities and approaches to do that, right? Because you have many opportunities around like, you know, what you can do with data, but strategy is like, what are we choosing to do and what are we choosing not to do? So you could use, you could sell data, you could send data to different customer, but you're making decisions to not do certain things with data. So strategy kind of helps you align with like, we're using data for this, we're not using data for that. Like data, so in our realm, like, you know, data is going to this system and this system is not going to this system. So it's really that kind of like, like actual like action plan and more of a decision-making tool to say, hey, we think that this is the best use of data for value creation. And this is how we plan to use that at this company. So it was not about technology, right? So like Power BI, SQL, Oracle, that's not a strategy. Those are tools that those are enablers for a strategy, but it's not a strategy. The strategy is a very specific around like, this is what we're choosing to do to leverage data in our organization for these different benefits. Very nice. So, do you see the importance of data management and the number of jobs working with data increasing or decreasing over the next 10 years and why? I would say it really depends on the organization. I would say that if you have a company that truly views data as like an enabler of business value, you're going to see the number of jobs increasing because we just know that there's going to be more data. Like digital was a huge transfer, like digital transformation is a huge enabler of data. So like when you see like, you know, more companies through the pandemic, like using their e-commerce or apps, like all those things are creating data. So you need people that know how to manage and utilize that data, but the business has to have the overarching kind of belief and vision that this data will provide value to our organization. So if the business says that, yeah, this data has value, you're going to see the number of data jobs increasing because that someone has to be able to manage and use that. But we've also seen, especially during this kind of last couple months of the economy that you see people reducing the data team. So I think that's because the business doesn't believe that data has value or they're not, have not seen the value is maybe more of a cost center than an asset of innovation. So I would say it really depends on the company. I would say that like a lot of the leading companies, you see that data jobs are growing because they know that they need more people to manage data. But some companies you see in the shrinking because the executives are like, we just, like we've invested millions of dollars or tens of millions of dollars. We've not seen any benefit from this. So they're reducing, they're reducing data jobs. So I really think it just depends on like if you're a growth company that's like much more visionary or like you just don't see data as a differentiator for your company. Very interesting. So what advice would you give to people looking to get into a career in data management? I would say my advice is that, while data is important, we really need to focus on the business. Cause I think the challenge is a lot of times data is, it started, I think very much back off as an IT but we've seen that it's really growing even out of IT and some aspects in terms of we need to understand how the business wants to use it and the value that it creates, right? So we should know, we should know more about the business. So I would say my advice usually is like learn about how a business makes money, how the business creates value. So the business model, the operating model. So if you understand how the business makes money, how does it actually provide that value? So if you work for a fast food company, do you know how the storage works? How the workers create the food? How do they distribute the food? The supply chain, how does the food come in? Where does it come from? How does it come in so quickly? So as you understand more about the business model and operating model, even the technology model, right? So how do we efficiently send information? How do we have technology to handle these things? How does the POS, the ordering system works? As you understand that, that gives you a much better understanding around how we should utilize data. Because data is used as a enabler of business value, but the problem is a lot of times we don't associate the business value. So we treat data like in its own lane like it's like a isolated island. But the data is there to benefit the business. So I think that's where I would advise people is that you have to make the connection to the business or else you kind of like I said before, like the business doesn't see value. So if you don't connect to the business value, the business will say we don't understand how we have all these people doing this data stuff and they won't invest in you. They won't give you more resources. They won't give you more people or give you more tools. And then you kind of eventually kind of with their way, you kind of get reduced. So that would be my advice is kind of, follow the people, follow the business. I mean, you can learn tools, like that you can learn SQL, you can learn about databases. I learned that out of college. So I'll say, but the learning how to talk to business users, understand their problems, understand their challenges, that's the key I think in the data space. I think more people should focus on. I love it. So is there something that you've done? Is it just practice talking to people? Is there some education? Is there some reading materials that you've kept up on to really keep that engagement going and understanding of the business? I would say a lot of us is asking questions, right? So it's showing up and asking people questions and understanding their roles, right? So if someone's asking you for something like, understand how they're incentivized, right? So if it's a business person, like for example, marketing, okay? If someone's asking you for marketing data, like where are you gonna use with it? Then, once you have the data, what would you do with that? Okay, I would do this, okay? Then after you do that, we're gonna do with that. Like understand their incentives because we all have incentives around why we do things. So we talk with someone in sales, understand, okay, if they're asking for this data, they're gonna use it to make a decision, okay? Then walk us through your decision-making processes. So like a lot of this kind of work while we're just asking questions, you know, I can, you know, there's always kind of, the best thing is just kind of just ask questions and be curious and kind of just keep engaging people, even if you don't work with the business, ask your leader, right? If your leader is asking you to do something, okay? Hey, why is that important? Or what are you gonna do with that? Like how is that going to benefit you? Like it's really just kind of expanding the curiosity and just kind of more asking questions and listening, right? So that's the key is also listening. So don't ask with the intent to kind of have an answer right away. Like sometimes you just sit there and listen, you write it down. And I think that's kind of from the basis. I think it's practice because no one's great when you first start. You don't know what question to ask, you don't know the follow, because there's always follow, right? So someone can give you the answer, but it's typically a follow-up question. That's the next question you need to ask, but you really don't learn that until you get in the habit. So I would say that, you know, start by being curious, ask questions, be comfortable talking with people. So that's another one, just kind of like, are you, you know, are you approachable? Do people enjoy talking with you? Like, you know, make sure that you're someone that people want to work with. That's such great advice. And I love that you've carried that, that to be curious theme through most of your life and has served you so well in your career. So any other advice or skill sets? I mean, you've talked, how do you keep up on the technical aspects that you need to keep up with? I assume now in a more leadership role, you're not having to learn, you know, the coding on, you know, very specific products all the time, but you know, how are you keeping up to date to keep the company up to date for the data management? Yeah, I would say, you know, LinkedIn has been huge for me. So I would say going on to LinkedIn, like, you know, Googling like top data thought leaders and then kind of following them on LinkedIn to find what they're talking about. I mean, there's a lot of, there's a lot of discussion about data and LinkedIn. So I think it's just kind of like listening, like watching people, what they talk about. Like there's always articles. There's tons of articles, there's tons of newsletters, podcasts, like look up data podcasts. I would say the information is everywhere. You just need to kind of plug in and pick something, right? So like I said, there's podcasts, there's webinars, conferences are good. So you can like go to a conference and spend some time there. So you can kind of get a feel for, you know, what's out there in the space. Then you kind of have to filter to figure out what makes it, because sometimes there's things that doesn't make sense. But then you kind of challenge, okay, that makes sense to me. That doesn't make sense to me. YouTube is another one where there's always all kinds of YouTube. So I would say the information is everywhere. Like I think we're in the age where you can learn anything you want to if you put the time in. So I would say you just have to commit to putting the time in. And then just kind of picking a line. So maybe you focus on LinkedIn for a couple of months. Then you pivot to like podcasts, you're gonna follow podcasts and then take those recommendations and then, you know, we're gonna try YouTube videos. And you have to actually get to apply it, right? So that's the other thing is, you can listen all day until you actually like try it. And we also live in the, there's tons of free trials, tons of free software out there. So I would say listen, listen, listen. But then you have to actually have to practice it and try it out. So that's the, like, that's the step two is one, listen and learn. And then you have to actually apply it to problems, right? So there's always kinds of data sets out there or created data set. But I would say it's a pretty cool age to be around because like I said, there's information everywhere and it's easy to learn to pick up skills. Such great advice. Thank you so much. Okay, so the most important question of the interview here, Aaron. Who is your favorite baseball team? I don't really watch baseball. I'll say- I'll say probably the Detroit Tigers because they're local to me, but they've not been very good lately. So- Lost that passion a little bit since the kid. I understand. Well, Aaron, thank you so much for taking the time to chat with us today. And for all of our listeners out there, if you'd like to keep up to date in the latest podcast and in the latest data management education, you may go to dataversity.net forward slash subscribe. Until next time. Thank you for listening to Dataversity Talks brought to you by Dataversity. Subscribe to our newsletter for podcast updates and information about our free educational articles, blogs and webinars at dataversity.net forward slash subscribe.