 and welcome to My Career and Data, a podcast where we discuss with industry leaders and experts how they have built their careers. I'm your host, Shannon Kemp, and today we're talking to Lee Curzall from ERM. ["Dataversity"] Did you know Dataversity offers free monthly webinar series and online conferences throughout the year? Stay in the loop when you follow us on Twitter at Dataversity or on Instagram at dataversity underscore edu. Get podcast extras and bonus content when you subscribe to our channel at youtube.com slash dataversity. Hello and welcome. My name is Shannon Kemp, and I'm the Chief Digital Officer at Dataversity, and this is My Career in Data, a Dataversity 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. Yay. We are joined by Lee Curzall, a principal consultant at ERM, and normally this is where a podcast host would read a short bio of the guest, but in this podcast, your bio is what we're here to talk about. Lee, hello and welcome. Hello. Thank you. It's great to be here. Oh, so glad you could join us. And so glad that we met up with you at DGIQ to invite you to be in this podcast. Thank you for saying yes. DGIQ is one of our conferences, Data Governance and Information Quality, conference in San Diego. Yeah, so much fun. Okay, so tell me. So you're the principal consultant at ERM. Tell me about ERM and what ERM does. So ERM stands for, it's environmental management. Like the focus is they are like, we are the only pure place sustainability management company. And we've been here since the beginning of looking at sustainability. So we were established in 1971. We've been around for more than 50 years, almost as long as I've been around, a little longer. And it really, the biggest thing that we can say about a company is we've worked with all of our clients. We're global, 8,000 employees. It's a very technical consulting firm. We focus on operationalizing sustainability. And so what you do that can look at, okay, how are we doing that on the ground? We talk a lot about boots to the boardroom that we work on the ground all the way up to the C-suite to get everybody on the same page when it comes to sustainability. But it also has a huge data component to it because environmental itself generates so much data. And so being able to utilize that to be able to support through environmental sustainability data governance is really a huge thing. That's something that these clients are, that it's information that they're going to have to record on, not just internally to their company, but they have to report on publicly that they have to, that goes to financing companies. So it's something that is becoming more and more important to be able to say, what is the truth behind the data that you are giving me? What is the governance behind that metric? And so that's one of the reasons why, we've come to DJIQ, we wanna get more information. We wanna make sure that we stay on that bleeding edge of what is being done. But we also like to, we're speaking at DJIQ because a lot of companies aren't thinking about the governance behind this information that they are potentially reporting out in a public environment. Companies are used to reporting information internally that publicly reported is really uncomfortable. So we're hoping to be able to say, okay, there are people that expertise in this, this is their technical field. So typically we look at, and it's things where we're working with environmental health and safety and risk management. Those are kind of the pockets that we follow under, but it's across all industries. So everything from mining to manufacturing, to a chemical company, just all over the place. Oh, that's very cool. That is really cool. I love all the different industries that data gets into. There's not one that doesn't touch, right? So yeah, so what is it that you do for ERM as a principal consultant? So we have different, you know, I'm principal consultant, I'm considered kind of a senior consultant level. And so my, one of the questions, three questions you had said, what does a weak look like in my work? It's really diverse. So it appeals to that kind of, I like to do a lot of different things. I don't want to get bored. I get to do everything from talking to clients to say, okay, I think I have this issue. Can you help me brainstorm it? So design what their data governance could look like overall. Where do they potentially look for gaps in their governance plans? Or what can we do to help them operationalize their governance? They have this great governance that has been handed down from their higher governance, but how do I actually implement that, operationalize it at the manufacturing level, at the floor, on where the boots are? So it is taking governance itself and being able to turn it into a usable tool for people that they want to use. So that's one of the reasons why when we were speaking, we were speaking about putting the people at the center of our governance. And it's because we don't want to be the police. We don't want to be seen as the police. And we don't want governance work to be seen as the police. We're trying and we're succeeding in helping our clients to recognize we're here to make it more efficient because the asks of you are going to get more complex and bigger. So we operationalize, we make automatic as much governance as we possibly can. And that's actually a really big area that we're doing. It's not relying on AI and everything, it's just doing things where, okay, how can we make automatic metadata generation? So instead of the person having to think of all of their metadata as we're loading the document into the official library and document manager system, how can we create some automatic workflows from out-of-the-box platforms that you have access to everywhere so that it gives them basically, okay, here's all the metadata that this syntax, which comes from Microsoft, which everybody at the Microsoft house can have access to, what's going to tell us? And then you can click on it off, say, nope, those are appropriate, these are appropriate. And now it makes it easier to find that document in a storage system. So- I love that. So you're automating some things for your customers but you still drive home the importance of people. Yes, because- As people are part of that process. Yes, if we aren't doing that, then we give them a great plan, we give them a great operational plan for working with this, and it just sits there. Because they're going at 1,000 miles an hour. We have to make sure that our data governance moves as fast as they do and helps them move faster. So important. I love that. Well, let's get back to that a little bit. So tell me, Leigh, when you were very young, just a kid, was this the dream? I'm going to be a principal consultant when I grow up working with data governance. I'm totally, it's so, it was not a straight line to get here at all. Yeah. This is actually working in environmental and under the label of data governance. This is my second career. So I actually, and I've been doing under that label for the last five years. Prior to that, I actually worked in healthcare. And I worked in healthcare, but the thing that I've loved doing, so I worked in healthcare for 20, almost 25 years. And at a director level, so management level. And in my career is when we went from paper charts to electronic medical charts. That was an entire exercise in massive data governance because there are so many terms to describe what this is. And getting positions to agree on what this is, is the epitome of governance. And that's what you had to do for it to get people, everybody was used to writing what they wanted to write in a paper medical chart. But you had to standardize that into an electronic medical chart. And then we went to value-based pricing for medical services. Now, the doctor getting paid is completely dependent on what he wrote in the chart, complying with what they said they were going to put in the chart for what they said they did. So it was 20 years of developing and working through that on. And it had to be people at the center. The entire time, even though I wasn't calling it data governance, we were calling it digitizing the medical record for the 15 years that we did that. It was all governance work. And it was all working with, you cannot in the United States, you can't tell a physician how to practice medicine. So it was very conscientious about the verbiage is using and how we're saying, okay, we have to help you document so that the system recognizes that what you said you did, you did. And it opened my eyes. I love doing it. It was like the smallest part of what I was supposed to be doing for my entire career. Yeah. And I like a lot of people in healthcare, you get burned out on it because it is an entire career of banging your head against a wall. Yeah. Yeah. I understand. So when you're in, you know, you're in your late 40s and you're like, okay, I want to switch careers. And you're like, oh God, how am I going to switch careers? It took that really hard look at what did I love? Yeah. What did I love to do? And it was all data governance work. It was data. It was helping people be able to tell their story. So it was data visualization. It was all of that. And that's where I went out and pursued it. And I went into a field that environmental and sustainability, they're not at the point of being on medical charts, but they are in this journey. You're going to see my shadow of my dog jumping down behind me. They are in this journey of digitizing. They are pieces of the environmental field that is heavily digitized and they're pieces that aren't. So then putting that government in as well. Yeah. No, yeah. And that's so fascinating. And I love that. Because yeah, there is a lot of data governance, whether they call it that or not, in health care. Yeah. And I love that it became a passion of yours that you followed. So backing up even further, I mean, I know like when I wanted to grow up, I wanted to be Wonder Woman, maybe not really a realistic goal. I really wanted those bracelets though, you know that reflective bullets, right? It just seems to be the last one. Yeah, right. The last one. Yes. But so what was the dream? So let's back it up even further, you know, like, you know, before you got even got into health care, you know, what was the dream and what was the journey from there? I wasn't going to go into health care. I think that was just like coming into environmental data governance. Yeah. It was a quirk. So I was actually working on my master's and going through my PhD in sociology specifically studying social statistics and research methods. And I was, this was back in the mid-90s. So I knew it because up in the USA today, you know, everybody was reading the USA Today paper and telling them all the place and have all of these statistics in it. And it drove me bonkers that my cohort, my age group was going, well, this president like ability statistics says this, you can make a statistic say anything. It's anything. You didn't see a presentation. And so I literally wanted to go to teach so that there wouldn't be generations after me, they would look at statistics with a very eye instead of just absorbing. It was the first summer between my, so it was after my first year. And of course, you know, you have your teaching assistant and your research assistantships, but those only go during the school year. So then you have to figure out, you gotta earn a bunch of money in the summer to help pay for the next year. Right. And I took a temporary job in a medical facility in Cleveland. And I was sitting, I was worked as a secretary. And so I was working as a secretary and I was literally taking minutes in a medical director meeting. And this was truly when they were like the people 2000 with a goal of being able to measure the effectiveness of the physician. And it had not been done prior to that. There was no public information. All of these things that we have access to now didn't exist. And it was the goal was to try to encourage medical profession to get to those people 2000 dollars. And all of these medical directors are talking and they're basically, and it's of different strategies. And they're saying, well, you can't measure who a good doctor is. Now keep in mind, I've always been like this. So I'm supposed to be taking notes because I'm the secretary in the meeting. And I'm just sitting there. I said, I'm sure you can. It's whole room turns a look at me. It actually turned into my master's thesis. Oh wow. Because it truly what this was like a community health practice. It was multiple primary care specialties to get public dollars. They really had to be able to show their practice. And in that first conversation, I was asking questions about how do you, you guys know who a good doctor is because you know who you would send your mother to. We ask questions like that. We generate those kinds of things in our satisfactory surveys. We look at their statistics that you expect for being a good doctor. And we build those out of what they're documenting in their charts. And so it turned into my master's thesis. I never went back. I finished my master's. I didn't go finish my PhD. And I stayed in healthcare them for the next 20 years. Wow. Doing practical application of research methods. I truly was operationalizing how we do, you develop a good metric. In reality, I'm still doing it. What's the sustainability? What they're wanting us to develop governance for is how do I have a reliable metric that I am comfortable reporting to the public for my financial institute? I'm still doing it. That is super cool. I'll tell you later. This is, that is truly a journey of following your passion. Yes. That is really cool. And you've been really immersed in data since the beginning. I mean, going after statistical analysis and that's very impressive. I love that story. And I love that you spoke up. Like, you know... I haven't happened to doing that. You and me both. I think there's nothing wrong with that. Yeah, I agree. Yeah, well, look where I got you. Yeah, exactly. That is so cool that it turned, speaking up resulted in an idea for your thesis and started your career. Yes. That is really, really cool. And okay, and I have to pause because we at the University are huge animal fans. So when you got somebody talking there, I need to see the dog. She is. She's got a giant cone of shame. Oh. She is hugely allergic. She's on every allergy medicine and specialty food and she still has allergy reactions. So she wears a cone of shame. It is kind of like dolled it up for. Yes, there you go. Play later. It's a walk. Yeah, I understand. Schedules. Routines. So I apologize. It's hopefully that you can walk out the center of her garden. Oh gosh, you know what? This is the world we live in now, right? It is. Yes. So no worries at all. Again, we're huge animal fans here at the University. So yeah, absolutely. We all have animals. They often join our groups. They join a lot of mine. Everybody knows her name is Cindy. There's a big recliner behind me. And she'll like jump down. That's awesome. I love the name too. She is both of our dogs at rescues. And that's the name she came with. The only thing we know, I'm in Michigan and she came from Detroit. And the only thing she came with was the name Cindy. We don't know anything about her. But she's adorable. Absolutely. Oh, all right. Well, to continue our journey. Thank you for a little pause. Absolutely. Dougie pause is always appropriate. Very important. With a robust catalog of courses offered on demand and industry leading live online sessions throughout the year. The Dataversity Training Center is your launch pad for career success. Browse the complete catalog at training.dataversity.net and use code dbtalks for 20% off your purchase. So, so, so tell me, Lee, so. What. What was your biggest lesson so far in your career that you kind of take with you and, and, and maybe even. Advise, use to advise other people. Two important lessons. And I've just, I've mentioned both of them already. Don't be afraid to speak up. If you know what you're talking about, then talk about it. Yeah. And the second one is. Don't be afraid to walk away. I spent probably five years longer in healthcare. And I was truly good for my mental health in my physical health. I didn't, I should have left sooner, but I was. I bought into the, the. What else can I do this time? You know, 48 years old, I can't go to anywhere else. You can't transition at this age. I bought into all of that. And I, I got reached a point where I said, okay, no. I, I changed the verb into, I'm only 48 years old. Knowing myself, I'm going to work for at least another 20 years. And I'm not going to do it like this. Oh, I love that. You really. The inner dialogue. Yes. For yourself from negative to positive. That's hard. It's very difficult. It was, you go through. You go through the emotions. You're going to mourn. You walk away and mourn it. Set a limit on that. And then dig it. And the biggest way you can dig it is to figure out who you are. What makes you excited. Yeah. Yeah. Those are two great lessons. I'm really great advice. So. Tell me that. So how do you work with data so long? You know, what is your definition of data and, and how do you work with it? So my definition is going to be very broad. And it's, and out of necessity. If we broaden, if we use the definition of data where it is anything that helps you make an informed decision. Yeah. If I go to. What internal to my, my field. Internal to data governance. And or internal or external to clients. And I put it in that framework. What do you need to interact with to make informed decisions? Not. Just gut decisions, but informed decisions. It helps them to recognize data where they don't think of it as being big. And that's the biggest thing, especially in a field. Like I had to do it in healthcare. And I'm doing it in environmental is getting people to recognize what you're interacting with is all data. Which means it all needs to have standardization around it. And that's the biggest thing. It's very broad. I deliberately suck because it helps for me. It helps me to reach the people that go, oh, this is a data work. It is. And here's why. Yeah, that makes sense. Yeah. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. I like it. Yeah, that makes sense. Yeah. I like it a lot. So, you know, and we've talked a little bit already about how you, how you work with it and how you work with your clients with it. But, you know, so let me kind of move on to, you know, having been so immersed in data for so long. And through most of your career, even, even unintentionally in the past, you know, you've been so focused on the management and the number of jobs with data increasing or decreasing over the next 10 years. And why? Increasing. Definitely. And part of it is increasing because we are generating so much data. And we are, there's, if you watch on LinkedIn, especially if you like try to follow sustainability and data. There are more and more articles talking about the impact of all of the data that we're generating. So it's one of the things that we spoke a little bit about it. We're going to present, we're going to include, we're going to try to do another speak that'll be more focused on that. Yeah. And it's, I think that as we as humans focus more and more on the sustainability of our work and reducing carbon footprint, it isn't just, you know, we need to, okay, How do we, what do you think, how do we manage that? That's more of a challenge. So it doesn't, it's not just about the number of refineries. It's also when they were generating huge amounts of data that is stored somewhere. The cloud is actually a cloud. It is a server for software, which means it is having a global impact. So how do we actually get smart. About data, the way to get smart about data is to govern it. Think you get smart retention plans. You stick with the retention plans. think should be very obvious that there isn't a plan around to actually go through and find out, okay, where are you replicating data? And it's all over the place. Huge amount. Why is it being replicated? Oh, we just want to make sure we have a backup. Okay, that backup is generating towards your company's carbon footprint. So it's really necessary to have that backup. Or do you need to talk to IT so that you feel more comfortable about their methods of supporting your data? So I think we will see those, my two passions, the environmental impact and data getting closer and closer and getting more intertwined. I think that the fact that we now have this, the formalization of what are the different areas under data management and data governance allow us to then go to people going, okay, you don't have to be this quirky outgoing person, likely person to be in data governance. There's a role for all personalities. There's a role for all learning styles. There's a role for all communicating styles. And it is as broad as we want to make it. So it is going to keep increasing. And we're going to need generalists, which is what I tend to consider myself. I have a love for metadata just because it makes it easy for me to work with it. It's an easy thing for my clients to hang their hats on. I know a little bit about everything, which is how I can help them develop an overarching plan. And we're going to need specialists, those people that can go in and dig into, okay, where in your architecture have you redundancies that aren't needed? And put that under the guise of sustainability. Yeah, it's very, very true. So what advice would you give to people then who are looking to get in for data management for the first time with that broad spectrum? And like you say, it can fit so many different personalities. There's so many different aspects. So how do people explore that? My advice is actually it's what I literally tell everyone because we're talking about people in environmental and ERM, they come into data from other parts of the environmental world. So we've got geologists, we've got biologists, we've got all of these and engineers, and those are who become our data people in the environmental world. And so they want to know how do I get the verbiage for the way my brain works? And I literally, they're not paying me for this, I pointed with the data diversity. You need to go there because you can get the broad spectrum. You can sit there and I said, and you can do do internal ground back lunches using their webinars. It's going to give you the spectrum of look at everything and then be honest with yourself about what of those intrigued you and then pursue it and go drill deeper and learn more. Yeah, I promise we did not pay you to say that. It warms my heart. Because you could ask anyone that I talk to at ERM, I'm constantly pointing them to go to data diversity. That's where you find the broad spectrum that's where you can drill down, you can follow these learning paths and you can get to what is my niche part of the data world. Oh, very cool. Oh, thank you for that. We're doing something right. Yes, yes, you are awesome. Well, Lee, this has been amazing. Anything else you want to add? Just that I love that you guys are doing this topic for a podcast. This is my first podcast ever. I typically don't hit. I love talking to individuals like it really nervous talking to groups. You picked a topic that is near and dear to my heart, so it's going to pull me in. Thank you. Please consider doing more topics like this. I think it's very important, especially as we're looking at, there's a huge younger generation coming up behind us, and there isn't a lot of mentoring and informal mentoring, any of that going on for them, and they're basically coming out of college and they're being thrown in the deep end. These kind of podcasts help to point and give guidance, and that is something that I'm passionate about, is that your career is supposed to be the support for your life. So let's give you all of the information that I've attained in my 53 years open book, whatever you need. I love that, Leigh. That is so lovely. It's one thing that I'm hearing repeatedly about people who have been successful in data and nobody made it on their own. It's having mentors, having, building those relationships, learning, taking the time to learn. I can still remember at 28 years old, someone asked me, okay, because I had started so what, how did you, how were you successful? How did you turn a son? I said, find a mentor, and they literally laugh. Now, I'm not joking. Right. Yeah. Find someone that is doing what looks interesting to you and pass them about it. Yeah. We have to talk about ourselves. They're going to answer you. It's true. So many people are so more willing to talk about and help people than you think. I know I've been afraid to approach people before, but when I have, they were willing to open up. Yes. And I think it is something that my generation of women, we are definitely passing on the knowledge of, okay, you don't have to be superwoman, you don't submit, that you don't have to be everything and how a lot of conversation, a lot of mentor conversations around work-life balance. Is that a myth? How do you actually do it? And how do you actually maintain it over the course of your work life? Is it okay to want to work? Yes. Right. Is it okay to not want to work? Yes. It's all okay. It's all okay. It's so very true. I heard I worked for Microsoft for a while and they had a women's event and one of the VPs came in and said, people often talk about work-life balance and tell me that I work too much. She's like, but I love what I do. So I feel like my life is balanced because work is not separate from life. It's part of it. Yes. Exactly. And that's what we have to be sure to possess. I think one thing that happened to my generation and women, probably a generation younger than me, is we saw these women doing all of that work. We never asked them and we assumed that's what we had to do to succeed. And it wasn't until we thought to, okay, now we're the senior level and we're going, oh, I didn't have to do it. I really didn't. It was, what is my passion? My passion will lead me to do it more and want to be in that place. So follow that road and then work as an a burden, learning the new things, keeping your knowledge up isn't a drag or a burden or something you have to do. It's something you want to do. Yeah. Exactly. My other thing that I would encourage and it could be because I'm a very people-y governance person is recognize that your creativity is needed in the data world. Yeah. The data world is not, as much as we talk about statistics and predictiveness and correlations and being able to visualize and being able to organize, you have to come up to put things into an operational world. You have to be creative about how they will interact with humans. Find your creativity and let it come into your work. Such good advice. Oh, Lee, this has been such a pleasure to chat with you today. I really like your story. I really like the lessons that you bring to it and great advice for those coming into any career, really. Exactly. Yeah. So I would be remiss if I didn't ask, you know, if somebody wanted to solicit the services of ERM, where would they go? The erm.com is our website, but you can also find me on LinkedIn. You can find ERM on LinkedIn and that's probably a really good place to go. And I'll make sure that I'd link to this podcast so that if anybody wants to find me, they can go straight to that link. Perfect. And we'll grab those links from you too and post them on the podcast website. Thank you. Lee, thank you again so much for taking the time to chat with us today. You're welcome. And for all of our listeners out there, if you'd like to come up today on the latest podcast and the latest in data management education, you may go to dataversity.net forward slash subscribe. Until next time. Thank you for listening to Dataversity Talks, a podcast brought to you by Dataversity. 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