 Hello and welcome to Dataversity Talks, a podcast where we discuss with industry leaders and experts how they have built their careers around data. I'm your host, Shannon Kemba, and today we're talking to Lauren Mifeo, a service designer at Steampunk, an author of a recently published book, Designing Data Governance from the Ground Up. With a robust catalog of courses offered on demand and industry-leading live online sessions throughout the year, the Dataversity Training Center is your launchpad for career success. Browse the complete catalog at training.datavercity.net and use code DBTOX for 20% off your purchase. Hello and welcome. My name is Shannon Kemba, and I'm the Chief Digital Officer at Dataversity, and this is my career in data at 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. And today we are joined by Lauren Mifeo, a service designer at Steampunk, member of the editorial board of Springer AI and Ethics, adjunct lecture on interaction design at the George Washington University and author of the recently published book Designing Data Governance from the Crown Up. 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. Lauren, hello and welcome. Hi, Shannon. Thanks so much for having me. I'm excited to be here. Likewise. So, so many titles. It's amazing. I love it. So let's start with service designer at Steampunk. What is Steampunk and what is it that you do there? Those are great questions. I get them a lot. Steampunk is a human-centered design firm serving the federal government. So we work on everything from Salesforce implementations and database interface redesigns to website migrations and service model implementations. So we work on technical projects for federal government agencies in the US, but we take a human-centered design approach to that, meaning that we try to have designers on every project to make sure that whatever we build is in service to real users of the products that we are building and redesigning. And so I am a service designer, which means that I am basically the user advocate on any team that I join. I'm responsible for everything from writing the research plan for the project to selecting which users I should interview. I'll host various types of workshops with clients and stakeholders to help them talk through their challenges and figure out how we can solve them. Once I've done my user interviews, I will create design assets ranging from personas to journey maps to service blueprints showing how users engage with products and services today versus how they might be able to do so more effectively in the future. And then ultimately I work with engineers and architects to figure out what we should build that's going to help solve those user challenges. Oh, very nice. So you're also a member of the editorial board at Springer's AI and Ethics and Adjunct Lecture on Interaction Design. So tell me about those two roles. Yeah, those are both fairly new. I joined the founding editorial board of AI and Ethics in the summer of 2020. So COVID was still raging and in-person networking was still impossible. And I saw that Springer was standing up a new peer reviewed editorial journal devoted to the academic study of AI and Ethics. And so I reached out and was able to join the founding editorial board. So my main role in that capacity involves reviewing manuscripts when authors submit new articles and op-eds to the journal. I'm part of the peer review process which reads the articles and evaluates them, gives feedback on whether they are ready for publication in the journal. And then on top of that, I also do teach a course in interaction design at the George Washington University here in DC where I live. And I'm part of the Corcoran College of Arts and Sciences here. I teach a course on interaction design for graduate students where we focus on really the human computer interaction part of design. So we really take the lens that tech is existing to do a particular job and it needs to do that job for particular types of users. And so we focus actually less on the mechanics of design in and of itself and more on how you can use user feedback and human centered approaches to really design solutions and products that meet very particular needs. My students are currently doing their capstone projects and we have about two more classes until the end of the semester when they will present their projects and portfolios. And I just started adjunct lecturing this past semester after wanting to do it for a few years. And it's been a really awesome addition to my work at Steampunk. And it's been great to help guide people at the graduate level through their design studies. That's amazing. I love that. So and you've recently published a book we'll get into what the why I think a little bit later but tell me about the book designing data governance from the ground up. Yeah, so I was inspired to write this book after working with some clients for several companies for several years, who were very intent on being tech savvy they heard all the hype about AI machine learning they wanted to use it in their own organizations. But the challenge that I first discovered in my prior role, when I was an analyst at Gartner was that most organizations today have very low levels of data maturity, which means that they don't have good habits when it comes to accounting for data quality. Many of them don't do data lineage tracking they don't have business glossaries which classify technical versus business metadata. All of this contributes to the fact that most machine learning algorithms once deployed are not successful and only 13%, about 13% reach production at all. So I saw very quickly that a lot of time money and human labor was being wasted on these non strategic initiatives that were just chasing the tech. And so then when I got to the design career that I have now I and I started working with clients more it more directly I quickly saw that many of them again lacked any automation, their processes took days to complete the integration involved two to three people that were doing this by hand, and that led me to realize that even when organizations exist to disseminate data, they often lack the backbone of a strong data governance program and framework to really account for the quality of data and then the reality is if you don't have that backbone of data governance established you won't be able to do any of the fun stuff when it comes to data. And that's the best case scenario the worst case scenario is that you could be involved in a data breach, you could not use PII masking when you're supposed to you could have duplicate data stored on several servers. And so that's where I got the idea to write this book, it is an intentionally short book it's a 100 page six step guide to getting your first data governance program off the ground. And it's short because there's a lot of nuance when we're talking about data governance depending on which software you use which cloud environment you're in. There are a lot of nuances to account for when it comes to what governance looks like for you, but the book does cover what, in my opinion, every organization should be doing at bare minimum to get their own data governance program up and running. I love that I love that it was born from issues, especially surrounding machine learning. We've heard so many companies run into the same problem they tried to stand it up but didn't have the quality processes in place. I didn't do enough user research and I do think I mean I'm biased as a designer in thinking that design should have a seat at the table in this process but I see so clearly how not accounting for user roles not not doing user interviews to figure out how people use different cloud environments not figuring out how to, you know, hook hook systems up properly and integrate them the right way. All of this contributes to technical environments that just don't serve their users they don't serve the people consuming the data outside of your organization but they also don't serve your primary users which in this case could be your colleagues who are tasked with using those environments and so I think taking a design thinking approach to data governance is very underutilized and I do think it's an important reshifting because data governance is often thought of purely as compliance or purely on the technical side of the house but the reality is that your culture determines which tech you use or not. And so I really think that reframing it as a design challenge and applying some principles there can reshift the conversation and make it more user friendly for everyone involved. Very nice. So, let's back up a bit. So, when you were very young in elementary school, was this the dream I, you know, I'm going to be at a service designer when I grow up. I'm going to write a book on data governance. I don't know. So I did not know what any of those words were until about maybe five years ago, a little longer than that but but I this is not a career that I think you grow up want knowing about and that's part of the reason I was really interested in this podcast at all is because I for the longest time didn't even know what a service designer is and I still to this day. I cannot say I'm a service designer without any getting the question oh what's that so because it's a very misunderstood role. It's very similar to either a product manager or a product designer depending on what the person does. I do tend to design digital services and so I'm more similar to a product designer that way, but I did not grow up wanting to be a service designer. However, I did grow up wanting to be a journalist and I really liked speaking to people and asking and figuring out what the right questions were to get the answers I needed. And I liked hearing different perspectives on various topics and that is a big part of what a service designer does because you are on your team to be the user advocate and be a voice for their collective needs. And to make sure that those needs are included and accounted for in higher level conversations about what gets built. And so that is a job that I take very seriously and I am pretty convinced that journalism and a background in that is ideal training and service design, because I think the, for all the talk about being user centered. It's very easy depending on the context for user needs to get pushed by the wayside or deep prioritize my job is to make sure that that doesn't happen and so I do feel like I found another outlet to do what I enjoyed so much about journalism in that way that I did always writing a book I never thought that it was going to be on this particular subject, but I did want to do that and I think and I so the facts that I've been able to do it has been a real privilege and it's been really exciting. It's it's really something to get the book in your hands, once it's all said and done. So, you know, original goals morph, even though they've changed like from the time that your original dream right with of journalism, those dreams still get that that passion still gets built into what you eventually end up doing which is just fabulous. So you want to be a journalist. Is that what you just decided to study or how do you transition and tell me a bit about your career path. It was so I went into college very clear on wanting to pursue a journalism career I had already done a few internships in high school at local TV stations and I knew that I wanted to work in broadcasting. I always had a natural aptitude for an interest in writing and I was not math and science oriented, which is part of why it's very ironic that I ended up in tech working with data, because I did not I saw myself very much as a liberal arts student to the exclusion of stem subjects, I went to college in a large city with the intention of doing as many internships as I could and launching a career in new TV news. I did do some radio reporting in college and then when I went to graduate school and then completed graduate school, I did freelance journal, I what did work as a freelance journalist for a year. I worked as a I covered the tech and startup scene in Europe I had gone to graduate school in London, and I stayed for an extra year to launch my career and Europe's tech sector at the time was small but rapidly growing. So I was able to get in through some connections and I didn't care about which beat I covered I just wanted experience getting clips for my portfolio. I quickly realized that I was actually really interested in entrepreneurship and tech, and my job was not to know everything about it it was to find the people who did know a lot about it, and asked them the right questions so I quickly figured out that this was a subject that I was interested in. I also became a parent that the global news industry was not going to provide the stable career that I really felt like I needed it became a parent I was not going to be able to do very basic things like a 401k plan save for retirement, all of those things and so I had to do some serious soul searching earlier in my career to figure out if it was going to really be worth it, and then what I decided was to actually try joining the sector. So I went and joined a set Silicon Valley based startup as a marketing specialist, and then I transitioned to working as a research analyst at Gardner, which is a fortune 500 research and advisory firm focused on tech. And then I transitioned to steampunk so that's cut in a nutshell how I got from a to be, it is certainly not what I expected to do, but I have found the user research aspect of design to be a really fascinating fit and a great outlet for someone with a journalism background I still am adamant that we need journalists and great journalists more than ever, but, and I'm not opposed actually in my later years to maybe going back into that career if I have saved enough, but I think the fact that that's my attitude to the state of the industry today the fact that I would really need a solid nest egg to be able to afford to do that type of work and so there's that's a totally different conversation. I love the path I love the transition and and how you got into tech. It's it I agree it's I mean it's so important. I did a brief stint as a as a freelance writer myself so it's it's interesting work and I loved it's great work I loved doing it. I mean it was not about get not having passion for the work I was very interested in it, but it became clear very early on with the rates I was getting with the rate of work coming in it was just not going to be sustainable. And yes I could have moved to a much cheaper area because London's very expensive but that the reality is the supply of people who want to do those jobs far exceeded the demand and this was 10 years ago so and things are no better now they're only getting worse so. So tell me a little bit about your time at Gartner our community certainly is familiar with Gartner and and what they do so what were you doing at Gartner. I was in a really unique part of Gartner, which is called Gartner digital markets and GDM was actually combined. So Gartner acquired three startups that were in the same market effectively in competition with each other, so it acquired all three startups kept Tara software advice and get up to, and these were all websites that helped startups small business owners find the right software to help grow their businesses and Gartner had always focused on the enterprise they mostly served companies with 500 employees at least and above to help them make the right technology choices for their businesses and so GDM was really their first for a into the small business market. So as a result of that they hired editors and analysts and writers to cover the technology sector for small business owners and entrepreneurs. So I spent four years there, mostly specializing at first in project management and accounting software and covering different features and functionalities of those types of cloud software products. And those were not my passion and so and about two years into my time at Gartner I started reading more about the this AI boom that was happening and specifically the different types of AI technologies that were coming to market in a more drastic way, everything from natural language processing to machine learning to facial recognition. And that was where that I really got my interest peaks that was where I found something that I was really interested in diving into in more detail. I transitioned from covering project management and accounting software to business intelligence software. So I would cut I would do things like cover the different features and functionalities of various tools from Microsoft Power BI to Tableau. I also co wrote papers talking about different things like semantic analysis and chat bots, different different things that folks should be aware of when it comes to accounting for bias I wrote a few I co authored a few Gardner research notes on cool features in different spaces like speech and natural language processing. And so it was a really interesting space to be in, because Gartner's job is to be at the forefront of technology advising clients and readers on what they should be working in versus what they should be skeptical of. So for someone like me who loves to read and loves to absorb a lot of information that was a really ideal job. And I think that that experience has really served me well. And it was also, like I mentioned a really interesting part of Gartner to be in because it really had that startup small business feel within this larger Fortune 500 company. 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 dji q 2023 West dot university dot net lock in early bird savings when you register by May 5. We'll see you there. I love it. And then. And then from there you went to steampunk where you are now. Yes, and I've been steampunk since 2020. Nice. So, what then is your definition of data and how do you work with it. That's a that's a great question. I would say data is a point of information. That's the best way I can think of to describe it and I do think it's an important description because everybody has their own ideas about what data is about what governance is. You have to, I think, start any conversation about those topics by defining what you mean. And so I would say that data is a point of information and so that can be anything from your birthday to your social security number to your city that you live in. It can be anything, but it's a it's a piece of it's a point of information and and taken out of it can be used in many contexts that's the other thing is that data in and of itself is not valuable or helpful that's something that I say in the book because there's all this about the volume of data being produced and the implant the implication is that it's valuable on its own and that's actually not the case at all. It can left unchecked be actually a huge liability for businesses and I think and it can be far from helpful if you don't have that data within its proper context and so I think that's also a really important point when it comes to governance. That's pretty much so. Now, and especially since you work so closely with AI and, you know, how do you see and this kind of this crosses a point of contention, you know, do you see the importance of data management and the number of jobs working with data, increasing or decreasing over the next 10 years this AI going to you know get rid of our jobs you know what's that what's happening there you know and why. I want to see a rise in the number of data specific roles, because I think it's becoming very clear that the volume of data being produced today is way too overwhelming for one person to handle the past I think if you talk to any diet data or a dentist or chief data officer they will tell you that over the past decade, people have tried to just give them any and all data in their organization for them to figure out what to do with it. They will also probably tell you that they spend the vast majority of their time clean cleaning spreadsheets and data to get it ready for production, they will then they don't spend as much time building the fun models that they're sold as the cool job. And, but I think we're even seeing now that in this cost cutting period we're in an emphasis on business value and I don't think that in and of itself is a bad thing because I think there has been kind of carte blanche over the last decade to throw money at people who have these very particular skills, assuming that just because they have the data science title, and the company has a lot of data that there will naturally be synergy to use business jargon. And the reality is, if you don't have data governance established if you don't have quality standards if you don't have a strategy for which data you are going to use for which business use cases. All of it falls apart and you would be shocked at how few organizations have that you'd be shocked at how many she faded data officers either do not have a strategy for how to connect particular data pieces to particular business problems, or how many are not given the resources to execute that strategy that they're responsible for. And so I think we are going to see an increase in investment in roles devoted to managing data, especially when it comes to AI, because the sector as we as evidenced by chat with this popularity is growing in spurts that get that are very large and sudden, and that's going to trigger a lot of jobs. That does not mean I don't think that it inherently there's going to be more value created or that those jobs will even last over the long haul but I do think that there is going to be increasing demand for people who understand how to work with data and that's another thing that I cover in the book is this idea that we really need to move away from data management as being the sole responsibility of the chief data officer or the data scientist team or the data engineers, we need to equip everyone in an organization to understand the very basics of data governance and what that looks like for the data in their domains. And that is something that is still very new. It's still something that not a lot of people are willing to invest in, but I think 10 years from now, people are going to have no choice because there is going to be officially too much data, and it's going to be too big a role in everyone else's job that you are going to have to know the basics of it. That's a great point indeed, very important. Yeah, I wouldn't disagree with that. So if somebody's looking to get into a career in data management and maybe a service designer what advice would you give, you know you mentioned that you know we need more journalists, you know, more more of that skill set. And what advice. So how would they get into that kind of career. I think ultimately the biggest skill you can have to have a good career in data is to know how to ask the right questions and be really interested in the business that you're serving and the people who run that business and the reason I emphasize all of that is because ultimately again the data scientist job is to create value for the business using data, the data it possesses, and they can't do that we can't provide value if we don't know who we're serving and who our users are. And so this is and this is something that constantly comes up because certain people just want you to take the latest framework or technology and run with it and implement it, and you'll do all the data governance stuff later and the user interviews and design design later, I have heard will do design later more often in my career than I would like to count. And it's and I really think at the end of the day, whether you are on a designer path or a data science path you do have to understand very clearly who your users are what they need from you, and then how to design a model or a service or a product in such a way that it fulfills those needs, and that really comes down to asking the right questions and knowing who you need to ask those questions of. It's really good advice is there a question that you find that is commonly missed from people is there like a couple or one or two good questions that you should ask. I think the framing of those questions is really important so you want I think you want to stay away from questions that could elicit a yes or no answer because though and that can happen a lot especially if you're working with people who are a little more introverted they might have more technical roles like if you're working with scientists or statisticians and they, they get a little cagey or about the conversation you're having. You want to steer away from, from anything that could elicit a very simple response that cuts off the dialogue you instead want to say things like how do you, how do you fulfill X function or tell me about your process doing, doing xyz or what did you, what did you, what, what makes you frustrated at your current job or using this system you want to use words like how, when, what, who those types of things as opposed to do you fulfill xyz because then that's a yes or no question. And you really want to get when you're having a user conversation as open ended feedback as possible. I also think it's important to keep that feedback confidential where possible. This is especially important for political reasons if you're interviewing colleagues of your client. And then on top of that I think it's really important that you're if you're building personas or user roles. It's really important for those personas and roles to be informed by conversations you've had with real users. There's a pretty big backlash in the design community now against personas because they are often unvalidated archetypes of particular users that are not based on anything but assumptions and stereotypes. And in design, we say that everything is an assumption until you test it. So you put together, you can put together, you know, a low fidelity prototype or mockup based on what you know, but then your job is to validate those assumptions with the right people to make sure that you are on the right track. And so I also think that one important piece of doing these user interviews is that you always want to make sure that they are not happening in and of themselves that they are informing personas but that they are also accurate and informed the personas are informed by real conversations with real users. It's great advice. That's really helpful. I think I'm going to definitely mentally taking notes there. You need to go back and listen and take notes. Well, and recording them and recording those conversations is also really helpful because that you're just not going when you're leading the conversation you're not going to remember everything that they tell you, you certainly I mean I know people try to take notes and listen. You can't do it well. And so it's important to record with permission and then get a transcription so that you can go back and hear everything and it also gives you a record of the conversation. Very good advice and definitely speaks to your journalist background. It really is a great match that way because I think and I think that's also valuable advice because I was very, you know, sad to be honest when I realized I wasn't going to have that journalism career the way I wanted but then when I unpacked what I really enjoyed about it. It was the opportunity to ask questions of various people to uncover real the root of problems to add to make sure that I was telling the store inaccurate story about the way someone uses a product and so those aspects of the job that I enjoyed are things that I am still able to fulfill, even though I don't have that career that I initially envisioned and so I do think that's something that's important to consider. Well, Lauren, well we're so excited to have you in the data space. Speaking of you know how do people solicit services from steampunk how do they you know connect with you and most importantly how do they find your book. So you can find my book by going to Prague Prague calm. That is the name of the publisher. And so if people go to Prague Prague calm they will find the book there. But you can also buy designing data governance from the ground up from any online book retailer barns noble target Amazon local book shops have it as well so if your local bookstore has it I would love for people to order it from there. I would love for people on all readers and kindles as well. If folks want to get in touch with steampunk they can go to steampunk calm and learn more about us and our services there. And then I am also available on LinkedIn if people want to connect and learn more. I love it, and we'll get those links for me I make sure they're posted on the podcast page as well so people can easily click on them. Thank you. Well, Lauren, thank you so much for taking the time to chat with us today. Thank you so much for having me this was really great and I hope it was the first of many conversations. I agree yeah and to all of our listeners out there. If you'd like to come up to date and latest in podcasts and the latest in data management education you go may go to data varsity net four slash subscribe until next time. Thank you for listening to data varsity talks brought to you by data varsity subscribe to our newsletter for podcast updates and information about our free educational articles blogs and webinars at data varsity net forward slash subscribe.