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Leading Enterprise Data Teams

Posted Apr 26, 2024 | Views 192
# Enterprise Data Teams
# Leadership
# ExecutiveAI
Sol Rashidi
Sol Rashidi
Sol Rashidi
CEO and Founder @ ExecutiveAI

With eight (8) patents granted, 21 filed, and received awards that include: "Top 100 AI People" 2023 "The Top 75 Innovators of 2023" "Top 65 Most Influential Women in 2023" "Forbes AI Maverick of the 21st Century" 2022 “Top 10 Global Women in AI & Data”, 2023 "Top AI 100 Award", 2023 “50 Most Powerful Women in Tech”, 2022 “Global 100 Power List” - 2021, 2022, 2023 “Top 20 CDOs Globally” - 2022 "Chief Analytics Officer of the Year" - 2022 "Isomer Innovators of the Year" - 2021, 2022, 2023 "Top 100 Innovators in Data & Analytics” - 2020, 2021, 2022, 2023 "Top 100 Women in Business" - 2022

Sol is an energetic business executive and a goal-oriented technologist, skilled at coupling her technical acumen with story-telling abilities to articulate business value with both startups and Fortune 100's who are leaning into data, AI, and technology as a competitive advantage while wanting to preserve the legacy in which they were founded upon. Sol has served as a C-Suite member across several Fortune 100 & Fortune 500 companies including:

Chief Analytics Officer - Estee Lauder Chief Data & Analytics Officer - Merck Pharmaceuticals EVP, Chief Data Officer - Sony Music Chief Data & AI Officer - Royal Caribbean Cruise Lines Sr. Partner leading the Digital & Innovation Practice- Ernsty & Young Partner leading Watson Go-To-Market & Commercialization - IBM

Sol now serves as the CEO of ExecutiveAI LLC. A company dedicated to democratizing Artificial Intelligence for Humanity and is considered an outstanding and influential business leader who is influencing the space traveling the world as a keynote speaker, and serving as the bridge between established Gen1.0 markets and those evolving into 4.0.

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With eight (8) patents granted, 21 filed, and received awards that include: "Top 100 AI People" 2023 "The Top 75 Innovators of 2023" "Top 65 Most Influential Women in 2023" "Forbes AI Maverick of the 21st Century" 2022 “Top 10 Global Women in AI & Data”, 2023 "Top AI 100 Award", 2023 “50 Most Powerful Women in Tech”, 2022 “Global 100 Power List” - 2021, 2022, 2023 “Top 20 CDOs Globally” - 2022 "Chief Analytics Officer of the Year" - 2022 "Isomer Innovators of the Year" - 2021, 2022, 2023 "Top 100 Innovators in Data & Analytics” - 2020, 2021, 2022, 2023 "Top 100 Women in Business" - 2022

Sol is an energetic business executive and a goal-oriented technologist, skilled at coupling her technical acumen with story-telling abilities to articulate business value with both startups and Fortune 100's who are leaning into data, AI, and technology as a competitive advantage while wanting to preserve the legacy in which they were founded upon. Sol has served as a C-Suite member across several Fortune 100 & Fortune 500 companies including:

Chief Analytics Officer - Estee Lauder Chief Data & Analytics Officer - Merck Pharmaceuticals EVP, Chief Data Officer - Sony Music Chief Data & AI Officer - Royal Caribbean Cruise Lines Sr. Partner leading the Digital & Innovation Practice- Ernsty & Young Partner leading Watson Go-To-Market & Commercialization - IBM

Sol now serves as the CEO of ExecutiveAI LLC. A company dedicated to democratizing Artificial Intelligence for Humanity and is considered an outstanding and influential business leader who is influencing the space traveling the world as a keynote speaker, and serving as the bridge between established Gen1.0 markets and those evolving into 4.0.

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Demetrios Brinkmann
Demetrios Brinkmann
Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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In the dynamic landscape of MLOps and data leadership, Sol shares invaluable insights on building successful teams and driving impactful projects. In this podcast episode, Sol delves into the importance of prioritizing relationships, introduces a pragmatic "Wrong Use Cases Formula" to streamline project prioritization, and emphasizes the critical role of effective communication in data leadership. Her wealth of experience and practical advice provides a roadmap for navigating the complexities of MLOps and leading data-driven initiatives to success.

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Join us at our first in-person conference on June 25 all about AI Quality:

Sol Rashidi 00:00:00: Hey everyone, my name is Sol Rashidi. I'm a former slash recovering C suite executive who's not in transition, but I've definitely started my own company, doing my own thing, speaking, advising, writing. I got a book out which has done well. Super happy about that. I am so excited to be here and Demetrios asked me how I like my coffee. All black, no b's, no fillers, no nonsense, just straight black. Get to the point and give me that caffeine rush so I can keep doing good shit.

Demetrios 00:00:33: What is happening folks? Welcome back good people to the ML Ups community podcast. If you don't know soul, I highly encourage you to check out her newsletter and or buy her book, your survival Guide to AI, because it is an absolute gem. Leave a link to it in the description. She has so much experience leading data teams. I mean, one thing that she said was that the size of the teams have been anywhere from 120 people to 834, which is absolutely insane to me. 834 people. So she talked about what she does to make sure that the decisions and the initiatives that they are taking when she goes into a company are the right ones. She also mentioned how to stay out of perpetual Poc purgatory.

Demetrios 00:01:29: I think if she did not coin that term, she should because it is incredible. I love that term, perpetual poc purgatory. Hopefully you have not been on a team that has been stuck in that purgatory. I gave her a bit of a multiple choice answer or question that she could answer. It was all around what's the most important thing for you when it comes to building these teams and going out there and gaining influence in the workplace? And she said, without a doubt, relationships are paramount. It's relationships building those relationships, cultivating those relationships above all else. So this one's gonna stay with me for a long time. I know it already.

Demetrios 00:02:17: If you like and enjoy it, leave us a review, drop in some stars on Spotify and let's get into this conversation with Sol by her book. If you do not have it already, talk about the wrong use cases for AI. What have you been seeing out there?

Sol Rashidi 00:02:39: You know, I think everyone in general, and whether you're running use cases for a data product, data ecosystem, AI, everyone has this notion of like let's pick use cases based off of business value. I don't know how other people's have done their job, but like, my job as sort of the CDo Cao CD AIO or whatever CXO title you want to be has always been to support supply chain manufacturing. The brands the label. So, like, the business that runs the P and L and also the functions, and they all are, like, fatigued or plagued with a problem that they want fixed. And I kind of get stuck in this position where my team is yay, so big, my capex is yay, so large, I can only put so many individuals on a certain project. And quite frankly, if they've brought it to my attention, all of it has business value. And so, for me, it's been really hard to pick use cases based on business value. And I stopped doing that because I actually unconsequentially made enemies along the way where I had to prioritize things.

Sol Rashidi 00:03:37: So I would pick one business's problem over another business, right? Pick one functions problem over another, and people just don't like their shit being deprioritized. Part of my French. So I was like, business value is not the way to go about this, because what's business value to manufacturing is different than what's business value to supply chain, which is different than procurement, HR, brand X, brand Y, region Y, market B. And so I have this formula that I created, and it's complexity versus criticality. And I created this at IBM when I was like, yay, here to all the work that I had to do for everyone. And it's applied in everyone in my c suite position, and it helps me just sift through the clutter, prioritize in a way that's both qualitative and quantitative. And then there is a method to the madness. So if people disagree, it's not a problem, but they can fundamentally understand why we came to the conclusion that we came to.

Sol Rashidi 00:04:34: And so the criticality of it is, how critical is it for the business? I understand it's a pain point for you, and I understand that something you've been plagued with, but, um, is there a fine or regulation that's been set our way, and are we in trouble? Is there a massive competitive threat? Do we have excess inventory, for example, that's about to go stale, or the shelf life's about to expire? Is there a new product launch where we've invested a ton and we're not able to see the consumer acquisition numbers that we're like, what is it that makes it so critical? And then you fundamentally grade it based on these questions, and it naturally gets its own score. But then there's the complexity side of it, the complexity to deploy. Do we have the basic infrastructure to even be able to move something? Do we have the data? And is it accessible? Or am I going to have to go through this massive data ecosystem around cleansing and hygiene and accessibility and quality and et cetera, or is it ready to go? Do the people I need involved in the project, are they even available? Because you find that in a lot of organizations, they're really smart ones are on multiple projects, and so they tend to be spread really, really thin. Are those folks even around? And so there's a series of five to seven questions that I ask on complexity. So everything gets a weight and everything gets a score. And I have this quadrant where on the x axis, I mark you against. How critical is it to the organization? And on the complexity score, how complex is it to deploy? If it's highly complex and low criticality, it's a non starter. I'm not doing it.

Demetrios 00:06:05: Get it out of there.

Sol Rashidi 00:06:06: If it is low complexity and highly critical, we're prioritizing you, because I know I can actually execute on it and I can do so with the resources I have. So I do this every quarter and I plot everything because, as you know, things always come up. So even if you set your strategic initiatives for the year, or you've got your projects that you want to run personally, professionally, for your startup, for your vc, um, you do your yearly planning based on that method, and then I update it every quarterly. And I always communicate what's being prioritized so that people know what's in the bucket and what's not in the bucket. And if things need to change, then they got to go up higher in the food chain for me to prioritize stuff, but it neutralizes the playing field. So back to your question, or what are the wrong use cases? I think a lot of people choose business value. That's great. But if you only use business value as your marker, so let's say criticality but not complexity, that's where a lot of companies get into trouble and they get stuck into perpetual POC purgatory.

Sol Rashidi 00:07:05: You have a lot of AI use cases that are just in POC mode, and they're wondering why they even have a hard time shifting things into production. And the reason they have a hard time is because they don't even have the basic infrastructure. They can't even calculate the cost of workloads to be able to push something in POC. Could you imagine pushing it into production? Or they've got your classic DevOps mechanisms in place, but they don't have mlops or DevOps for AI, which is totally different, because when you push, when you do software development, you push a piece of code into production, it is static. Once that code is containerized and it lives in the ether, it's alive and well. That's not how it works with AI. It is a live wire. It's a live stream.

Sol Rashidi 00:07:47: You're only as good as your last piece of information. So building data pipelines and the intricacies associated with that, the orchestration of data being fed into the ops and then managing the security protocol, it's just a different beast. And people aren't prepared for that. So I always say, if you have the maturity, great. If not, you have to take complexity into consideration to see what's realistic or not to get out of that PoC perpetual, or perpetual Poc purgatory, where most folks are.

Demetrios 00:08:15: Great term, by the way. That is the three p's.

Sol Rashidi 00:08:19: The three p's. Get out of the three p's. Pick a use case you can actually deploy. Um, I was recently on a client side because I'm advising now, and one of the major management consulting firms had done a strategy. There were like twelve use cases and they're like, we don't know where to start. I was like, well, I'm going to ask you a series of questions. And after I did, I was like, nine of these twelve you can't even do. I'm like, you won't even be able to soft launch this stuff because you're missing this and you're missing this and you're missing this.

Sol Rashidi 00:08:47: And I'm like, so I would even consider it. So the answer is these three. It's kind of easy. And like, they were pissed off that they paid nearly a million dollars for this ax strategy for use cases they wouldn't even be able to. Yeah, launch. It's kind of funny.

Demetrios 00:09:02: All right, we're analyzing a quarter later. We thought this was going to be done in a quarter, or we thought this was going to be done two quarters ago.

Sol Rashidi 00:09:09: Yeah.

Demetrios 00:09:09: And it still is happening. It's really hard for us to say stop now because it feels like it's just around the corner, but you know that, like, maybe in, in your heart of hearts, it potentially isn't going to be finished this quarter either.

Sol Rashidi 00:09:26: I think there's two key decisions you have to make. Call the shelf life or reassess and do better forecasting the shelf life. I learned, oddly enough, like, through an experience I had playing college sports. You know, I was a great high school athlete, and I played water polo for a division one school, and I was like, second string to second string. I was still training 6 hours a day, and I was working my ass off, and I talked to my coach, moe, and I'm like, am I ever going to get in the water? I played water polo. And she's like, listen, I love your tenacity. I love your effort, but, you know, the girls are 510. You're like, five three on a good day.

Sol Rashidi 00:10:06: And, like, you can make up a certain portion of it with power, but you're just not naturally built to be professional at the sport. So you got to make a choice. You want to keep swimming 6 hours a day and train with the team, or do you want to move on to other things? So I was like, I'm not a quitter, but this is point of diminishing returns. I was like, maybe I'll just refocus on academics. I'll just be, you know, a professional student. And then randomly, a week later, I got recruited by the rugby team.

Demetrios 00:10:32: She.

Sol Rashidi 00:10:33: She tapped me on the shoulder. Kathy. And Kathy's like, do you ever play a sport? I was like, yeah. Until a week ago, I was playing waterfall. She's like, have you ever tried rugby? And I was like, what on earth is rugby? And she's like, well, it's kind of like football without pads. And I'm like, whoa, whoa, whoa. Why would women play this? We just are built for this. She's like, I just have a feeling you're going to be natural at it.

Sol Rashidi 00:10:51: Well, I had great ball handling skills because what you do, treading in water. I now had land. What was a deficiency in water polo, which was I was short, was a strength in rugby because I was five three, lower center, gravity, harder to tackle. By calling my shelf life in water polo, I found my calling in rugby, and I was a natural at it, and I became captain in three months. And that taught me that sometimes you just have to reassess something, and it's not that you're giving up, and it's not that you're failing it just for different parameters, variables, constitutions. It wasn't meant to be. So I think we've all gone through projects where we are spending endless nights, endless weekends, and that goal marker just keeps moving, and you have to truly assess and go, are we ready to do this, or is the team putting effort into a bunch of things that we just got to call it shelf life? So I think that's one. If there's hope and if there's faith, then I think the alternative option is redo the forecasting and be realistic about what it's going to take.

Sol Rashidi 00:11:57: We assumed these folks were going to be available. They are not available. And when they are, it takes us six weeks to get on their calendar. We assume we had this data, we have it. It's not accessible. And the only people who can grant us access are the application leads. And it's not two application leads, there's eight application leads because the data happens to be fragmented. Not only do we have to get permission approvals, but we now have to aggregate it.

Sol Rashidi 00:12:19: That's going to take an extra three months. And just being very honest about what the new forecast is going to be, because the last thing you want to do is keep pushing the timeline because you lose credibility.

Demetrios 00:12:31: And when you talk about business value not being the right metric, I instinctively see that just because it is fuzzy and it feels like you said, it's like, okay, business value means one thing to one person, it may mean something totally different to another person. And the numbers that they are thinking about could be completely on two sides of the universe. So they're very far apart.

Sol Rashidi 00:12:58: And the numbers are sometimes made up. Forgive me for saying that, that could be kind of bold, but the numbers are sometimes made up.

Demetrios 00:13:06: You of sometimes are being thrown numbers at you. And it's like, well, if we put this into production, we're going to be making or saving x millions, which obviously is much more important than anything else we're doing right now. So this should be highly critical. Right? So I guess the question is, how can you stress test those numbers?

Sol Rashidi 00:13:30: I'm a big believer of the Reagan, quote, trust, but verify. I get numbers thrown at me all the time. And, you know, numbers are very manipulative. And so for me, I understand why we need them just because it proves a point and approves the case and it makes it really convincing. Unfortunately, because I'm a data person, I don't take anything at face value. So if someone's giving me statistics, if we do this, we're going to gain x amount of market share. If we do this, we're going to increase our efficiency by x amount. I love the percentage points.

Sol Rashidi 00:14:03: I'm like, okay, great. Walk me through the method in which we calculated this, because I want to make sure I understand the context, the assumptions, the players involved, and that I could, once I understand your measurement, I could track towards that measurement. It has to do with understanding how those numbers were created so that when we get to a point where we need to measure and monitor and report on our progress, we're doing so according to based on the original metrics and baseline. And I also do it to validate and make sure that people aren't making.

Demetrios 00:14:34: Shit up, which is wise. Very wise. I'm sure that you have a reason for that because you've been through enough cycles where people were making shit up, and so you saw what happened.

Sol Rashidi 00:14:46: That's right. And it became a number that stuck. And no one asked the question of where did this come from? How was it calculated? What were the assumptions that went in, and what do we need to be conscientious of? That is 100% true. And I hate to say it, but sometimes I was the analyst doing the calculation. I'm like, making a bunch of stuff up, but I hope it sticks. And then sometimes it was the person who had to execute because something got bought in from above. And I was like, but this doesn't make any sense. The most we can get is 13%.

Sol Rashidi 00:15:14: Why are they promising 37%? And we keep going and we keep going and we kill ourselves because some executives said this number was achievable and we don't want to disappoint them. So, fortunately, with my career, because things have kind of progressed and I have a seat at the table now, I'm like, okay, wonderful. We absolutely want to support this. First thing I need to know is, how is this number generated?

Demetrios 00:15:33: Talk to me about inheriting teams and how you've gone about that, especially data teams.

Sol Rashidi 00:15:41: Building teams is easier in the sense that you understand what you need to do, the talent that you need to do it. You're often restrained with capex because it's not like you get an endless bucket of funds to hire and build, but you build really good ones, you hire really good teammates, and if they've got that drive, that grit, the tenacity, like, a lot, a lot can happen, but you're starting from scratch, and the recruiting process takes a long time. So it's you, yourself, and I for a really long time until you can do the right hires and you get some support. So progress up front is really slow, and then you hit critical mass. I've inherited teams as small as 170 and as large as 832, and I'm very specific.

Demetrios 00:16:28: Wow.

Sol Rashidi 00:16:29: I knew the number. And oftentimes I get brought in not as the first transformational leader. Well, I did with Royal Caribbean, sort of with Sony, but, like, in the other positions, they've had a few leaders prior to, and they've had mixed results or it wasn't the transformation they wanted. And so they'll bring me in like, okay, you know how to do this. You've done this four times over, at least in the data and analytics and AI space change, it's really interesting. It's a mixed bag of nuts, and you inevitably get the doers, the evangelists, the cheerleaders, the naysayers, the curmudgeons like, you get these archetypes of personalities, and you could pick it up in the first week. And it's amazing how so many people don't want to impress the new boss. They do not give a damn.

Sol Rashidi 00:17:19: And that's just not the camp I grew up in. And there's others who are so, like, we're so excited about this. We've been wanting this. We've been praying for this. Let me walk you through every issue we have. So I go through a few things. One, assuming it's not 800, let's say it's a couple hundred, I spend the first four to five months getting to know everyone, and I will literally kill myself doing one on one, first with my leadership team, then lt plus one. Lt plus two.

Sol Rashidi 00:17:48: And then I'll get to know the middle managers and then the practitioners. And I ask some basic questions. What should we start doing as a team that we haven't done? What should we stop doing that we continue to do, and what should we continue to do that's working really well and we're building good reputation, and we have credibility about it. And I will ask everyone that same question, and then I'll understand. Is there clarity on what my job is? What do you think my job is? Is there clarity on what our team does? What do you think our team is supposed to be doing? And then I'll ask questions of, who should we be partnering with? Who've been our allies, who've been our advocates, who is not our ally and who's not our advocate, and what are the reasons why? I'll ask those questions. And then all I do is listen, take notes. Listen, take notes. In about four to five months, I will come up with a map of the start, stop continues.

Sol Rashidi 00:18:35: Partnerships, allies, advocates, the ones not so much. And I will create a sort of like a mind map of where we are. And then what I'll do is throughout that time, in parallel, I'm having conversations with key stakeholders, executives, middle managers. And I will ask him, who from my team is helping you? Who has created the greatest impact? Who do you consider a teammate of yours? And if I've got people consistently saying no one, or if I've got people saying the same five people, then I'll start understanding, okay, where the issues are from there, like, I will actually create what I call a will skill map. And it's like those that have the skill sets and are willing to do the work. They're hungry, they're motivated, they're excited. Me coming on board is a breath of fresh air for them and they've been wanting to do something right. So there's purpose and impact and they're just hungry.

Sol Rashidi 00:19:26: They haven't been. They just haven't had the right leadership. Then there's those that have the skill but don't have the will. They're complacent, they're tired. They've been with the company 20 plus years. They're not worried about change because they're not going to change. They've been there too long. Right? Then there's those that have the will but don't have the skill.

Sol Rashidi 00:19:43: You have to assess and go, are they coachable? Is this potential? Can I put them in this role? And will they flourish if I put enough time and investments? And then there are those that don't have the skill and don't have the will. Honestly, the ones that don't have the will for me are automatically into a bucket of assessing. Do I need to make an organizational change? Because I can't create change without making change. And everything starts in the mindset, the mentality and the team that I have to work with. So inevitably, unfortunately, when I inherit a team, some people are naturally just a little bit apprehensive and scared, like what changes is she going to make? But I take a really long time. I know about six to seven months of what changes I want to take, but I usually take up to about a year to 14 months before I thoroughly make the changes because there's a lot that goes into it. It's not an easy task, but for me it's all about how hungry are you and do you seriously want to be here for the right reasons? And if the answer is no, there's just no room on my team. So the first option I give is transfer to another one.

Sol Rashidi 00:20:46: Let's find you another job, team or worst, worst comes to worse, we may have to discuss a package because they clearly don't want to be here.

Demetrios 00:20:55: All right, let's take a minute to thank our sponsors of this episode. Weights and biases elevate your machine learning skills with weights and biases. Free courses including the latest additions and enterprise model management and LLM engineering structured outputs. Choose your own adventure with a wide offering of free courses ranging from traditional mlops, llms and CICD to data management and cutting edge tools. That's not all you get to learn from industry experts like Jason Louie, Jonathan Frank, Shreya Shankar and more. All those people I will 100% vouch for. They are incredible friends of the pod. Enroll now to build better models.

Demetrios 00:21:42: Better and faster and better and faster. And just get your education game on. Check the link in the description to start your journey. Now let's get back into the show. How do you assess if someone has the will but not the skill?

Sol Rashidi 00:21:57: If there's folks that I have learn to respect, I will assign them to the leaders or middle management or non leaders and saying, assess their skill and see if they can benefit you. They can benefit the team, they can benefit the group, or sometimes if there's a rising star. But I'm not quite sure I'll assign them as my chief of staff. Usually I'll have two or three because we will always get random projects that come to me directly. They don't go through the normal funnel or filter and I'm just going to need help and I'll say, listen, we've got a strategy deck that's coming up. We've got a percent with XYZ. Here's the narrative that I want to communicate. See if you can create a flow or there's an analysis that needs to be done.

Sol Rashidi 00:22:39: Marketing wants to do a customer acquisition strategy. They're going to do an A B campaign testing. Between this consumer cohort and this consumer cohort, I want to build a methodology for us to track and monitor. Put your thoughts on what we should do and how we should communicate. So oftentimes like, I'll know the answers to these, but I will assign it to this individual to see critical thinking, common sense. Are they leveraging the tools available to them? Do they know? Can they ask questions from the people who are known for this space just to see how resourceful they are? So for those that have the will but don't have the skill, I'll just assign them to different individuals or they'll be my chief of staff so we can assess their skillset level and where they're best suited. Some people aren't strong engineers or have really strong analytical mindset, but they can think through how a storyline should connect and we all struggle with storyline, or they should think through how something should be presented, something we all struggle with. But if they're also a brilliant engineer, then I'm going to put them next to a brilliant developer and group them up within the scrum team of a product manager that I trust wholeheartedly.

Demetrios 00:23:43: Do you think that holding people accountable on the data team is any different than holding people accountable on any other team because it feels like there is. The excuse of data is messy. We need exploration. It's a science sometimes. So not all hypotheses are going to come out.

Sol Rashidi 00:24:03: I think the accountability is worse, meaning there's more pressure. There's a lot of things that you can hide with business processes. You can't hide with data if something isn't of good quality or of good hygiene. And let's say in most of my organizations, I own the enterprise data management team and something's just not right. Like, why isn't it right? That's literally our job. So then we'll have to go through and peel the onion. I'm like, what happened? Is it someone on our team that's not doing their job? Is there a business process that hasn't been redefined? Is there a tool that hasn't been configured to make sure that we get this format consistently and through our outputs? Where is it broken? Because we're the EDM team. So if there's bad hygiene, I'm going to blame it on us, unless it's not in our scope.

Sol Rashidi 00:24:53: So, like, in my last employer, we had product, we had vendor, we had location, but we didn't have customer. And we constantly were getting bad customer data requests of like, can you help fix this? I'm like, it's not in our scope. So in the following fiscal year, I said, you know, here's what is in our scope and here's what's not. And here's how many requests I got in last year for these following domains. Should we change the scope? And if so, I'm going to need funding and resources, and here's what I can fix for you, and here's what I'll be able to do for the team. If not, then we have to make it very, very clear that we have made an active decision to not incorporate this into the enterprise data management team for the following reasons. And it's what I'm going to communicate on. But if right now it's sort of headless and it doesn't have an owner, I'm willing to take it on, but I need the resources to take it on and I will find a way of integrating it into our operating model.

Sol Rashidi 00:25:46: And so I'll actually make the case because that often happens and I'm not sure why different master data domains get split out to different teams. It doesn't make any sense, but sometimes it just never makes it in. But we'll always get the requests. And at some point, people are like, data's broken. Data's broken? Like, which data? Yeah, because not all data is created equal. If it's data that my team owns, let me know specifically what's broken, I will have it fixed for you. Oh, but it's this data. We don't own this.

Sol Rashidi 00:26:13: Will you come with me to the board and say that we now need to own this so I can fix this for you and it never becomes an issue again. And then that's where you start building partnerships, because you have a leader who's being an active advocate and stepping up to the table and saying that, I'm a janitor. I'm just here to clean shit. I'm here to clean shit and build really cool stuff from it. And that's how you build your credibility. Like, some of my deepest relationships have nothing to do with folks in the data analytics space or the AI space. It's with business partners that I've served in the past, and they're like, you were the only one who's willing to get their hands dirty. I'm like, down straight.

Sol Rashidi 00:26:45: That's our jobs. It's a dirty, dirty job.

Demetrios 00:26:48: Talk to me more about the other stakeholders that you have to deal with and how being a data professional and a data leader plays into that.

Sol Rashidi 00:26:59: This is probably the part that I've struggled with the most. We now have a world where we have a CIO, a CTO CIO, a CDO chief digital officer, another CDO chief data officer. Everyone has their vps, everyone has a line of commands, like, oh, you. And even with the chief technology officer, like, I know databases, but I'm not a database administrator. So just because you have a CTO title doesn't necessarily mean, you know, the modern data stack. It's a lot to know. All of us are trying to be masters of our craft, but it's impossible to keep up with. But the challenge that I've always had, and it's never gone away, is where does one rule start and another one end? So, for example, when I'm developing data products, like, I don't want to build dashboards anymore.

Sol Rashidi 00:27:43: It's too time consuming. There's always tiny little changes. I'm going to build data products to serve multiple use cases, multiple user groups and Persona, and I call it the one to many build. I build once and it serves many, but I fundamentally have a reliance on infrastructure, on DevOps, on security protocols. Well, I don't own those. I have to partner up with my fellow CIO but depending on what's on his or her list of things to do, where we fall in line in terms of priorities, and they're barely able to keep up with everything. The business is lobbing over the fence, my stuff barely makes it in the front line. And I'm like, this just can't work.

Sol Rashidi 00:28:21: So I'm constantly having to ask the question if I can't get the resources to own. And I will follow all the processes and procedures and protocols that the office of the CIO have set, but I want to control the pace of development and the quality of development, and I'm going to need funding and resources to be able to do so. If you choose an alternative path, something that should take three months will take us nine months, because based on the priorities already outlined, my ask won't even slot in for another three quarters. Are we okay with that? And the thing is, I make it all very, very clear for the stakeholders, the business, the board, the C suite, and all teams, and whether it's town halls, whether it's group meetings, whether it's one on one, I very much communicate the state of the union because part I over communicate because people only absorb about 10% of what you say. And Malcolm Gladwell had this great saying, if you got to repeat something 27 times before it actually is heard, I need everyone to know of, like, the limitations oftentimes aren't on our ends. It's actually, we have too many competing priorities, and we're just waiting in line. But the darn thing is built. I just can't push it into production.

Sol Rashidi 00:29:34: So you asked that question of working with everyone. It's hard because there's just too many priorities within companies, and you're constantly having to battle and prioritize your stuff over others. And it's not the right answer, but we tend to overcome it. And division of labor is not clear amongst the CXO suites and lines. And you don't know where one thing starts and another thing ends. Like, I'm the chief data officer, but do I own all data platforms and data ecosystems? Do I, though? No. All right, so maybe I own the stuff for analytics, which now means the data lake. Do I own the data lake, or do I just own the architecture that conform to the semantic layer? Like, all those questions, and it's messy.

Demetrios 00:30:17: Speaking of the amount that you want to stay up to date on all the tech versus all the other stuff that you have to keep in mind, how much do you feel like it is valuable for you to know? The newest tool that comes out versus I'm going to spend. Instead of an hour researching the newest tools and the cool ways to do things, I'm going to spend an hour trying to figure out our strategy or trying to network with the other stakeholders so that I can get my stuff pushed through.

Sol Rashidi 00:30:49: Yeah.

Demetrios 00:30:49: Is there a hierarchy that you feel like in the needs of the executive?

Sol Rashidi 00:30:57: 100%. And it will. The priority is always the relationships. Always. People don't do business with you because you have the greatest tool. They do business with you because they like you, they trust you, and you've shown them that you're interested in solving their problems. And that only comes when you have the relationship. Now I say that it sounds so obvious.

Sol Rashidi 00:31:20: I got my ass handed to me in my first job. I went in gunslinging so cocky about the position that I had gotten, saying like, I'm going to fix everyone's problems. I had no idea about the politics. I had no idea about the relationship building. I had no idea that the higher up you go, it has less to do with your iq and more to do with your EQ. No idea. And I got my ass handed to me. But I learned a lesson.

Sol Rashidi 00:31:47: I've never made that mistake. So the first thing I do when I go in is not call people's baby ugly. It's not say, here's how we're going to fix things. It's not come out with a mission statement and a vision statement. I literally spend the first four to five months getting to know as many individuals as possible, doing the due diligence, asking, what do you think my job is? What if I had a magic wand and I could fix three problems for you, what would it be? While I'm asking my teammates to start, stop continues. What you think our role is, etcetera, it's all about the relationships. And so I've always built my reputation on that. Like, she actually wants to listen.

Sol Rashidi 00:32:23: She's not coming in and trying to fix things off the bat. And that gives me context into the business. And when I can get to know their language and I get to know the business and I get to know context, anytime I story tell what we're going to do and how it's going to benefit them, I use their words. And that's probably the biggest advantage I've ever had. I call myself just like a glorious translator, but I get to know the words and the language and the metrics that are important to them. And I use their language, not our language. I don't talk to them about semantic layers and data architecture, engineering and orchestration and observability. No, I'm like that thing that takes you 14 weeks to get.

Sol Rashidi 00:33:01: Here's why in very simple forms. Here's how we're going to fix it, and here's what you're going to get in four weeks. It builds the relationship. So I rely on people a lot smarter than me to do the tool discovery because every six months there's a new tech stack that we can lean on. And I've got a lot of smart individuals who not only love it, they do it during the daytime, but they do it at nights and during the weekends for fun. And I don't ask one person, I ask a ton of individuals because based on what they suggest and why they like it, that's person number one. I then go to person number two. I spend the hour or two.

Sol Rashidi 00:33:36: Instead of researching myself, I spend the hour talking to about three or four individuals to come up with an opinion and a judgment, and then I'll come up with a perspective and present it, and then we'll have a discussion from there. So I'd rather go straight to the people who work with it day in and day out.

Demetrios 00:33:53: Let them be the ones that can synthesize that information for you. And then you get the higher level.

Sol Rashidi 00:34:01: It's what they love. They want to feel valued. It's sort of their shtick. While I'm building relationships to make sure whatever we built has credibility, they get to do what they love. And the fact that I come to them, you know, sometimes they do feel valued about it. They're like, okay, she respects my opinion now. It doesn't mean that what they say I'm going to take and be like, okay, this is our answer. I'll ask many individuals.

Sol Rashidi 00:34:22: I'll always form an opinion on my own, but always say, okay, I heard you guys say this. There seems to be some contradictions here. Let's come to a conclusion together. And like, yeah, they tend to respect that.

Demetrios 00:34:35: You know what's hilarious? When you were talking about how you don't use the words that we're used to using, and you just say, it's almost like an abstraction above. And you say things like, you see, you know that thing that takes you a while? It reminded me of a, one of my favorite physical therapists who would give me all of the muscles and just call them that guy or those guys or this guy. There was no, like, squishy latourist bendy thing. Yeah, not of the. Because the muscles are super complicated. You have 20. You know, different muscles and all the names, they're hard to think about. And it's so easy as the expert to dive into these names and then you cause it like makes you feel good.

Demetrios 00:35:28: Like, look how much I know. It's almost showing off. Yeah, but the end user, the person you're trying to help, is sitting there and they're like, wait, what did they just say? And they're thinking about what muscle it is. And so with this, it was exactly that. They would just go like that guy right there. You want to feel it burning in that guy. And there was no naming the muscle, nothing like that. And so it's very much, it just reminded me of that story where you.

Sol Rashidi 00:35:54: Do the same thing 100%. We have to. And I think that's part of the challenge that we as an industry have. Like, as an industry, I think we have three challenges, data analytics. And let's loop AI into it. Because at the end of the day, it's not the AI applications that are complicated, it's be able to supporting the ecosystem because it's still fundamentally a data ecosystem. The pace of change is extremely fast. We can't all keep up.

Sol Rashidi 00:36:18: And so like our heads are being blown off with just the latest advance and tools and startups. Like we can barely keep up. Second, we have a bunch of technical individuals who are learning the business language, but haven't invested in the business language. So we struggle with storytelling, we struggle with the narrative. Like, if I go and talk to a CMO, I'm not talking about digital campaigns and a b testing and data pipelines and consumer cohorts. I'm not using that language. I'm talking about our consumer acquisition cost. I'm talking about our CRM, I'm talking about our consumer lifetime value.

Sol Rashidi 00:36:52: And I'm using the metrics they have presented in the deck that I saw as a means of describing what we're going to help with and which of those percentage dinghies are going to go up and which of those percentage dinghies are not going to go up and why I use their language and we just don't do that. And I think the third issue with our space, it's really, really hard to deal with is, you know, my analogy is when's the last time you flushed the toilet and called your plumber and said thank you? When's the last time you flipped a switch and called your electrician and said thank you? You don't, you just assume it's going to work. And that's like, that's our jobs. It's very thankless, and it's not commodity based. But you hear news when things aren't working. When things are working, you're not getting a pat on the back. You're not getting a thank you or a hallelujah. You're in the business like the janitorial business.

Sol Rashidi 00:37:46: We're here to fix things and build things and make things. We. We are construction workers and janitors. No news is good news. And everyday news means something else is broken we have to fix. And that's just kind of like our industry pace of change. We suck at storytelling. It's very hard because we got to keep up with our own space and all the businesses we serve.

Sol Rashidi 00:38:06: And in general, it's a very thankless position. And so I feel like you sometimes got to be a masochist to choose a space. I love it, but it is so frustrating, day in, day out, but I still love it.

Demetrios 00:38:16: Do you think that any company can be turner turned around?

Sol Rashidi 00:38:22: When you're a company that was born out of disrupting existing companies in a pre established vertical industry, it's in your DNA to disrupt, and so therefore, changing, adapting, pivoting, saying, whoopsie, that didn't work. Let's go this way. They come very natural at you. Change is a constant for companies and industries who are within certain verticals or domains that have been around part of the S and P family, 1015, 2050 going on 100 years. And while there be disruptions, tiny little micro disruptions, every five to ten years, but they haven't fundamentally had to rethink their entire business model. And usually they introduce a new product to the market or a new service to the market, or they have a new brand or a new name, and that's helped them to survive and do acquisition. Those companies have a hard time. They just do have a harder time because their culture isn't inherently built on disruption and change.

Sol Rashidi 00:39:24: And it's so funny. Demetrius, you may laugh, but like, in my interview process, I asked two questions to understand whether it's a culture that's fit for change or a culture that's not. Do you have a pension fund, and what's the average tenure ship of your employee? Do you know why I ask those questions?

Demetrios 00:39:41: Well, is it, if there's a pension fund and the average tenure is long, they are less likely to change. Really? Oh, wow.

Sol Rashidi 00:39:51: Because they are legacy based. Very few companies offer pension funds nowadays. It's. But those that do means they fundamentally have employees that have stayed there because their interest is more the pension fund pension fund versus evolving and pivoting and adapting and changing. And so by default, if your answer is yes on the pension fund, you're going to get individuals. The average tenureship is greater than 20 years, as the majority mean. And that's not a crew I can change. You learn these things, but not because you read it in a book.

Sol Rashidi 00:40:24: You're like, why is this so hard?

Demetrios 00:40:27: Oh, unless it's your book. That is the perfect place to mention that. Yeah. If you do want to read and learn these things in a book, we're going to be. We're going to leave the link to your book in the description so everyone can grab it. And also your newsletter is. It is for the leaders out there, 100%. Your wisdom and learnings are unmatched and I really appreciate you coming on here.

Sol Rashidi 00:40:57: Ew. Thank you. I'm super, super honored. You've done amazing with this podcast, by the way. And I found out about it just because a bunch of friends of mine who have either worked for me or I truly respect cause they're amazing at their craft or like, this is an awesome podcast. You got to get to know Demetrios. He's super amazing. And they were not wrong.

Sol Rashidi 00:41:16: So thank you. I'm humbled to.

Demetrios 00:41:17: That is so cool. Yet, hold up, wait a minute. We gotta talk real fast because I am so excited about the Mlops community conference that is happening on June 25 in San Francisco. It is our first in person conference ever. Honestly, I'm shaking in my boots because it's something that I've wanted to do for ages. We've been doing the online version of this, and hopefully I've gained enough of your trust for you to be able to say that I know when this guy has a conference, it's going to be quality. Funny enough, we are doing it. The whole theme is about AI quality.

Demetrios 00:41:54: I teamed up with my buddy Moe at Kalenna, who knows a thing or two about AI quality. And we are going to have some of the most impressive speakers that you could think of. I'm not going to list them all here because it would probably take the next two to five minutes, but just know we've got the CTO of Cruz coming to give a little keynote. We've got the CEO of coming. We've got chip, we've got Linus. We've got the whole crew that you would expect. And I am going to be doing all kinds of extracurricular activities that will be fun and maybe a little bit cringe. You may hear or see me playing the guitar.

Demetrios 00:42:39: Just come. It's going to be an awesome time. Would love to have you there. And that is again June 25 in San Francisco. See you all there.

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