Women In Data w/ Sadie St. Lawrence

Rob Collie (00:00:00): Hello friends. Today's guest is Sadie St. Lawrence, CEO and founder of Womenindata.org. When I sat down today and reflected back on the things that we spoke about, I came to the very strong impression that this conversation is going to go into my top five personal favorites in the history of this podcast. Bold claim, I know. But you know how we subtitle this show, data with the human element? This conversation is very much about that, except the data part. 100% human element from the jump. And while we certainly talk about women in data, there was almost nothing about this conversation that was exclusively focused on women. It makes sense when you think about it. If something makes an organization, for instance, a more hospitable place for women, those same improvements will benefit you even if you're not a woman. For example, just today we, P3, decided to update our public job descriptions for the consulting team here at our company from 25% travel to travel optional. And the spark for doing that came from my memory of this conversation with Sadie.

Rob Collie (00:01:10): One of the things that Sadie really crystallized for me during our conversation was how much of the unpaid labor at home disproportionately falls on women. And in particular, how the COVID pandemic really exacerbated that dynamic. And today I connected that 25% travel estimation/requirement in our job description, which by the way, is a leftover from multiple years ago. I connected that with how that one line in this job description very well might be disproportionately discouraging women from applying for jobs here. Of course, when we went and thought about it deeper, we discovered that we're not traveling anywhere near 25%. It's more like 3% to 5%. That line in the job description might not just be discouraging women. It's probably discouraging a lot of people and it doesn't match our reality anymore. So there you have it. Travel optional from here on out. Benefits everyone. Thank you, Sadie. Helping us put the adaptive in P3 Adaptive. All right. I don't want to spoil anything else. If this conversation were a book, it would be a page turner. So let's get into it.

Speaker 2 (00:02:15): Ladies and gentlemen, may I have your attention please?

Speaker 3 (00:02:19): This is The Raw Data by P3 Adaptive podcast with your host, Rob Collie, and your co-host, Thomas LaRock. Find out what the experts at P3 Adaptive can do for your business. Just go to p3adaptive.com. Raw Data by P3 Adaptive is data with the human element.

Rob Collie (00:02:45): Welcome to the show Sadie St. Lawrence. How are you today?

Sadie St.Lawrence (00:02:48): I am doing well. Excited to be here and have this conversation.

Rob Collie (00:02:52): I've been looking forward to this. Where are you located these days? Where are you right now?

Sadie St.Lawrence (00:02:56): I'm on the west coast in California in the capital of the state, Sacramento.

Rob Collie (00:03:01): Sacramento.

Sadie St.Lawrence (00:03:02): Most people don't know where it's at so I always refer to it, it's right in the middle between Tahoe and San Francisco. So it's commonly referred to as the best place to live if you want to get away on the weekends.

Rob Collie (00:03:14): That makes sense. This is going to sound funny. I spent a little time in Folsom.

Sadie St.Lawrence (00:03:18): Oh wow.

Rob Collie (00:03:20): The city, not the prison. So Intel has a big plant, big facility in Folsom. When I was working on the Excel team at Microsoft and we were investing heavily in business intelligence, we would go on all these customer visits and the Intel crew down in Folsom was one of our more popular destinations to visit because they just had so much going on. So I think we flew into Sacramento for that. I'm familiar with that area. But it's a great joke. Yeah, I've done some time in Folsom.

Sadie St.Lawrence (00:03:48): Yeah, it depends on how you set it up, right? The context is key in so many situations.

Rob Collie (00:03:54): Totally. Totally. So what's your job title? What's your professional role these days? What's your purpose in life at the moment career wise?

Sadie St.Lawrence (00:04:00): Yeah. Currently my official job title is Founder and CEO of Women In Data. And I would say my purpose in life is really democratizing data by providing access for individuals to get in the space and continue to excel and grow in the space. I had a long career in data and AI and nothing makes me more excited than being able to help other individuals now grow in their career in this space. And so I'm just so excited about what the future of data and AI holds and excited to have more people and diverse minds working in this space.

Rob Collie (00:04:40): Yeah. So when did you start the Women In Data organization? How many years in are you now?

Sadie St.Lawrence (00:04:45): Women In Data started in 2015 and for the first five years I was part-time with it. I'm a big fan of what I call slash careers. So you have your first job title, then you do something else/something else/something else. And eventually these replace whatever was in the first slot of it. So for me, Women In Data was a slash on the side. It wasn't at a point where I could focus on it full-time. But it started in 2015. And it started because I was in my master's program for data science and was also working as a research analyst and I just was so surprised when I entered the field and saw there weren't any other women. And I was like, okay, this is weird. One, I did not expect to come into a space where women weren't a part of it. And also a few years prior, the Harvard Business Review article came out that said sexiest job of the 21st century. I was like, okay. If this is how we're starting out, then the prospects of the future of this industry are not looking good and it's going to be a big industry. So I knew that I had to do something because I needed community in order to survive in the field, but also wanted to create more equality in the spaces as we continue to progress and grow.

Rob Collie (00:06:04): Talking about that slash career thing, to be cool I think on LinkedIn, you now need two or three jobs whose date ranges overlap. I've never had that. I've been one track forever. But yeah, I like that. That's an appealing thought to me. It's just never worked out that way.

Sadie St.Lawrence (00:06:21): See, I might argue differently because to me, I look at you and I'm like, you're already a slash career. You're this podcast host, you run this amazing podcast. You also are the founder and CEO. To me, I look at it, you probably have a lot more slashes in there. Maybe it's just peeling back the onion a little bit further.

Rob Collie (00:06:39): I need a better LinkedIn game. I need to get in there and make some edits. Well, I appreciate that. So it surprises me to hear you say that in 2015, in the master's program ... Is that what you said?

Sadie St.Lawrence (00:06:53): Yep.

Rob Collie (00:06:53): That you did not see a lot of other women in that program. Because one of the things I've been saying for years ... And I'm positive that you're correct about your experience. I'm not disputing it. I've been in multiple different tech fields in the course of my time at Microsoft, for instance. I went to a lot of conferences and at every conference there's always some session about women in tech field X or just women in tech in general. And then of course the panel at that discussion comprises some significant percentage of the women at the conference. There's 20 women at the conference and six of them are on the panel. That's a lampoon.

Sadie St.Lawrence (00:07:31): That's how they got those women to come to the conference, was having them on the panel.

Rob Collie (00:07:35): Right. That's how we stack the percentage a little higher. When I was teaching a lot of classes on power pivot or Power BI, I found myself staring at classrooms full of people and slightly more than 50% on average were women and going, "Wow, this is different." And immediately being incredibly curious as to whatever the filter is that's normally leading to my normal tech conference experience versus what I was running into in the world of data and being just really pleasantly puzzled in a very positive way. Like, okay, this is great, but I don't really know why I was seeing this difference. Also, anecdotally, I feel like ... And this is not a data driven conclusion. This is more one of those gut instincts. Just scrolling through LinkedIn, I see a lot more female faces in data roles than I see pretty much in any other technical role. It's surprising and a little bit concerning that ... I know it was seven years ago now, but that you were running into that in a data science program. Again, I would've guessed that that wouldn't be the case, but clearly it made an impression on you.

Sadie St.Lawrence (00:08:47): Yeah. I think it's a little bit different now in education. What I tend to see in new technical industries that are emerging is in the beginning, we tend to have less diverse audiences when it's first picking up steam. And I think 2014, 2015 does not seem that long ago to me. But in retrospective, I remember looking for a master's program at the time. There were only five in the US. Today there's over 100 programs. So I think it's important just to take a moment to think about where the field was at within its development within data science and where we are today and how much progress we've made in that space now. So I think at that time from an education standpoint, it was still relatively new. I'm seeing the same thing happen all over again with web three and blockchain.

Sadie St.Lawrence (00:09:42): That to me is where AI and data science was 10 years ago. And in those initial stages, we don't see those diverse audiences get into as much. Today, I think the experience you're seeing and you had with teaching your class where women were represented about 50% of the population is more of the standard in a lot of the education programs, but where we have a big problem is then not getting them necessarily into that first entry level job, but then moving into that management, senior management VP level. So that's really where a lot of our work and focus is today is how do we continue to progress up channel for that retention as well?

Rob Collie (00:10:26): My first knee jerk response question to that is, what are the sorts of headwinds that you're working against? If there weren't headwinds, there wouldn't be a problem. You're saying that things have made a lot of progress on getting that first job, getting started in the career, but then running into something glass ceiling-ish. Is that a fair characterization of what you were saying?

Sadie St.Lawrence (00:10:46): Yeah. I think the glass ceiling is something that buckets what we're seeing really well. I think it's a good term to use so that we can all grasp what we're seeing. There's a lot of different issues. One that we saw really come to life during the pandemic was just the burnout from women in terms of having to care for children and all of the unpaid labor that they're doing at home. And so it's a lot of those unseen work that they take on, whether it's in the workplace or outside of the workplace. The other thing I see a lot too is ... And this is just through personal experience. I mentor a lot of people in the organization and one of the things they see a lot is not wanting to play politics or self promote themselves. And they're very much, "Tell me what the job is. I will get it done. I will do it the best, but I don't understand why I'm being promoted."

Sadie St.Lawrence (00:11:45): I'm the best person. I know I'm the best person. The quality of work, the work that I do. And that, unfortunately ... I love the saying that the techniques you use to get to one position are not going to be the same techniques you need to get to that next position. And I think there's a lot of work we have to do to unravel that, but also to support women in that journey so that they aren't getting burnt out in that process.

Rob Collie (00:12:09): I joined Microsoft in the mid '90s and it was very, very, very much a male dominated culture at the time. And I'll be honest. I found it alienating too. The things you're talking about, the imposter syndrome type of stuff and not going in for the self promotion, I ran up against all of that as well. And a lot of my male peers did not. I'm not saying that my experience was equivalent to a woman's experience in that environment because it definitely wasn't. It took me a long time to feel like I belonged. In hindsight, I clearly did. It was a long multi-year struggle to come to terms with it. I'm very sympathetic.

Sadie St.Lawrence (00:12:51): And you make a really good point there because I think if we pull back the layers a little bit further, what we're really talking about is not just men and women and the barriers they have, but really the values that are promoted at an organization and regardless of your gender or your race, you can feel that the values promoted at the organization are not the values that align with you. And that is why I'm so passionate about helping women move up in their career and get into this space because the values we see that are promoted by women are one of collaboration. One that tends to care about people. One that wants to make sure what we're doing as an organization has purpose and value. These all sound like great values regardless of being a man or a woman. These sound like the values ... You're also saying, hey, I wanted that at XYZ company I was working at before. I think that's why I'm so passionate about just diversity in the space as a whole. Because when we do that, we're bringing in values that the company may not have today that will be beneficial as we move forward into a half digital, half three dimensional real life world that we're working in.

Rob Collie (00:14:12): Just to echo that, we're talking about at a high level cultural problems or suboptimal cultures in business in general or in organizations in general. And I do believe that some of these things we're talking about do disproportionately impact women or minorities relative to me. It's not a perfect subset. If you've ever been exposed to the personality insights test that gives you the four colored blocks, the green, the blue and everything, I'm heavily green forward. It aligns with what you were saying. The collaborative human focused approach. I didn't know that about myself. I took that test many years too late. It's like, oh, thanks for explaining my last decade. But I think the Microsoft that I showed up to was a very red dominated personality culture. Sometimes way over the top. The red being the super terse, hard charging executive. Personalities that we associate with Bill Gates and Steve Job. That stuff is terrifying to me. So there's even fringe benefits to this. We just become healthier in general the more we embrace these sorts of things.

Sadie St.Lawrence (00:15:26): 100%. A recent MIT study found that the number one reason people leave their job is because of a toxic work culture. So this is just all people in general. And when they dove into that a little bit more, like what constitutes a toxic work culture, the number one way people define that was there wasn't a promotion and support for diversity, equity, and inclusion. So why does this affect everyone as a whole? Because it's exactly what we're talking about here, right? You didn't balance the squares of the personality test. You leaned heavy too forward on the red or the blue. Where yes, when we don't balance those values, the diversity that we have within our organization, it's going to definitely affect minorities and women. But more importantly, it also affects all of us, whether we identify with one of those groups or we don't, because what happens is we're out of balance. And so I think it's just so helpful to remember that when we promote these qualities and make space at the table for everyone, it makes us just more resilient as a whole so that we are making sure we have that space to bring those ideas forward, to bring the very best out of people.

Rob Collie (00:16:47): Yeah. I agree completely. I have this personal theory, which is encourage people. Even if you just want to be ... It's like a joke. First, be a good reptile. If you were the most calculating, cold unfeeling person on the planet, but you committed to your own best interest and really followed it to its long term conclusions, you would still be in on these things. If you're a leader of an organization who has never had a feeling in your life ... And sympathy, what is that? If you just calculated it out, you'd realize that you want to lean into these inclusive cultures, because you're going to get the best results out of it. It's even in your own best interest. And so when those align with the humanity of things, it seems pretty clear, let's do this. You don't get too many clarities like that in life.

Sadie St.Lawrence (00:17:44): I think a lot of us, we've made a lot of progress, I think, as a society in this space. And I don't think there's ... Or at least maybe they just aren't telling me, but I haven't met someone who says, no, I don't support diversity, equity and inclusion. I definitely think they wouldn't probably say that to my face so I'm probably a little bit biased in there. But I'm seeing a lot more support-

Rob Collie (00:18:06): Probably the last person.

Sadie St.Lawrence (00:18:07): Yeah. I'm probably the last person they're going to say it too. Unless they're just really missing that heart aspect. But I think where our work now is, okay, when we say that, how do we translate our words into actions? And I love what you mentioned of start with being a reptile. Have a heart and think a little bit beyond yourself to tap into some of those deeper meanings of how does this make me feel? And it may sound a little wishy washy, but I think it's even more important as we move forward in a digitally engulfed world where technology is taking over so much of our lives that we move forward in this space really conscientious about the human element, about the feeling element, about the heart element. Because if we don't, that's I think when we get to the doomsday of AI taking over and ruling our world, because we've missed that balance between the technical and the human. And so for me, it's like this work is so important because we're paving the way for the future of our world and how it's run with technology. We must be incorporating that human element from the beginning.

Rob Collie (00:19:24): How do you think we're doing at that as a society? I'm a little cynical at the moment. I couldn't agree with you more that it's important. There are people that in my own personal network for instance, who work in data science in some very, very prominent roles that I have declined to invite them to be on the show because even though they're great people, I think they work in organizations that are on net doing a lot of at least potential harm. I couldn't interview them authentically without asking them about that. Just mark that person off the list. I doubt you're as cynical as I am. Do you have that same feeling that we have a tremendous amount of work to do on that front? I get the sense that technology's getting out ahead of our humanity. It's outpacing it pretty fast these days.

Sadie St.Lawrence (00:20:09): I think it is. I think that the pandemic really put us behind in a lot of ways because it forced us to all work in a box. And for a couple years we didn't have much human connection. And I've seen people be very, very rude and nasty and mean online when you're blocked behind a screen. I would expect that they would never be that way face to face with that individual. And now that we're coming back to a sense of normalcy, I've really enjoyed attending some conferences and talking to people and we've been having just great conversations about diversity and what we're doing in this space. And people are able to be very open and honest. And things that I just see not being able to be had online. And so I think that yes, with the pandemic, we got set back a few years because we missed those raw and authentic conversations where we may have different opinions, but at the end of the day, I see in your eyes that you are a human and we can agree to disagree and still leave this conversation respectful and understanding of where the other person is coming from. And so that's what I'm hoping to bring back now as we move back into a little bit more sense of normalcy in this space.

Rob Collie (00:21:39): Yeah. And all those things you're talking about, the commonalities that get de-emphasized, the problem is they just don't drive clicks. They're not good clickbait headlines. Got to get people upset. That's the trick.

Sadie St.Lawrence (00:21:51): So I asked the question then, do we as data professionals have an opportunity to re-navigate this? Because what you measure is the results you'll get. So if we're saying, hey, we want clicks and reactions and spread, well, we're getting that. And unfortunately the way we're getting it is not what we all intended, but could we find a new measurement? A new measurement that has meaning and says, hey, you get good business outcomes, you're driving traffic. That underlying ... Your revenue's growing. But it doesn't have this secondary effect, which is making everybody mad and making people hate each other. So I think we as professionals in this space have an opportunity to say, hey, we've found a better way to measure and drive positive outcome for the business and for individuals as a whole.

Rob Collie (00:22:43): Something that was triggered by what you were saying there is, imagine we could rewind to the beginning of Facebook. It was a relatively arbitrary product design decision to add a button called like. What if instead of calling it like at the very beginning, they had called it something like this gave me a warm feeling. So that would be the reaction. You can like someone saying something awful about someone else if you think they happen to be correct. It's like you're endorsing it. But if someone's saying something awful about someone else, you're probably not going to click a button that said I got a warm feeling from this. At least I hope not. And imagine how different society would've turned out over the next decade plus if that button had been labeled differently. Maybe we would've optimized for a more collaborative feeling in society even. Maybe that's what we'd be driven towards. And all of the vitriol and the bile, as you said, you get what you measure. Look at how potentially it would've been different with just one little semantic twist to the name of that button.

Sadie St.Lawrence (00:23:56): Yeah. I think there's so much opportunity in this space to reimagine what we're measuring, how we're measuring it and the small changes we can make for the outcomes. But I think it's also really important with algorithms in particular that we don't put these in a narrow box and remember that what we're trying to optimize ... This is somewhat the problem with AI is you have a target variable. Well, that's one single variable. But our lives are not put into silos. When we make decisions as humans ... Should I eat this pizza or should I not eat this pizza? There's a lot of inputs and factor-

Rob Collie (00:24:36): Yes. Yes is the answer.

Sadie St.Lawrence (00:24:36): Oh, always. I'm like pizza four times a week, right? 100%. But there's additional downstream effects for one target variable for what we're trying to optimize. And so therefore I think it's important that we start looking at the algorithms we're creating and what we're trying to optimize a little bit broader. Just as it seems simple and non harmful to create a like button on Facebook, there's so many more downstream effects because of the interconnectivity of our world and our brains that it's important to bring these into the conversation. And I think the time is now. I know I'm fed up. You sound pretty fed up. I'm sure we have a network of people who are like, "Wait, this is not what we intended. Let's start to break the model."

Rob Collie (00:25:24): And of course the number one thing that everyone's optimizing for is money. And that's a tougher problem to crack. I could get behind a campaign to rename the like button or whatever in a more positive direction, but I don't know how we get the money thing straightened out. That one's going to be tougher.

Sadie St.Lawrence (00:25:41): This is what we'll dive you into the whole decentralized blockchain web three space. I think those are the people who are trying to work on the money problem, but that's a whole different conversation.

Rob Collie (00:25:52): Yeah. I'm a recovering libertarian. I had some of those leanings in my 30s. Leaning into that whole reptilian analysis and taking it to its real conclusion. Don't be lazy with it. Don't take it three levels deep, take it all the way to the bottom. I don't read too many non-fiction books, but the book Sapiens, I made it halfway through. And he talks very, very compellingly about how we're biologically wired to collaborate at the village scale. But look at what's happened since then. We collaborate at grand scale. And the only way to do that is to have these shared beliefs. He calls them religions. Even if the religion happens to be named Toyota. So I've always been an underdog type of person. At the same time though, look at all the problems that we have to deal with in society that are now shared commonalities, shared externalities like global warming. And I'm going, oh no, maybe decentralization is exactly what we don't need right now because it's going to fragment our ability to collaborate at the scale that we need to and I don't have a strongly formed opinion. I don't even really understand the web three thing all that well yet. I'm still working on that. I agree that a lot of our institutions are harmful and it's high time that they exert less power. But full decentralization might be just as terrifying.

Sadie St.Lawrence (00:27:11): Yeah. It's a tricky one. I'm happy you only read half the Sapiens book because that's all ... I think I only made it through a quarter of it so we can have a great conversation about the book since we both stopped midway through.

Rob Collie (00:27:23): Yeah. Neither of us had the courtesy to start at the end. We could have covered the whole thing if one of us had read it backwards.

Sadie St.Lawrence (00:27:30): But in terms of decentralization, I think even if we move into a more decentralized world, we have to remember that it will never be fully decentralized. I think that there is opportunity for decentralization of data, which I'm excited about because today what we've seen is that data is power and fuel. And unfortunately the majority of people are left being the creators of it, but not the owners of it. So I'm a big fan of decentralizing information and data. I don't think we'll ever fully decentralize the world, I guess. Because we live in an interconnected world where everything we do has a cause and effect. And as much as we want to distill these apart into individual compartments, just as we talked about with algorithms ... I'm just going to optimize for likes or I'm just going to optimize for this. You can't. I mean you can optimize for it, but at the end of the day, there's downstream effects because of the interconnectivity that we have. So I don't know. I'm pretty hopeful about the future of web three and decentralization because I think every new technology starts off with these really high hopes and the problems that it's going to solve and then we start getting a little further in and we're like, "Okay, it's solved a few problems, but it also created five more. So now we got to build a new one to tackle those." So it's just a constant evolution.

Rob Collie (00:28:57): I like that non-binary way of looking at it. The people that I've talked to about web three tend to be revolutionaries. This is how we're going to tear down governments and really get the power back to the people. And I get that. A lot of evils emanate out of big governments. Look what's going on in Russia and Ukraine right now. A decentralized Russia would not invade Ukraine. If everyone's voting with, yeah, I don't want this visited on my family. I don't want to visit another family. Human beings wouldn't do that. A government might. So I get it. Then I keep coming back to that, oh no, but increase the number of actors. Maybe collaboration gets harder. I like the idea that there's a middle ground. Because again, I'm mostly just reacting to those tear down government types. There might be a little-

Sadie St.Lawrence (00:29:42): Yeah. I try and stay away from the tear down government people because I do think that order and authority has importance. And I think that sometimes we don't want to throw the baby out with the bath water. I think more so we need a pool net where we just need to clean out a few leaves versus throw everything out of the pool. So I'm more of a pool net person of like, hey, let's just get a little cleaning crew, make a few adjustments, slow tweaks. We'll be in a much better place.

Rob Collie (00:30:12): And the people I'm thinking of, they're like let's nuke the pool. Vaporize it. Everything about pool is evil. So data science, this is not something that I do. And our company does get into the fringes of that at times but that's not the center of mass for us. I have a saying, which is the next big thing in data is the basics. Because so many places ... In fact, it rounds to almost 100% of non Silicon Valley companies. Even knowing what your own data is saying right now is not really feasible. That's like the evolution or revolution that our company is primarily a part of. But I'm very much aware of this other space. So if you're a data scientist, what are the chances that you're connected to one of the FAANG companies, Microsoft, Facebook, Alphabet, Amazon? If you take those big tech giants and then you take all of the tech startups, what percentage of data scientists in the world are connected to that cluster of industry versus connected to the rest of the world? Again, I don't expect you to have a precise answer to that. But even order of magnitude, is it 1% of the data scientists? Is it 90% of them? I could believe in a way, either extreme.

Sadie St.Lawrence (00:31:28): Starting off in 2015, I would say it was 90%. But now it's started to even out more as hype in the industry has grown, people have seen value from it. This year the US Army now classified a role within the Army as being a data scientist. So when I look at things like that, I go, okay, the hype is gone, we've made it, it's here to stay in the industry. It's becoming widely adopted. And so I see it more as a shift in a wave. I would say today, it's probably maybe 20% the FAANG companies and the rest industry. That would be my guess. And I think it's going to start to even out in terms of how large a company is and how many employees they have. I'm seeing a lot more democratization in terms of where data scientists work and the organizations that they're a part of.

Rob Collie (00:32:27): On that Army role for a moment, I hadn't heard of that. I hadn't heard that that had happened. So I could get out of high school, go into the Army and when it's time to select a specialty, instead of rifle company, there's a data science specialty that I could opt in for instead? Wow.

Sadie St.Lawrence (00:32:43): I believe so. I'm not an expert on the roles within the Army and how they work. I'm only a bit familiar because my partner wanted to go into the Army to be a cook and learn how to be a chef, which I guess is also a role within the Army. And unfortunately he scored too high on his tests and they're like, "Yeah, we're not going to let you be a chef." And so he didn't go through with it. My understanding is yes, you could be 18, sign up for the Army. I'm sure there's a ton of tests that you take and evaluations, but that is now an actual role. And I think it's exciting and also maybe a little bit scary of, okay, what are we going to do with these skills?

Rob Collie (00:33:24): I'm going to tell an embarrassing fact about me, which is that I had zero intention of going into the armed services in high school, but I still took that ASVAB test because I was so addicted to doing well on standardized tests. That's how much affirmation I needed from Scantron tests that I went and took that test just so I could get that high score and get that dopamine feedback like that. I would go and spend the two hours or whatever of boredom. Sick little boy.

Sadie St.Lawrence (00:33:53): You and I could not be any more different on that aspect because I hate standardized. I was homeschooled and I never took a standardized test until I had to take an ACT test to have some record to get into college. And I remember getting in the room and they handed me the little bubble sheet. The Scantron. And I leaned to the person next to me and asked, "What do I do with this?" And I swear that person was just white faced, like, "You should just go home now. If you don't know how to use one of these this is not going to be good." So I'm so happy that there are people in the universe who love Scantrons, because that is not the story of my life.

Rob Collie (00:34:36): It was a misguided love. I think it really had a lasting hangover in a negative way on my career. Imagine a world where it was always multiple choice, a through D, in real life. And one of them is right. 100% right. And the others are 100% wrong. Falling into a groove of expecting the world to be that way. The hammer that thinks everything is a nail. I was good at A, B, C, D. All the gray continuous non-distinct reality of the real world, very, very challenging for the Scantron fan. Took a long time. I don't think I would enjoy it. I hope I wouldn't anyway.

Sadie St.Lawrence (00:35:20): Wouldn't life be so easy if every decision you had to make was four options and it was choose your own path, right?

Rob Collie (00:35:27): Yeah.

Sadie St.Lawrence (00:35:28): Unfortunately it is not that simple. I'm just looking at the painting behind me, which is a bunch of interconnected swirls. And I think that's how decisions feel a little bit more is yes, you have maybe one or two options, but there's so many factors that go into those options that our brain is constantly trying to compute and to crunch and to think about what are the outcomes? Who will this affect? What's the short term effects? What's the long term effects? What am I optimizing for? I don't know. Scantrons seem pretty straightforward now.

Rob Collie (00:36:03): Yeah. And again, just a real disappointment. It's just a lie. You can go a long way on being good at Scantron tests. You eventually run to the end of that road and you find yourself in real life. Like you were saying about all the different things going on in your brain, even intuition is a calculation of sorts. It's just like the results of a sufficiently complicated machine learning model. You can't explain why it came to that decision. You can sometimes validate that it was right, but explain how, it's like intuition.

Sadie St.Lawrence (00:36:36): It's a great example. And I think it's important for us to remember how limited we are by our five senses. So as humans, if our brain is the algorithm, our five senses are the data inputs. And anyone who's worked with data before knows the representation of the data, the quality of their data, the sample of their data is going to affect what those outputs are. And the same is true for us as humans. We are not able to see the whole spectrum of light. So we at many times are held back by our five senses. I cannot hear what my dog can hear, right? His five senses expand way further than mine. And so I think it's even important to realize that as individuals, yes, we have a lot of inputs and we've been able to achieve a lot as humanity with these five senses, but it's not all that's out there.

Rob Collie (00:37:32): The day that I realized that radio was actually light that could just pass through everything, if you could see it, everywhere would be lit because radio goes through all of the walls of your house and everything. Your wifi router would be blindingly bright to look at. It's weird. I'm a first rate dorm philosopher so I'll join you down this rabbit hole for sure. At least I think I'm a first rate dorm philosopher. I've ever actually been rated.

Sadie St.Lawrence (00:37:59): There was no Scantron test to test it.

Rob Collie (00:38:02): No, that's right. That's right. But if there were a Scantron test on dorm level philosophy, oh I would kill it. 1600. So what are the day to day activities that go on at the Women In Data organization? What's a day in the life for you, but also a day in the life for the organization? What sorts of programs and activities are there? When I say activities, by the way, I want to be clear, I don't mean fun things to do. I mean, what are the things that the organization does?

Sadie St.Lawrence (00:38:36): No, I got you. I got you. I got you. Yeah. So Women In Data, our mission is to increase diversity in data careers. So how we do that is through three pillars of awareness, education and empowerment. Within each of those pillars, or you can think of them as buckets, there's a variety of things we do. So on the awareness side, while information is readily available to most of us through the internet, we now live in these echo chambers based on past likes, dislikes, who our network is. And yes, we have a lot of information, but now these algorithms have been over optimized to continually show us the same thing. And so our goal is to break out of that echo chamber and help individuals see leaders in this space, people working in this space, the job opportunity, the skills that you need so that they can see themselves in this role, if this is something that resonates with them.

Sadie St.Lawrence (00:39:37): So I love the saying, you can't be what you can't see. So our whole goal is to provide that awareness to be able to see that role model. So we do this through webinars, chapters events, podcasts, highlighting our members in the community. Really just trying to break down those barriers of what it means to be a woman working in this space. And then the third thing we do is on the education side. Awareness alone is not going to get us to where we want to be. We all need to be continually up skilling and re-skilling. So for this, we provide learning pathways where individuals can select their career journey that they want to go on or can select some skills that they want to learn to up skill and re-skill. And they get paired into small study groups to be able to complete these certificates. They also do residency programs where they work on projects for companies or nonprofits. And then also do portfolio builders, datathon, lots of different things within the education space.

Sadie St.Lawrence (00:40:38): And then on the empowerment side, what we've seen is that as you become aware of the opportunity, as you start to up skill and re-skill, we all need support. Whether it's entry level job, whether we're a director, whether we're even a chief data officer, I think there's so many times a lot of us feel we're missing that sense of belonging and sense of support. And so for empowerment, we have mentorship programs and life coaching and do a lot of empowerment through our community, which we have an executive data forum and community groups for data visualization and interview prep. So from the empowerment side, it really is about that network of connectivity where you can find that support and belonging.

Rob Collie (00:41:24): That last one in particular really resonates with me. My career ended up being in some sense, almost like a sociologist that studied a particular demographic and that demographic was and it really even is still to this day, what I call the V look up and pivot crowd in Excel. And those people are awesome. They're my favorite people in the world. There's tens of millions of them. But they're also, unfortunately all alone. They don't have a conference. They don't really have a community. Tech has to reach a certain level of perceived sophistication for a community to coalesce around it. Power BI has a community. SQL Server has a community. SharePoint has a community. All these things from Microsoft. Excel doesn't really have a community. It hasn't coalesced in the same way. And so there's all these people out there that are so similar to each other and struggling with the same sorts of things and they almost never get group bonding.

Rob Collie (00:42:24): I noticed this when for a little while there, we would do these social go out to dinner as a group events on the middle night of our Power BI classes. And by definition, at that time, if you were taking our Power BI class, you were currently a V look up and pivot person in Excel. That was the only demographic that was breaking in back then. And that would be their favorite part of the two day class was finally for the first time mingling with their own tribe for the first time ever. And they said, "Listen, don't take it as a slight. We love the class, but the outing was the best." So coalescing a community around any oasis or beacon, I get it. It helps people a lot.

Sadie St.Lawrence (00:43:08): Yeah. I think the majority of the world is run on V lookup. So I think it's time now that we give it the awareness and support that this community needs. I'm already thinking, we need a power pivot group within Women In Data for all those power pivot V lookup people out there, because it is an opportunity to connect. Nothing is more exciting than to have a tool or an algorithm that you love to use and be able to just nerd out about it with other people. I'm sorry. My family is not asking me about the cool things that I did in Excel, the new algorithm and dive into the details. So it's opportunity for us to really dive deep into those conversations. And it's so valuable in terms of learning from one another, exploring new ideas ... I mean maybe how you pivot is not how I pivot and there's some opportunity to learn how we can pivot together.

Rob Collie (00:44:11): Let me point you to the Twitter arguments about whether or not the compact access feature of pivot tables that I helped introduce in 2007 was either a good thing for humanity or the ultimate evil. There's some very passionate opinions.

Sadie St.Lawrence (00:44:28): And where do you stand?

Rob Collie (00:44:29): I was part of helping add that feature so my past history indicates that I was on board for it. I'm still on board for it. This is that humanity thing again. You've got to be careful in anything not to just cater to the expert end of the spectrum. And the people who are religiously opposed to the idea of stacking multiple fields nested under each other in a single column like a human being would want ... Most human beings would want. Like don't eat tremendous amounts of real estate. Let me see as many columns as I can. Let me see the nesting underneath each other very clearly. These are good things. The people who are in favor of that aren't opinionated. They don't even realize that there's even something to worry about. It's like the argument over don't make dashboards with a dark background because human beings can't perceive information off of the dark background as readily as they can off of a white background.

Rob Collie (00:45:23): That's a very academic and I think truthful fact. But engagement ... So this is my argument on that is that people's engagement with the dashboard is part of the funnel of whether or not they absorb information. And if they think that the dark dashboard is cooler, they're more likely to lean into it. And that's going to drown any of the cognitive advantage of white versus dark perception. Again, that's me. I'm more of a populist on these sorts of things as opposed to the ivory tower sort. And so the ivory tower. And some of the people that I'm arguing with, it's all tongue in cheek. We're friendly with each other. I'm pretty firmly rooted in the commoner, not so much the ivory tower.

Sadie St.Lawrence (00:46:04): Yeah. But I think the dark dashboard is such a great example because it also is important for us to remember that there's research that happens. And then it becomes this common opinion. Don't use dark dashboards. But the great thing about science is we continue to find new things and new discoveries. And sometimes there's a new discovery out there that finds, but actually the dark dashboard works really well for these types of people. And so I think it's important that whenever somebody just throws a blanket like don't use this, it's important for us to dig a little deeper and question that because in your dark dashboard argument, I am aware that for people with disabilities, having a dark background with white text is more accessible to them. So I think it's always important that whenever we hear somebody like, yes, no, black and white, there's got to be gray area. And let's talk about-

Rob Collie (00:47:01): That nuance again.

Sadie St.Lawrence (00:47:02): Let's talk about the gray area, because that to me is the space of interest in where we find breakthroughs.

Rob Collie (00:47:09): Yeah. It's where the good stuff is. We have a saying in our house, don't get caught in the binary thinking. So often when you have a sentence that you want to split the two halves of it with the word but, it's really and that's more accurate.

Sadie St.Lawrence (00:47:26): Or or.

Rob Collie (00:47:28): Yeah. Exactly. Decisions end up being binary. There are a lot of things in life that when you vote with your feet, it is a binary decision. But the reality that you're mining to make that decision is anything but binary. It's like coalesce your own binary decisions out of the gray scale and that's an art. It's important and it's fundamental to being a human. But that binary, Scantron world, it looms large over everything. So membership. This is a soft ball of a question. First of all, is there such a thing as being a member of your organization?

Sadie St.Lawrence (00:48:09): Yes.

Rob Collie (00:48:10): Is there a membership?

Sadie St.Lawrence (00:48:11): Yep.

Rob Collie (00:48:11): What is of the minimum skill or experience required for becoming a member? Someone wants to explore it, maybe sign up. They're asking themself right now, am I skilled enough and experienced enough to belong to this organization? What's your answer to that?

Sadie St.Lawrence (00:48:26): Well, that's a great question. It's one that comes up quite frequently. And I would say there are no skills needed. What's important to becoming a member is that we have the same values. A lot of our members who we classify as data citizens. They're not people who work in a traditional data career, such as an analyst, data scientist, machine learning engineer. They're individuals who are curious about data and want to learn more and want to become more aware of the skills of how you can work with data. So fundamentally within Women In Data, we say all are welcome. Anyone who wants to be part of a community, wants to learn from others, wants to support individuals are welcome.

Sadie St.Lawrence (00:49:11): So no skills. What's important here is that we share the same values. So obviously me sharing that all are welcome, that is a value we have. Another value we have is that we all share knowledge. So this is not somewhere you should come in to get all the knowledge from other people and then leave. Our goal is that you get knowledge and then you share that back with someone else. Additionally, it's important for us to cheer each other on. So we want to make sure that when we talk about empowerment, we're empowering ourselves and others, and then last but not least, we want to make sure that each of us are leading and then creating opportunities for others to lead. So no skills needed, just same values and vision.

Rob Collie (00:49:54): Okay. I like that. And of course, some version of that was what I expected. I didn't expect the values part to be so clear. So I definitely did learn something from your answer. And this is self-selecting. It's not even a requirement. Curiosity. Curiosity about this space. I actually think curiosity is almost a prerequisite for even being in data. That's the filter. The best jokes are true and I have many of these jokes that I've learned over the years. Everyone eventually collides with Excel. If you think of everybody as just random particles bouncing around in society, eventually there's going to be the spreadsheet collision. And most people bounce off violently. They go back the other way faster than they came in. But some people stick. I just call it the data gene and it can lay dormant forever until it's discovered. Whatever it is, it cuts across demographics so perfectly. You find it everywhere. It is a minority of the human population. I've even done a little accidental research on this. At most, it's one out of 16 people. That's the top end for data gene in the population, but still we're talking about potentially 6% of humanity. That's a lot of people.

Rob Collie (00:51:09): And the values. Sharing, helping. There's a demographic out there that I call nerd bullies. People who are bullied in school growing up, and then they turn around and now use their newfound nerd powers to just perpetuate that cycle. And I saw a lot of those in mid '90s, late '90s Microsoft. Often in positions of power. So I'm assuming it's not necessarily explicit, but no nerd bullies. Sounds like it.

Sadie St.Lawrence (00:51:42): I love that term. I've never called it that. When I first entered data science, I called them the high priests of data science. They were these ones that I saw who I think were referring to the same thing of the nerd bully. Had finally found their space in the world. And unfortunately, probably weren't treated the best in high school or in school and now decide to treat other people that same way. And that's just not how we make progress. The nerd bully is maybe a new term that I have to steal or borrow with accreditation.

Rob Collie (00:52:14): Feel free. It's open source technology.

Sadie St.Lawrence (00:52:18): Open source. Great.

Rob Collie (00:52:21): You don't need attribution. It's fine. I think this is one of those positive viruses that we would never want to restrict the spread of this term because it just captures ... Full disclosure, middle school was hard for me. I mean, people were awful to me. Maybe you've seen Tim Minchin's graduation speech where he talks about you really can't take credit for who you are. Whatever it was about me that I think mostly decided ... At least mostly decided later in life, no, I'm not going to do that. I'm not waiting for my turn to be the bully. But I've run into a lot of people who did. And for me, it's one of the worst and deepest levels of betrayal. You can just see it in them. Yeah. You were right there being stuffed in the locker next to me. And what are you doing now? Anyway, nerd bully. Yeah, don't be that. So what have we not talked about that we should?

Sadie St.Lawrence (00:53:19): I don't know if we should talk about it, but I'm really curious. I know it's not me interviewing you, but I'm so curious because you said you had to almost relearn everything because you went so Scantron route. And I'm just curious from your perspective, what that experience was like, but also I see it a lot with data people too. They come in just learning tools and then forget that they need all these soft skills. And I'm wondering if there's a correlation between those two things of when you try and over optimize for a Scantron and then realize, oh I got to rethink this whole problem.

Rob Collie (00:53:54): I think it's fair to describe me in my teen years and into my 20s, essentially as a refugee. Crushing anxiety, probably undiagnosed ADD, probably some form of undiagnosed autism or Asperger's or something. On the outside, I didn't look that way. People could look at me and go, oh, he doesn't have any ... Oh yeah, I did. And it just didn't work is the problem. You go out into the business world, even somewhere at Microsoft. So I wasn't a developer. If I had been a programmer, if I had been a developer, I think the runway would've been longer for continuing on that same course. But I didn't choose that because it didn't really appeal to me. And I wasn't very good at it to be perfectly honest. The difference between skill and enthusiasm is often an arbitrary distinction. I just didn't care about writing C++.

Rob Collie (00:54:48): So instead I chose to be a product manager at Microsoft, which guess what? Is the human zone. And it's just mind boggling looking back that they let me do that job at that age and being the way I was. The first project I worked on actually worked for that. It was the setup engine, the MSI setup engine that installs some vast percentage of Microsoft and windows software today. The setup engine that they let me supervise. No one else wanted the job. But then I found my first real job. After that I changed product teams and I was working on a real product that had real human users and all of that. And I was just bad at it. Just bad. It beat me up badly. The caterpillar who goes into the cocoon, it turns into this mush inside, before it emerges as a butterfly. It took me down to mush.

Rob Collie (00:55:44): It squashed me. And then I had the good fortune of running into a couple of ... One accidental mentor. He didn't realize he was mentoring me. You know how if you publish a machine learning algorithm, super sophisticated machine learning algorithm, as an interface, someone else can come along and use your algorithm to train theirs. You can clone it. You can clone it by using the published one. So that's what I started doing with this guy, Zeke, that I worked with. He was very successful and he was good. And over time I started to slowly understand and allow myself to believe that he was. For a while. I tried to convince myself that no, I'm just as good as he is. No I wasn't. Playing the game in my head, what would Zeke say developed systems in my brain that weren't there before. Just trying to emulate someone else even when they weren't in the room, turned out to be very valuable.

Rob Collie (00:56:38): And then later I had a manager who's been on this show, David Gainer, who explicitly said about being my mentor and was perfect. He was just perfect for me. He did so much for me and forced me to play the what's Dave going to say game. I really feel like it was starting from zero learning a completely new operating system. And when you're so impoverished in this way, and you're mimicking others in some weird ways, you can actually be a better version of them than them sometimes because this comes effortlessly to them. To mirror it, you have to start to try to extract what the essence of it is and develop principles and things that they just intuitively knew. And the fact that Microsoft gave me both the beatdown that I needed, but didn't fire me and kept me around. It took about probably about five years to complete this transformation. It's always continuing. If it had worked, I would've never changed. Didn't work.

Rob Collie (00:57:41): I think a lot of what we saw in terms of the Microsoft culture, not all of it, but a big part of it was that it did work for a long time for a lot of these programmers who then ended up again being promoted again and again and again. There still was something off about their personalities. There's no reason to be mean. And a lot of them were.

Rob Collie (00:58:01): But Microsoft eventually created the product manager position because they started to slowly recognize that the best programmers didn't make the best human deciders of what the software should look like and how it should operate and all that stuff. So you can think of it as I was a bad programmer who got repurposed as a product manager and was given time to grow into it. I see this everywhere. I think a lot of people who were good at math, good at the STEM fields and things like that ... And that was one of them, this is a transformation that sooner or later comes for us because the real world just doesn't play that way. It isn't math. If the real world is math, it's math that is so complicated that none of us could ever do it.

Sadie St.Lawrence (00:58:41): I think there is math in the real world, but I think so often we miss just the applications of that. And that's what I see happen a lot in technology is we need more bridge builders. More people who are going to be that bridge between the math to the solution. Product managers, program managers. Now we even have data product managers. I think that's why they're so essential is to me, they're the bridge builders. They probably were good at math or some stem, but just didn't resonate with them anymore. To me, I'm like, we need so many more bridges because that's how we get rid of the nerd bullies. We build bridges to get more access ways and access points into society and into this and say, "Okay, I'm sorry, troll. We're now taking over this bridge. You do not own it anymore."

Rob Collie (00:59:29): That's right. I was going to make the joke, we have to build the bridges so that we can throw the bullies off of it.

Sadie St.Lawrence (00:59:39): So we can be our own trolls in the bridge.

Rob Collie (00:59:43): That's right. Yeah. You're not going to gate keep, I'm going to gate keep. That wouldn't be progress.

Sadie St.Lawrence (00:59:50): No, no, no.

Rob Collie (00:59:52): Well I've thoroughly enjoyed this. Our organizations met through no effort of mine.

Sadie St.Lawrence (00:59:58): Or mine. I will say that too as well.

Rob Collie (01:00:01): We've been on a very interesting journey. I've said this so many times on this podcast, but it's a story that bears repeating is that I was seeing this breakdown of greater than 50% females in my classes and then looking at the applicant pool we were receiving and seeing like 95/5 men. And this is very disappointing. It wasn't that too many men were applying. It should be 95, 95. 190 should be the total.

Sadie St.Lawrence (01:00:29): Yeah. You don't have a cap on your application system that says we can only have 100 people apply for the ... As many people can apply can.

Rob Collie (01:00:37): As we grew our team on what we call the grow div side of the company, which is most people think of as marketing. I just have a preference for verbs over nouns. They're less ambiguous. As recruiting became part of our mission over time, it was very clear one of the places that we can almost cheat code our recruiting would be to remove this imbalance because we're missing nearly half the population. Christi on our team ... This problem is on the way to being fixed. We're still not 50-50. We're doing much, much, much better than we have historically. And it's always hard to attribute these things and know exactly what confluence of factors is making a difference. Christie on our team went through the language on our job pages and stuff. Most of which I had had written at one time or another and I really don't want 95-5 right?

Sadie St.Lawrence (01:01:36): Yeah.

Rob Collie (01:01:37): It's like these unknown unknowns. The things you don't really think about. Christie went through and identified all these places where I was accidentally using language that would disproportionately appeal to other men. And as she pointed out, I'm like, "Okay, right." Now that I know, it's almost embarrassing to talk about. Things like you'll be on the front lines of data. No, no, it's not a combat Rob. Combat's not even my thing. And so as part of that initiative, we went looking for ... We, not me specifically, but our team went looking for ways that we could make some additional outreach. Under that umbrella is how our organizations met. One of the things I say about our company is so often people choose between being good at business or being a good human. It's the and right?

Sadie St.Lawrence (01:02:30): Yeah.

Rob Collie (01:02:30): No, be both. I think this is both.

Sadie St.Lawrence (01:02:34): One of the best mentors I ever had, his big thing was we do well. So we do well as a company. Drive revenue, all of this. So we can do good. And I just was like, yes. That's simple. It's straightforward. We got to care about the bottom line, of course, but we're going to use that to be able to do good. And I love the journey that you guys have ... I'd love to have you on our podcast too, to discuss what you found and I think just your vulnerability in the space of, I had no intent to be on the front lines of data. But also why we need diverse people in our audience reviewing things. Because I do those things all the time. I put in a job description to have mastery in this skill. Well, mastery is not one that resonates with a lot of people.

Rob Collie (01:03:29): Yeah, mastery scares me.

Sadie St.Lawrence (01:03:32): That's why it's so important to have people on our team and different mindsets coming in to review and look at things. And I think it's super exciting what you guys are doing and I'm excited to see where some of your diversity stats are in a year or two. I know all the changes that you're making are going to pay off and not only for the people at the organization today, but also for the long term success of it too.

Rob Collie (01:03:56): Well, I certainly appreciate that. I'd love to be on your podcast. When the time came to nominate someone from our side, it was like, oh, should, we send the man?

Sadie St.Lawrence (01:04:08): So you know what's funny? We've talked about gate keeping and Women In Data has always allowed men to be a part of the organization. Some chapters have a lot of men come to their events and meetups. And it was a very conscious decision because I thought if we are keeping men out, then that's the exact same action that got us to this point. And we're not going to make progress with the same actions that got us here.

Rob Collie (01:04:40): Well, Sadie, it has been a real pleasure meeting you.

Sadie St.Lawrence (01:04:42): Same.

Rob Collie (01:04:43): Thanks for making the time for us.

Sadie St.Lawrence (01:04:44): No, thank you.

Speaker 3 (01:04:45): Thanks for listening to The Raw Data by P3 Adaptive podcast. Let the experts at P3 Adaptive help your business. Just go to p3adaptive.com. Have a data day.