Alter Everything

A podcast about data science and analytics culture.
Alteryx Community Team
Alteryx Community Team

We're joined by Leah Knowles, Michelle Kosmicki, and Christine Bonthius for a chat about their experience working in the private vs. public sectors, Women of Analytics, and tips for breaking the mold.





Leah Knowles @LeahKLinkedIn, Twitter
Michelle Kosmicki - @MKosmickiLinkedIn, Twitter
Christine Bonthius @ChristineBLinkedIn



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Episode Transcription

BRIAN: 00:00 

Hey, everybody. Happy 2019. Brian Oblinger here. Before we get this show on the road I wanted to take a few moments to say thank you. First of all, thank you to you the listener. Without you, this show doesn't happen. There's no way that they're going to let me continue to do this if you guys stop listening. So please keep listening [laughter]. But seriously, thank you so much. The feedback and the reception that we've got has been just tremendous and anything beyond what I think any of us thought it was going to be. So without you, this doesn't work. I also want to say thank you to the guest hosts that we've had. We put out 23 episodes last year of the podcast. Several of them were hosted by people that were not me. People that are probably way smarter than I am and were probably better to listen to. And without them also this show doesn't happen. So thank you to all of them. You'll be hearing some awesome new guest hosts this year as well. So stay tuned for that. And last but not least I wanted to say thank you to Maddie Johanson. So if you don't know Maddie, she's been on a couple of the episodes so far, but she's really the one that's behind the scenes doing the heavy lifting here. She's co-ordinating guests, she's doing the logistics, she's doing the show, she's sending microphones around the world so that we can get this great audio for you. And so a lot of the due of the success of this show should go to Maddie. So wherever you're at right now, if you're out walking your dog, you're on the subway or you're in your car, you're at your office listening to this, whatever, just do me a favor and say thank you to Maddie because she does a wonderful job and the show is great because of the work that she puts in. 

BRIAN: 01:37 

And last but not least, before we get on with it here, I do want to say you probably saw some different artwork on your podcast player and that's because at Alter Everything, well, we're all about altering everything. And we thought, "Wouldn't it be cool if we just keep this thing fresh and in the spirit of our theme throw some new artwork at you, throw a new awesome theme song at you?" So last year we had the rock guitar riff. We went in a little direction which when I get done gabbing here in a minute you're going to hear all about. And I'm just really because we have this huge guest list lined up for this year. So stay tuned, tell your friends, help us promote this thing on social because we're about to take it to the next level. Let's do it [music]. 

LEAH: 02:34 

Welcome to Alter Everything: A podcast about data science and analytics culture. I'm Leah Knowles and I'll be your host. We're joined by Michelle Kosmicki and Christine Bonthius for a chat about their experience about working in the private versus public sectors, women of analytics, and tips for breaking the mold. Let's get into it. 

LEAH: 03:05 

All right. So I am very excited to be hosting the Alter Everything podcast for the first time. For those who don't know me, my name is Leah Knowles. I work with and for Brian. And today we have two very special guests on the show: Christine and Michelle. How are you guys today? 

MICHELLE: 03:28 

Doing well. 


I'm good. How are you? 

LEAH: 03:31 

Fantastic. So in typical podcast form, I'd like to start with a roundtable introduction. And let's go ahead and start with you, Michelle. Maybe a bit about yourself, where you come from, what you do. 

MICHELLE: 03:47 

Sure. I'm actually sitting in the middle of the country right now in Iowa and I'm working as a senior marketing data analyst but I've lived most of my life in the middle of Nebraska. So I moved just a little to the right on the map to continue my data science journey. But I have a background actually in what is known as the soft sciences - so psychology and education - and somehow through that, I've ended up in data science. 

LEAH: 04:16 

Awesome. And Christine? 


Yeah. It's great to be here. My name is Christine Bonthius. I'm a senior instructional designer here at Alteryx. A little bit about my background too is I have a similar background to Michelle in that kind of soft sciences. I come from a background of geography which doesn't normally lead itself here to this world of data science but here we are. My journey here at Alteryx is I started here as a customer support engineer where I really started working with our customers to help resolve some of their technical issues whether those were big or small, whether that's editing a simple expression in a formula tool all the way to reviving a server and making sure the gallery is back up and running. And about a year-and-a-half or so ago I transitioned here to the community learning team where I am in charge of creating engaging and informative learning experiences for our Altrex users. 

LEAH: 05:04 

And for those who don't know, Christine and I are on the same team here at Alteryx. So I get to see her smiling face every day. 


Lucky you [laughter]. 

LEAH: 05:14 

So yeah, lucky me. Michelle, I was curious to hear a little bit more about your career progression and kind of how you got started in analytics to where you are today. 

MICHELLE: 05:30 

Well, just like every good superhero, every data scientist has an origin story. Mine started a long time ago in undergrad when I took my very first statistics class. And the professor was well-known for actually not supporting the women who took his class especially the ones who wanted to go on in the analytics vein of things and research. And there were two levels to the class. So he would try to wash as many women as he could out of the first one so they wouldn't go to the second one. And all you have to do to make me do something is tell me, "No, you can't do that. Not possible. I'm not going to let you do it." And, of course, I burned through that class and got an A. Took the second class, got an A [laughter]. And at that point, the bug had bit me and I was very deep into clinical research at that point in the psychology program, and then moved onto to psychometrics in my educational science program at the University of Nebraska. So started off with kind of humble beginnings there but then ended up working in government for about 16 years or so for Nebraska state government in different departments. Usually the sole researcher or data scientist. Back then we weren't data scientists. We were analysts. We were statistical analysts. No one really wanted to call us data science at that point yet and there was a definite divide between those who programmed and those who did research. But as time has moved on, that line has definitely blurred. I've picked up a few programming skills here and there and now I don't have to rely on that as much because I have Alteryx. So... 

LEAH: 07:27 

That's fantastic. Christine, do you have anything you'd like to share about your career path and how you kind of, I guess, caught the Alteryx bug as they say [laughter]? 


Yeah. Sure. I mean I had to admit, ending up where I am now or in this field where I am now wasn't necessarily what the goal-- this wasn't the goal. This wasn't the end I had in mind. In fact, I was on a track much more in the social sciences originally like I mentioned before. My educational background is in geography which most people don't necessarily associate with being very technical but I was actually, even myself, very surprised. As you progress through this world in higher education of geography it surprisingly becomes very technical very quickly especially if you engrain yourself in this world of GIS - geographic information systems. And that's kind of how I ended up where I am now is in my time in higher education, specifically in graduate school, I had the opportunity to get into teaching. And that's where I discovered that I really loved teaching GIS. I loved the world of teaching and I loved teaching computers which is kind of a strange combination. And so that's actually what got me thinking about, "Well, is there an opportunity somewhere to do what I love?" Which really was research. I really did enjoy my time as a researcher, but how can I also integrate that with my love of teaching and my love of technology? And that's what got me started on this path of looking at where there are other opportunities to just work with data. And I happened to stumble upon Alteryx and I just fell in love with the software itself, and I love teaching it, and I love helping other people learn it too. 

LEAH: 09:15 

So, Christine, what is a, I guess-- and I'm not sure if I'm going in the right direction here. But if you could name one of your favorite projects that you worked on with data what would it be? And then I'm going to ask you the same question, Michelle. So noodle on that for a second. 


Yeah. I would say one of my favorite projects that I've worked on with data comes from before I had started working for Alteryx. And that was when I was working for-- my time as a state employee for the state of Texas where I used to live before I moved to Colorado. I worked for the state office of Parks and Wildlife in Texas and I was tasked with a project-- I was working for inland fisheries - inland waters and fisheries division - and I was tasked with this project working with this really ambitious, pretty young, other female researcher, lead biologist in the department who really wanted to find a way to create a very data-driven decision-making model for figuring out where fishing permits should be issued or where they should not be issued in the state of Texas. So we took all these fishing surveys all the way back from probably the '70s. A lot of them were just on paper. So we spend a lot of time [laughter] manually entering this data and creating this data for ourselves and then creating those kind of geographically-based raster model of figuring out where hotspots for presence of invasive species might be in Texas or where the presence of endangered species would be in Texas. So that would help us-- or that would help inform our decisions about, "Well, what's the likelihood of issuing a permit to this person and what's the likelihood of the fishing impact or the gravity of the fishing impact on other species that we know are present in these inland waters. I would say that was a pretty interesting project. Not just because inland waters and fish are interesting, but also because we had to come up with this pretty innovative approach to integrating just tons of different data sources from all over the place to create this new, novel approach for helping with environmental decision-making. I thought that was pretty cool to be a part of that. 

LEAH: 11:42 

That sounds exactly like you, Christine. Only you would find inland waters and fish interesting [laughter]. For sure. 


It is a special interest I will say. 

LEAH: 11:58 

What about you, Michelle? What's your favorite project that you've worked on with data? 

MICHELLE: 12:05 

There's probably a lot of different ones. Before I moved to Iowa I worked for the public radio stations in Nebraska. And so through that, I had the opportunity to work on a wide variety of really interesting projects. But I think my favorite one that I like to tell people about and I love to bring up most in job interview is I worked on a project with one of our journalists as Colorado was legalizing marijuana. And we pulled data out of the crime commission, we pulled data from several different sources where we were finding out how law enforcement was dealing with the influx of marijuana coming from Colorado, how they were preparing for it, did the feel they were prepared. And this was before recreational became legal. This was only medicinal was available at the time. And I created surveys that we sent out to county attorneys and all the sheriffs' departments, in every county in the state of Nebraska and I compiled all that data, built some visualizations around the data and our journalist was very kind to give me a byline on that. So I actually have an official story out there with my name on it out in the NPR world which is kind of funny but it also ended up being a half-hour special program that our station produced in Nebraska. So it was a lot of fun doing that project but I still tend to look over my shoulder a little bit when I drive Nebraska because I'm still afraid the state patrol is going to pull me over [laughter] because of my work on that project. Because at the time there was a little bit of discourse between what the sheriffs' departments and local agencies were seeing closer to the border versus what we were seeing all the way on the eastern end of the state. 


So can I ask a question about that? Sorry, Leah. I don't mean to go off-script-- 

LEAH: 14:13 

Oh, no. No, please do. 


--or anything but what you just said, Michelle, I think is really interesting. It's something I've been thinking about kind of a lot recently is this integration and this mix of journalism and data. And when does the line-- is there such a thing or should there be a thing or does it exist, data-driven journalism? How do you think that landscaped from your work as a data analyst and having worked with the journalism field a little bit? What's the mix there? What's our responsibility or what could be a role for data analysts in this world of trying to talk about truth or tell stories? 

MICHELLE: 15:01 

Well, a lot of what I saw happening working for the station is that we actually had some journalists there that were pretty data-savvy. So they were able to look at different data sources and understand where the data was coming from. But overall, the larger discussion really needs to be around data ethics. You can get your hands on so many different types of data. There is so much data that's publicly available. You can request data from the state government, from the federal government. What you do with that information though is a totally different story. You have to be very careful when you interpret that data and process that data because if you publish something that is not quite true, maybe you weren't familiar with the subject area-- which is unusual. Most journalists are very deep in their subject areas. But if you misrepresent something in that data it could impact a lot of people especially when you're looking at public policy and that's something that as our young journalists are coming out of journalism school some of them have background where they've taken extra data classes. Sometimes it's been actually taught in the journalism courses. But there really needs to be almost governance on it. More of a deep dive into the ethics behind data and use of that data especially in reporting on. You're reaching a lot of people across the nation and even around the world. 

LEAH: 16:37 

Have you ever faced your own, I guess, data ethics challenge as you were looking to report on something yourself? Have you ever come across that? And how did you deal with that? 

MICHELLE: 16:57 

I pretty much had a very hard line that I drew. I protected my participants. Anybody who participated in any type of research that I had or if I was given data that had identifying information in it whether I was working on someone else's project or my own, my main goal was to protect the people that were part of that data source and nobody had access to that data but me. I pretty much put a moat and a brick wall around everything I worked on because it was very important to me that the data was protected, the people participating were protected, identities were protected, and that I could take that data and build it into data that was going to be helpful and not harmful. Occasionally, the results did show that there might be harm and then partially I had to tell those stories too. But it's something that you learn when you work with data, especially through education and psychology. There's a lot of sensitive data. The stakes are usually pretty high. And sometimes when you're processing that data you find things that we call unintended consequences and those are almost a bigger story sometimes than the actual results you were looking for. But that's when the ethics comes in. You have to decide who to report it to, how to report it to the people in charge so that you're not causing more harm. 

LEAH: 18:46 

Absolutely. It's interesting. And not to get too far off-topic here, gosh, it must've been over a year ago we had posed a question to our community similar to the same topic but it was more geared towards personal data and what types of things community members had come across in their careers that they had second thoughts about. Like, should we really be collecting this? I guess that opens up a whole other can of worms which we don't necessarily need to get into now but it's all very fascinating [laughter]. 

MICHELLE: 19:36 

Yeah. I was actually listening to HBR: After Hours this morning and part of the discussion was 'how much data is out there that's being used by marketers'. And when you really sit and think about how much data's been available about what you do on a daily basis I would suggest not sitting down and thinking about that very long because [laughter] it will push you over the edge pretty quickly. But there's a lot of data out there that people don't even know is being collected and it's-- yeah, ethics are a big deal right now. 

LEAH: 20:09 

Absolutely. And we'll be sure to scrape the community to find that thread again. It was a while ago but we'll link to it in the show notes. So one question that I think would be interesting for the audience and our listeners since both of you have some experience working in both the public and private sectors, curious to hear about that experience and if you've noticed any cultural differences between those two spaces. 

MICHELLE: 20:45 

Probably my experience between the two when I worked in state government I was always the only person on my team. There wasn't a lot of backup. And other than that the one thing that's vastly different, whether you're in a small department in private sector or in the government sector, when you're on a team by yourself it gets really lonely because there's no one else to talk data to or statistics or just bounce ideas off of. And it's really difficult. Now it's probably not as bad because we have things like the Alteryx community where I can out if I have a question and I can bounce it off somebody. But there might be occasions where-- now I have one person on my team. I worked in other private sector companies where there were five or six of us on a team and it was nice to just walk next door and say, "I have an idea. Can I bounce this off you?" But having the community there that kind of gives me that same presence. But, boy, when it came to conference time and got to be around my own people for a whole week, I pretty much shut off my work email and say, "Don't bother me. I'm with my people." 

LEAH: 22:08 

And, Christine, can you comment on your experience working in both the private and public sector and any cultural differences you've noticed? 


I would say a couple of different things have probably been brought to my attention in my experience between the public and private sector. For public sector, I've worked for both federal and state levels of government. And then private sector I've been pretty much in the software industry. I think two things really have-- I've noticed two really big things. And one is that the transition between-- or I'll just say in the public sector, in my experience, in particular, it's been much more male-heavy. We can always edit this I suppose but it always felt a little more like a boys' club in that there were always male-dominated leaders in our field and there were always male leadership. And it really wasn't until I worked at the Texas State Parks and Wildlife Division where I was working with, as I mentioned before, a young, ambitious, female biologist who was really driven to kind of break that mold. She was someone who wanted to be out in the field collecting the data, analyzing the data. Whereas it was actually pretty rare to see another woman taking on those type of responsibilities. So I was really lucky in that I got to work with her, and kind of have that perspective of what she was trying to do. It was hard. It was tough and she got a lot of pushback. But I think she's been really successful there in really transforming some of the practices and some of the ways that now that division looks at data, takes on projects, and communicates the results. 


I would say that's another big thing that I've noticed between public and private sector is this willingness to take risks or this willingness to innovate. I understand why public sector organizations tend to be a little bit more entrenched in some of the ways that things have always been done because they've always been done that way and that's what gets funded and I understand that. But one thing I have appreciated about my experience here in the private sector is that we are given a lot of freedom and independence to innovate and do things differently that other people might not have the opportunities to try. 

LEAH: 24:54 

Absolutely. Michelle, can you relate to anything of what Christine has commented on in terms of the private and public sector or even the different opportunities to innovate? 

MICHELLE: 25:09 

Oh, yeah. Absolutely. Even though I was doing a lot of innovation at my job at the state, every job required a little bit of something had to be creative. I did a lot of creative work on every project because every project was different. But in the private sector, you're looking to innovate. At least as I've worked in the field of marketing and research, you're always looking to innovate your product and evolve it and make it better. The same is probably true in the software industry. So there is innovation as part of the job and that makes it fun, it make it interesting, it makes you want to go to work every day because there's never a day where nothing is happening. There's always something that you can reach in there and grab onto and put together and innovate with. But the other thing that Christine was talking about was that it really can be a boys' club. A lot of times it's very difficult to get your voice heard because you're a woman in the room. And I haven't experienced that type of thing that much recently where I'm living now, but my first round in the private sector right out of college definitely. Absolutely. And even when I first got into the public sector that existed a little bit because there weren't a lot of women in Nebraska that were working in technical positions or science type positions or data science or research. It was mostly men in the higher-up levels doing that. 

MICHELLE: 26:58 

And so it was really hard to get your voice heard. But once you got on the map then people would come to you with their questions: whether they needed something put together, whether they needed you to take on a project because no one else had time to do it. And that's the other thing, if you're the woman in the room, you're going to get piled on. All the projects that nobody else wants to do usually end up on your desk. So learning how to say no is a big deal. Men can say no whenever they want to. They can say, "Oh, no. I've got this project. And, oh, wait. I was going to go golfing. Oh, wait. I was going to go to somebody's baseball game [laughter]." But women just basically just have to take everything that's put on their desk because the fear is if you say no you're not going to get that promotion. You're not going to move forward in your career. Someone may not come back and give you another opportunity because you said no. 

LEAH: 27:53 

Yeah. Absolutely. I can definitely relate to that, and I think a lot of our listeners can as well. So if you had any advice to share with the women of analytics community about how to go about really advocating for yourself and your successes or accomplishments, what would you say? 

MICHELLE: 28:23 

It's really difficult to learn to be your own cheerleader sometimes. I actually have trouble being my own cheerleader and my mentor said-- my current supervisor's coaching me a little bit. She like, "We never hear from you what you do. We hear about it from other people all the time. We need to hear it from you more often." And I think it's a hard thing to learn. It might be generational for me. When I grew up it wasn't something that we-- you didn't go around bragging about yourself all the time in everything you did. Now, younger generations, everything's out there. You know what everybody is doing. They're proud of everything they're doing. You don't have to really look around too hard to see what people are proud of and what they're doing. So learning to be your own cheerleader, promoting your own projects, it's a good skill to have. It's a good communication skill to have. And it's so important to be able to tell people these are what my skills are. Look at this great project I just finished. I'm really proud of this. Look where things are going. And then to not only promote yourself but then accept any praise that comes your way. And that's also a good skill to have to be able to say, "Thank you. I worked hard on that." Also something I've been working on as well because I tend to be a little more introverted. So I try to fly under the radar probably a little more than I should which makes it difficult than to highlight that I'm a woman in this industry. So it pushes me out of my comfort zone a little bit. 

MICHELLE: 30:09 

And also connecting with other women here in the Des Moines area and across the country who are involved in different areas of data science, analytics, data visualization is very valuable as well. And there's a pretty good strong community here in Des Moines. We have some really good data programs at the universities in the state and colleges in the state. So that helps feed the pipeline quite a bit. And one of my goals is to make things better for the women coming through the pipeline now so that they can get those jobs and get into data science and promote themselves and really do well as they move through their career. 

LEAH: 30:52 

Absolutely. And Christine, what about you? Do you have any advice or stories you'd like to share about where you struggled in terms of advocating for yourself? Or even better, where you found success? 


Yeah. Michelle said a couple of things too that I've been writing down that I'll circle back to in a moment. But I think one story that I have regarding this about what it can take or what it means, I think, to kind of be successful in this field or navigate this field as a woman is-- I had a kind of mentor. A female professor who was a type of mentor when I was in graduate school. And one of these sayings that she would say to me a lot that stuck with me is, "Be unapologetic in your truth." And it's really beautiful and I feel like it should be on some kind of inspirational magnet or something. And I think she meant it in a couple of different ways in that don't let anyone marginalize your experience or don't let anyone kind of discount a story or experience you have to share whether that's uncomfortable or whether that's owning your own awesomeness. And don't be apologizing or don't apologize about the fact that you're correct or that you know what you're doing. I think that goes to Michelle's point about being your own cheerleader in some way. When you know what you're right or you know that you're doing something well, I think it's important that you need to acknowledge that and you need to own your successes. 


Now I think with that comes the caveat-- a nice side dish of humility there. And I think to another point of what it takes to be successful is don't be afraid to say I don't know because I think that's a really good sign of acknowledging not just your limitations, but also understanding that there's more to learn and there's more that you can do. And it's acknowledging, I think, too that-- it's kind of a hard negotiation between-- something that Michelle you said earlier was getting your name on the map. You have to establish credibility. You have to be able to be seen as some kind of the voice of authority and owning your own awesomeness and being like, "Yes, I do know what I'm doing." But at the same time being able to say 'I don't know' is a really admirable quality in that admitting your vulnerability, that there's still more to be done, there's still more to learn. But I think on the third point of that you have both the sides of 'I am awesome but I don't know everything' I think is adding the word 'yet' to all that because you can learn. And I think it's acknowledging that you are capable of getting there with the time, with the resources. It's not impossible. And that you are capable. And I think that kind of trifecta of a mentality is hard for women in particular to own. Because being your own cheerleader, saying, "I am awesome," like Michelle said it's not something that we're naturally prone to do. And for those of us that are a little more introverted, I include myself in that, you're not the first to toot your own horn. 


And then acknowledging or admitting that you don't know everything is again discounting your credibility. And is that a position you want to put yourself in? Not necessarily. So I think that mix of being able to acknowledge your awesomeness, being able to say, "I don't know everything," but then being able to say 'yet' at the end of that, "I will learn. I will get there," is a really important combination of things as a woman, I think, to be able to do in a workplace. And so that leads me another question I had for you, Michelle, as a follow-up is that you said that something that you would like to take on or that you are taking on is that you're trying to make things better for other women who are coming up that ranks in your organization. And I want to know how you are doing that. Or what are you trying to do to make that path more accessible? 

MICHELLE: 35:23 

Not only at my organization. On my team, we have quite a few women in the data space on my larger team. We all have different tasks. But in the Des Moines area where I'm at or even greater Iowa part of what we're doing here, I actually have a group that I set up to bring together all the women that are in data. So it's in the spirit of Women of Analytics or Data+Women, She Talks Data. All of those organizations. In the spirit of that but bringing all of us in the data space together. So we have students that drive in from Ames which is about 30 minutes away; we have students from [inaudible] University, we have women across all industries who are in this group. We don't get together formally more than a few times a year because we see each other-- being in a small community, we see each other all the time at other meetings as well but we have a dedicated space that we can communicate with each other. And that, I think, is really important in helping mentor younger women coming into the industry, women transitioning into industries - whether they're moving from insurance to academia or different types of organizations. Just helping people move through their careers, be competent, providing mentorship, providing sisterhood. Just knowing that we're all in this together, we all have all these experiences. 

MICHELLE: 37:13 

And really I think it'll help support anybody who's coming into the data field whether they're going to be hardcore data science, if they're wrangling the data, if they're analyzing the data, if they've just on the vis-end of things. It doesn't matter. We all need to kind of lift each other up and help move this whole thing forward because there are a lot of interesting things that happen as women in this industry. Some people fly right through it and don't think there is-- just have an easy time of it because they've had good people to help them move up in their career. And if we establish a network of that I think it'll really help everybody. Not only women in the field, but also men in the field really develop their careers and become more effective at what they're doing. If we can all figure out how to move everybody forward. 


Michelle, I've heard you say a couple of times I think in our conversation today something about mentorship. And just to ask, did you-- you said you had a mentor at one point? Or do currently? 

MICHELLE: 38:28 

I currently do kind of have a mentor. And over the years I've had different mentors but not necessarily in the data space. I didn't get my first data mentor until I came to Des Moines. And this person probably doesn't even know they've my mentor which is [laughter] probably okay. But I've had different mentors over the years. Not a single one of them has been a woman which is an interesting point. But also something I've noticed talking to other women across the industries whether you're in data or journalism or broadcast or insurance. I don't care what you're doing. I've found very few women who were in senior positions or executive positions who actually had other women helping them. That's something that needs to change. But the only way it's going to change is to get more women further up in industry. But having a mentor is very valuable if for nothing else to help you talk through career problems, personal issues, questions you might have. It's kind of fun having a mentor that's in the data space because I can talk about things specific to the data space if I'm not sure if it's just something everybody experiences moving through data science as a career or if it's something that's particular to where I'm at right now in my career or my situation at the time. So that's been valuable having someone actually in the data space. But my other renters have really helped me grow. Not only as a researcher and as a data scientist, but also as a person. Definitely grew in my leadership skills knowing these people. 

LEAH: 40:30 

Yeah. I guess another follow-up question for both of you around this topic is it's clear that - and myself included - there is some struggle around feeling like we are almost-- and I'll speak from personal experience. Just feeling like I don't have the capacity to really advocate for myself and it makes me very uncomfortable. And one thing I think about a lot - and, Christine, you and I were talking about this yesterday - is how much of this is a cultural problem? And when I say cultural I mean a corporate-environment-type cultural problem. Versus how much of the responsibility is on us to speak up and change who we are and what we're comfortable with just to get ahead? And I guess the question would be if we could sit down with the business leaders at our company and ask them to make certain changes, what would we expect them to do? How can we as women in analytics have those conversations or even have [inaudible]? 

MICHELLE: 42:12 

I'm not going to answer the question directly right now but I think a kind of peripheral conversation comes back to something that even, Michelle, you and I were talking about a little bit earlier is that there are different personalities, I think, in leadership and I think you and I kind of resonate on the fact that we're not necessarily the most outgoing or cheerleadery kind of type of personalities. We're not going to be the first to kind of go out and self-advocate. And I think that's an important thing to recognize across the board that women are less likely to go ahead and advocate for themselves, but that there's a big value, I think, in having these different personality types in forms of leadership and whether that's kind of the more-- I'll resort to kind of the Sheryl Sandberg kind of approach - the lean-in approach - of you have to be a little bit more maybe aggressive to get a seat at the table. Or maybe you have to be-- but is there value also to maybe a quieter, more self-assured, kind of less traditional - maybe I guess I would say - view of what a leader is. And I think that recognizing those different personality types in leadership and I think that making space for those different personality types in leadership I think would be a huge benefit in helping everybody feel welcome in trying to progress further up their career. In knowing and understanding that your specific strengths, whether it's being the first to raise your hand with a comment at a meeting or not. That both of those are valid in terms of leadership space. I don't know if you have anything to add to that, Michelle, but that was just the kind one thing I was thinking about when I was talking with Lea yesterday is that I wish personalities kind of like mine were a little bit more represented [laughter]. 

LEAH: 44:21 

Yeah. That's exactly where I was going with that question. Thank you for clarifying, Christine. And it's kind of like why do I have to change myself to get ahead. That's kind of-- it's a frustration that I have and I think about a lot and it makes me very uncomfortable. It's a hard thing to grapple with I think. 

MICHELLE: 44:52 

Everybody needs to learn as they build their career that the two things that you absolutely have to have no matter where you're at in your career is communication skills and leadership skills. And if you're an introvert like a lot of us seem to be that is really, really hard to do. And you can read all the books, and you can go to all the seminars, and watch all the webinars, listen to all the podcasts but until you put it in practice you really don't know how good you are at it and you learn really fast whether you're good at it or not, what your skill level is and what you need to build or you need to start over, what you need to change. But you have to be open to that too. So it's just really, really important skills to have, and it can be very difficult. 

LEAH: 45:48 

Absolutely. So another I guess-- and maybe this is a bit of a thought experiment but we're going to go here anyways for fun. So it seems like companies in general, from my perspective, pay a lot of lip service to the value of diversity and inclusion initiatives and I guess I'm wondering what we can do as women of analytics with the skills and know-how that we all have-- I guess what I'm trying to say is what can we do to make sure that what our companies are saying and presenting is more than just words? Or what can we do to contribute to evaluating or even improving the efficacy of these types of programs? And to give a bit more context where I'm going with this is we at Alteryx have our Women of Analytics initiatives which were really putting more time and resources in 2019 and really want to set the example for others to follow and try and solve and provide resources that people need to succeed in the analytics space. And so just looking for, I guess, advice, feedback, thoughts. 

MICHELLE: 47:36 

When it comes to initiatives like Women of Analytics just the fact that it's out there is a huge deal. The initiatives are still really young and I think some of them are still trying to find some direction and how to create impact. Definitely what I've seen with a lot of the initiatives is that we're definitely connecting with women who are more advanced in their careers or maybe higher up in their organizations who are willing to share a little bit of their experience and how they've come to where they are and maybe offer advice to those still coming in. But at the same time, I see reluctance from a lot of female leaders to step into that position and say, "This was my experience. This were the pitfalls I ran into. Here's the advice I can give you." Or even willing to get up and speak about it. Which is interesting because I would like to think that all of us in the space we're all feeling the same challenges for the most part whether you're entry-level or further along in your career and these initiatives are so important into bringing us all together, giving us a larger voice for one, and helping those of us who've been around for awhile bring in that next generation. Maybe provide a path for them to follow that hopefully will be a little bit easier than what we had to deal with. So it's going to be interesting to see initiatives like Women of Analytics, Data+Women move forward as they gain some experience and really become a part of the culture. 

LEAH: 49:49 

Absolutely. Christine, do you have anything to add? 


I have a question for Michelle actually. Is actually why do you think women are so reluctant to share their experiences? 

MICHELLE: 50:02 

I wish I had a good answer for that [laughter]. I'm not exactly sure other than I'm wondering if there isn't just a little bit of a fear in there somewhere. "If I speak out and tell my story of how I got here someone might think that I'm not grateful that I'm here and that my impact my VP status, might impact my senior status." Things like that creep into you, creep into our minds and I think that's something that we have to be honest about too. There's a lot of fear that drives some of our decision-making as women especially in a male-dominated career. So that's something that a lot of people don't like to talk about at all. But I think if we can find a way to really bring these initiatives to the forefront to make our voice a little louder and really - as Sheryl Sandberg would say - get a seat at the table [laughter] then I think we're moving everything forward if we can accomplish that. And hopefully some of the women who maybe they don't think they have anything to offer but maybe we can get more women to come out and talk and share their story and provide some support for those who are just getting into the industry and just starting out on their journey. 

LEAH: 51:37 

All right. So let's go ahead and wrap things up as always with community picks. Christine, let's start with you. 


Yeah. So I picked a little bit of a hodge-podge of a list here. So forgive me if it seems I'm jumping all around the community. In the spirit of some of the things that we've talked about today I think my first pick to share with everybody, share with a lot of our listeners would be our interactive lessons that we have on the community. This is my pride and joy [laughter]. This whole section of the academy with the interactive lessons has been a really big effort of mine in particular over the past year and most recently I'm really proud to announce that my team and I have recently just redone - we just completely gutted - the whole 'getting started' interactive lessons series. And we built it from scratch - from the ground up. And I love to say to people we just re-imagined the learning experience. And I'm really proud to put it out there for our learners, and I'm excited to see what they have to say and how they experience it. And, of course, all feedback is always welcome. I like to hear it all. A second pick of mine that I would like to share is a community article that I've had bookmarked on my homepage in the community for years now, and that is the 'ultimate input data workflow'. It is this really awesome-- or this article that helps you decide the best way to use the input data tools which is stuff put on your workflow typically. But how do you understand, how do you want to bring in all these different data sources? Is it just going to be one input tool? Is there an option to use a wildcard or are you looking at maybe a batch macro input? I think that Alex Koschitzky is the author of that one and he did a really great job in helping you make that decision of the best approach to bring your data in a really nice accessible way. 


Another pick I have is a blog article that can be found in the alternation section of the community. And it's a really cool article from one of our aces [Trayson?] Marks. It's all about collaboration. And I like it because he brings some of these topics to life that we've even talked about today is this feeling of validity in 'I belong to this awesome community'. In this case, he is an ace. But sometimes you might not always feel like you belong to this kind of exclusive club. And so I like the approach he took in saying, "I have this macro I'm trying to build. I'm trying to build out this process. I've done it one way or I'm running into troubles in this or I'm running into challenges in this particular area. Let me connect with my fellow aces." He brings in Mark Frisch, he brings in Nicole Johnson, and Daniel Brun to help him validate and test this really cool macro that he ends up producing and really shares about his experience with collaborating with other experts in the community. I think that's a really valuable lesson and experience to see even from someone that we know is an awesome user of Alteryx. I think it's really cool. 


And then finally, I'm going to bring in our Alteryx for Good initiative. I'm going to bring a charity or kind of initiative that's going on here in Colorado. And that is this initiative that is being run through our member station of Colorado public radio. I told Michelle I'm a big NPR fan girl. Colorado public radio is the first thing that I have on in my car every morning, what I listen to when I go home at night. And one of their big initiatives that I am passionate about is music education in public schools. And so for the next few weeks or so the Colorado Symphony is hosting a few different concerts where you can bring used musical instruments that this initiative called bringing music to life will either repair or distribute to schools across Colorado whose music education programs are badly in need of instruments for their students to learn on. So those are the picks that I would share with our listeners. 

LEAH: 55:50 

Awesome. Thank you, Christine. What about you, Michelle? 

MICHELLE: 55:54 

My picks are-- I have just a couple. The first we one, we talked a lot about leadership and mentorship. I picked up a book earlier this year called 'The Art of Possibility' by Rosamund Stone Zander and Benjamin Zander. And that's Z-A-N-D-E-R. So not sure I'm saying the Z loud enough. And it's just a wonderful book to read. There's a lot in there about basically not letting yourself get in the way of being a good leader or a good teacher or a good mentor. And one of my favorite things in this book is something called 'rule number six' which I think you're going to have to read the book to find out what that is. I don't know if I can just tell you what it is. But it's something that I've instituted in my two-person department but I constantly remind myself about rule number six because I do sometimes get in my own way. I'm getting better at it but it's a work in progress. 

MICHELLE: 56:59 

The other thing that I'd like to recommend - another pick-- I'm a terrible podcast junkie. I'm always out there looking for new podcasts. I listen to them throughout the day. I have a whole bunch of NPR podcasts. But I also tend to listen to quite a few different data and data science podcasts as well as leadership podcasts. But Alternation was one of the first ones that I found that I really, really loved listening to that. But there's one that DataCamp has-- and now the name of it has just popped out of my mind as I'm telling you about it. Oh, my gosh [laughter]! I might have to send you a link to that one. But there's one that DataCamp has that's also just kind of fun to listen to. And then talk to different people in data science doing different things with data science. And so it's a lot of fun to listen to and just kind of in a different vein of things. And then I mentioned earlier HBR - Harvard Business Review: After Hours. And it's basically a discussion of current events. There are three Harvard Business School professors that are on the podcast and they basically discuss not business stuff really. It's basically current events as they're happening and just how maybe it's impacting how they see the world, how they're interpreting it. Sometimes from a business angle but not always because they all teach in different areas of business at the business school. 

MICHELLE: 58:43 

So just a few interesting things that I play around with in my off-time. 

LEAH: 58:50 

I love that you mentioned podcast episodes and shows. I'm always looking for new things to listen to. So I'll be sure to check those out. And funny enough I actually have chosen a podcast episode for one of my community picks as well. So I am a fan of Freakonomics Radio and they put out a podcast that's been going on for quite a while. I also know Brian is a huge Freakonomics fan. He's always sending our team links to episodes he thinks we'll find useful - and they usually are. But anyways there's this episode, it's called 'What Can Uber Teach Us About the Gender Pay Gap'. And it kind of digs into this study that Uber I believe they sponsored it along with some economists about a study where they used data from over 1 million Uber drivers to try and figure out if what was going on with the gender pay gap. And it's not as simple or straightforward as you would think. So definitely listen to that episode if you're interested. 

LEAH: 01:00:18 

The second community pick that is relevant to what we've been talking about is a thread that is on the Alteryx community. It was actually originally posted to our community lounge almost two years ago-- a little less than two years ago as a 'Thursday Thought'. And the thread is basically a question that we had posed to the community around asking folks to share actions that you or your company has taken to achieve gender equality. And no one has ever answered this thread. So I would like to encourage folks to check it out and share what either they themselves or their companies are doing to promote better balance in the workplace. So we will be sure to link to everyone's community picks in the podcast post on the Alteryx community. And from there that is the end of our episode. Thank you, Michelle and Christine, for joining us. It was such a pleasure and I really enjoyed our conversation today [music]. 

CHRISTINE: 01:01:52 

Thanks for having us. This was great. 

MICHELLE: 01:01:54 

Yeah. Thank you. 

BRIAN: 01:02:04 

Thanks for listening to Alter Everything. Go to for show notes, information about our guests, episodes and more. If you've got feedback, tweet us using the hashtag #altereverything or drop us an email at Catch you next time. 


This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).