Alter Everything Podcast

MaddieJ · ‎02-01-2021

Lanier Mason, CPA with EY, joins us for a look at how it can be difficult to "turn off" an analytical mind, and how his family history served as a catalyst for his data journey.

Panelists

Lanier Mason - @LMason, LinkedIn
Maddie Johannsen - @MaddieJ, LinkedIn,Twitter

Topics

Lanier’s first appearance on Alter Everything, episode 38: You don’t need to split an atom
EY
Molloy College
Bias in data resources:
- Using Data to Seek Racial Justice and Transparency, blog by @SusanCS
- Analytics as an Equalizer, blog by @SydneyF
- Reflecting on race, data, and our world: open discussion on Community with resources around bias in data
Gallup strengths finder assessment
“How cold was the ice age? Researchers now know” article from University of Arizona

Lanier audience question.png

Transcript

Episode Transcription

MADDIE: 00:00	Welcome to Alter Everything, [music] a podcast about data science and analytics culture. I'm Maddie Johannsen. And in this episode, I had a chat with Lanier Mason, a CPA registered in the state of New York, working at EY.
LANIER: 00:14	This is a bit of a, I guess, quarantine hobby. I don't know if you've gotten any of these when the pandemic started, but I started meditating kind of in the middle of last year, just for 5, 10 minutes a day.
MADDIE: 00:28	Interestingly, our conversation got a little philosophical. We unpacked how it can be difficult to turn off an analytical brain when you're done with work for the day, how Lanier's family history served as a catalyst for his understanding of bias and data, and we briefly hypothesized what it would have been like if humans in the Ice Age had access to a platform like Alteryx. And real quick, before we get started, I have a teaser for you. Be on the lookout for a super special announcement about a secret project we're planning. We'll announce it right here on this feed, so make sure you're subscribed, so you'll be the first to know. Let's jump into it. Welcome, Lanier. I'm so excited to have you back to Alter Everything.
LANIER: 01:13	Thanks, Maddie. I'm definitely excited to talk more. I know, obviously, since we've last met at the conference, I've been eager to have some more discussions with you, so I'm definitely looking forward to it.
MADDIE: 01:26	Yeah, I'm really excited to talk with you about what it is about you as a human that's driving data culture. How did you get to where you are today?
LANIER: 01:37	Yeah. So interestingly enough, I had first heard about Alteryx and other tools like it when I was kind of starting full-time at EY. And currently, I'm in the financial services office, really providing support to our wealth and asset management clients for our audit practice. And for me, I think what kind of got me started wasn't directly in that realm. Shortly after my first year, full-time, learned about my grandfather's passing. And like what typically happens after losing a loved one, you hear more about this family history, stories that you obviously weren't there for that kind of lets you know more about that person's life. And I think it was kind of an interesting way that the two paths converge in terms of my personal and my professional life, and that draw a lot of parallels to what I was exposed to, kind of new information about my family and my family history. That really kind of encouraged me to dig deeper and know more about myself and my own family history. But at the same time, I think the parallel is what else is out there from a professional perspective, specifically in the world of accounting and really in our communities overall, just information and news that we aren't necessarily always privy to that could have a significant change on how we look at the world?
MADDIE: 03:11	Yeah. And I want to dig into that a little bit more because, I mean, I think a lot of people can definitely relate to that when you go through an experience like that with your family, and suddenly, everybody's sharing favorite memories and stories that you have never heard. And let's say that you tell a story about a favorite memory, and then somebody else in the room says, "Oh, well, I actually remember it this way," and there's just kind of different versions of that history. And it is really interesting how things change over time and how those memories kind of evolve and how people record them differently, right? So I want to talk more about history as data and how it can have very significant impact, positive and negative, in the way that we understand our culture.
LANIER: 04:01	Yeah, I've actually kind of been thinking about just the premise of how data and information is collected. And I think what a lot of larger companies are starting to find and, really, at the community level, also starting to be developed is that the world around us is kind of having conversations with us moment to moment. And I think that the way that that's actually expressed is through what we would describe as data. Now, the manner in which it's captured and how complete and accurate it is depends on kind of the mechanisms that are set around that. But I think, really, if there's things that we can see, but we have trouble kind of actually quantifying or putting numbers to, I think that's really, the manner in which we capture information and data, where that actually comes into play.
MADDIE: 04:54	And when you tie that back to your professional experience of, like you said, at the company, just trying to get a grasp on the amount of data that's coming in and the amount of data that humans are producing each and every day, every minute, every second, what's important to you as a data person in terms of making sure that you have a well-rounded perspective of the data that you're analyzing in order to make sure that what you're analyzing is accurate to start, so that way, your analysis is accurate?
LANIER: 05:29	Yeah, and this is a really big concept in the auditing world, in particular. And before we come to any conclusions, from a professional perspective, specifically in the auditing world, we have to make sure that what we're looking at is complete and accurate. And part of the reason for that, obviously, is that when making decisions or drawing conclusions, how comfortable you are with those conclusions can vary, depending on whether or not you have all the information. So I would say that's kind of the first step. And that from our broad perspective, what we're considering is making sure that all the information that we're looking at is complete. On another level, I think it's also our job to make sure that we aren't bringing any expectations that are unfounded because we can sometimes bring our own preconceived notions to what we're looking at, or we may draw our conclusions based on our prior experience that, in this vacuum of this new cycle, isn't really applicable.
MADDIE: 06:33	Yeah, I think that's super interesting, especially the part about ways that we are maybe bringing in our own experiences from things that have happened in the past or maybe our bias. And I wonder if you have a couple of examples of ways that that bias can enter into our analysis.
LANIER: 06:55	Yeah, so I think the first would be, for our broader perspective, communication. There's a lot of discussion around internal versus external noise, internal noise being what goes on inside of ourselves and our own minds, and external noise, things outside of us that we can't necessarily control. So and speaking to bias and things like that in terms of our approach, I think one example would be perception, specifically when it's inconsistent with our own reality. I think emotions is a big part of it also. And thinking about data, specifically, when you're analyzing or in a professional services role like I am, which kind of is directly connected to people and their lives, accountants aren't-- as much as we're number crunchers, or we get that expectation a lot, a lot of our work is meant to tie to how it impacts people and individuals. So I think being in tune with that responsibility but also being able to take a step back and realize when things from your own experiences, from your own personal life may be coloring how you're actually interacting with the client.
LANIER: 08:13	And in the same way, to go a bit deeper and share a bit of a personal story, one feedback that I got early on in my career-- in making the transition from being in academia or someone being in college, a lot of the work you're doing on your own. So once you go into the professional setting, and you're working on a team, things, like communication, are really big, making sure you're communicating up to whoever it is that you're reporting to directly. And I think that as much as that was a professional and a work item that I needed to work on personally, I think that the raw expression of that in my personal life was not always communicating with family and friends. I think that that's kind of one of the reasons why that story about my grandfather kind of really shook things up for me a bit because-- and I'm happy to speak more to that, but immediately, before my grandfather passed, we've been meaning to have some just discussions about what our family history is. And not that I was reluctant to engage in that, I just think I ended up putting more emphasis on my career than conversations like that, which were incredibly important to my own personhood.
MADDIE: 09:31	Wow. Yeah, that's really, really fascinating. I can personally relate to that too. And it is tricky, especially looking back. It's like hindsight is everything. It's like, "What should I be engaging with more right now? And what should I be prioritizing?" And it's always really tough when things like that happen, and that access is cut off, really, and you don't have that first-hand account anymore. And it reminds me, too, of my-- so my nana passed away, too, last summer, and she left me a bunch of letters that she sent back and forth with my papa. So when he was in Korea during the war, they would write letters to each other. But she kept his because it was easy to keep his that he was sending back here, but he being in the military couldn't really collect piles and piles of letters and hold on to them. So what's interesting about that is that it's only a one-sided conversation that I have. I don't have any of her correspondence or things that she was sending to him. So it is interesting too, that one-sided experience or that one-sided record.
LANIER: 10:44	Right. Yeah. And to that point too, it's funny because I had a conversation with my grandmother after my grandfather passed, and he had wrote her some letters also, but they were on loose-leaf and written in pencil, so it's kind of wearing away. And to the point, really, and tying it to complete data is parts of it I could read. I don't know if you had a similar experience, but it's like as you're reading through it, parts of it, some of it you could read, or trying to make out the dates of when it was received kind of helps to piece together, the story also. And the first thing that I wanted to do after that was, one, recognize that these are artifacts. It's a really important physical documentation of what's transpired in your family history. And I just kind of went immediately to scan them and preserve what we could, so that it didn't disappear further because I think the unfortunate part in it all would be, at some point, not being able to read those or at least to have that captured.
MADDIE: 11:54	So yeah, with this being such an eye-opening experience for you in terms of understanding the well-rounded perspectives and data collection and with what you said earlier about the internal, external noise, would you consider that to be internal noise? And if that is the case, would that be a good thing in a way of what you're bringing to the table as an accountant or as a data worker?
LANIER: 12:20	Right. Yeah, I think the first thing is being able to recognize it. I think for a-- and this is kind of nearly four years in the making of reflection and revisiting it, but I think a lot of the times, we aren't really aware of what is causing certain reactions within us. Speaking for myself, this is a bit of a, I guess, quarantine hobby. I don't know if you've gotten any of these when the pandemic started, but I've started meditating kind of in the middle of last year, just for 5, 10 minutes a day. And there's a practice specifically connected to it called noting. I didn't realize how much I kind of got carried away and thought that would take me away from what I'm actually doing but just being able to note when you're lost in thought and kind of what has brought you to that and then just being able to recognize it, not getting carried away in it but also just coming back, back to the center. And that's something that-- I'm sure a lot of listeners that are really interested in analytics, I think it ends up being a lot of different branches off of an initial thought that can kind of go really deep. So for me, I think to directly answer your question, the best way that you can address that is, one, being able to notice when it's occurring and, at the same time, not allowing that personal connection to it to discount the real reason that you're doing the work or engaging in that kind of service, and it's being present and actually mindful of what your clients' needs are, what your community's needs are, and what your family's needs are.
MADDIE: 14:08	That's awesome. Yeah, I've been dying to start meditating. But for some reason, I just never get around to it, but I need to. 5 to 10 minutes a day, I definitely have that to spare, so I need to actually do it. Well, and it's interesting too because somebody recently told me that-- just in a conversation offhand, they were like, "Well, I think that you, in general, kind of overanalyze things," or, "I think you just analyze everything maybe a little bit too much." And my immediate reaction was like, "Look, don't you know what I talk about all day? Obviously, I'm going to have this deep within me." And it's really hard to turn off. And so I'm with people who are actual analysts and accountants and data scientists. I imagine that they have that problem too. And at the same time, though, part of me wants to say, "Is it a problem?" And part of me is like, "Maybe it is." Maybe it is good to kind of just take that time and, like you said, meditate and just really try and understand what your mind is doing because especially today, as a society, we're living and breathing this data culture so coupled with the immense computing power that we have access to. It's understandable that we can't turn that off even when we're just making lunch or going for a walk. We're just going to be constantly overanalyzing everything. And it makes me curious if we've evolved as humans to be more analytical about our everyday lives than perhaps maybe our ancestors were or even just a couple generations ago when they didn't have the computing power or just the full access of the internet or things like that.
LANIER: 15:59	Yeah. Actually, I love this question. So in terms of the feedback that you've gotten in terms of overthinking or overanalyzing, right, I've gotten that same feedback so much that I always viewed it as a problem. And I think the first thing is noticing that it isn't and that people are just different. For example, they have the strengths assessment, and Gallup has a really good StrengthsFinder assessment that I did and kind of went through each of those. And one of the strengths that I had identified was exactly in this realm. It was deliberative thought. And with that, to your point of both sides of the spectrum, some view it as being overthinkers, but I think in the same sense, we just think deeper about things. And that's not a fault, but for others, it can kind of be frustrating for those that kind of come to decisions a lot quicker.
LANIER: 17:02	So first, I wanted to say that because this is just out the gate, something that I noticed about myself that I wanted to refine a bit. I think part of what has caused that for us, especially people that would get really deep into thought, is that the wealth of information that is available has grown exponentially. If we think about how much we're tied to smartphones or the internet, part of it is the craving for us to want to either know more or be in touch with more, specifically when we've kind of been locked inside our homes or trying to navigate this health crisis that we're currently going through, but it's, "How can we stay connected to our friends? How can we stay connected to what's going on in the world?" And I think as a result of that, it's just our brain's natural tendency to continue to move towards that or to get dragged into those thoughts.
MADDIE: 18:07	Yeah, I agree with what you're saying about it's not necessarily a bad thing. I think the only way that it would be a bad thing and I think in the context of this personal conversation that I had where somebody pointed this out to me was that if it's within the context of, "What's affecting the way that you're living your life? Would you be happier if you could just kind of let things go and be quicker about decisions?" Or for me, personally, I'm a very indecisive person. So I like data because it is pretty black and white, obviously, if it's accurate and well-rounded and those kinds of things. But yeah, so I think in my personal life, when things aren't black and white, and you can take one path or the other, and either path is going to lead you to somewhere, but you don't know where that end destination might be, then I think it is where it gets tricky for me and I'm sure a lot of other analysts and people who are very, very much a fan of that black and white. So yeah, I agree. I think it's definitely not necessarily inherently a bad thing as long as you can kind of balance it in a way. I think the balance is really important.
LANIER: 19:13	I completely get the indecisive piece, especially when there's a lot to consider. It's difficult to sift when are you comfortable with this choice and when does it need some more reflecting? And I think for me, I can tend to stay in the reflection phase a lot, as opposed to kind of getting stuck in that loop that's prior to action. And the better we're able to give ourselves some permission to be able to stop after that point right before you jump into action, then it's less of a guilt trip and just a natural process that you go through. Yep.
MADDIE: 19:55	Yeah. And this is kind of a good segue into something else that I found really interesting about you is that you're really involved in your community, and that's really important to you. And I'm wondering how you bring this mindset of how does bias play into any sort of experience that you're going through, and I'm wondering if you can share a little bit more about ways that you're involved in your community. You've mentioned before to me being involved at your alma mater. And I'd love to hear more about how you're bringing this perspective into those community experiences.
LANIER: 20:36	Sure. So my alma mater, Molloy College, based in Rockville Centre in New York, as a result of the protests around racial injustice that occurred over the summer, they created a task force geared specifically towards diversity, equity, and inclusion and included administration, faculty, and some alumni. So first, the task force was charged by the newly appointed president to fulfill certain objectives around needs in the college community and specifically addressing the needs of the students, what needs there are from a recruiting and admissions perspective, how can the college better step into roles that are related to social justice and the community. So really, the task force was charged with all of those objectives, kind of thinking through what is most needed in the spirit and the tradition of the school. And this past year, recently started a scholarship in honor of my grandmother that recently passed who was also a nurse, and Malloy is pretty well-known for nursing. And since it's specifically for black students, I also felt that it was kind of a unique opportunity to be a part of something that would obviously affect whatever student received the scholarship but making sure that they had an experience that was really worth it for them and that they felt enriched by.
MADDIE: 22:12	Definitely. Yeah, I think that's so cool. And having, again, that analytics skill set, I'm sure that that is really valuable for them. I'm sure that maybe some interesting conversations have spurred because of that perspective that you bring to the table being so data-driven in your professional life and then bringing it into your community, for example, with that task force or with the scholarship fund. I'm sure that that really helps. So I think what would be interesting too and what could be fun is if we talked about-- I just want to kind of be really hypothetical here. But I want to think about a moment in history that maybe there wasn't the data collection that we're used to today and just imagine what it would be like to live during that time and how different things would have been if the data was being collected in what we think of as traditional data collection today. So for example, if we talk about the Ice Age, the data that we have from that time we're looking to things like fossils or the ice cores that they drill for or ocean sediment and things like that where it's just-- it blows my mind how much scientists can pull from these things, how much data that they can find in those objects. And it's crazy to me to think about what if the human beings were able to document like, "These are the people in my tribe. And this is how long we lived. And this is what we did every day. And here's what we talked about," all of those cultural things that we don't necessarily have access to, but researchers have maybe clues as to what life was like. It's interesting to me to imagine what it would have been like-- or what it would be like now to have more of that well-rounded understanding.
LANIER: 24:14	Sure. Yeah, yeah, that's a good point. I think it was an article or a video recently just about how much we're able to learn about the diets of people that lived thousands of years ago just by looking at remains and the dental patterns and things like that, which I think especially now-- I know I definitely have, I'm sure the listeners also, which is trying to be more mindful and intentional about what you eat. And I think the more we learn about the diets of those that lived long before we do-- or before we did, I think it kind of informs more what are the best decisions we can make in terms of what we are putting in our bodies. And I think that's just one way that we can continue to inform these decisions that we make every day, multiple times a day. But what is it that we could learn from that?
MADDIE: 25:12	For sure. And yeah, I mean, let's say somebody living in one part of the world had a certain diet because that's what was available to them. What if they had the Internet, and they could post their recipes? But then also, taking that a step further, thinking about things like the weather or the availability of food, are they able to grow anything? And what if they were able to have Alteryx, and then they could have made a model to try and predict when is the weather going to be warmer or when is the Ice Age going to end? It's just crazy to imagine if they had access to that information and what they might do with that information.
LANIER: 25:51	Yeah. And part of it, Maddie, also, I think, that's interesting to what you pointed out is speaking about being able to leverage-- even now, being able to leverage that data that was collected or maybe that wasn't collected in the same manner that we're able to analyze and use now. I think in the same way, we have responsibility for however many years into the future that people may be looking back and thinking-- obviously, there's a wealth of information, just from what we search on the internet to how long we stay watching shows on streaming sites and everybody listening to music, things like that. Those are all data points that who knows what they could be used for in the future. And I think part of it is a bit of a responsibility from our end in collecting this information or making sure what is useful. But also, I think to allow people to be able to take advantage of that information and leverage it becomes an interesting, "What if?"
MADDIE: 26:58	100%. We point to Isaac Newton, for example, as having sparked this curiosity for understanding science and understanding the world better, but it's always going to be a question of the humans that our mind doesn't automatically click to and think of for their scientific contributions or for their ability to think about the world in a new way because maybe history didn't record that person, or maybe their history got lost somehow. And because there isn't much we can do with that lost history-- or once that history is gone, there isn't really a lot that we can do with it. Kind of going back to what you're saying about meditating, just being intentional about understanding or acknowledging that we might not have the full picture because we never will or because it didn't make it into the history books. I think it is important to acknowledge, in some way, that there's-- even people today, voices aren't heard. So it is interesting and important, I think, to keep in mind that there's always going to be people and ideas and histories that need to be sought because they're maybe marginalized, and we don't always celebrate that history.
LANIER: 28:24	Yeah. And then how do you account for that in instances when the data that you do have isn't complete? Or obviously, there are things like margin of error that you account for or precision in your analyses, but I think it is important to address that specifically in scenarios where you're doing a more holistic analysis that isn't as specific as sales projections or things that tend to be more concrete that we look at in the business world but when we take a step back and think about actual life events that have had significant impacts on the direction of where we go next as a society, as a civilization, having to consider that and really be aware that those gaps in knowledge exist.
MADDIE: 29:16	Totally. And even when we think about machine learning bias, I think that's a huge hot topic right now about what kind of bias do models have in terms of talking about women or people of color or other marginalized communities, or maybe there's that economic bias of people who are more wealthy or people who are maybe struggling economically. So yeah, I think it's all super important and really relevant for analysts to consider, maybe not necessarily the Ice Age-specific example. But I think the principles apply, though, that it's super important to have that well-rounded perspective on anything that you're doing to make sure that the analysis that you're doing is fair, ultimately. [music] Well, this was such a fun conversation, Lanier. I really appreciate you joining me, and I'm so glad that I was able to have you again on Alter Everything. Like I said, after we had talked in Nashville, I knew that I wanted to have you back on the show, so I'm really happy that we were able to find the time.
LANIER: 30:22	Absolutely. Thank you, Maddie, for inviting me. Oh, I definitely enjoyed the conversation. Look forward to staying in touch.
MADDIE: 30:31	Thanks for listening. Check out our show notes at community.alteryx.com/podcast for links and resources about the topics we discussed. And while you're there, be sure to comment and share your thoughts. You can also join us on social media by following @alteryx and using the #AlterEverythingPodcast. And don't forget to subscribe to this feed and be on the lookout for a special announcement coming soon. Cheers.

MADDIE: 00:00 Welcome to Alter Everything, [music] a podcast about data science and analytics culture. I'm Maddie Johannsen. And in this episode, I had a chat with Lanier Mason, a CPA registered in the state of New York, working at EY. LANIER: 00:14 This is a bit of a, I guess, quarantine hobby. I don't know if you've gotten any of these when the pandemic started, but I started meditating kind of in the middle of last year, just for 5, 10 minutes a day. MADDIE: 00:28 Interestingly, our conversation got a little philosophical. We unpacked how it can be difficult to turn off an analytical brain when you're done with work for the day, how Lanier's family history served as a catalyst for his understanding of bias and data, and we briefly hypothesized what it would have been like if humans in the Ice Age had access to a platform like Alteryx. And real quick, before we get started, I have a teaser for you. Be on the lookout for a super special announcement about a secret project we're planning. We'll announce it right here on this feed, so make sure you're subscribed, so you'll be the first to know. Let's jump into it. Welcome, Lanier. I'm so excited to have you back to Alter Everything. LANIER: 01:13 Thanks, Maddie. I'm definitely excited to talk more. I know, obviously, since we've last met at the conference, I've been eager to have some more discussions with you, so I'm definitely looking forward to it. MADDIE: 01:26 Yeah, I'm really excited to talk with you about what it is about you as a human that's driving data culture. How did you get to where you are today? LANIER: 01:37 Yeah. So interestingly enough, I had first heard about Alteryx and other tools like it when I was kind of starting full-time at EY. And currently, I'm in the financial services office, really providing support to our wealth and asset management clients for our audit practice. And for me, I think what kind of got me started wasn't directly in that realm. Shortly after my first year, full-time, learned about my grandfather's passing. And like what typically happens after losing a loved one, you hear more about this family history, stories that you obviously weren't there for that kind of lets you know more about that person's life. And I think it was kind of an interesting way that the two paths converge in terms of my personal and my professional life, and that draw a lot of parallels to what I was exposed to, kind of new information about my family and my family history. That really kind of encouraged me to dig deeper and know more about myself and my own family history. But at the same time, I think the parallel is what else is out there from a professional perspective, specifically in the world of accounting and really in our communities overall, just information and news that we aren't necessarily always privy to that could have a significant change on how we look at the world? MADDIE: 03:11 Yeah. And I want to dig into that a little bit more because, I mean, I think a lot of people can definitely relate to that when you go through an experience like that with your family, and suddenly, everybody's sharing favorite memories and stories that you have never heard. And let's say that you tell a story about a favorite memory, and then somebody else in the room says, "Oh, well, I actually remember it this way," and there's just kind of different versions of that history. And it is really interesting how things change over time and how those memories kind of evolve and how people record them differently, right? So I want to talk more about history as data and how it can have very significant impact, positive and negative, in the way that we understand our culture. LANIER: 04:01 Yeah, I've actually kind of been thinking about just the premise of how data and information is collected. And I think what a lot of larger companies are starting to find and, really, at the community level, also starting to be developed is that the world around us is kind of having conversations with us moment to moment. And I think that the way that that's actually expressed is through what we would describe as data. Now, the manner in which it's captured and how complete and accurate it is depends on kind of the mechanisms that are set around that. But I think, really, if there's things that we can see, but we have trouble kind of actually quantifying or putting numbers to, I think that's really, the manner in which we capture information and data, where that actually comes into play. MADDIE: 04:54 And when you tie that back to your professional experience of, like you said, at the company, just trying to get a grasp on the amount of data that's coming in and the amount of data that humans are producing each and every day, every minute, every second, what's important to you as a data person in terms of making sure that you have a well-rounded perspective of the data that you're analyzing in order to make sure that what you're analyzing is accurate to start, so that way, your analysis is accurate? LANIER: 05:29 Yeah, and this is a really big concept in the auditing world, in particular. And before we come to any conclusions, from a professional perspective, specifically in the auditing world, we have to make sure that what we're looking at is complete and accurate. And part of the reason for that, obviously, is that when making decisions or drawing conclusions, how comfortable you are with those conclusions can vary, depending on whether or not you have all the information. So I would say that's kind of the first step. And that from our broad perspective, what we're considering is making sure that all the information that we're looking at is complete. On another level, I think it's also our job to make sure that we aren't bringing any expectations that are unfounded because we can sometimes bring our own preconceived notions to what we're looking at, or we may draw our conclusions based on our prior experience that, in this vacuum of this new cycle, isn't really applicable. MADDIE: 06:33 Yeah, I think that's super interesting, especially the part about ways that we are maybe bringing in our own experiences from things that have happened in the past or maybe our bias. And I wonder if you have a couple of examples of ways that that bias can enter into our analysis. LANIER: 06:55 Yeah, so I think the first would be, for our broader perspective, communication. There's a lot of discussion around internal versus external noise, internal noise being what goes on inside of ourselves and our own minds, and external noise, things outside of us that we can't necessarily control. So and speaking to bias and things like that in terms of our approach, I think one example would be perception, specifically when it's inconsistent with our own reality. I think emotions is a big part of it also. And thinking about data, specifically, when you're analyzing or in a professional services role like I am, which kind of is directly connected to people and their lives, accountants aren't-- as much as we're number crunchers, or we get that expectation a lot, a lot of our work is meant to tie to how it impacts people and individuals. So I think being in tune with that responsibility but also being able to take a step back and realize when things from your own experiences, from your own personal life may be coloring how you're actually interacting with the client. LANIER: 08:13 And in the same way, to go a bit deeper and share a bit of a personal story, one feedback that I got early on in my career-- in making the transition from being in academia or someone being in college, a lot of the work you're doing on your own. So once you go into the professional setting, and you're working on a team, things, like communication, are really big, making sure you're communicating up to whoever it is that you're reporting to directly. And I think that as much as that was a professional and a work item that I needed to work on personally, I think that the raw expression of that in my personal life was not always communicating with family and friends. I think that that's kind of one of the reasons why that story about my grandfather kind of really shook things up for me a bit because-- and I'm happy to speak more to that, but immediately, before my grandfather passed, we've been meaning to have some just discussions about what our family history is. And not that I was reluctant to engage in that, I just think I ended up putting more emphasis on my career than conversations like that, which were incredibly important to my own personhood. MADDIE: 09:31 Wow. Yeah, that's really, really fascinating. I can personally relate to that too. And it is tricky, especially looking back. It's like hindsight is everything. It's like, "What should I be engaging with more right now? And what should I be prioritizing?" And it's always really tough when things like that happen, and that access is cut off, really, and you don't have that first-hand account anymore. And it reminds me, too, of my-- so my nana passed away, too, last summer, and she left me a bunch of letters that she sent back and forth with my papa. So when he was in Korea during the war, they would write letters to each other. But she kept his because it was easy to keep his that he was sending back here, but he being in the military couldn't really collect piles and piles of letters and hold on to them. So what's interesting about that is that it's only a one-sided conversation that I have. I don't have any of her correspondence or things that she was sending to him. So it is interesting too, that one-sided experience or that one-sided record. LANIER: 10:44 Right. Yeah. And to that point too, it's funny because I had a conversation with my grandmother after my grandfather passed, and he had wrote her some letters also, but they were on loose-leaf and written in pencil, so it's kind of wearing away. And to the point, really, and tying it to complete data is parts of it I could read. I don't know if you had a similar experience, but it's like as you're reading through it, parts of it, some of it you could read, or trying to make out the dates of when it was received kind of helps to piece together, the story also. And the first thing that I wanted to do after that was, one, recognize that these are artifacts. It's a really important physical documentation of what's transpired in your family history. And I just kind of went immediately to scan them and preserve what we could, so that it didn't disappear further because I think the unfortunate part in it all would be, at some point, not being able to read those or at least to have that captured. MADDIE: 11:54 So yeah, with this being such an eye-opening experience for you in terms of understanding the well-rounded perspectives and data collection and with what you said earlier about the internal, external noise, would you consider that to be internal noise? And if that is the case, would that be a good thing in a way of what you're bringing to the table as an accountant or as a data worker? LANIER: 12:20 Right. Yeah, I think the first thing is being able to recognize it. I think for a-- and this is kind of nearly four years in the making of reflection and revisiting it, but I think a lot of the times, we aren't really aware of what is causing certain reactions within us. Speaking for myself, this is a bit of a, I guess, quarantine hobby. I don't know if you've gotten any of these when the pandemic started, but I've started meditating kind of in the middle of last year, just for 5, 10 minutes a day. And there's a practice specifically connected to it called noting. I didn't realize how much I kind of got carried away and thought that would take me away from what I'm actually doing but just being able to note when you're lost in thought and kind of what has brought you to that and then just being able to recognize it, not getting carried away in it but also just coming back, back to the center. And that's something that-- I'm sure a lot of listeners that are really interested in analytics, I think it ends up being a lot of different branches off of an initial thought that can kind of go really deep. So for me, I think to directly answer your question, the best way that you can address that is, one, being able to notice when it's occurring and, at the same time, not allowing that personal connection to it to discount the real reason that you're doing the work or engaging in that kind of service, and it's being present and actually mindful of what your clients' needs are, what your community's needs are, and what your family's needs are. MADDIE: 14:08 That's awesome. Yeah, I've been dying to start meditating. But for some reason, I just never get around to it, but I need to. 5 to 10 minutes a day, I definitely have that to spare, so I need to actually do it. Well, and it's interesting too because somebody recently told me that-- just in a conversation offhand, they were like, "Well, I think that you, in general, kind of overanalyze things," or, "I think you just analyze everything maybe a little bit too much." And my immediate reaction was like, "Look, don't you know what I talk about all day? Obviously, I'm going to have this deep within me." And it's really hard to turn off. And so I'm with people who are actual analysts and accountants and data scientists. I imagine that they have that problem too. And at the same time, though, part of me wants to say, "Is it a problem?" And part of me is like, "Maybe it is." Maybe it is good to kind of just take that time and, like you said, meditate and just really try and understand what your mind is doing because especially today, as a society, we're living and breathing this data culture so coupled with the immense computing power that we have access to. It's understandable that we can't turn that off even when we're just making lunch or going for a walk. We're just going to be constantly overanalyzing everything. And it makes me curious if we've evolved as humans to be more analytical about our everyday lives than perhaps maybe our ancestors were or even just a couple generations ago when they didn't have the computing power or just the full access of the internet or things like that. LANIER: 15:59 Yeah. Actually, I love this question. So in terms of the feedback that you've gotten in terms of overthinking or overanalyzing, right, I've gotten that same feedback so much that I always viewed it as a problem. And I think the first thing is noticing that it isn't and that people are just different. For example, they have the strengths assessment, and Gallup has a really good StrengthsFinder assessment that I did and kind of went through each of those. And one of the strengths that I had identified was exactly in this realm. It was deliberative thought. And with that, to your point of both sides of the spectrum, some view it as being overthinkers, but I think in the same sense, we just think deeper about things. And that's not a fault, but for others, it can kind of be frustrating for those that kind of come to decisions a lot quicker. LANIER: 17:02 So first, I wanted to say that because this is just out the gate, something that I noticed about myself that I wanted to refine a bit. I think part of what has caused that for us, especially people that would get really deep into thought, is that the wealth of information that is available has grown exponentially. If we think about how much we're tied to smartphones or the internet, part of it is the craving for us to want to either know more or be in touch with more, specifically when we've kind of been locked inside our homes or trying to navigate this health crisis that we're currently going through, but it's, "How can we stay connected to our friends? How can we stay connected to what's going on in the world?" And I think as a result of that, it's just our brain's natural tendency to continue to move towards that or to get dragged into those thoughts. MADDIE: 18:07 Yeah, I agree with what you're saying about it's not necessarily a bad thing. I think the only way that it would be a bad thing and I think in the context of this personal conversation that I had where somebody pointed this out to me was that if it's within the context of, "What's affecting the way that you're living your life? Would you be happier if you could just kind of let things go and be quicker about decisions?" Or for me, personally, I'm a very indecisive person. So I like data because it is pretty black and white, obviously, if it's accurate and well-rounded and those kinds of things. But yeah, so I think in my personal life, when things aren't black and white, and you can take one path or the other, and either path is going to lead you to somewhere, but you don't know where that end destination might be, then I think it is where it gets tricky for me and I'm sure a lot of other analysts and people who are very, very much a fan of that black and white. So yeah, I agree. I think it's definitely not necessarily inherently a bad thing as long as you can kind of balance it in a way. I think the balance is really important. LANIER: 19:13 I completely get the indecisive piece, especially when there's a lot to consider. It's difficult to sift when are you comfortable with this choice and when does it need some more reflecting? And I think for me, I can tend to stay in the reflection phase a lot, as opposed to kind of getting stuck in that loop that's prior to action. And the better we're able to give ourselves some permission to be able to stop after that point right before you jump into action, then it's less of a guilt trip and just a natural process that you go through. Yep. MADDIE: 19:55 Yeah. And this is kind of a good segue into something else that I found really interesting about you is that you're really involved in your community, and that's really important to you. And I'm wondering how you bring this mindset of how does bias play into any sort of experience that you're going through, and I'm wondering if you can share a little bit more about ways that you're involved in your community. You've mentioned before to me being involved at your alma mater. And I'd love to hear more about how you're bringing this perspective into those community experiences. LANIER: 20:36 Sure. So my alma mater, Molloy College, based in Rockville Centre in New York, as a result of the protests around racial injustice that occurred over the summer, they created a task force geared specifically towards diversity, equity, and inclusion and included administration, faculty, and some alumni. So first, the task force was charged by the newly appointed president to fulfill certain objectives around needs in the college community and specifically addressing the needs of the students, what needs there are from a recruiting and admissions perspective, how can the college better step into roles that are related to social justice and the community. So really, the task force was charged with all of those objectives, kind of thinking through what is most needed in the spirit and the tradition of the school. And this past year, recently started a scholarship in honor of my grandmother that recently passed who was also a nurse, and Malloy is pretty well-known for nursing. And since it's specifically for black students, I also felt that it was kind of a unique opportunity to be a part of something that would obviously affect whatever student received the scholarship but making sure that they had an experience that was really worth it for them and that they felt enriched by. MADDIE: 22:12 Definitely. Yeah, I think that's so cool. And having, again, that analytics skill set, I'm sure that that is really valuable for them. I'm sure that maybe some interesting conversations have spurred because of that perspective that you bring to the table being so data-driven in your professional life and then bringing it into your community, for example, with that task force or with the scholarship fund. I'm sure that that really helps. So I think what would be interesting too and what could be fun is if we talked about-- I just want to kind of be really hypothetical here. But I want to think about a moment in history that maybe there wasn't the data collection that we're used to today and just imagine what it would be like to live during that time and how different things would have been if the data was being collected in what we think of as traditional data collection today. So for example, if we talk about the Ice Age, the data that we have from that time we're looking to things like fossils or the ice cores that they drill for or ocean sediment and things like that where it's just-- it blows my mind how much scientists can pull from these things, how much data that they can find in those objects. And it's crazy to me to think about what if the human beings were able to document like, "These are the people in my tribe. And this is how long we lived. And this is what we did every day. And here's what we talked about," all of those cultural things that we don't necessarily have access to, but researchers have maybe clues as to what life was like. It's interesting to me to imagine what it would have been like-- or what it would be like now to have more of that well-rounded understanding. LANIER: 24:14 Sure. Yeah, yeah, that's a good point. I think it was an article or a video recently just about how much we're able to learn about the diets of people that lived thousands of years ago just by looking at remains and the dental patterns and things like that, which I think especially now-- I know I definitely have, I'm sure the listeners also, which is trying to be more mindful and intentional about what you eat. And I think the more we learn about the diets of those that lived long before we do-- or before we did, I think it kind of informs more what are the best decisions we can make in terms of what we are putting in our bodies. And I think that's just one way that we can continue to inform these decisions that we make every day, multiple times a day. But what is it that we could learn from that? MADDIE: 25:12 For sure. And yeah, I mean, let's say somebody living in one part of the world had a certain diet because that's what was available to them. What if they had the Internet, and they could post their recipes? But then also, taking that a step further, thinking about things like the weather or the availability of food, are they able to grow anything? And what if they were able to have Alteryx, and then they could have made a model to try and predict when is the weather going to be warmer or when is the Ice Age going to end? It's just crazy to imagine if they had access to that information and what they might do with that information. LANIER: 25:51 Yeah. And part of it, Maddie, also, I think, that's interesting to what you pointed out is speaking about being able to leverage-- even now, being able to leverage that data that was collected or maybe that wasn't collected in the same manner that we're able to analyze and use now. I think in the same way, we have responsibility for however many years into the future that people may be looking back and thinking-- obviously, there's a wealth of information, just from what we search on the internet to how long we stay watching shows on streaming sites and everybody listening to music, things like that. Those are all data points that who knows what they could be used for in the future. And I think part of it is a bit of a responsibility from our end in collecting this information or making sure what is useful. But also, I think to allow people to be able to take advantage of that information and leverage it becomes an interesting, "What if?" MADDIE: 26:58 100%. We point to Isaac Newton, for example, as having sparked this curiosity for understanding science and understanding the world better, but it's always going to be a question of the humans that our mind doesn't automatically click to and think of for their scientific contributions or for their ability to think about the world in a new way because maybe history didn't record that person, or maybe their history got lost somehow. And because there isn't much we can do with that lost history-- or once that history is gone, there isn't really a lot that we can do with it. Kind of going back to what you're saying about meditating, just being intentional about understanding or acknowledging that we might not have the full picture because we never will or because it didn't make it into the history books. I think it is important to acknowledge, in some way, that there's-- even people today, voices aren't heard. So it is interesting and important, I think, to keep in mind that there's always going to be people and ideas and histories that need to be sought because they're maybe marginalized, and we don't always celebrate that history. LANIER: 28:24 Yeah. And then how do you account for that in instances when the data that you do have isn't complete? Or obviously, there are things like margin of error that you account for or precision in your analyses, but I think it is important to address that specifically in scenarios where you're doing a more holistic analysis that isn't as specific as sales projections or things that tend to be more concrete that we look at in the business world but when we take a step back and think about actual life events that have had significant impacts on the direction of where we go next as a society, as a civilization, having to consider that and really be aware that those gaps in knowledge exist. MADDIE: 29:16 Totally. And even when we think about machine learning bias, I think that's a huge hot topic right now about what kind of bias do models have in terms of talking about women or people of color or other marginalized communities, or maybe there's that economic bias of people who are more wealthy or people who are maybe struggling economically. So yeah, I think it's all super important and really relevant for analysts to consider, maybe not necessarily the Ice Age-specific example. But I think the principles apply, though, that it's super important to have that well-rounded perspective on anything that you're doing to make sure that the analysis that you're doing is fair, ultimately. [music] Well, this was such a fun conversation, Lanier. I really appreciate you joining me, and I'm so glad that I was able to have you again on Alter Everything. Like I said, after we had talked in Nashville, I knew that I wanted to have you back on the show, so I'm really happy that we were able to find the time. LANIER: 30:22 Absolutely. Thank you, Maddie, for inviting me. Oh, I definitely enjoyed the conversation. Look forward to staying in touch. MADDIE: 30:31 Thanks for listening. Check out our show notes at community.alteryx.com/podcast for links and resources about the topics we discussed. And while you're there, be sure to comment and share your thoughts. You can also join us on social media by following @alteryx and using the #AlterEverythingPodcast. And don't forget to subscribe to this feed and be on the lookout for a special announcement coming soon. Cheers.

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

Alter Everything Podcast

Podcast Guide

78: The whole (data) story

Panelists

Topics

Transcript

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

Alter Everything Podcast

Podcast Guide

78: The whole (data) story

Panelists

Topics

Transcript

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.