Ep. 72 - With Morgan Depenbusch, PhD (science-backed strategies to finally get your work noticed)

Speaker A: Foreign. Mhm.

Speaker B: Hey, welcome back everyone to episode 72 of the data Ideas podcast. Pleased to be joined today, um, by Morgan Deppenbush. Morgan, welcome. How's it going today?

Speaker A: Thank you. Happy to be here. How are you?

Speaker B: Yeah, doing well, doing well. And good morning, good afternoon, good evening to everyone joining. I feel like this is a good time, like, for most folks, um, to join. We have folks that can join from the west coast, from Central time, the east coast, out to the uk, so, and Europe. So welcome to everyone that's joining. Um, glad that you're here, Morgan. I always like to kick off each episode with asking how folks got interested in data analytics. What was it that got you interested in data?

Speaker A: Yeah, it's probably not a very exciting story. It's just I've always loved data and numbers and math is always my favorite type, uh, of, uh, classes at school. And I was also always really interested in psychology and human behavior. And, and in my mind I thought those are two separate things. You know, I thought you have the data and the math and, you know, like that all that nerdy work you could do over here. And then you had psychology and human behavior, and that was all very liberal arts and kind of woo, woo and feelings. And so I wasn't sure how those were going to come together. And it wasn't until I was in college and I was majoring in psychology and I sat down with one of my professors and I said, you know, I love psychology, I love the idea of, you know, why do we do what we do? And behavior, but I can't sit one on one with someone for an hour outside of this amazing podcast and do something like therapy and just, you know, talk, talk with someone about, like, how are you feeling? I was like, I can't do that. And he said to me, he's like, uh, you might, you've probably never heard of this because we didn't. It was a small school, there was no classes in it. And he said, but you might be interested in IO psychology. It's, you know, psychology applied to the workplace. You use data and analytics and research. And I said, yes, that. And so I went off and I applied to a bunch of PhD programs in it based on that conversation, trusting it would be the right field. And thankfully it was, um, but yeah, it was just a way I could kind of marry those two interests. I loved data and numbers, but I love to apply those to humans and our behavior and why we do what we do.

Speaker B: And the intersection of those two things is really critical to being an Impactful. And we'll talk about later in the episode, influential, um, analysts. I know that you've put together, you've used your expertise in both of those areas and the experiences that you've gotten along the way to put together some resources for analytics professionals to leverage both of those areas to make an impact, which is awesome. Um, again, we'll, we'll dive into some of that and new, uh, resource that Morgan just released, um, around that later in the episode. But shortly after finishing your PhD, you started at a company I think probably everybody in the world has heard of.

Speaker A: A few people have.

Speaker B: Yeah, a few people have heard of it. Right. Um, did you always want to work for Google?

Speaker A: You know, I did. I mean, not since I was like a young girl, but, you know, since I was looking for jobs, I. So around 2015, when I was finishing up my PhD, if you were in fields like IO psychology and you wanted to go do that at a, at a workplace, we really, it was just the beginning of this field called people analytics. Right. Using data and research and analytics to understand the employee experience, what motivates people, what makes a good leader. But people analytics was pretty brand new. Uh, there weren't, you couldn't. Today you can go and you can search people analytics jobs, you can get a laundry list. You couldn't do that in 2015 when I was looking for a job and Google was really putting people analytics on the map at that time. So they were doing conferences about it, they were publishing externally the research that they were doing internally. The chro at the time, Laszlo Bach, came out with a book called Work Rules. And so it really was, if you wanted to do this kind of work, Google was the place to be to do it. Because A, not a lot of companies were even doing it and B, Google's at the forefront. They were really leading the way of what would it look like to do this. And so as I was graduating, it was kind of like, you know, it's, it's Google or bust. I don't know what I'm going to do if it's not at Google. Um, I had, I looked at kind of some other companies. I didn't think I was ready for Google. I was like, you know, who am I? I'm just coming out of grad school. I've never had a real job outside of an internship. But I was very fortunate that one of my dear friends from my grad program had started at Google six months before I was graduating. And he said, you know, it's great here. I think you would love it too. Let me refer you. We have an opening and that's kind of how I got my foot in the door.

Speaker B: Very cool. Um, and so next question is one that I'm sure that you probably get all the time, but can you give folks a feel for like, what is it like working at Google? You mentioned, I think like, you know, most people are like, oh, like, is that even a place that I could belong at? Or whatever. Like, it's, it seems like this like aspirational thing that's really hard to get to and it's, I'm like, should I even be interviewing someone that works for Google? Like, it's just like, it seems like, um, I don't know, just this thing that's out there, right? Like, um, what is it like working there? And like what makes it different than other places?

Speaker A: Yeah, it's, it's funny, I get this question a lot. Um, especially so I was at Google for almost 10 years and I've done a lot of interviews while I was there for the various teams I was on. And near the end almost every candidate says, you know what, what's the best thing about working at Google? You know, what do you love about it most? And my answer has always been the same from day one to, you know, day last. I don't know, the opposite of day one.

Speaker B: Several thousand, right?

Speaker A: Several thousand. Um, my answer was always the same and it was, it's the people. It's, Google has this knack for hiring the smartest, the hardest working, the most collaborative, creative, kind, fun people. And so it's kind of like no matter what project you're working on, it could be the most frustrating, the most head bangy project. But you're working on it with people who make you laugh, who just say, all right, let's just, let's figure this thing out together and then let's go have lunch and you know, kind of laugh about it. Um, and so I think for that, that just, I would, I would always rather work on a frustrating project with people who make it fun, then work on a cool project with people who just kind of make you want to bang your head against a wall. So for me it was always nice that and you know, as I was thinking of leaving Google and you know, coming up that 10 year mark and really thinking about what's next, what I want to do, that was my biggest concern was am I going to find a culture like this where any teammate I'm excited to work with and I know they're going to have My back. I know they're going to have great ideas. I'm going to learn from them every day and they're going to make me better. Uh, and so after I left Google, I started at Snowflake. It's been about two months and was just. Was just so excited to find kind of like that same culture where everyone I'm working with is just. They're so kind and smart. Right. To hop in and help you. Uh, but they're also so collaborative and creative. Right. Because you also. It's nice to work with nice people, but you don't work with nice people who can't do the job. So it's always nice when you have that combination. Right. They're very nice, but they're very smart. So I think that for me, and

Speaker B: competence, I hear that's very. I'm not a behavior.

Speaker A: It's very important. It makes a difference.

Speaker B: Yeah.

Speaker A: Yeah. So for me, it's. I just realized that, you know, it's. The projects you work on will change, the teams you work on will change, the companies will change. But for me, that's been like the most important piece is just who am I doing this work with and are they making it fun or are they kind of making it a headache?

Speaker B: Very cool. That's awesome. And glad that you found this environment that you described at Snowflake as well. Congrats on the new role.

Speaker A: Thank you.

Speaker B: By the way. That's really exciting. Yeah, yeah, for sure. Um, did want to just take a pause and I see there are some folks joining live. If you are joining live, let us know who you are, where you're coming from. It's always good to see who's joining, uh, the live stream, the podcast recording. Hello to everyone that's joining. Um, that recording, uh, in a week from now, um, will be available on Friday, September 12th. Um, but, um, let us know in the chat where you're coming from. It's always good to, uh, to see who we've got with us live, um, thinking about people analytics, you know, and working in that. You mentioned in 2015, you know, it wasn't, it was really just kind of an emerging field. Google was one of the first places, um, that allowed you to work in that field. And now, you know, you're still working in people analytics at Snowflake. Like, from your perspective, what's some of the biggest opportunities, um, in terms of applying analytics to the world of work in general?

Speaker A: Yeah, I think so. We're at, we're at a big moment right now and we have Been a while, right? So it's, we have this age of AI and it's everyone, you know, how is it going to change how we do our work? And we're also still kind of coming back from COVID in terms of, you know, do. Is it better to be in the office and everyone, you know, rto return to office, or is it okay to be remote? And yeah, we're in this big period of uncertainty and I think uncertainty can stress out people a lot. It can make us, uh, you know, default to assumptions or anecdotes or our biases we have. And I think that's where fields like People analytics are going to be so important is we can say, yes, we're in this moment of uncertainty, but we can ground ourselves in, in data, in research, in, you know, looking at not just this happened to this one person, here's this anecdote, but what are actually we seen as broader trends, what are we seeing across different companies? And, and I think that's the biggest opportunity right now is to bring some of this rigor and this research and data to this moment of uncertainty. You know, is AI going to make us all more productive? Well, we can research that. You know, we can, we can set up the studies now to gather the data and answer that question. Or is AI going to rot all of our brains like some of those studies are saying, right? And we're no longer know how to think for ourselves. Well, we can study that and we can research it, especially that we think about the workplace. Right. And how are people interacting with AI and are we more productive in the office? Are we doing better remote? Who does better remote in the office? You know, who does that help? Who does that hurt? That's where this type of work can really shine right now is because we can outsource our, uh, coding all day long to AI. I have been leaning on it so much. I love it. But what we can't outsource is what's the research design to understand this big question that we don't have? Right. We can't outsource to AI. You have this leader who is gung ho on this assumption that remote work is terrible. It's never going to work. Everyone needs to be in the office five days a week. You need to be the one who goes in there and says, we've done some research. You need to have a little bit of ability to influence that decision that AI can't do. So I think that's where I see the biggest opportunity right now is can we do some Myth busting. Can we put some guardrails around the assumptions we have right now using these, these principles, these methodologies that we've, we've refined for decades and we know work

Speaker B: that's really interesting and I think there are a lot of myths out there and putting science to it is critical. Um, and things have changed so much in the world of work. That makes a ton of sense to me. That's awesome. Um, and things are changing rapidly in the tech field and in data, you know, and so definitely, um, answer resonates strongly, um, with what I've seen. So, um, did want to just give a shout out quickly to, um, several folks that said hello in the chat. Um, and again, if you are joining live, um, let us know where you're coming from. Just wanted to say hello to a few folks. Taiwo's joining from Rwanda.

Speaker A: That's so cool.

Speaker B: I know, right? Hello from Dubai. See, I mentioned I felt like this was a good time.

Speaker A: Wow.

Speaker B: Yeah. So, um, Kashish is joining from Dubai. Um, we have someone joining from Asheville, North Carolina. Apologize for security reasons or whatever. I can't see who this LinkedIn user is. Someone from Seattle. So look at that. East coast, west coast, outside the US Got someone joining from Toronto, Canada. Got Steven. Hello to Steven. Steven. Someone I know. Uh, in the Milwaukee area, we've got Amy from upstate New York. Hey. To Jitendra from Kalamazoo, Michigan. Sidra. Uh, from North Carolina. Pittsburgh, Denver. I'm just going to shout them out. Brazil, Dallas, Minneapolis. Very cool. Wow, you're very popular, Morgan. Everyone wanted to.

Speaker A: These are all my friends. I paid them all to be here.

Speaker B: Oh, gotcha. Okay. All right. Okay. Okay, cool. Awesome. Well, if you are joining, um, let us know where you're coming from and if you do have a question, drop it in the chat. Can't guarantee we'll be able to get to it, but, um, maybe we'll have time for one or two as we go, uh, through the rest of the episode. Thanks everyone for joining from. From all over. All right, um, so you've been producing some really, really cool content, really helpful content. I know it's been very, very popular and I suspect will continue to be for quite some time. Um, and there's contents around data visualization and storytelling. Also influence. Um, I want to get into, um, the Analyst Influence Playbook that you just released this morning. Um, but before we get into some of the content, what was it that inspired you to kind of start educating others in these areas?

Speaker A: Yeah. So I, uh, think when we're in school or early in our career, we are taught all of the technical skills. We know how to pull data, we know how to report it, we know how to build dashboards, we know how to run analyses. And then we get on the job and we're told, okay, go have impact. You know, we get our performance reviews back, and they say, you don't have enough impact. And, you know, you really need to be a partner to this stakeholder. You need to influence this decision. But no one teaches that. And I definitely felt that when I started my career at Google, you know, I came in thinking I was a hotshot, to be honest. I was like, I have my PhD. I just got hired at Google. Like, clearly I know what I'm doing. And I got there and I was humbled real fast because what I realized was, yes, I have the technical skills, but these days, everyone does like technical stills. They're just table stakes right now. You need them to get your foot in the door. But in order to actually have people see your work, care about your work, do something about your work, you need to be able to take the next step, right? So going from data to insight, which we talk all about the time, like, I'll get insights from the data. Great. That's act one. And right. Most of us are there, and then there's this intermission. And now you have to go from insight to that has to do something and go somewhere. And we're not taught that. And I felt really fortunate being at Google, where I just was around amazing teammates, amazing managers who taught me this, right? You, uh, know who gave me a lot of feedback. I got to see people who are great at it and how they did it. And so I started to realize, like, wow, like, there's no way to learn this stuff unless you're just lucky to have someone to teach you. And especially even when it came to things like data visualization, um, you know, coming from a grad program, I was taught how to make these charts technically correct, which basically meant you made it in Excel, you use the defaults, you slapped it on your document, and you were good to go. And then I took this, this course at Google my first year there ten years ago called Storytelling with Data. Uh, it was by Cole Neussbaumer Nathalik, who went on to make a bestselling book. And it just blew my mind. I was like, oh, my God, like, this is how you're supposed to communicate your work and your data. And I just threw myself into that. And I just realized that most of us aren't taught that. And so that kind of was in the back of my mind for a while. I also love writing, I love teaching. And I was kind of missing that in my current role, which, which makes sense, right? If you're. You're in analytics, like big tech company, you're not like, please go write and teach. So I was thinking about how can I kind of scratch that itch and maybe in so doing I can help other people kind of learn these skills I've been so, so lucky to learn. And I was thinking about where, where could I write and teach this? And I'm not really on social media. I don't do like Instagram. I've never had a TikTok account. I was like, well, l. And all you have to do is write text. I don't have to take pictures. The irony being I posted a picture this morning, but you don't have to take pictures or do little like videos

Speaker B: and that you're on a live stream right now.

Speaker A: I'm on a live stream?

Speaker B: Yeah.

Speaker A: I, yeah, I'm honored. When I first started, I was like, I will never do a podcast. And here we are. Um, so I was like, maybe I'll just see what happens. And so I started kind of posting and really throwing spaghetti at the wall at first. I started talking about, um, productivity tips, how you can get more done because we're asked so much. And that was. Some people liked it. It didn't really go anywhere. I did a couple of posts about data visualization and those just took off and I was like, oh, okay, great. This is, this is like the thing that people, people are responding to. And so I just, I kept sharing and then the things that got more reactions, I leaned into that more and that kind of helped shape what I, what I talk about today.

Speaker B: Very cool. That is awesome. Um, and it's. There's so much that resonates with me, um, in terms of what you said. I know when I started out as a data practitioner, like, I was doing very, like, hands on keyboard work. Like, um, you know, kind of like just responding to requests that came to me. And like the first several years of just kind of grinding out, you know, analysis and things like that, like, I was valued for the work that I did, but I never really, like, felt I was, I don't know, like I was never, I wasn't influencing anything, you know, to use the word from the resource that you just, um, put together and published out today. And so, um, I realized very quickly once I got into a manager role, in analytics, I kind of got into the manager role because of the good technical work that I had done. But when I had to start actually, you know, getting investment in projects and getting people excited about using new data products we were releasing and things like that, like what, there's that saying of what got you here is not going to get you there. And um, Right. Like the technical skills were not going to get me to the point of where I would be scaling data products, you know, and getting them widely used across an organization and getting everybody excited about it. Like that had nothing to do with the technical skills. And um, um, I had to get really good and interested really fast at influencing and presenting. Um, and you know, like I said, I'm not an expert on behavioral science, you know, but um, um, I had to pick up on kind of what others that I noticed were good at influencing were doing in their presentations. These were non technical folks and bring that to my presentations on data products and around technical products. Right. So um, I love what you're doing. I think that um, folks would be very, very wise to follow your content to you know, to get the resources that you're putting out around this because it's critically important. Um, especially right now. It's, it's not like this was just important a few years ago, this is important today. Um, I think probably the most important it's ever been.

Speaker A: So I think it's, it's, it's extra important for, for two reasons too. It's, yeah, uh, I m mean more than ever and I think we probably said this every year, but it continues to be true. People are bombarded data and decisions and information all day long. So when you're presenting your analysis to a leader, you're probably the 30th piece of information they've received that day. And it's 9am Right, right. And so it could be the right answer. Like the answer could be, you know, we found X, we should do X. Yeah. But at that point what, what makes yours stand out among the 30 other things that came came before it in just the hour before. And so we have to find a way to cut through the noise. And it's the same thing as you could have the cure to cancer. And I'm not saying our work is the cure to cancer, but you could have the cure to cancer. And if you can't get that message to people in a way that they can hear it, it can cut through the noise of all the other news that is out there and the information they're getting, they're never going to benefit from it. And so I think I've had people sometimes say, oh, it's so, it's so salesy, it's manipulative. I'm like no, because even not having a strategy is a strategy, right? It's, you have something important to say, why not say it in a way that people are going to understand and pay attention to, right? You're only doing yourself a disservice if you're going to say, well they're logical, all they need is the number and they'll make a decision. Every single person makes decisions with emotion, even the most senior of leaders, right? You can say here's the hard data and they can say my gut is saying do this instead. Not saying that's the wrong answer. Sometimes the gut is better than the data, but saying that decisions are not made based off of a number you pulled out and we have to cut through the noise when there's just so much data and information out there right now the second piece is with AI, it is probably going to take a lot of our like 80% of the work that we do now could probably get moved over to AI. All the time we take cleaning data, making the reports, making dashboards, running analyses, putting together reports. That's all the stuff that AI can get really good at. And it is what AI is not going to get good at. I mean I won't say never. Who knows, it's terrifying what it can do. But at ah, least for now, you know, it's not going to take that. It's not going to know that leader's goals and priorities and pain points and how to cut through the noise and how to get them to care about that data and that analysis. So it makes that skill so much more important right now because the playing field is getting leveled when it comes to technical skills right now. It just is. And the thing that is going to set you apart is saying how do you make this insight matter? I, I have, you know, worked with people who are 10 times the analyst I will ever be. They can run the most advanced analyses, they can pull out insights and they can work with data I could only dream to work with. But it goes nowhere because they present it and it's confusing and it's, it's like this wasn't really tied toward anyone's goal. And I can run an average on something. I can do more than run averages. But just for the sake of the example, right, you can like run an average and if that's the information someone needs and you can get it in front of them at the time that matters. That's going to go so much farther than that crazy cool analysis someone else just did. So, uh, a bit of a tangent, but just why I think that like, these, these skills are so important right now, but no one's teaching us that and we're just told we need them, you know, so that, that was the gap that I really saw.

Speaker B: I see it as well. And it's a perfect segue into kind of the next question here. And that is. Well, you mentioned, um, in the first part of uh, your comment there that, um, you have to be able to cut through the noise. And why is it, you know, you're absolutely right and that we have an abundance of data, probably the most that we've ever had access to. We have the most technical tools we've ever had, you know, to analyze that data. Why is it that data professionals, um, and I mean, I guess anyone in general has such a hard time cutting through the noise, finding insights and sharing what's really needed while making that emotional connection like it sounds, it seems like it makes so much sense as we talk about it here now. But like, why is it that folks have such a hard time pulling that together?

Speaker A: I think it's never been part of our education and it has been called the soft skills, especially in fields like technology and data, which make it seem like, oh, that's, that's squishy and that's not as important. And I, I, to be clear, I don't think it is school's job to teach us these skills. Right? I think it is school's job to teach us the technical skills, the foundations, everything. We're going to need to be a good analyst. Whenever I post or share things, I am assuming that you know what quality data is, that you know how to analyze it, you know what makes something reliable and valid. Right. And I think that comes from school, and it should. It's not a professor's job to teach you how to influence a business leader. That's insane. That's not their job. Right. Just like we wouldn't ask your manager to teach you how to like, calculate an average. That'd be ridiculous. But then we get into the real world and I think there's a number of reasons that we aren't, we aren't taught this one. It's, you're just kind of, everyone's busy. You have to be kind of thrown into the fire and you'll kind of hopefully learn by doing. If you're working with good people. Um, it's also, you mentioned this before. What gets you promoted to manager is often you were a really good ic, right? But the skills that make you a good manager are not the skills that made you a good ic. And so you have these managers who are like, I'm a manager now and I'm really good at technical skills, but I actually was never taught how to set a strategy, how to lead a team, how to write. Like I'm supposed to just now learn that in my new manager training. So I think it's just not, it's not formalized. It's harder to formalize. It's easy to say there is a right way to calculate an average. And here it is. It's very hard to say. Here is how you influence a decision because it's so contextual, right? You have to know your stakeholders and your leader and the goals and the pain points and where you're at in the quarter. And you have to have all that context. And so, uh, you can't just make a training and teach someone about it. And then we go so far to say, and influencing is a soft skill and it's a people skill and that people go, oof. Uh, I'm, you know, I'm an analyst and you know, I've had people say, if you actually worked with like good people, they don't need any of that influencing. They can just see a number and they know it's important. I'm like, no, like. And no one has made that comment to me who's ever worked with senior leaders in some of these companies, right? Because they know it's so much more than that. So there's kind of a number of things working against us in this. Um, but I think people are seeing more and more how important it is. And I think people are so hungry to learn it, they're just looking around like, how, how do I, you know, if I don't have a manager and a team who are really pouring into me and investing in the skill, where do I look next for it?

Speaker B: And that is, I totally agree. That is a perfect segue into some of the resources I'd like to talk about that you've put together, um, for data practitioners in this area. Um, I know you have a self paced course. There's a couple things I'd like to talk about. I know you have a self paced course called Story Driven Charts. And then you just released, uh, the Analyst Influence Playbook, which I downloaded my free preview of the first six pages this morning. Um, and Uh, I am certain I am going to make the purchase of the rest of it because I think this is such an important topic. Um, but uh, would uh, love to hear kind of how you're educating folks on these things in those resources that you're making available to the data community.

Speaker A: Yeah, happy to. Uh, so the first one, Story Driven Charts, it's about a 90 minute self paced course and it's the whole point one, it changes your mindset around charts, right? Oh, I see you're putting up comments of people saying such nice things. Thank you all.

Speaker B: Yes, these are comments from your fans.

Speaker A: Uh, the ones I paid extra. I'm like. And now chime in, um, so they'll get their money's worth. So with Story Driven Charts, it's. I had started posting all these things that I had learned on LinkedIn and this was still when I was at Google. And the. I never expected. But also I started getting emails and pings from other Googlers, which is what we call other Google employees, saying, hey, could you come talk to our team about this? Do you have a workshop on this? And I was like, oh, I mean I, I could if that would be helpful. And so I was like, let me noodle on that. And so I kind of went back and I thought about, I was like, well, what would it look like to make a workshop and what would be my goals for it? And I had a couple goals and one was there's a lot of workshops out there right now and they are eight, 10 hours long. They will teach you every edge, case, nook and cranny and if that's what you need, amazing. They will deliver that. Let me know, I'll recommend some to you that I think are great. I think a lot of analysts, they just need the foundation. They need to know what's going to cover them in 90% of scenarios and then they'll know where to go look to get that 10%. And so my goal was I want to give you what you actually need to know in as short as time as possible because you are busy, you don't need to sit and watch my eight hour course. I want you to learn here's what works, here's why and here's the mindset shift you need to make around your charts. And the mindset shift is it's not just I'm going to show you everything I did and all the data in one chart and I'm going to hope that you understand the takeaway. The shift is what is the point you are making with this Chart. So I call it story driven charts. Before you even design that chart, what is the message your audience needs to know? What is the one thing, if you didn't even have a chart in this presentation, what would you need to know to take away from it? And so that's kind of where I started with. I put it together and I was like, let's see if this resonates. And so I started to offer it internally at Google. Um, and I just got so much amazing feedback. You know, I was able to refine it even further with people saying, you know, that was a little bit confusing. It was like, great, I'll make that section a bit more clear. I'll add more examples. And we're just hearing people saying like, oh, my gosh, that totally changed. And I thought I was making it for people analysts, but the people who are buying it the most or who were signing up for the most were people in sales who had to go give presentations to CEOs, to other companies and convince them to buy our product, to invest more in ads. And they were saying, we have no training in how to put these into charts, and I need to show them, you know, what'll happen if you invest in our, in, you know, in more ads. What, what does this look like compared to competitors? I was like, wow. Like, this isn't even, this isn't even just a people analytics problem. This isn't even a people fresh out of college problem. Like, if you've been at Google for 10 years and you're saying, oh my gosh, I've never had this kind of training. And so I was like, okay, it's getting great feedback. And at first it was two hours, and people said, shorter. I was like, okay, shorter. Like, I want to give you as much information as you can as quickly as possible. And so that's kind of where that, that developed. And I've been now selling it. Um, I did a few live versions, but, you know, time zones, people saying they couldn't make it. I was like, great, I'll just make it on demand. You can do at your own pace. And so I was really proud of that. And then I started. Like I said, I've always been interested in behavioral science and psychology and why we do what we do. And I love to read books about influence and persuasion and marketing and copywriting. And, uh, I had no agenda when I was reading these books or listening to these podcasts. It's been years. I just thought it was fascinating, right? Like, you could use certain words and people are more likely to say yes to you or to buy your product than other words. It's the same product, but the words you use or, you know, if you try these kind of tactics, Week one, week two people will do XYZ and I started thinking, why are we not doing this with our work? Like we are selling our insights to leaders, right? Just like marketers are selling products. Just like people negotiating deals are trying to get people you to say yes their deal. We're doing the same thing with our data. We're trying to cut through the noise just like marketers are. We're trying to get you to see the value. We're trying to get you to say yes to our recommendation. And so that became part of my newsletter was let me just, you know, every week share some tips about here's a way you kind of approach your work that's going to give you more m impact. Again, it's not a here's a new analysis you don't know. I'm assuming you know all of that. It's what do you do once the data is ready and you're ins and you have your insight? And so then I decided, well, I keep telling myself I was like, I need to take a break, I'm doing too much. And then I get a new idea and here we are. And so I was like, well, what if there was just this playbook? And it was, here are ah, the behavioral science principles that matter for analysts. Here's what it is and here's how you apply that as an analyst to data, to working with stakeholders, to leaders. Here are kind of like phrases you can use. Here are scenarios you're going to run into. Instead of doing this, which is the typical way, try this way instead. And so I put that all into, into a playbook. It's called the analyst influence. The analyst influence playbook. Um, and packaged it all together and then just offered it this morning and it's taken off, which I am just so humbled by. Um, really excited to see what people think about it. My goal with all of these is as I get feedback, I want to refine and make it better. Right. So if you're like those principles, oh my gosh, that totally worked great. I will make that section longer. Or if you're like that one didn't really apply, great, we'll cut it. And so I just, I feel like I've just kind of, I've kind of covered all the things I love. Like, I love data visualization, I love influence, I love teaching and communicating. So it's just kind of become this little, this little world I feel like I'm creating. And I'm so glad that people are coming into this world with me because I'm so passionate about it. And it's been so fun to see, see the reactions, to hear the feedback. And so, yeah, I. Would it be helpful to kind of talk through some of these. These influence principles to make it a little bit more concrete?

Speaker B: Yeah, for sure. That would be awesome. That would be amazing. Yeah. And I love how this just organically came together. Like, um, I think that's how the best products and resources are put together in the data space especially. I've seen folks come in and try to push new things that did not come as a result of their own learnings and experiences or organic, um, just interest that they had or questions that they got from people. And so I love this and I'm not surprised that this has taken off.

Speaker A: But yes, honestly, I thought I was like, I'm only going to post about data visualization and it comes from, okay, people say, great, but how do I get people to care? How? I'm like, oh, right, right. And so you listen to the questions that people are asking you and if you say, I have an answer to that, like, why would you not address that? Right. If I was only posting charts, I'm sure a lot of people love it, but it would also miss out a huge need. Again, you made a great chart. How do you. How do you tell a story around it? Um, so let's talk about some of those principles. Um, there's like an insider look into the playbook. Oh, these comments are so sweet. Uh, I didn't even pay for this one, Dustin.

Speaker B: I know. I can't help but share them. Yeah, yeah, there's several comments coming in and, um, I don't want to hold you up, Morgan, from what you want to share, but, um, like, I'll just take Rita's for an example. These are really cool testimonials. So Rita says, I absolutely enjoyed the story Driven charts course and have already started applying some of the tips in my role. I'm excited to dive into Morgan's analyst influence playbook next. And there's other comments like this, but thank you, Rita.

Speaker A: Um, send me a connection request on LinkedIn if you haven't already. I'd love to hear kind of like your feedback on them. So let's talk about a couple of the principles just to make it more tangible, because I think if you haven't really, if you haven't been like, Me. And you've just nerded out on these things. You can be like, well, what do you mean by behavioral science principles? So, so I'm going to talk about three. The, The Playbook covers seven, and it covers these three in, in much more detail. So cool. I'll start with reciprocity. This is probably one of my favorites. And reciprocity, this is. It is across cultures, it is across time. And the idea is when you give first, people are more likely to want to reciprocate and give back. It sounds super simple, but it's also against our nature. Right? We're looking out for ourselves often. We're often thinking about, like, what do I need? What do I want? But the thing is, like, no one wants to feel like a freeloader. No one wants to feel indebted to somebody else. And so the idea with reciprocity is when you make a move first, you are more likely to get something in return. And there is maybe one of my favorite studies ever is from the 1970s. There's a sociologist, and he sent out 600 holiday cards. And people he did not know, he. He got like a Yellow Pages or something, picked out 600 addresses, and sent out his holiday card to these people. And then he waited. And 20% of people sent a holiday card back with warm wishes, pictures of their family wishing him, like, you know, a great merry Christmas. And it's just this wild idea of they have no idea who this is, but they got this card. Oh, uh, I should, I should send them a card too. Like, you don't want to feel like this person something for me, and I didn't do it back. And so there's just this innate pull in us to say, I don't want to like you. You took a step towards me. I don't want to just be ungrateful for that. I don't want to be. I don't want to, you know, take from you and give and look like a freeloader. And you can just see this everywhere. And so how I think about it for. For analysts in the workplace is oftentimes we are getting ready to. To make a recommend. And so we spend all of our time putting together our slides and our proposal and making sure our presentation is ready. And then we just go in cold, ready to ask for what we need. Sometimes that works, sometimes it doesn't. But if you think more about, okay, reciprocity, how do I invest first in this person before I need something in return? And that can look like a few things. One of My favorite moves is, I call it like the back pocket. And it's whenever you have a leader or a stakeholder and they are about to, you know, maybe go do an all hands meeting, or they have, uh, a call with investors, whatever it might be coming up, you can just send a brief email that says, hey, I know you have this all hands coming up. Here's a few data points that might be relevant to any questions that you might get. You might need them, you might not just sign along. They might use it, they might not. Sometimes they will need it, and they'll be so grateful for you. But it says them. Oh, like, I did not expect to get this. This email. This is, this is helpful. They're thinking about me and my goals. That's so great. And, you know, they might say thanks, not think about it again. But a few weeks later, when a new project comes up and they need an analyst on that project, who are they going to think of? They're going to think of you. You're top of mind. They know that you're proactive. You get it, right? And so there's these little moves that you can do that position you as more of a strategic partner. Right. It's also reciprocity works in terms of, uh, concessions. That means you, you're the first to kind of concede a little bit. And so someone else feels like they should meet you halfway. So what that might look like is I say, dustin, can you give me a hundred dollars? You say, no. I go, I know, that was crazy. Can I have 20? And you're like, okay, well, she backed off. Maybe I'll say, sure, here's 10. Right? Like, you feel like you need to give a little because I gave a little. So in the workplace, you might say, hey, our dashboards, they're not good. I think we need to redesign all of our dashboards. And someone says, that's a lot of work. No, you're right. Thank you for that feedback. What if we just take our two most used dashboards and we just kind of update those, see how they land? Well, now you've conceded, so they feel like they should concede a little bit in return, and they might say, okay, that sounds reasonable. Go ahead and do two or do one. And so there's these little strategies you can do. Your dream was still to get all the dashboards right. So you're not going to suggest something that is actually not what you want, but there's these little ways that you can interact and you can give first or make the first move. That's going to get you a lot more influence. So that one's reciprocity. Um, in the playbook, I give a lot more examples for how you can use that. The second one I'll talk about is social proof. And social proof is the idea that we often look to others to figure out what the right thing is to do. So if you've ever gone to a restaurant and there's like, these are, uh, our most loved items on the menu, or you open up Netflix and it says, here's the top 10 today. That's all social proof, because you are more likely to watch one of those top 10 movies to order the most loved item on the menu because, well, if everybody else is loving this and doing this, it must be good. And social proof works best in times of uncertainty, when you don't really know what to do or when you're looking at others who are similar to you. And so, for example, if you already know that you want to watch Love is Blind, I just finished the finale. You want to watch Love is Blind on Netflix, you're not going to be influenced by those top 10. You know what you're there for. There's no uncertainty. But when you're not sure, you are going to look and say, well, what are others watching? What are my friends saying are really good? What's the most popular thing? And so you can use social proof to get your recommendations across in your work as well. So, for example, say you want to suggest that we use a certain vendor. Well, don't just go and say, hey, I looked at all the options. I think we should do this vendor. Look at it and say, hey, our top three competitors, they also use this vendor, too, and have done so really successfully. Or, hey, finance, uh, our HR teams are using this vendor, and they've seen really great results in their goals. I think this would apply here, too. So when you start to point to these other references, uh, if you look to major research like McKinsey or Gallup, and you're saying, here's. Here's like, experts who also agree with this thing, that's going to back up your recommendation. Now, your recommendation should never be just, what are other people doing? Because sometimes that's the blind leading the blind. But once you have your recommendation, you want to look for other examples of social proof to kind of, like, give it wind beneath its wings, right? Like, it's not just me saying, do this. Like, look at all these other credible sources who agree with it, too. So that one's social proof. And the Third one I'll talk about is autonomy bias. An autonomy M bias is the idea that people want to make their own decisions. They don't want to feel cornered, they don't want to feel what, they don't want to be told what to do. And oftentimes people will go in and say, hey, I did this analysis, here's what we found, we should do X. And people are like, no thanks, like great, thanks for the analysis. I don't think we should do X because when you give just that one idea, you've kind of cornered them. You've said, I think you should do this, agree with me. And you've also made the decision to be do we do this? Yes or no. Autonomy, uh, bias says give them two to three options. They should all be reasonable options and then kind of say what your recommendation is. So you might say, hey, we looked into this. If we stick with the status quo, here's kind of what will happen. If we do option A, which is my recommendation, you know, we could, this could be what happens. We could also do option B which could also work. And here's what would happen. Then you say things like, the choice is yours or I defer to you. You give them that you're telling, reminding them like you are the decision maker. My recommendation was a, you know, for these reasons, here are the trade offs. What do you think? And a couple of things will happen when you do that one. Now it's no longer a do we do this yes or no conversation, it's which of these do we do to move forward? Right. So it's not just them saying, nope, um, I'm out. Thank you for coming. It's okay. Let's discuss these options, these paths. And it also puts them more in the driver's seat where if people feel like they've had a hand in the decision, they're much more bought in. M. So if the leader says, great, I agree with you. Option A, let's go with that. They're going to feel more part of that decision and more ownership. So if it gets challenged down the line, they're not going to say, well, Morgan said we should do it. I, uh, didn't really know if it was going to work out. They have skin in the game because they, they chose that too. So they're going to defend it, they're going to stand by it, they're going to be happier with it because they feel like they were part of that co creation process of the outcome. And so it's again, it's all the same work, it's the same analysis you did. It's just how do you present it in a way that people are going to be more receptive to it and also going to be way more bought in even once a decision is made that they're going to kind of keep, keep their hands on it too. Not just say, great, approved, go forward if it fails. Not on me. So m. Those are my three. There's four other in the playbook. Um, I know I'm also pushing the time on how long we were going to chat, but I'm just so excited about this stuff. So I wanted to give people a lot of examples that they could start using today.

Speaker B: No, that's, there's, there's no problem with the time that um, was such so insightful that there's uh, no way that I would ever put a cap on the time around talking about those topics. Um, reciprocity, social proof, autonomy, bias. I have so many ideas both as like a practitioner as well as like a programmatic leader, strategic leader, you know, in terms of how, um, those things can be applied. And I don't know about anyone else, um, but um, I've got to go and buy the Playbook now to learn about the other four. Like that was the best possible tee up that you could give to the rest of these very. I've got to know what the other four are. Uh, because those three were so powerful, I've got to know what the other four are. Um, that's really, really cool and really, really powerful. Um, appreciate you walking us through a preview of those three pieces. And like I said, I think whether you're in an analytics role, technical role or programmatic strategic role, um, these things will be really, really helpful to you in terms of your ability to influence and make an impact with what you're doing. So I'm totally bought in and a believer in this, um, based upon my, you know, years of experience as a practitioner. Yeah, for sure. Um, very cool. This is super exciting stuff. Um, and I, uh, guess there was one question in the. Well, you know what, how about this. Let's talk about how folks can get access to this content and find this content first. And then maybe to close out, there was a question around personal branding. Maybe we can sprinkle in one final question, um, around personal branding, because I think you've done a really great job, um, of that. But, um, how can folks find this content, um, and your newsletter and all of the stuff that you make available to the community?

Speaker A: Yeah. So, uh, I think the one you can follow me on LinkedIn. I'll, I'll post, I post about things. I have some links in there. Uh, my kind of like One Stop Shop link. I need a better one. I need to be more techy but I'm not yet uh, is you can go to Stan Store slash Morgan Deppenbush. Um, Stan Store is if you've ever heard about thing people used to kind of like house their, their products. Um so you know one day I'll have just morgandupenbush.com lead to that. Right now that just leads to my newsletter. But you can start with that link. Uh if you can't remember all that, thank you for putting it up there Dustin. If you can't remember all that, uh just go to my LinkedIn and I have in my featured section I have, I have some of this stuff plugged there or send me a message and I can, I can point you to it.

Speaker B: Very cool. Awesome. And I, yep I just put the website address there in a banner. Um so for those that are watching live you can see it on the recording. Again it's the stand store. Um, Stan Dot store Stan Store slash Morgan Duffenbush.

Speaker A: Um, I guess it's like a man's. I don't know what Stan. It's like a man's name. S, T A N. I don't know where the name came from but it's his store I guess.

Speaker B: Well I guess it makes it more memorable if anything. I, we'll um, but we'll, we'll, we'll put it in the show notes. So if you are listening to the recording I recognize that you can't see the visual that I have up right now but I will put a link um to the Stan Store slash morgandeffenbush in the show notes. Um so that's available to take a look at um, as you get back to your computer um, or your phone or whatever. You can take a look at the link there. Morgan does have her trending up newsletter. Um her Data Viz Resources, the Analyst Influence Playbook which we just talked about and got um, some preview content from and then also the self paced story driven charts. Um, course is accessible there as well. Yes, very cool. Um, there was a question um, that actually tied to I think the last question we didn't get to and that was around personal branding and so maybe we'll just um, let the question from the chat drive this one. Um, wait.

Speaker A: Okay. Someone just said I don't know if this is a joke or real but someone said Stan as in the Gen Z slang for being a huge fan of someone. I don't know if that's true or a joke, David. I hope that's true.

Speaker B: That's awesome. If that's true. David. Yeah. Um, wow, cool. Thanks for sharing. Um, uh, cool, cool, cool. All right, I'm just going back up here. Um, so, yes, personal branding. Um, Kashish, um, has a question. Do you have any tips for any new analytics grads developing their personal brand on LinkedIn or entering the job market? So we had, we had talked a little bit about maybe talking briefly around personal branding. Just because I think Morgan has done such a great job with building a personal brand. I think it's going to go continue to skyrocket with the content that you're putting out. But any advice that you have around, um, personal branding for a tech professional?

Speaker A: Yes. So there's kind of two parts to that, that question. I'll do the second part. That's quicker. So in terms of on the job market, if you are applying to jobs and you're interviewing your technical skills, like I said, they're table stakes. Put them on your resume, that's what's going to get past the screen. But when you're in those interviews really highlight that you understand the second stage, what happens after the insight, Right. How might you tie it back to companies goals? How might you get leaders to care and understand? Because at least when I'm interviewing, that's what I'm looking for. I know that if I'm interviewing you, you've passed the technical skills checklist because we looked at your resume. I'm looking for do you understand what comes next? And you'll get a lot of people who are interviewing will just say, I know this analysis and this analysis and I ran this, it's like, great, I know you can do that. But do you know what comes next? So really make sure you highlight those then in terms of building a personal brand. Um, yes. I think it comes down to a few things on LinkedIn. So one is knowing your why. So are you posting on LinkedIn because you want to get a job? That's going to be very different content than you're posting on LinkedIn because you want to have a giggle. I have a good friend and he posts every day too. And his whole value, not all his value, but a lot of it is just giving people a smile, right? So he'll post funny things on LinkedIn. People love it, they laugh, it resonates with them. And that's a very different approach than if he was on the job market, right? And he was trying to talk more about what he's doing. So again, if you're building your brand, why and is it because you want to expand your network and just know other people? Are you trying to get a job? And so you're trying to position yourself. So first, know your why, because that's going to determine your content. And then a lot of people I'm going to assume the why is, you know, I want to position myself as a good candidate. I want to be able to discover from recruiters or I want people to look at that when they're interviewing me and want to hire me. So I'll assume that's the answer is you're trying to kind of put yourself on the job market. There's a few mistakes I see people make. The first is they want to come out and act like an expert. And so they'll post things and be like five dashboard mistakes you're making today. And it's like, okay, you know, like you've made one dashboard, right? Or, or they come out and they'd be like, here's how, uh, you get leaders to say yes. And they, you know, they're, they're one year in the job and it's like, you don't have to be an expert there. You, if you are, great, be the expert. Talk about it. You can also be someone who is just kind of like the, you know, the giver of information, right? So you might say, hey, I just learned about this great tool. I'm going to give you guys. Here's a quick three bullet recap of this tool and what it does. Or hey, I just did this, this workshop and I learned this tip. I'm going to share it with you guys. You guys might like it too. And so you're not trying to say, look at me, I know everything. But one, it signals that you are kind of plugged into your field and your industry and you talk about things that are relevant. People want to follow you not because they think that you're 10 years ahead. They will follow you because, hey, this person is kind of going out, finding these resources and putting them all in one place for me to find them, right? So you can post on LinkedIn. And that takes away a lot of that imposter syndrome, right? We're like, well, I'm not an expert. You don't have to be. Right? If you are a grad student right now, post two times a week and give a quick summary of an interesting article you read and how that might be relevant to companies. Right. I would follow that. I'd find that super interesting. And then the third, the other mistake I see people make is they, they're just talking about the. Like, I was going to say the no shit, but like, the no does. Like, you know, people post and be like, you need a dashboard.

Speaker B: We just saved ourselves. Uh, you just saved me from having to check the explicit content box on the.

Speaker A: It's family friendly now you can listen with your kids. M. Your kids will love it. You know, it's like, you don't need to go out there and be like, Excel is not dead. Like, obviously, you know, like, don't, don't just kind of post the things that are common, like have a point of view and those are what do. Well, I post things all the time that people say, I disagree. I'm like, great. Like, there's more than one way to do this. I've sometimes revised my opinion because someone had a really good counter. But if all I was doing was going out there and saying, you need charts. And I was terrified of anybody disagreeing with that, like, no one would follow, they'd be like, great. Thank you. I know that. So that's how I think about building your personal brand. And then just the basics. Like have a, uh, clear, close up headshot of just you, right? It's. You see these pictures of like you're way back holding a dog and like you can't even see who they are with you and three friends and. Or it's blurry. Have a picture of you. Have a. An about you section that is really clear about like what you do. Make your headline good. Your LinkedIn headline is the thing that is like searchable with keywords. And so sometimes I see headlines that's like, be the change in the world. Like, yeah, you should. But like, don't make that your headline because that's not doing you any favors. Like, recruiters are searching. Analysts, they're not searching. Like, be the change. So your headline should be, what are the keywords that people might be looking for? Mention the field you're in. Mention two or three skills you have. Mention kind of like what your unique positioning is. Right? You know, and. And then my last thing would be like, just kind of drop the cliches. Like people who are like, you know, insights into action or like passionate about data. Like, yes, okay, but what, what kind of makes you different? So just look at people's profiles that kind of stand out to you. Look at what they're doing and then just that's your. That's kind of like your new resume. Make it look approachable and make it look you and human and don't have chat. GPT write it. It's the last tip.

Speaker B: That is fantastic advice, and you have given some amazing advice on some super, super important topics today. So, first of all, I wanted to thank you, um, for taking this hour to do this, especially considering you were planning on going on LinkedIn to do writing and you agreed to do a live stream of a podcast, which you never. You said you would never do a podcast.

Speaker A: So, I mean, for the first, like, three or four months, I, I would. I would be. People. Nice people would ask me, like, do you want to do a podcast? And I would say, like, no, thanks. Like, that's not really, like, what I'm into. And then I, I did a. A live with my friend Bill Yost. We did a dashboard confessional, thinking it'd be like. Like, we thought it'd be like a giggle. We'll call it Dashboard Confessionals. We'll just talk about it, like, to be an analyst. And then he went and uploaded that to Spotify, and he was like, boom, now you're on a podcast. I was like, well, I guess that band aid's been ripped. I can't. I can't say I'll never do a podcast.

Speaker B: So.

Speaker A: And it was fun. So this was fun as well. So thank you.

Speaker B: Yeah, for sure. Absolutely. Yeah. And I think because, you know, Morgan was willing to do a podcast, um, you know, which was something that she said she wouldn't do, like, and she came here and gave us an hour's worth of knowledge on such critical topics. Like, I've got in my. I have a page of notes, actually, myself. So we talked about Google, we talked about people analytics, but then you got into data visualization and, um, how it connects with, um, or how you can make an impact with it, um, from some, you know, behavioral science, um, concepts. And you talked about how. You mentioned how they can influence, um, folks in the workbook that or the playbook that you put together. Um, you talked about branding. I would encourage folks if, you know, you had to have learned something. If you listened in to whether it's the live stream or the podcast episode that gets later released. If you learned something, share it on LinkedIn and tag morgan to it. You know, let us know what you learned from this episode. Or if, if you don't want to do a post, drop it into the comments right now. You know, on the. The video recording here, let us know, like, what is.

Speaker A: I hope you learned at least one thing and I did not just take an hour of your time.

Speaker B: No, I've got tons myself, especially around the concepts of reciprocity, social proof, autonomy, bias. So many ideas on how these can be applied. Like I said, I have to go get the playbook now to get the other four that you mentioned there. But I'm going to do a post myself. I would encourage others share what you learned. How would you use it? This episode was packed with great information, so thanks so much, Morgan.

Speaker A: Fun. Thank you so much for inviting me. Podcasts aren't so bad.

Speaker B: That's awesome. I'm glad you think so. Mission accomplished. Podcasts aren't so bad. Um, I got on the scrolling marquee underneath us. Be sure to follow Morgan on LinkedIn and then I'll put up one more time, um, and read it out for those listening, uh, on the recording. But, um, Stan Store, slash, Morgan Deppenbush. Um, check it out. She's got all of her resources out there that we talked about in this show. This will be in the show notes as well. One last time. Thanks, Morgan, for joining.

Speaker A: Thank you, Dustin all.

Speaker B: Uh, right, take care. Have a good rest of your day.