#219: To Generalize or to Specialize? That is the Question!

There are only so many hours in a day and only so many days in a year. Logically, then, the best way to grow a career as a data worker is to spend as many hours as possible doing focused data work, right? Well… probably not. In this episode, we dove into generalization versus specialization — what does that even mean, and how should we think about balancing between the two, and how can interests and activities outside of the data work itself actually make us better analysts? Bonus activity: listen for the hosts’ overt trolling of Tim to see if they can get him to come off mute in his role as associate producer for the episode.

Links and Items Mentioned in the Show

Photo by Jannes Glas on Unsplash

Episode Transcript

[music]

0:00:05.8 Announcer: Welcome to the Analytics Power Hour. Analytics topics covered conversationally and sometimes with explicit language. Here are your hosts, Moe, Michael and Tim.

[music]

0:00:22.9 Michael Helbling: Hey everybody, welcome back. It’s the Analytics Power Hour, and this is Episode 219. As I get further along in my analytics career, I frequently make this joke, something along the lines of, I used to know things, but now I just know people who know things, and it’s sort of true, to make progress, it looks different ways, sort of like, is there an ideal path in analytics? It’s just a lot of different disciplines that are part of our industry, and so sometimes it feels like you have to be very specialized, but then other times it feels like you need to know a lot of different skills, and let’s be honest, not many of us can replicate the super-specialized set of skills like somebody like Tim Wilson, the quintessential analyst, but we can all certainly feel a little bad about the fact that we can’t. But anyways, joining me in that feeling sometimes are probably my two co-hosts just occasion and my conversation partners, Moe, welcome back.

0:01:24.8 Moe Kiss: Hi, how are you going?

0:01:24.8 MH: I know it’s going great, and I’m so glad to be back on the show with you, and I’m very happy to welcome back Julie Hoyer as our guest co-host for this episode. Julie, how are you going?

0:01:39.2 Julie Hoyer: It is going well, I’m so excited to be here and I can’t wait to talk about this topic.

0:01:44.4 MH: Yeah, I’m also really glad because I sort of… For this episode, you’re kind of like a Tim replacement, and this is gonna go so much better. I had a line in here about how much I was looking forward to having this conversation with you as part of it and not Tim, but I took it out, but now I just said it again.

[laughter]

0:02:00.9 JH: You hear that Tim?

0:02:01.1 MH: Anyways. Alright, that’s… He’ll hear. But it’s okay. Alright, so I thought maybe with this sort of idea of sort of specialization or generalization, and we’re probably gonna talk a little bit about this book ‘Range’ by David Epstein, or is it Epstine? I don’t know how to say his name, but as we go through the podcast, I thought it might be fun to maybe just share a little bit about our different backgrounds, ’cause I think we’ve come from a wealth of different experiences and things like that. I don’t know if somebody wants to go first, but I will cease talking and see who starts.

0:02:38.3 MK: You want me to go?

0:02:40.5 MH: I mean, yeah. If you want.

0:02:43.9 MK: I’ll start us off. All right, my background. We’ll start after high school. It’s a good place to start, right? [laughter] So I ended up going to college to actually play volleyball, so that’s how I ended up at Akron, and I started off as chemical engineering because I was convinced that my science was what I wanted to do from high school, and so I started in Chemical Engineering for two years, and it was actually a math professor that convinced me to make a pivot in my sophomore year to a five-year program that was Applied Math, Bachelors and Applied Math, Master’s. Actually, I think my first pivot, I was supposed to pair it… My master’s was supposed to be in polymer engineering ’cause I had all the chemistry classes that I was taking. Yeah, and then I was a semester into that and I realized I kind of hated the chemistry stuff, it wasn’t… The way they apply it was not how I imagined, so then I pivoted fully to just math. So I did that and I finished up volley ball.

0:03:43.2 JH: For the record, my jaw has dropped to the floor hearing this, but carry on.

[laughter]

0:03:51.8 MK: Yeah, and I… It’s funny, I… People were like, “So what do you… You use your calculator a lot?” And I was like, “No, I just work with symbols, that’s literally all I do in all my classes,” it was all theoretical. So it was actually really hard trying to figure out my first job coming out of that, because even when you go to a job, there’s… Nobody’s like mathematic degree, it’s like nobody wants you. Engineers don’t want you. Nobody knows what to do with you. So I was kind of floating around, and to be honest, I happen to find one of the only booths that said, “Math majors welcome,” and it was for Search Discovery, and I ended up realizing I could do a job in digital analytics. And Michael Helbling was my boss. [laughter]

0:04:33.5 JH: Oh my God. I never knew this. This is phenomenal.

0:04:38.8 MH: Wow, after hearing that though, that’s so impressive. And frankly, now I’m re-intimidated and it’s so cool. Anyways, awesome. Thanks for sharing.

0:04:48.3 MK: Yeah.

0:04:48.3 JH: Oh God. Mine couldn’t be more different. I feel like over the years at conferences and stuff, and possibly even on the show, people have heard me talk a little bit about, like when I was going through school in university, I thought… Dad was an engineer, mom was an English teacher, and I thought I had to do more Sciencey and Mathy stuff or I had to do more humanity stuff, and I really felt pressured to choose between the two, even though I loved both. I did end up going down the humanities route, and my first “real job” was actually working with youth offenders for the WA state government, so literally working in the courts and the prison system and all that sort of stuff, which everyone is always like, “Huh? I don’t understand.” But when you… It actually makes sense. So basically, I was working, I guess, in what you call frontline services, and I realized that I wanted to go write the policy that informed those services, ’cause people kept flying in from Australia’s capital, Canberra, from the federal government and being like, “We’re gonna do X, Y, and Z,” and I was like, “You don’t know shit about this because you’re not working here every day.” So I decided to go to the capital of Australia and write policy.

0:05:56.8 JH: And then I realized over time that policy is informed by data, and so then I made a move from one department to another one to work in the data space to inform the policy, and then lo and behold, I now work in data. So it’s like… Yeah, I’m weird, I’ve had five totally separate careers, I haven’t really had… I’ve definitely… What’s that word? It’s a maze. My career is a maze, not a ladder that’s for sure. What about you Helbs?

0:06:24.0 MH: Well, yeah. If yours is a maze, mine is a pile of string that’s been stomped on and twisted up for… [laughter] No, I mean, I took three solid attempts at college, and I did a little bit of work each time. Some of them even… I made Dean’s list once, but I was like… First I was gonna be an electrical engineer. So yeah.

0:06:46.7 MK: Similar starting points. Yeah.

0:06:47.0 MH: Engineering people. So that’s right, yep. And then after a freshman year at doing that, my parents were like, “Yeah, we don’t wanna pay the kind of money for you to get those kinds of grades, so why don’t you figure out what you really want.” So then I took some time off. Then I went back, I studied Accounting, studied History, and almost finished the degree in History and Accounting, but I never actually finished ’cause I ended up in this weird field called Web Analytics and did a bunch of other side jobs and things like that. I was a Telemarketer for a little while. I was a credit card account specialist, I did data entry, I’d worked some construction, I traveled all over Europe, I did a lot of different random things, but eventually found a home in this weird little misfit community called web analytics back in 2004, so yeah. It’s really interesting because my journey and Moe your journey has these paths where we find our way in, and Julie, I know you didn’t start out being like, “Oh, I’m gonna go into analytics,” but it was sort of like, “Hey, what I studied in school applies to the thing I’m gonna do.” How does that feel like?

[laughter]

0:08:10.9 MK: Well, I think you were sold the falsehood that you go to college and you decide on a degree and there is a linear path and it’s easy to follow, and then you go to get a job and you realize it’s not. Yeah, I was very happy just to find something that used some of the training and things I did in college, but I will say, I think I even said this in parts of my interview, I know nothing about marketing, and I’ve never worked with this type of data or numbers, but I was like, but it’s still numbers, that’s what I’m passionate about, and I wanted to problem-solve. So I was excited for the chance that it did feel like a step in the same direction I was hoping to go, and I loved the idea of consulting as well, so yeah, I felt really lucky to fall into that because people kept saying, “Oh, your first job will probably be something you don’t wanna stick with, or you realize you hate it,” and this and that, I’m four and a half years in, and I still love what I do, so I feel extremely lucky. But, we’ll see how it keeps going. It’s always an adventure, ’cause now after reading ‘Range’ and hearing your guys’s stories, I’m like, “Should I pivot hard?”

[laughter]

0:09:19.6 MH: I don’t know. Once I found analytics, I have stuck with it for 18 years or so, so I don’t plan to quit now.

0:09:28.1 MK: That’s good.

0:09:29.1 JH: I guess though when we talk about specialization or generalization, so far we’re really talking broadly about analytics versus other things, and I guess in my mind, when we first started talking about this topic, I went deep in just the analytics and data space of like… ’cause I’m actually facing this a lot with people in my team and their career development about whether they wanna specialize or generalize in terms of like, “Do you really wanna go deep on machine learning models, do you wanna become an analytics engineer and really specialize in I guess data-warehousing and pipelines and ETL and those kind of skills or… ” There was one, I guess job group that we started talking about within the team as being like an analytical powerhouse, and I’d call that as being more of the generalist, you are able to do a little bit of A/B testing and have some stats background, but you can do a really deep piece of analysis. And I suppose what I’m trying to get at is, I’m still not sure what the right answer is specifically for our industry, and whether it all just comes down to personal preference or whether they are like pros and cons to one or the other.

0:10:44.5 MH: Yeah, you’re so right. And the weird thing is, Moe, the longer I go, the more I’m kind of like, “Oh yeah. You need to respect that there’s these different disciplines, even within analytics and their specialization.” Part of maybe my goal on this episode is to find a way to get Tim to come off of the mute and say something because he’s so frustrated with something I say. And so just know that’s out there. But I think early-on, my first job in analytics, just to be clear, was implementing this analytic software that was popular at the time, which was mostly installed as a piece of software on a server in a physical location. So companies would hire my company and we would go in and I would implement this software inside of their server room and you wanna talk about impostor syndrome. [laughter] I was like, I had no idea what… I was like, “No one should be hiring me to do this.” But what I started to learn was sort of like, “Is that what I wanna be doing?”

0:11:51.9 MH: And I remember I was interviewing for a job with a company, we were getting pretty far along, and they flew me out to Seattle where their head office was, to sit down with the leadership and talk about this job interview, and basically they’re like, “We want you to be this key resource person to manage the implementation of this massive client that we have, and it’s all these websites, but it would basically be an implementation-focused role,” and I remember being like, “I absolutely don’t want that job.” I wanted to steer my career towards something that was more like a business analyst, not necessarily an implementation specialist, and I remember basically nuking that interview and being like, “I gotta go home, this is not the job I want.”

0:12:36.5 MH: And it was sort of like, “Okay, then how do I chart a path to the thing I wanna do?” But there’s, in our industry, there’s a lot of different people who have a lot of very different skill sets, and they can be sort of general skill sets. I think the world of Google Analytics is probably the best example of this, where you’ve got these varying ranges of skill sets in terms of implementation capability, analysis capability, data visualization and storytelling capability, and all the layers are sort of there in analytics, but they’re done at varying levels of skill in terms of the people involved, and each one of those, like we’ve all interviewed people on the podcast who are specialists in every one of those things I’ve talked about, and their whole career is focused on those things.

0:13:23.0 MH: So like Brent Dykes on storytelling or Leah Pika on visualization, or Jeff Chasin on architecture of implementations or whatever the case may be, we all know those people or at Search Discovery, Julie, like the optimization team and the incredible people there like Val and… So there’s all these people who have such unique deeply specialized skill sets. And so for me, a lot of times I’m like, well, yeah, I sort of have this general knowledge, but I’m not one of those people, so I don’t know. I find it very limiting a lot of times in terms of like, “Oh no, I can’t possibly do that,” and then sometimes you’re forced to get in there and do that and you’re like, “Okay, I guess I did it okay.” But I’m not Tim Wilson.

[laughter]

0:14:09.8 MK: I think it’s interesting too that you bring that up, ’cause I like reading the book ‘Range’ and then even talking about how you guys started off in your career, it’s like it felt like bigger jumps, even outside of the industry. But it’s interesting for the fact that within our industry it is like a microcosm of all these different specializations, and even to be a generalist in digital analytics covers a lot of specialties, and I do think…

0:14:36.5 JH: Totally.

0:14:37.4 MK: That is something that I think is unique to Digital Analytics. I’m sure that happens in all industries, but I feel like it’s maybe more… It’s blown up somehow in digital analytics because you range from super technical backend-type technology all the way to like, “How do I actually utilize it, how am I approaching mathematically how to use this data? What is it telling me?” And then you’re trying to give it to a bunch of different verticals within your company, and your companies go across a bunch of different industries. I don’t know, it just seems like there’s a ton of complexity there.

0:15:16.3 JH: I’m curious. Okay, so I’m a hardcore generalist. I always have been. That’s my thing. I’ve never been particularly drawn to one area of specialization, if there was, and maybe this will be the thing that will make Tim cringe, it would be really the business communication side. Helbs, what do you always call it? The…

0:15:42.8 MH: I don’t know.

[laughter]

0:15:43.5 MK: It’s like…

0:15:46.0 MH: I’m like, did I just say something smart? Well tell everybody. [laughter]

0:15:48.9 JH: No. Yeah, no, you say this term, it’s like the data whisperer or something that communicates with your business. What’s… There’s some term that you use for it. But the…

0:16:00.1 MH: Oh. But Tim hates it. It’s the analytics translator.

0:16:00.8 JH: Yes.

0:16:01.4 MH: A data translator. Yeah, yeah.

0:16:02.6 JH: See.

0:16:03.7 MH: And I don’t use that in practice, but I do say it in front of Tim to get the reaction. Absolutely.

0:16:08.0 JH: Exactly. I feel like that’s the thing that I probably naturally gravitate towards the most, but I couldn’t help reading some of David’s work, and I guess coming to the conclusion that you need to have a bit of both on the team, you need to have people that specialize and people that generalize, but I feel like it’s quite hard to get that balance right and also how you then help people develop their careers when, like you said, Helbs, it’s like there isn’t always a clear path, so you’re trying to help people navigate and you wanna help their development, but it’s like someone who specializes is so different and needs such different support from you or from the business than someone who’s general. And I don’t know if we’re doing that well yet.

0:16:55.7 MH: Certainly, in terms of how we look for talent, companies will want both generalist and specialist skill sets in abundance because they don’t really know a lot of times how to nail it down. So if you’re looking at a job posting and being like, “Should I apply for this job?” And it’s like, “Well, how do I have 10 years of experience using GPT4?” That’s not a thing I can have yet, so I’m using that as a joke, but I think we’ve all sort of looked at some of those job postings over the years and sort of been like, “Who are you possibly even talking about that could even have all these skills and have developed meaningful skill sets or specializations within them?” But I think it’s because people… Yeah, and to your point, Moe, they try to cut across so many different things, and at the same time, a lot of my thinking about this is, some of this, I think, has to do with personality as well. And sort of like, okay, ’cause I’m fully a generalist as well in terms of where my career is, or what I do and those kinds of things in terms of analytics, and I want to bring other people to the problem so they could be solved in more nuanced and sophisticated ways than I could do it myself.

0:18:09.7 MH: But the reality is, is that some people really are geeked out and super excited to go solve a very specific problem. There’s a really good friend who like his whole thing is the QA of analytics implementations, and he’s passionate about that specific thing, and then he has shaped his career around innovating and operating in that specific area. I couldn’t tell you… I mean, I care about those things and wanna do good work in that regard, but I don’t… It’s just a job I have to do in that regard, you know what I mean? And when you deal with that part of a project or that part of implementing analytics tools.

0:18:53.0 JH: Do you think it’s limiting? Do you think… Particularly specialization in the data realm, do you think it can be quite limiting in terms of your career?

0:19:02.8 MH: I guess what do we mean by limiting, maybe is a good question, ’cause limiting in terms of whose scale? ’cause if something is really making you happy and you’re really… It’s fulfilling you to do that work and to work on it, then what’s the limit? So I guess that would be the only thing I’d say back, is sort of like I feel like business people generally, so not just analytics, but generally, we all carry maybe expectations that we gain from somewhere, whether that be sort of like our own expectations we put on ourselves or expectations that we inherit from other people about what we ought to be or how successful we ought to be, or what does that success look like, that maybe sometimes could force us. Honestly, I feel like sometimes it forces us into specialization or generalization, because we’re responding to that stimulus as opposed to sort of being our true selves in a certain sense. So in other words, if somebody really loves the nuances of doing deep analysis and writing R and doing analysis with data and data science, and then someone comes along and says, “Well, you’re never gonna progress in your career unless you go into a management track and you manage a team of data scientists.”

0:20:21.7 MH: Well, that’s a whole other skill set and a whole other thing, and how do you know that will make you happy? And we’ve talked about this on the show before, about the advancement of your career and what does it mean? Anyways, I feel like I’m talking an awful lot. I’d love to hear from the both of you.

0:20:38.6 MK: I mean, you bring up a great point and it just makes me think like… I think a lot of people fall into the… Not the trap, but like you just mentioned, the normal path is, if I love to be an individual contributor and I love to specialize in a very specific area of data, I love being hands-on, I love being very technical, and to me, growth is to be able to make more money, get promotions, have more responsibility, do harder work, but at some point, I do feel like the reality of the world… You hit a cap, I think, where you can do that. And so if to you, success or… You’re thinking, “I’ve been doing this job for 10 years and I feel like I’ve hit the ceiling, but I don’t wanna go into management,” I do feel like specialization kind of makes that hard. But if it’s what you love to do, then it’s like, who’s to say that’s limiting? But I do think limiting in the fact of some of the roles you can take or how far you can take it as being just the individual that gets to have hands-on work, that’s unfortunately, I think, a reality a lot of people do run into.

0:21:39.6 JH: It’s funny, so many, many moons ago, when I was still working in Canberra, I heard Gillian Triggs speak, and Gillian Triggs is the former human rights commissioner for Australia, and she is very phenomenal, very smart lady. And this was when I was back… I think in my late 20s. But I said to her… This is my favorite question I ask people, “What advice would you give 25-year-old version of you?” And this is a woman who basically said to me… After having children, she raced straight back to work, she didn’t wanna take a big break because she felt the time out was gonna be problematic to her career and all that sort of stuff. And she goes, the biggest thing that I’ve learned now is… And I say this to everyone on my team. She’s like, “Spend more time in the weeds,” she’s like, “Everyone is in such a rush to progress that they don’t spend enough time working laterally across some of the ‘junior levels.’”

0:22:39.1 JH: And she’s like, “I actually think that… ” Especially if you wanna be a people leader, she was like, “I think that spending more times at a lower level, but getting familiar with different areas will make you a better people leader.” And she was like, “I didn’t know that back then, and I wish I had, because it would have… I would have enjoyed those periods more.” Because those are high learning and growth periods as well, because you’re stretching your brain to… Rather than focusing really deeply on something, you’re really trying to master a new skill.

0:23:12.6 MH: Yeah, and it’s hard to enjoy that part of the journey sometimes because you feel like you need to progress into something else a lot of times, and so it’s sort of like… I think it’s great advice. It’s kind of why I encourage people who are interested in it to spend some time on the consulting side occasionally, because you get a range of things that you can see. And I don’t think consulting is for everybody, forever, I don’t think that’s the case at all. Some people definitely don’t want to do it as a career and they shouldn’t. It’s not for everyone, but it is just such a good… A way to see a lot of breadth in terms of experience and types of companies you work with, and types of teams and structures and all those things, and it just helps you develop a framework for the world that you’re working in. With then, you can then pick and choose what you apply. ’cause I think the death is sort of when I… And I see this happen, leaders come into an organization and they immediately try to rubber-stamp the same playbook they used somewhere else, in the new org. And I just am like, “What a failure of understanding? This is not where you were before. You need to take what you’ve learned and adapt it to this context, not the other way around, and try to be like, okay, I do this, I do this, then I do this.” And it’s like, “Okay, that’s not the playbook that’s gonna work here.”

0:24:41.3 MK: What’s interesting of you saying that, like the playbook… So I guess two things, one is I definitely felt that being young in my career where the first couple years, it was really nice to have the time to be in the weeds across different areas, and then I felt like I’d kinda hit this point where I knew the lay of the land, and it was almost like pressure to move quicker into delegating to other people and think higher-level. And I have been, actively I think the last couple years, trying to make sure I can stay in the weeds enough. Not enough to take away my time, but it’s like, how do you split up your time as you’re growing, enough to be in the weeds, keep your hands on things and still experience things, so that you’re not too high-level where you’re like, “Now I’m too removed and I’ve cut myself off from a lot of that great learning,” but, how do I open myself up for some of the more general, broader thinking to help tie together the different pieces you’ve experienced? So I think that just really resonated with me when you were saying that.

0:25:41.0 MK: And the other piece was when you said people come in and say, “I do this, then this, then this.” It’s interesting, ’cause reading the first couple chapters of ‘Range’, they were saying how people love to learn process rather than concept, and I think a lot of people love to go to, “I have a process,” instead of like, “I learned a general concept of how to run a great team and I’m going to come into a new experience that I’ve never seen and not assume that it’s the same situation I’ve seen in the past, and apply the same thing. I’m going to take it as something new, I have a flexible concept in my head and I’m going to apply it in the right way.” And I think that is an art that not a lot of people have, and reading that just made it more concrete in my mind that those are the people I think are so valuable that you run into at work or in other companies, but it’s so rare.

0:26:33.7 JH: It’s funny, okay, I’ve been dying to talk about this because it’s actually come up recently, but… So David, I don’t know if it’s Epstein or… Epstein, Epstine? I don’t know, anyway.

0:26:45.1 MK: I think it’s Epstein.

0:26:45.1 JH: Okay, Epstein. One of the concepts he talks about, he talks about a specific experiment that was done about types of learning, and so whether the learning method is chunked, so whether you learned task A five times and then you do task B five times, and then you do task C five times, or whether you mix them up and you do two As, a B, a C, a D, and mix them all up, but ultimately everyone learns the same tasks over the semester and then they’re tested. Now, the test scores in this particular experiment show that the group that had the tasks mixed up did significantly better, although the learning curve at the start… They did worse at the start, but in the long run, they did better. Now, I find this really, really interesting because this is actually something that’s come up at work, that I’ve had to adapt, because that is my natural way of working. I would say that I’m one of those people that… Like I said, I’m highly generalist, think that a lot of variety is good because you can apply what you learn from one thing to another thing, but I have had people in the team who are genius, that we’ve had to stop and say, “This method of learning isn’t working for them, the variety is too difficult.

0:27:57.7 JH: And we actually need to take a step back.” And we’ve had to revert to using the chunking method of like, “We’re gonna get you to do task A five times. Once you feel confident in it we’re gonna get you to do task B five times.” And part of it is to do with them developing confidence, so they get good at a task before they tackle another tricky thing. And so I do wonder, reading some of David’s work, whether this stuff is also dependent on the person. Because yes, when you look at broad groups of the population, one particular method might work better. But when it comes down to coaching individuals, I feel like you do have to kinda take a step back and be like, “What method works best for this individual person?”

0:28:43.9 MK: Well, one thing that’s interesting too is, I don’t think work is a great environment to take advantage of that. I think he calls it interleaving or something, but the mixed-up version.

0:28:54.3 MH: Yeah, like interleaving.

0:28:55.4 MK: Because he calls out that the progress in the moment or the… Oh my gosh, the way you think, “Oh, I can see you progressing in front of my eyes,” is them learning the process, like they’re, “I follow this process because it’s always the same type of experience, or the situation I’m applying this process to,” so you get good at it in the moment, so you look like you’re progressing. Whereas, the other one is you’re going to fail. And though that helps for long term learning and more flexible applicability of what you’re learning to other situations, unfortunately, I think though at work, “We can’t let you fail. You can’t deliver things that are failing,” so it’s like you either have to be practicing and learning in a situation where it’s okay that you have wrong answers, or you can’t learn that way at work, I feel like.

0:29:47.8 MH: Actually…

0:29:49.6 MK: Well…

0:29:49.7 MH: Yes, you can, it just doesn’t go very well, [laughter] ’cause I absolutely…

0:29:53.3 MK: True, you can.

0:29:55.4 MH: Learned that way in my first analytics role, and there were some definite hard learnings and things that didn’t go super well as a result of some of my inexperience and not really knowing some of the things. But then you learn and you incorporate those, but yeah, you’re right, it didn’t pay off within that org very well, I’ll say that.

0:30:19.8 MK: Yeah, it paid off for you, ’cause I even have examples of like, “Oh, I kind of messed up, and I really remember that and I’ve never made the same mistake because it sticks with you.” But for an org, I guess I should have clarified that. For an organization, yeah, I don’t think it’s conducive to let everyone learn that way if you’re learning on deliverables, because that is the face of your organization to your clients. So I just think it’s like you’re stuck between a rock and a hard place of, the best way to learn and develop people into someone who can have this flexible problem-solving, but you’re doing it through delivery to clients when you can’t mess with that.

0:30:56.0 MH: Yeah, it has to be perfect.

0:30:57.7 MK: Do you think… Okay, that’s really interesting, ’cause I feel like at my work, we definitely go with the varied approach, but I guess I wouldn’t see it as something fails or is successful, which is quite different, and I know, ’cause obviously we’re in-house. It’s more that… Okay, so I’ll just give you a typical six-month onboarding. Someone will do a data warehouse task and have to write a pool request to build a table in our data warehouse, then they’ll have to do analysis on an A/B test, then they’ll have to write up an analysis and some learnings and share those. And so I wouldn’t necessarily see them as success or failure, I would see them as like, there’s a degree of how good they can be, and some people are better at other ones. So yeah, I guess I’m just interested… ’cause I feel like our learning approach is that… What was the word? Inter…

0:31:51.3 MK: I think it’s interleaving.

0:31:51.5 JH: Interleaving, interesting word.

0:31:56.6 MH: Yeah, they could’ve chose a simpler word, probably, for that. Anyway…

0:32:00.9 JH: Do you think when you’re at agency side, is that different? ’cause it sounds like it’s success or failure, right?

0:32:08.3 MK: I think when it comes to what makes it to the client, and so I think there’s a lot of ways to let them try things and be safe internally, but I think you as a company have to build the space for those review processes, you have to give them the time to do that, you have to give the people above them time to review it, you have to give them time to go back and fix it before it has to go to the client. And I think sometimes, that timeline is so short and the pressure is so high that it can’t always function that way. But I also think though, that’s part of why we revert to thinking we should do the chunking method. And I think young analysts come in, one, from school learning that way and then wanting that to learn in their career. So it’s hard, it’s like, how do you help them, again, build that flexible mindset concept-type skills, that’s really going to help them long-term? But you have to perform and get them moving pretty quickly for the success of everybody, and so they don’t feel like they’re constantly failing, because you as the individual learning in that mixed-in way, you’re going to feel more of the frustration and struggle than maybe feeling successful. And I think that’s kind of scary in your job too, you don’t wanna feel that all the time.

0:33:22.7 MH: I’ve definitely had conversations with people on my teams over the years who are like… They’re like, “I’m just screwing everything up.” And I was like, “From my perspective, you’re doing amazing.” And it’s sort of like… They’re like, “What?” And I was like, “Yeah, you’re literally doing everything I could hope for in this particular environment, even as challenging as it is.” And that’s hard because nobody likes to feel like they’re not doing well, and people need the feedback, I think. But I also think in our industry, sometimes specialization also just comes and finds you. So, like Cory Underwood, did he think he was gonna become this internationally-known person about privacy and all this stuff five or six years ago? I don’t know, maybe it was part of his master plan, I never asked him that.

0:34:08.8 MH: But he speaks all over the world about this topic now, it’s really interesting. Another classic example would be somebody like Simo Ahava who is basically the world’s number one authority on all things Google Analytics and things like that. And obviously, Simo’s quite capable in all kinds of other places. But he does a podcast now with Juliana Jackson who I’ve not met, but she recently got into analytics, I think she came from more of a marketing background, and so she’s bringing a different skillset over, into now analytics, and it’s kind of fascinating to watch her learn in real time and engage with analytics topics. But I feel like it’s accelerating her progress immensely, all the other experiences and things like that that she’s had, because there’s context for so much of it.

0:34:57.4 MH: I don’t know, we’d have to get her on the podcast and ask her but, or listen to her podcast. Their podcast, by the way, is called Standard Deviation, so just in case you wanna check that out. But I think about that all the time too, is sort of like the value of lateral thinking and lateral skill sets or complementary skill sets, or experiences.

0:35:17.3 MK: I keep, Julie, thinking about what you said about process. It just keeps flying around in my brain and I’m… ’cause I’m trying to process it, [laughter] about the fact that… So I feel like this skill that we’re talking about, that is, I guess, one of the advantages of a more generalized learning experience or bringing… I guess bringing experiences from other areas of life or work or whatever, to your job, there’s a real advantage to that, and it’s something that I’m often trying to teach analysts, which I actually think is the hardest thing to teach people. And now, I remember asking one of my really amazing analysts, being like, “Can you write down a process of what you do when you have an ad hoc investigation?” And an ad hoc investigation to me is like the pinnacle analyst example of like… You kind of just need to go with the vibe and experience, and having seen lots of different situations is really beneficial, because you’re like, “Oh, this one time, it was this thing, and this other time, it was this other thing. And I’m gonna check these three things.” And trying to get an analyst to write down that process is impossible, it’s never happened.

0:36:32.1 MK: He’s never written it down for me, because he’s like, “How do I write down… Like, I just know this stuff from experience, or varied experience.” And I’m like, “Cool, but I can’t… ” I’m trying to get a junior analyst to have that same knowledge that you have, and the way to start might be a process to begin with, and then as they get more experience, they don’t need the process anymore because they have their own varied experience to help drive them about which way to go. Does that make sense?

0:37:02.0 MK: Yeah, and that’s really tricky because I guess where my head goes to is like… So me and Tim running the analytics guild that we do at work, he and I had a lot of conversations in the past about, how do you help teach young analysts ways of thinking? Because that’s what it is. It is your process, but when you’re an analyst, your process is like, “How am I thinking about a problem?” And so I almost wonder if it’s more… Like how… I’m trying to think through things I do, like, how would I write that out to help someone understand the way I’m thinking? Is it like questions I’m asking myself? Is it things I would always go check? Like, that is so hard… But I do, I feel like you’re trying to teach someone younger than you the way you’re thinking, not the steps you’re taking.

0:37:44.9 JH: Yes. Yes.

0:37:47.0 MH: And I think personality has a lot to do with this because experience and intuition are these irreplaceable attributes that people can bring to something like this, and you can be like, oh, have a lot of experience and have a really great intuition… It’s not an answer. Right? And I think the ways of thinking is a perfect way to kind of start to frame up a process, and this is honestly what I love about Tim so much, is like I’ve been asked so many times in my career Moe, to document my process. How do you know that? How did you know to ask that… How did you know to answer the question that way? I was like, “I don’t know, I obsess about this constantly, and I think about it all day, all night,” and then I show up in meetings and I say the thing and it just so happens to be the right thing to say or the right insight at that time, but don’t ask me like how I did it, like it’s just who I am, and that’s not very helpful for scaling, and I’m not a high scale person as a result of that, I don’t really like that process very much of trying to take knowledge or experience and scale it, it’s important to try to figure that out, but it’s important to understand the components, so it’s why everybody at Search Discovery who came into the interview process got a problem-solving question was like, “I wanna see how you tackle a problem that doesn’t have a good answer.”

0:39:08.1 MH: It’s just… And a lot of times I think about it visually, like, “Here’s my problem, hanging in space,” and then I’m going to sort of walk around and look at it from every angle and try to ask questions of it from every side, and the better I do that, the more likely, I’ll come up with something that is like a really good solid approach or an answer, but that’s my way of doing it. I don’t make other people think about problems as dimensional objects in… You know what I mean? I just don’t think people or even brains work like that…

0:39:41.3 JH: No, but I actually love that. I think it’s a really cool way to think about it, and it’s for people that are visual like me, that actually is a really good… ’cause then you can actually be like, “Have I gone the 360 degrees? Or have I only done 180, and therefore I’m missing something.” I think it’s a very helpful visual. I know what I think it points to too, is that you’re able to look at it 360 because you’re looking at it through different lenses, different angles, you are able to think, “If I’m stakeholder X vs stakeholder Y, how am I looking at this problem, or why does this problem affect me?” And I do think generalization vs specialization, like I think if you are too specialized in an area, then you’re used to seeing a lot of problems from the same point of view, and I do wonder… I mean, they talk about how when you’re used to always attacking things from the same angle, or like “These are my tools, and this is how I do it.” That when you see a scenario so different that is not actually conducive to that process you follow or the things you’ve experienced.

0:40:47.5 MK: That’s when you get a really bad outcome. Compared to someone who has the varied experience, even if it’s just within the analytics world, like I fully believe and I tell all new analysts, “I believe you cannot be a good analyst unless you have mastered QA before you move on.” I think you need to have the understanding of where the data comes from, no seriously, where the data comes from and how it’s collected, so then you can go use it and you can move on. But you can check your work. I think when people are forced to be good in an area, then you can move on, be good in an area, then you can move on. You start to gather those things, like when you go look at a problem, you just already have so many more tools and points of view in your tool kit to figure out how to tackle it.

0:41:31.5 MH: Yeah, maybe it’s about a willingness to address things from multiple angles, so like you asked at the beginning Moe, if you’re a specialist where you specialize, is that limiting in some way? And maybe that’s… Julie, you are kind of stumbling across something, which is, if everything you ever do is this one thing and you’re happy doing that thing, well, then more power to you, but if you’re unwilling to move past it or look at things from a different perspective or change your angle of attack based on what the problem is, much like you don’t do plumbing with carpentry tools, you know what I mean? Or at least I don’t. I don’t do either of those things.

0:42:13.1 JH: I was gonna say and you do how much plumbing?

0:42:14.4 MH: Not handy. This guy, not handy, wish I was more handy. But that’s kind of the idea it’s like, “Okay, yeah, there’s a different angle of attack here, so we have to adapt to that.” And what I liked was in the TED Talk that I watched about ‘Range’, isn’t that every single person has to have every single experience, it’s teams also with lots of different diversity and the ways of looking at the world also then combined for the best solutions and approaches as well, and so I think that’s also really important is you can be a specialist and be very successful and very accomplished, and maybe when it’s required if you’re gonna be that specialized as other people that are specialized in their area, so that as a whole…

0:43:00.7 MH: Or as a unit or as a team, you make up that, and I think things like military units or things like that kind of replicate those kinds of things, right? Not everyone has the same role, or like…

0:43:11.9 JH: Or even just a traditional cross-functional team, a traditional cross-functional team that is not traditional cross-functional team.

0:43:15.0 MH: Yeah. Yeah, right.

0:43:22.9 JH: The thing though, is when I did… When I heard that, I actually had quite a visceral reaction to it, ’cause I was like, “Yeah, cool, I get it, I get that we need diversity of thought in teams,” and that sort of stuff, but it’s like now this is other component. I feel like I’m constantly on this like, “How do you create great teams thing?” And it’s like, “Oh well, now there’s another thing you need to consider, which is about having the right mix of specialization versus generalization.” And it’s like, “How do you get that perfect potion of people that make an amazing team?” And so I just had this heart palpitations of another dimension I need to figure out.

0:43:58.3 MH: But I think you don’t have to… This is my own opinion, and it’s not based in anything more than just an observation, I don’t know that you have to perfectly plan that.

0:44:08.2 MH: I think you can kinda bring people in and let it… See what comes from it sometimes and let some of the parts be greater than… Part of the whole be better than some of the parts. ’cause I couldn’t have told you. Like I always say one of the things I feel, makes me feel smarter than anything else I ever do is when I see the potential in bringing somebody in or hiring someone, and they just out-perform anything I could have ever imagined and really exceeded my expectations. That makes me feel like I saw something that was even just the beginning of what the greatness they could accomplish on their own in the first place was, right? And it makes me feel really smart, but I couldn’t have planned it out, and so that’s the only thing I’d say is like… I don’t know if you have to worry about that so much.

0:44:56.1 JH: I don’t think you can plan it out per se, but I think you can be quite aware of it and aware of what the team is missing or like what the gaps are that you need to fill.

0:45:08.8 MH: Yeah, there’s tools, there’s tools for that like you can do based on… Built on personality, built on work styles.

0:45:15.2 MK: But I wonder too, even if you’re worried about a mix of specialization and generalization, like I’ve been thinking about this recently for some of the younger analysts I’ve been talking to, like is it… Could you even just talk to your specialists and urge them to branch out a little bit or just not even branch out in what they’re doing, but if they could better understand what the specialist next to them is doing in a different area, then it would give them just a little bit of context to be a little more general of like upstream downstream of them, like if you’re a little more in tune with the people that are before you or after you in a bigger process of a team, I feel like you start to get the benefits of being a generalist, but you are still a specialist in your area, but it will probably make you better because you will consider those things when you’re doing your part.

0:46:02.2 MH: Oh, I love that…

0:46:04.7 JH: Me too.

0:46:06.4 MH: And I realize now, we do that in our team meetings every week.

0:46:08.3 MK: That’s awesome.

0:46:10.1 MH: So we have partners that all have different skill sets, and so every Wednesday when different partner presents something they’re working on or they’re learning, and that’s where we’re all benefiting from their specialization. It’s like, “Oh, I didn’t even know you could do that. Oh my gosh, you did that with machine learning or like… Okay.” And the application is obviously great for business, ’cause now I know we have that capability and we can do that in our work, where I might not have known that before, but so does everybody else, and we’re all learning from each other a little bit, you know, every week on that, so anyway. Wow, now I feel smart. Way to go us! Although, it wasn’t my idea. It wasn’t my idea. I have to give credit to the team who said they wanted to do it that way, I do not, so… I’m not that smart. Sorry.

0:46:54.2 JH: I do have a bone to pick though, because David Epstein in his content really talks a lot about that like 10,000-hour piece, which maybe we should have discussed at the start versus the Roger Federer example of like, he grew up playing many different sports and then later in life, really jumped on to tennis versus Tiger Woods who had a club in his hand at seven months, and like I’m not gonna lie, that 10,000-hour thing gets said in our house pretty much every single day by my husband, when Harry’s like, “Kickball, kickball,” and Jamie’s like, “10,000 hours, 10,000 hours.” And I feel like now this has been totally debunked, and he should be like kicking balls, catching balls, doing ballet and doing swimming and all these other things, because it will probably… Like a big conclusion is basically that… A lot of the skills you learn through generalization will make you better at whatever the thing is that you’re trying to get good at.

0:47:50.9 MK: Yeah, I know you’re already worried like, “Oh, get them 10,000 hours, at something they’re good at.” And now you’re like, “Oh wait, no, now I have to have them try everything.” [chuckle]

0:47:58.6 JH: Yeah.

0:48:00.7 MH: Yeah, I’ll keep in the work context, because I certainly have no idea when it comes to kids, how to solve that, and I have two wonderful kids and you end up driving to a lot of different things to get those 10,000 hours. I don’t know, like that’s an interesting question ’cause I do feel like focused learning is super important for any field, but certainly for analytics and so in a sense, you should be working on building a competency in areas that are interesting to you, but again, I guess you’re… Yeah, I don’t know, I’m not sure exactly how to frame it. You were gonna say something, Julie, I could tell.

0:48:43.7 JH: Well, I feel like I live in the world of gray. I’m always like, “Moderation, be in the middle bla bla bla.” ’cause that’s how I feel here. I’m like, I kind of feel like it’s like a spectrum, like if you’re too general, you’re just bopping around and never get deep enough on anything, then are you really ever good at anything, but then if you’re too specialized, I mean we kind of like belaboured that point so yeah, then it’s like how do you give yourself enough focus time on something you’re interested in or curious about in the moment and let yourself go deep and be wrong and struggle through it and learn it, but I feel like you have to get to the point of learning it before you move on, but if you’re just touching everything at surface level, I don’t think that’s right either. So it is, it’s like, “I’m just gonna live in my gray moderate world, somewhere in-between on the spectrum.”

0:49:29.9 MH: Yeah, I don’t know, and luckily, now we do need to wrap up, so we’d never will know the answer, but if you listen to this podcast for 10,000 hours I bet you’d be really smart. So little plug there. No, I’m just kidding. I don’t know. Closing thoughts, Moe?

0:49:47.5 JH: Look I mean, I’m always been on team generalization, I feel like Julie summarized it really well in terms of, “If you really like something and you wanna specialize in it, that’s cool,” but I also agree that what success looks like will then be different and that’s okay. I definitely support people on my team that wanna go down that path, but it definitely looks different, and I think maybe that’s what we also need to get our head around it’s like, “If you do wanna specialize, the typical career path might not look the same, and that’s okay.”

0:50:17.7 MH: Yeah, yeah, as a generalist with a deep love of people who like to specialize, it is strange, but… It’s pick your poison, I guess. Alright, well, one thing we definitely specialize in here at the Analytics Power Hour is doing a last call, which is going around the horn and sharing something we think might be of interest. Moe, would you like to share your last call?

0:50:44.1 JH: Sure, I recently read an article and it was almost straight away that I had to share it with a bunch of people at work. So it was in HBR and it’s called Beware a Culture of Busyness. Organizations must stop conflating activity with achievement. By Adam Waytz. And it just resonated with me so much because…

0:51:06.0 JH: I see it so much, even in my peer group of almost this competitiveness of who can be busier, “I’ve got more meetings or I did longer hours,” and it’s actually something that… I spend a lot of time thinking about because I feel like I’m a person who upwaits business as well, but then at the same token, when it actually comes to what’s good for the business, being busy doesn’t necessarily mean that you’ve had an impact, and so trying to wrestle those thoughts for me is something that comes up quite a lot in terms of, particularly performance reviews and stuff as well, because I’m a person who thinks that effort does matter, but at the end of the day, it’s like when you’re actually talking about performance in a business context, it’s normally about the outcome, so they’re just concepts that are floating around my mind all the time, and I definitely don’t have the answers, but I really found that article interesting in terms of the busy culture that we’re living in now.

0:52:07.0 MK: Can that be a whole podcast topic, ’cause I love that.

[laughter]

0:52:13.2 MH: Yeah, that one hits close to home, but I like it. All right, Julie, what about you? What’s your last call?

0:52:22.4 MK: Alright, mine, in the spirit of ‘Range’, I guess, one of my favorite podcasts, I’ve been listening to it for a while now, and I love it because there are so many back episodes that even if a new one hasn’t come out yet, I can go back in the library and find one, it is called Allergies. And pretty much she goes and interviews a bunch of different specialists on each episode, so each episode will be like someone who is a specialist on studying chickens, somebody who’s an allergist in studying, not just a psychologist, but she’ll do ones that… Cicadas, she’s done chimpanzee, she’s done sleep, she’s done dreams, they’re just a bunch of fun topics, and so I love that podcast ’cause you always learn something cool on a topic you maybe didn’t think of learning more about, and they’re just great, and I find them so entertaining and I fly through them, I can listen to seven in a week, easily. It’s a great one.

0:53:22.0 JH: It’s funny actually, The Michael Lewis podcast had a series where they did that… Where he did that as well, and I actually loved it, where he’d interview different specialists in different spaces, and I got so into it, I don’t know why there’s something about it, like getting to delve into someone else’s specialization or something.

0:53:38.5 MK: Yeah, so cool.

0:53:39.9 MH: It’s like why I think I love documentaries so much too, you sort of see the world from a whole different angle. And I guess we all just have great range. Alright, well, what’s my last call? Probably, I’m asking myself… Well, interestingly enough, one of our good friends, Jim Genolio, has started his own podcast called Measure Up, which is gonna focus on marketing and measurement, and which is an awesome topic. Jim has been working on a website around the media mix modeling space for a while, so a lot of cool topics, and we’ve talked about that on the show a couple of times, so with Jim starting that podcast, I would say give it a listen. He just did an episode with the founder of Cassandra, which is a marketing mixed modeling tool that I believe is…

0:54:30.8 MH: Well, I’m not gonna speak more to it ’cause I don’t know, so I won’t say something wrong. But anyways fascinating topic. Alright, I’m sure as you’ve been listening, you’re like, “Hey, that, I identify with that,” or you know what, no, you have to specialize in this or You… Generalist is the way to go. Well, we’d love to hear from you generally speaking, and the best way to do that is specifically through LinkedIn or the Measure Slack group or on Twitter, so please reach out and feel free to contact us, we’d love to hear from you, and if you love the episode, feel free to go rate us on your favorite podcasting platform, and I will say this with no hesitation, no show would be complete without a huge thank you to our producer, Josh Crowhurst.

0:55:15.4 MH: And in this particular episode, our associate producer, Tim Wilson, behind the scenes, making sure all of this stuff works well for us, so thank you both for making this show possible. Alright, Julie and Moe, thank you both for this awesome conversation, I appreciate you both taking the time, and I know I probably speak for both of you, when I mention that no matter if you’re specializing, or generalizing make sure you keep analyzing.

0:55:48.1 Announcer: Thanks for listening. Let’s keep the conversation going with your comments, suggestions and questions on Twitter at @analyticshour, on the web, at analyticshour.io, our LinkedIn group and the Measure Chat Slack group music for the podcast by Josh Crowhurst.

0:56:06.7 Charles Barkley: Chill smart guys want to fit in, so they made up a term called analytics, analytics don’t work.

0:56:12.6 Kamala Harris: I love Venn diagrams, it’s just something about those three circles and the analysis about where there is the intersection… Right.

0:56:22.9 JH: I appreciate this thoughtful nudge towards sorting my shit out.

0:56:26.8 MH: I think it’s just great that you were already recording Tim, so Josh has to wade through all of this and the… Jim said that.

0:56:42.3 JH: Oh, Tim, you always set me up. It’s not fair. I never notice.

0:56:43.5 MH: I’m acutely aware now.

0:56:50.9 JH: Oh, I never notice.

0:56:51.0 TW: Michael didn’t even mention the check. He had to cut me for some of the stuff I’ve caught him on a hot mic with. That’s actually my post Search Discovery employment.

0:57:03.0 MH: I don’t know how I work all the time and have zero ideas for a last call.

0:57:09.1 MK: Oh my God, I didn’t even think of that. Did you see the panic in my face? Like, wait…

0:57:15.0 MH: I did. Thank you.

0:57:20.6 TW: Josh you’re welcome.

0:57:21.2 MH: Like group hug. Just group hug everybody. This is amazing. We should kick Tim off the podcast. Just the three of us do it. It would just be so much more affirming.

0:57:34.4 MH: Perfect. Well-oiled machine. Love it. These guest-less episodes are my favorite. So we don’t have to have the pretense of having our act together.

0:57:44.3 MH: Oh wait. Who’s gonna do the rock flag and Eagle?

0:57:51.3 JH: I was hoping you.

[laughter]

0:57:52.9 MH: No Julie. It’s not middle school. [laughter]

0:57:52.9 JH: Nose goes nose goes.

0:57:58.7 MH: All right, I’ll give it a shot. I’ll give it a shot because we heard when Moe did it.

0:58:06.3 JH: I seriously was like, Helbs how have you not picked up that someone needs to do this? I was like…

0:58:11.7 MH: I didn’t really give it a second of thought I can, I’m… Well first off I invented it. I am the one that told Tim about it. ’cause you think Tim even knows about always Sunny in Philadelphia. All right, let me think of a good rock flag in Epstein or Epstein.

[laughter]

0:58:34.7 MH: Tim, what would you have gone with?

0:58:36.4 Tim Wilson: I might have gone with, 10,000 hours of generalization.

[laughter]

0:58:42.6 MH: 10,000 hours. Yeah, it’s nice. General hours. Yeah.

0:58:47.8 JH: Yeah.

0:58:47.9 MH: Excellent work everyone.

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