It’s the end of the year, and we know it, and we feel fiiiiine. Or, maybe we have a little anxiety. But, for the fifth year in a row, we’re wrapping up the year with a reflective episode: reflecting on changes in the analytics industry, the evolution of the podcast, and the interpersonal dynamics between Tim and Michael. From the state of diversity in the industry (and on the show), to the trends in analytics staffing and careers, to the growing impact of ethical and privacy considerations on the role of the analyst, it’s an episode chock full of agreement, acrimony, and angst. And, it’s an episode with a special “guest;” it’s the first time that producer Josh Crowhurst is on mic doing something besides simply keeping our advertisers happy!
Trends, Techniques, and Episodes Mentioned in the Show
- (Podcast) DAPH Episode 109: RAD Podcast Analytics with Stacey Goers from NPR
- (Podcast) DAPH Episode 110: Creating Balanced Teams (and Avoiding Groupthink) with Alison Vorsatz and Aubrey Blanche
- (Podcast) DAPH Episode 117: What’s in a Job Title? Maybe the Data Shows! with Maryam Jahanshahi
- (Podcast) DAPH Episode 118: Ethics in AI with Finn Lattimore
- (Podcast) DAPH Episode 122: Dealing with Disparate Stakeholders with Astrid Illum
- (Podcast) DAPH Episode 123: Ad Fraud with Dr. Augustine Fou
- (Podcast) DAPH Episode 124: Image-ine What the Analyst Can Do Using Machine Vision with Ali Vanderveld
- (Podcast) DAPH Episode 126: When the Data Contradicts Conventional Wisdom with Emily Oster
- (Podcast) DAPH Episode 130: Data Stories with Nancy Duarte
- (Article) 100% of Shoptalk 2020 Speakers Will Be Women: Here’s Why
- The Women in Analytics Conference
- Michelle Kiss
- Man who has it all
- (Paper) Words Matter: Experimental Evidence from Job Applications
- (Article) One Month, 500,000 Face Scans: How China Is Using A.I. to Profile a Minority
- Measure Slack
- Josh Crowhurst
0:00:04 Announcer: Welcome to the Digital Analytics Power Hour. Tim, Michael, Moe, and the occasional guest discussing digital analytics issues of the day. Find them on Facebook at Facebook.com/AnalyticsHour and their website AnalyticsHour.io. And now, the Digital Analytics Power Hour.
0:00:27 Michael Helbling: Hi, everyone. Welcome to the Digital Analytics Power Hour. This is episode 131. It is our last episode of 2019. It is our fifth completed year doing the podcast, which incidentally, Tim Wilson, you’ve been a part of all but one of those.
0:00:53 MH: Oh, been a part of all of them, but one of them you were not on. We’ll talk about that more later. Can you believe the passage of time? Is it credible to you, Tim Wilson?
0:01:04 Tim Wilson: I actually was surprised when I realized this was five years. I’m not sure how that happened, but I was like, “Really?”
0:01:12 MH: I’m not sure how we got to 131 when we do 26 episodes a year. And I haven’t gone back and tried to figure that out, but it should be 130. Moe, how do you explain this discrepancy?
0:01:27 Moe Kiss: I take no responsibility, ’cause I haven’t been around for five years.
0:01:31 TW: It’s bi-weekly. It’s not…
0:01:34 MH: Yeah, it’s bi-weekly. Yeah. It’s just so funny because it worked out. I was trying to do the math and I was like, “Wait. It’s one different.”
0:01:41 TW: Didn’t you work in retail long enough to realize that there are approximately two weeks a month?
0:01:46 MK: Oh man, I’m just saying I’m not gonna cover for your mistakes.
0:01:51 TW: Michael worked at retail, and he should be able to figure this out.
0:01:53 MH: Yeah, that’s right, but we don’t follow the three, four, three calendar, or whatever, or the four, five, four calendar, whatever it is.
0:02:01 MH: I even forgot. I’m either doing weird haiku-type stuff or retail calendars. Anyways… All right. Ian’s also joining us for the year in review episode. Josh Crowhurst, my fellow multi-touch moment partner in crime.
0:02:19 MH: And also our show producer. Welcome, Josh.
0:02:22 Josh Crowhurst: Hey, yeah. Thanks, Michael.
0:02:23 MH: Yeah. So, this show, and I’ll just do this again for everybody listening, we do 25 for you and one for us, and we spend the last show kind of reflecting on the year that’s passed, which is sort of not new content. It’s all stuff you probably could have heard before, but we’ve got deep thoughts. We cover a lot of tricky issues. We make charts and graphs about the performance of the podcast and the areas that are important to us. And we think back on all the guests and topics we’ve covered in the previous year, and then we look forward to what is happening in digital analytics, this industry that we love. Who wants to kick us off? We’re gonna go with reflecting on our industry for 500.
0:03:17 MH: Okay. Well, don’t all jump in.
0:03:20 MK: Tim, you’re allowed to talk about women in analytics. Just because I’m the woman, doesn’t mean I need to raise it. We need men to like…
0:03:27 MH: Yeah, Tim.
0:03:28 TW: Oh my God, I try so hard to not jump in all the time. And when I don’t…
0:03:35 MH: Yeah, Tim. Listen. Tim, this is… Maybe this is a topic where we can get into some of Tim’s issues, because…
0:03:43 TW: Reflections on Tim?
0:03:44 MH: Yeah, Tim. Well, I know how much you love to reflect on personal matters, Tim. No.
0:03:51 TW: We can talk about how I’ve grown my emotional intelligence over the course of the last 12 months.
0:03:56 MH: Absolutely. I would say you’re top four in the podcast in terms of emotional intelligence and stuff.
0:04:07 MH: All right. But let’s do talk about women in analytics because I think, as an industry, there are some really cool things to talk about in terms of women in analytics. And I think probably my most proudest moment of 2019 was sitting in my car listening to the International Women’s Day podcast episode that, Moe, you hosted, and just furiously agreeing and making mental notes and writing stuff down. And it just spurred so many amazing things of, like, “Oh my gosh, this is so good.” But actually, Tim, you’re involved with some other stuff in this area, too. I don’t wanna steal all of your thunder, but…
0:04:48 TW: [chuckle] Well, I thought you were gonna say you were furiously scribbling down notes ’cause you needed to explain to Moe what she had… What she could have done better, and… Or, what was so great about the episode.
0:05:00 MH: Absolutely nothing. Aubrey Blanche and Alison…
0:05:04 TW: Four sets.
0:05:05 MH: My friend from Fairygodboss, four sets, yeah, did such an amazing job. And anyways, I felt like we had done something right in that episode. And I loved being associated with it, I guess, as well, I’d say.
0:05:21 TW: I think the topic is, it’s tricky, ’cause I think it is hard to look at 2019 and not see bright spots and see progress, and see a lot of things that are really positive. But then, with this topic, we have to be so careful to not say, “And we’re there,” ’cause we’re clearly not at all there. I’m not saying that you’re saying we’re there, I’m just saying that’s where… It is tough. I always find it’s uncomfortable to celebrate wins, but always having the caveat of saying, “But that doesn’t mean sit back, pat ourselves on the back, and rest on our laurels.” Not about that episode. Just progress in many areas. I think they’re, I would say, a big thing. I think there are more men who the light bulb is finally coming on and they’re more aware. And I don’t think that’s ’cause the light bulb necessarily went on for me this year. It just seems like the conversations that I see, there are many, many…
0:06:22 TW: More men who are starting to get it. At the same time, there’s… This was one of those like, that’s awesome and infuriating. There was a post on LinkedIn a couple of months ago where the organiser of Shoptalk, if I recall correctly, they went and they had speakers lined up and then they decided they were gonna do 100% women speakers. And one, she said this was the first time that conference had done that. Well, hat tip to Jim Sterne, he did it a couple of years ago with eMetrics. Maybe a little bit of a fumble. It looked like they actually had speakers lined up and they went to the men and said, “You know what, can you find someone else in your organization who’s a female to speak?” Putting that aside, that was kind of a yeah, let’s try that more, let’s try more conferences where you say, “We’re gonna have all women speakers.”
0:07:10 TW: The Women in Analytics conference in Columbus does that, open to all, all the speakers are female. The comments on that LinkedIn post are the way to get that dose of reality, because you have people saying, “Well, when are we gonna have the all men speakers? When are… we just wanna have the best speakers.” And it was probably a mix of 60 to 40 at any other conference. There were more, frankly, white dudes weighing in saying, “Well, what about… That’s like having an all Aryan speakers conference,” or just saying things that were ridiculously moronic. So it’s like, “Hey, this is great, now let me read the feel-good comments,” feel-good comment, feel-good comment, clueless asshole not-good comment.
0:08:00 MK: But to be honest, that show for International Women’s Day was one of my career highlights. It was completely incredible, and a lot of thought went into it because I didn’t want it to be a show just about women talking about, I don’t know, “women’s issues.” But Alison and Aubrey are just such incredible people in the diversity space. But one of the things that did get me a little bit down is that when I went to look at the numbers of downloads for that show compared to the rest of the year, it definitely wasn’t up there. It was a little bit not great performer, and that made me pretty sad.
0:08:38 TW: Which is why we talk about it on this episode too, so that people can go back and catch the fuck up.
0:08:48 MK: But one of the things I do wanna talk about is the Women in Analytics conference that Facebook sponsored. And number one, I desperately wanna get invited, ’cause it’s invite-only. And I know my sister and Rachel went last year, and we got some amazing speakers out of that conference.
0:09:06 TW: You mean guests, we got amazing guests for the show, right?
0:09:08 MK: I mean, sorry, amazing guests, yeah. So Maryam, I got in touch with Maryam via that conference because so many people saw her speak and just said she was ridiculously amazing. And so I guess it just goes to show, you can have really good quality female speakers, I just think you have to work really hard and really use your network to make sure that you source great speakers.
0:09:33 TW: No, the podcast certainly shows… We got some amazing guests this year. Emily Oster, Nancy Duarte, freakin’ awesome. And a lot of other people too, I’m just picking really famous people.
0:09:53 MK: But for those listening, Tim did some analysis on our guest mix. So this year, 44% of our guests were female, 37% were male, and 19% of the shows didn’t have any guests. Which, the guys don’t know this, but this was actually a personal goal for me, is that one of the years I really wanted us to have more female guests than male, and I didn’t even know that we’d done it until… Yeah, Tim pulled the numbers and I was like, “Yeah.”
0:10:20 MH: Until I saw this perfectly formatted stacked bar chart that Tim pulled together. So quintessential, Tim, so quintessential.
0:10:32 TW: Well, and that’s… There was also a… I can’t remember, Michele, Moe’s, your sister had the… I can’t remember the name of the… There was one of those accounts that does the reversing of… Positing what if this thing that is said about women is actually said about men, and there was a thread about all-dude podcasts, and the thread was pretty funny.
0:10:57 MK: It’s called “Man Who Has It All” on Facebook.
0:11:00 TW: Yes.
0:11:00 MH: I just… I hate getting trapped in all of these things sometimes, ’cause we’ve been doing a podcast for a long time, and apparently, podcasts are now what everybody does like blogs back in 2007. So yeah, we’ve been here a while, folks.
0:11:16 TW: We started as all dudes droning on.
0:11:19 MH: Well, yes.
0:11:23 TW: But I think that it does skew male. I think blogs skewed male. There are, and I listed some, there are some very deliberate pushback against those. When it comes to the conversational industry type podcasts, I think we’re super fortunate to have Moe having now joined the podcast a while back, in the fairly distant past at this point, to have some degree of balance, but at the same time, we’re perpetually still skewing to the dude, even our no guest show.
0:11:57 MK: And also all white.
0:11:58 TW: Yes.
0:12:00 MH: Yeah. I actually think, for me, again, not that we’ve solved the issue of gender diversity or balancing in our industry by the slightest, certainly some positive things, but honestly, I think, for me, that is big on my mind. There is not enough ethnic diversity within the analytics industry generally, from what I see. And again, I see a part, I don’t see all. So it’s improving…
0:12:27 MH: But I think that’s the thing. It’s like all of us need to sort of have a sense of, in the back of our heads, where is the current state and then how can we push that forward just a little bit? So, this is a big deal to me because of what I realized when I was leading a practice at Search Discovery. I realized that I wasn’t the best person to be able to inspire people to do analytics well for everyone. I just couldn’t. And so then it became way more important to me to find people of all different kinds. And that’s why the balance team’s episodes really hit home with me, is because it finally was like, wow, someone’s actually doing the work that I realized needed to be done, which is there needs to be different perspectives so that other people can hear what’s so exciting about being involved with this industry.
0:13:11 MH: And we need to keep breaking down those barriers and all the other things that go with like learning about all this stuff. But I’m awesome and I get through to some people, but a lot of those people look exactly like me and they think what I think and they watch Rick and Morty or YouTube videos that are funny or whatever. But I don’t have a window into… Just the other night, somebody tweeted something about how people who buy expensive tennis shoes should pay a higher tax bracket and I was just like, that’s the dumbest thing I’ve ever heard. How dare you take your values that you don’t understand other people’s values or culture and make some judgement on it. That doesn’t make any sense to me. That’s what’s gonna, what we have to kind of start pulling away, but that’s why people, when I talk, some people can’t hear me. I’m just not gonna get through.
0:13:58 TW: Did you say something?
0:14:00 MH: Yeah, exactly.
0:14:00 MK: But I think that’s the thing, is like everybody needs role models like them.
0:14:04 MH: Yeah, exactly. They need to see somebody like them. I think that’s just in the US why Barack Obama is such a big deal as a President for eight years, not just because he was African-American, but because he then showed so many people who say, hey, he looks like I do. And that’s important. That matters. Anyways. Now, can we talk about GDPR? I’m just kidding. [laughter] I’m kidding. That’s a joke.
0:14:33 MK: I have no desire. I’m like GDPRed out.
0:14:37 MH: We spent the what, the first full year under the heavy boot of GDPR, if we will, right?
0:14:42 TW: But it’s broadened.
0:14:44 MK: Do you think we understand still what the enforcement is like? Because I feel like that was the thing where it was like, wait til it’s in place and then we’ll know what the enforcement looks like. I still kinda don’t know it.
0:14:55 MH: Now, there’s been a few wishy washy things and nothing. I feel like we’re still kind of in the midst.
0:15:01 TW: But I feel like the conversation… As an industry, it was the spark that now, because even if people don’t fully understand GDPR or CCPA, the discussion around privacy and partly that is I think also driven by browser with ITP and ETP and those sorts of things, that the just awareness of, hey, you know, there’s a lot of… This stuff’s been chugging along with cookies and tracking people kind of very loosey goosey kinda potentially shady activity depending on who’s viewing it. So, to me, 2019 was a progression. We don’t have the answer, but there are a lot more people kinda grappling with the topic.
0:15:47 MH: Yeah. I think people definitely started giving more attention to the concept of governance and it made me realize something actually around the idea of governance generally, which is governance only occurs under two sets of criteria. One is externality of regulation and those kinds of things like you’re forced to. The second is value. If you’re actually getting value out then governance emerges naturally to protect that value and grow it. But that’s the only ways I think people really spend any time on actual governance.
0:16:18 TW: But wait. You just… We went from privacy to… Do you just equate privacy with governance?
0:16:24 MH: No, no, no, but GDPR, it requires governance to make that happen.
0:16:28 TW: Okay. Gotcha.
0:16:28 MH: That’s why.
0:16:29 TW: Okay.
0:16:29 MK: That’s fair.
0:16:30 MH: In other words, you need to set up processes and governance structures. And before, there was no like, well, we got something, we don’t have much, but I think it sort of opens a door to all the other things you need to do from a governance perspective. People are like, well, you know what, I should probably just make sure my data is actually in good shape too, and since I have to go through it anyways, make sure I’m not collecting the wrong kind of data or whatever. So, that’s what I mean. It’s all in that governance bucket to me.
0:16:57 TW: I guess, it’s interesting ’cause it’s like, they overlap as a Venn diagram, but there’s kind of the ethical I think of when we had Finn Latimore on and then talked about the ethics of AI, there’s kind of an ethics of data collection and data usage and that’s sort of the corporate where do we culturally or ethically draw our line. That has to be really decided first and then the governance processes have to support it. It jarred me a little bit when you went straight to governance ’cause that’s like, that’s the regulatory requirements to track it, but then there’s the piece that comes in that says, where do we fit from how we philosophically want to think about the data that we’re collecting and using?
0:17:41 MH: Yeah. Well, I’ve been thinking a lot about that too, actually. ‘Cause being in the industry for a long time, before there was nothing, right, so it was just a wild wild west. We’re all trying to do stuff, be the best we could be. And I always sort of had this mentality of like, well, my attitude towards people’s data is very pure. I don’t personally ever intend to do anything terrible or advertise in negative ways or use data in negative ways. And so, therefore, as an actor, I’m a good actor.
0:18:11 TW: That’s back to projecting your values onto what…
0:18:13 MH: No, I know, and that’s what I’m saying, is I’m learning it’s not good enough. That’s just not good enough anymore to have that mentality because the day I leave, some asshole will come in and start misusing with data.
0:18:26 MK: But it’s also misuse of data is not just about intentionally misusing it. It’s also about really good intentioned people making mistakes.
0:18:34 MH: No, absolutely. Yeah. I think that’s what I was trying… I mean, I think we’re on the same page, Moe.
0:18:40 TW: But it’s not binary. I guess that’s the other… You could go to 10 people and say we’re gonna use this piece of data about you in this way and one person would say I hate it, one says that’s fine and eight other people would say, well, makes me a little uncomfortable and that’s just, it’s messy.
0:18:55 MH: Right. But I know best. So, that’s the thing. So, it’s okay.
0:19:02 JC: Yeah, no, but I think you guys have covered the existential threats to the way we’ve always done things. We’ve covered ITP and cookie handling in a previous episode and the discussions around increasing regulation and saw the ethical side of that. I guess just one observation I’ve hard, working in the Hong Kong market, or APAC more generally, is seeing more and more companies taking digital analytics functions in-house. And I think it’s coming from, in this region, an ever-expanding focus on data analytics as a critical function of their business, and it’s becoming less and less something that people want to totally entrust to external partners. So, I guess I’m curious, are you guys seeing the same thing where you’re at? Sometimes the market I’m in can be a little bit behind. It’s always playing a bit of catch up to, particularly to the United States and to Europe, so I’m wondering…
0:20:00 MK: See, I think the opposite. I think our region is often ahead of the game. And yeah, in Australia it’s definitely the case, where we now here, we have 27 people in the data function, between data science, data analytics, and data engineering. And I think more and more people do wanna take it in-house, because data, very quickly people are realizing that’s your IP, that is something that you need to have ownership of, and you need to understand and you need to be looking after the quality. And I’m even seeing a lot of data as a product. People are starting to want to build their own data products, because for whatever reason, what’s in market isn’t working, and that’s more and more coming in-house. And it’s something I still haven’t wrapped all my thoughts around, but I definitely think the analytics function, especially yeah, clients side, it should be in-house.
0:20:50 JC: Totally.
0:20:50 MK: You have the business context.
0:20:52 TW: But let’s tease that apart. It should be in-house, true. A lot of companies would like it to be in-house. I’m not saying it’s wrong one way or the other. The ability to bring it in-house, I feel like our industry, the reason that agencies and consultancies have been doing well is because finding that talent, bringing somebody in-house, it’s probably, at least in the States, in a lot of cases, it’s gonna cost companies more than they’re comfortable paying. They may be able to pay more for a contractor or a consultancy because it’s under that consulting contractor model than when they say, “Oh, for an FTE, I’m either gonna get… ” I think they hire plenty who aren’t that great. There’s still a supply and demand gap, so there’s… I don’t know if you guys see that at all.
0:21:41 MK: I think they’re hiring shit people.
0:21:43 TW: Yeah, if that’s your option, “I’d like it to be in-house, but I can’t afford or stomach the cost or find the talent,” what do you do?
0:21:54 MK: You go international, and then you find a way to bring them to you. If you don’t have enough talent in your market, go to other markets. There’s amazing, amazing talent in Eastern Europe, throughout Asia, Australia. I don’t know, I just think… And I’ve had this discussion before with other people in the US, that they’re like, “Moe, it’s not that easy to get someone a Visa, be real.”
0:22:14 MH: Yes, it’s pretty difficult, yeah.
0:22:16 MK: But to be honest, that’s how the Australian market is doing this. We don’t have enough good talent in Australia. We’re moving people here.
0:22:22 TW: But that’s… My understanding is Australia is… It is much, much easier to actually… Yeah, the States, particularly, oh, we’re fucked up on many, many fronts, but yeah, crossing international boundaries is… You’re basically pointing out that that’s hurting industry and that picking up that talent is really tough.
0:22:42 MH: Oh geez, we just landed on the pro-H1B side of the argument, that’s disappointing.
0:22:49 MH: Well, only for the negative backdrop to it. Anyways, I think, from my perspective, Josh, on this, I think you’re right about this. And actually, I’m making a pretty big personal bet that that’s the case, because I just started my own company to basically help companies build their analytics organizations up, to be able to do this kind of work. So, I’m a consultant, but I’m a consultant who helps companies in-house their analytics better.
0:23:15 MH: Yeah. It’s sufficiently complex enough that a lot of companies aren’t getting what they need from their in-house talent, so they still need help building that up. But I think the time is right for it. Or, people are starting to value it more than just what the traditional advertising agency was providing to them over the years, of canned reports with no real understanding of the context of the business and those kinds of things. And I think, to your point, Moe, of how things are proceeding in Australia, I think that’s really heartening to hear about a place where people are really giving it that kind of focus, ’cause that’s really what is demanded to make this work effectively.
0:23:56 MK: It’s hard, though. I still meet people at… We’re now Data Analytics Wednesday, and they’re trying to either transition into data or they’re finishing uni. And they’ll come up to me and they’ll be like, “Hey Moe, I really wanna get in the industry. What should I do? I’ve been playing around with Tableau and Data Studio.” I’m like, “That’s really cool. Learn SQL. No one will hire you in the Australian market if you don’t have SQL.” End of discussion. You can have all the database stuff you want, but to be honest, and I mean this in the nicest way possible, you can pick that stuff up on the job. But if you don’t have SQL in your resume… And I don’t know if the States is the same, but you won’t get a job here.
0:24:36 TW: Oh, who is it who came out with this fucking data translator thing? McKinsey? Was it McKinsey?
0:24:43 MH: Yeah, I think so.
0:24:44 TW: And I… Boy, that’s right up there with citizen data scientist for me. And I know a lady who… She just changed jobs, and she was like, “I’m looking for a new job, and I’m gonna be this data translator person, ’cause I can do this and that.” And I’m thinking… She got a new job, good for her. But I think that is a lot of people who were saying, “Wow, that seems hard. I don’t know if I wanna actually invest that much, or if I’m that jazzed about SQL, and then Python or R, and getting technical.” And I agree with you, Moe, I think it’s got longer legs. It’s like saying that Excel is gonna die. Everybody says Excel’s not going anywhere. It will still, still be around, but if you actually wanna be doing analytics, you’re gonna really be in a tiny, little niche if you’re just doing data visualization.
0:25:40 MH: There is a path, though, there is a path to not having it on SQL, and it’s have already been in the industry for 15 years, synthesize that information, and then start your own consultancy.
0:25:55 MK: But I think the problem is, and I’ve had these in workplaces, the people that don’t need SQL become dependent on someone else to pull data for them.
0:26:04 TW: Yes, that’s right.
0:26:05 MK: And then you have this… Pretty much every company, and I know I’m talking very generically about client-side, data is stored in databases. That’s where it lives. And if you want to find a way to pull that. And I’ve had finance teams who are like, “Oh, we wanna do all this analysis. We need all of these metrics.” And someone in the data team has to write SQL to pull the data for them and you’re like, “This is ridiculous. You need to learn SQL. If you wanna do analysis, you need to pull your own data.”
0:26:33 JC: Yes. But I think it’s… One of the things that I was reflecting on this was I actually kind of feel like it’s getting easier for people to find the resources that allow them to gain those skills. And maybe that’s just because of over the past couple of years I’ve become more involved in getting into the community, so whether that’s through the Measure Slack or this podcast and others like it and finding resources online, lots of amazing courses, lots of amazing resources for learning SQL, you don’t have to necessarily pay for that anymore, you could kind of do it on your own. So I do agree, it’s totally necessary. I just feel like it’s easier to pick that up than it was even five or six years ago when I was first getting into this industry.
0:27:16 MK: But it’s funny, I’m even getting to the stage with marketers and product managers. I know some companies here, they won’t hire you as a marketer or a product manager if you don’t know SQL now.
0:27:25 TW: Wow.
0:27:26 MK: And all my friends who were in the industry who were like, “What’s the one thing I should learn?” and I’m like, “SQL.”
0:27:30 TW: I’ll counter it a little bit. I mean, I’m obviously on that same path and I have… As a SQL dabbler, well over a decade ago who then had no need to use it and I’ve kind of gotten back into it a little bit, but the reality is working with a number of very large companies doing, I think, what would be considered real work, certainly seeing what is real work being done by their in-house talent, by our staff, by agencies, there are still, if you were living purely in the digital world of call it digital marketing and digital analytics, not everything winds up in a SQL database. The number of databases that I even have access to is vanishingly small. Now I’m outside and I’ve got a range of responsibilities, but even the people who are in-house and looking at the scope of what their mandate is which is reasonably legitimate and, yes, they could always be doing more, there aren’t necessarily databases that they are hooking directly into.
0:28:34 MK: 2024. 2024 we’re gonna revisit this topic and I am totally betting that things have moved to even more in the direction.
0:28:47 TW: I’m not the one defending. I’m just saying let’s not make it… I hate absolutes on anything, like, literally no absolute is ever right.
0:28:57 MK: I’m not saying an absolute. I’m saying when people ask what skills they should learn, that is the skill they should learn.
0:29:02 TW: Could you stop and acknowledge my joke first?
0:29:05 MH: Only a Kiss deals in absolute.
0:29:09 MH: Sorry. Star Wars joke.
0:29:14 MK: I do have one reflective topic which I’ve kept as a surprise reflective topic because I think this is gonna get even more push back.
0:29:25 MH: I’m on the same page with you SQL-wise, just FYI.
0:29:27 MK: Thanks, Helbs.
0:29:28 MH: So you know. I was joking about me not knowing SQL, but if you’re coming into the industry right now, you need to learn SQL. And the reason Tim and I can get away with not knowing it is because we’ve been around for so long, there’s other way we can add value.
0:29:40 TW: Yeah, totally. I feel like I know it better than Michael.
0:29:42 MH: I also have done SQL and can learn it again, so fuck you, Tim. I can totally do SQL anytime I wanted to at an appropriate level after a little bit of Googling and some statute page. Okay. Back to you Moe on your surprise reflection.
0:29:58 MK: Okay. So, the war was waged and… Drum-roll, please.
0:30:05 MH: I don’t know what we’re drum-rolling.
0:30:07 MK: Python won. Everyone I know who knows R is either learning Python or pretty advanced in Python. In my team alone, I’m the only person who is still just an R user. All the people that use R have gone to Python. I’m not saying that R doesn’t have use, and I still use it, but I think for the industry there was a war and Python won.
0:30:29 TW: I don’t think it was a battle, but okay. Yeah. It’s sort of like…
0:30:34 MK: Why don’t you think it was a battle?
0:30:36 TW: You just said, like, hey, peanut butter and chocolate had a war and peanut butter won.
0:30:40 MK: Well, in that one chocolate won.
0:30:42 TW: Google Analytics and Adobe Analytics had a war and one of them won. I don’t see it that way at all, but I like them both. I just don’t see them really in that much of opposition to each other. Like, I don’t.
0:30:56 MK: I’m really surprised by this.
0:30:58 MH: I think personally I would go Python because somehow it makes more sense to me, like, the way the syntax works. R still confuses the crap out of me, but I’ve done some tutorials. I promised Simo I would learn some programming language, so I’ll probably go the Python route, but that’s just ’cause Tim went R.
0:31:17 TW: Well, I can point to people who came up on Python, had no reason to switch from Python, started dabbling in R and said, “Oh, I see where I’d wanna use this. I’m really intrigued by it.” And out of their own as projects are coming up were saying, “I’m gonna do this in R because I see the benefit there.” And I still think Python has a ways to go when it comes to the visualisation presentation. I think there are packets of what R does and then the fact is they can cross over pretty seamlessly between using both. You can embed Python in R and you can embed R in Python. So if I had my druthers, I would totally know both, but wow, if there’s a package in R that avoids me having to write API calls from scratch in Python ’cause there’s not a package there yet, then just right there, I wanna pull data from X location. So, I don’t really see them in opposition.
0:31:52 MK: I don’t know. I think that the way that I’m seeing Python being used and this is because I am seeing a lot of this, like, people trying to build their own data product or you’re trying to build analytics back into your platform or like an ML model or all that sort of stuff. You can productionize Python better and therefore, I’m finding there’s less and less uses for R in my every day work. Like, I still… I still think it does an amazing job when you’re trying to do analysis and that sort of stuff. I just think that if I had my time over again I would be learning SQL and Python.
0:32:43 TW: I think you’re… I think it’s a fair statement and I’m not really authoritative enough to know that when it comes to operationalizing machine learning that you do wind up saying that should be done in Python but I think they both have massive install bases with massive breadth of use cases and to, again, make a declarative statement that one has… We’re not talking OS2 and Windows here so I… Yeah.
0:33:13 MH: We’ll finish with this which is some validation for you, Moe, because the number one language on the developer survey that people wanted to learn was Python. That was the Stack Exchange survey. It doesn’t make it right. It’s still a why not both type situation but definitely it’s growing.
0:33:30 TW: Right, but keep in mind, Python still general purpose with once Pandas came on and continued development, tons of analytics capabilities but you’re comparing a general purpose programming language to one that was built for and by analytics and statisticians.
0:33:45 MH: Right. Statisticians.
0:33:47 MK: But to be honest, that’s one of the things that I’ve loved about watching how Python has evolved in companies is that all of the engineer, all the full stack engineers are learning it too and so suddenly when you build data product, it’s not just about the analytics or data science people managing it, it’s like the engineers wanna be involved in it and then you suddenly have this conduit between these two different areas of the business.
0:34:09 TW: What’s the front end for that data product? Yet another language, right?
0:34:14 MH: Elixir or React or something like that.
0:34:16 TW: Right. So from a building… And again, I’m not… I’m saying this is not… It is not a win or loss…
0:34:26 MH: Tim disagrees with you but he’s trying to be very careful not to.
0:34:29 TW: Oh, I definitely disagree.
0:34:31 MH: Okay.
0:34:32 TW: But I’m not disagreeing by saying that R won. I guess I’m not… I’m saying it’s a false premise.
0:34:37 MH: Oh okay. It’s good. I think there’s a lot of room out there. So, Moe, would you ever ask a marketer to learn Python?
0:34:45 MK: Not Python but SQL.
0:34:47 MH: SQL. Interesting. Okay. I wasn’t sure how you’d fill on that. Alright, listen. There’s so much reflecting we could do and frankly we have to keep going. Let’s go to what episodes specifically this year, we’ve already talked about a couple, but I know each of us has got a couple in mind that we… Really stood out to us for some reason that we wanted to talk about with each other.
0:35:11 TW: Mine was every episode that Josh edited.
0:35:13 MH: That wasn’t on, that was a pretty good…
0:35:17 MK: Yeah, let’s start with Josh because he had to do all the listening.
0:35:21 MH: I think that’s a great idea. Yeah. Josh was like, “I hated all of them.”
0:35:27 JC: No, it’s great. I mean, yeah, I probably got the chance to listen through them all between editing it and checking it afterwards like two or three times of every episode so I feel like I’m… Had a deep knowledge of like the last 15 episodes. [chuckle] But no, I really… Probably the top one that stood out most to me was on working with image data with Ali Vanderbilt. I just thought… I mean, the topic itself is really, really fascinating but the way that she explained those concepts was incredibly engaging and for something that’s super complex, she made it quite approachable and easy to digest. I know very little about that space or that topic generally, that I came away from that episode feeling really, really inspired and I was telling my colleagues like, “Oh, you guys have to wait like, in a couple of weeks this great episode. You have to listen to it.” But then if I can do a twofer, I think the other one, just in terms of probably the splash and the impact of it was the ad fraud episode with Dr. Augustine Fou and just the kind of shocking scale of the issue. Yeah, just pretty jaw-dropping and got a lot of similar reactions with everyone that I shared it with.
0:36:40 TW: Those are a great two to contrast ’cause to me the Ali was something that it wasn’t an area I knew really anything about and hadn’t really factored in like how and where it could play and then the fact that she just explained things brilliantly, that’s like a motivator for doing the podcast is the opportunity to actually have a discussion with people like Ali on those topics. The ad fraud, I feel like I knew it was an issue, I brought it up, but at the same time, I would happily stick my head in the sand for a month or two months or three months at a time to have that just hit us in the face. I don’t think I quite realized how much he was out championing it.
0:37:20 MH: It definitely made me do some different looks at some GA reports.
0:37:24 MH: It sort of would be like, “What? Is that what I’m thinking? Okay, so that looks normal.” Like, “What? What was this?” Yeah. Anyways. What about you Moe? What was some favorite episodes of yours?
0:37:36 MK: Well, I got like six favorites this year ’cause it was our best ever year.
0:37:40 MH: That’s technically exactly not correct but let’s just see where you go with this.
0:37:46 MK: Okay. So, okay, this year we were really lucky. We did have a few “famous people”. So the episode with Emily Oster about contradicting conventional wisdom with data and of course the episode with Nancy Duarte on data stories. Those two were like… You know, people I never thought in my life I’d get to speak to and it was completely incredible, but then I just loved the episode with Maryam about what’s in a job title, maybe the data shows. I talk about that all the time with our internal recruitment team, it constantly comes up in conversation and I actually left feeling like I learned something really tangible about recruitment, and then of course, like, how could the creating balance team with Aubrey and Alison not be just this amazing highlight for the fact that it was the first all-female show, but also I was pretty nervous about hosting the show on my own because I think obviously you guys just have so much value but to have those two incredible women just bouncing off each other, it was almost amazing to just kinda be a spectator to that.
0:38:33 TW: Well I feel like we should cover up…
0:38:33 MK: Oh, and then the Ali episode. Sorry and then the Ali episode about working with image data. I liked that. Anyway, I can’t, I can’t change the rule.
0:39:01 MH: I also wanted to mention, it made me think of Episode 117, which is the “What’s in a job title?” with Maryam Jahanshahi. And Harvard, I think, just published a paper two weeks ago where they did an experiment across 60,000 different job applicants to Uber to show how the words used change who applies for these jobs. There’s academic research showing some of this stuff, and I was like, “Wow, we were way out in front on this on our show. Welcome to the party, Harvard.”
0:39:32 MH: No, that’s not really what I thought, but what I thought was, like, “That’s awesome, to see like more research going in.” We’ll put this in the show notes. I’ll find the document again and we’ll put it in the show notes. But it’s just pretty cool to see like, “Hey, this research is ongoing.” Anyways, totally agree with you, Moe.
0:39:49 TW: Well, to follow up on that, I think there was… We asked them after we were finished recording and I’d asked if another company that, I can’t remember who it was, was the competitor of Maryam’s and they are. But there have been some of those machine-learning-driven, trying to extract the metadata. We are gonna get to that natural language processing episode. It will be one of our favorite shows of 2020, even though we don’t know exactly who we’re gonna talk to or how it’s gonna go. [chuckle] ‘Cause it’s been a little bit of gap. But I think we didn’t make it super clear. You started to say this earlier when we were talking about the International Women’s Day episode, that Moe, you alluded to it. The idea was, this was not gonna be a show about women in analytics. It wasn’t going to be… It just landed people where that, essentially, it became diversity, so it was a little bit broader. That really wasn’t the intention. And when you do it this year, the amazing guests you had lined up, it probably won’t be that. So yeah, this is tough the farther we go down the list. These are…
0:40:49 MH: I know.
0:40:50 MK: I think one of the best ways that you champion women into analytics is not by women talking about women in analytics, but about women just talking about the amazing work that they’re doing anyway.
0:41:00 MH: Absolutely.
0:41:01 MK: The Allies… Ali Vanderbilt of the world, where you’re just still, like, “Look at this amazing woman who’s doing this really cool work.” Or Maryam, or Emily. That’s how you champion diversity in my opinion.
0:41:12 TW: Which this was before you joined when it was for the period when it was just Michael and me, and we had Krista on an episode, and it was a woman talking about women in analytics, and we kind of… We agonized, with her, we’re like, “This is… ” She had put out some thoughts and content that was really good on the topic and we said, I think we even acknowledged in the beginning of the show, that yeah, this is inherently awkward to have this discussion. And I think, well, this year’s we’ve had most of our discussions that have had women, has just been a topic where the guest is a woman. But that one still stands out to me as definitely a top show, probably just because when you get people who are really, really passionate about whatever the topic is and they articulate it really, really well, and it gets into a flowing conversation that actually circles back on itself and references back, because their thoughts are so well thought out and backed up by evidence. It was just… You couldn’t walk away without saying, “This is the most compelling argument.” You could bring in a counterpoint view and it would get crushed, because there’s so much depth of thought there. And I’d say that’s similar, like Dr. Fou was a similar, laser-focused on that topic of ad fraud in a similar thing, but…
0:42:38 TW: I had a similar experience to Michael, and I got to listen to the recording of the creating balance teams live, and then I listened to it again when I was editing it, but that was my number one show. We have not brought up the ethics and AI. We’ve referenced it a little bit earlier on this episode, but with Finn Latimore. And I think, that one actually… I think that is what helped me get from the good versus bad, this binary view. She had so many points. And not that I haven’t read, and even since then, I’ve become more aware of that underneath ethics are values, and people’s values can be different, their value systems can be different, organisations have values, and many of those are not right or wrong. It’s a spectrum, or it’s a range. And yes, there are clearly nefarious and evil things, and there are clearly pure as the driven snow things, but there’s a whole lot of stuff that is different things to different people. That one was just… It bit my brain a bit.
0:43:42 MH: Oh, I… I bet we’re coming back to that topic.
0:43:45 MK: Oh, I love poking at ethics in AI. We’ve actually covered it quite a bit in Data and Analytics, and at measure camp and Sydney as well. And it’s just a topic that I care so deeply about and I get so excited talking to like-minded people about it, because I think there are a lot of consequences of the work that we do, and unless we… And no one’s leading the charge, and unless we really have conversations about it, people can unintentionally make some really shitty mistakes.
0:44:12 TW: I worry that as human beings, and especially in the Snapchat, Instagram, Twitter culture that we’re in, where things are sound bites and our ability to think deeply is getting diminished, and the ethics and AI, it is a broad and deep topic that requires an attention span that’s longer than a one-hour meeting. Privacy and ethics overlap on that front, but I worry about the human race losing its ability to wrap our brains around complicated topics.
0:44:49 MH: Well, the New York Times has been publishing those documents from the Chinese government about how they’re using data and AI to basically oppress a people group, the weakers. I know by saying that, Josh, I’m putting you in harm’s way, so sorry.
0:45:00 MH: But…
0:45:10 MH: But I mean, we’re living on that frontier, right? Right now, there’s stories going around about how in China, they’re about to force you to use facial recognition to log on to your phone or to the internet, generally. So we’re headed down a track and it’s got some craziness on it. Anyways, ethics and AI is super important stuff, ’cause there’s… Could be used for really great things, it could be used for really the most evil things we’ve ever seen as a human race potentially. Okay, so let’s get back to shows we like. So Tim…
0:45:41 TW: I hit mine.
0:45:41 MH: Any other?
0:45:42 TW: No.
0:45:42 MH: Okay. You hit yours?
0:45:43 TW: Yeah.
0:45:43 MH: Okay. Well, I saw some of the ones that other people did, and so I was like, “Well let me not double up on some of these ’cause I certainly would count them, so I was like, “Well what are some ones that just… I super enjoyed it, I loved the content of it and the people we had on and so two stood out to me out of all the many great episodes. So first was episode 109, which was the podcast measurement episode with Stacy Gores from NPR and her team developed this RAD, Remote Audio Data, protocol, it’s open source, anybody who does a podcast could use it and set it up in their application. And it was just so cool because it sort of represented this nifty cool frontier of analytics that really hasn’t… I mean, we’re still working off of basically downloads for the most part in the podcast space so, so much work to be done. And so it’s kind of neat and just I like that one.
0:46:35 TW: I’m a little ethically squeamish about that one, because she did actually wind up sending my daughter like a little set of National Public Radio, like swag, socks and stickers and stuff and I felt like maybe I used the podcast for my own personal gain, but…
0:46:52 MH: So you were ethically challenged because you used your connections to get stuff from NPR? You could be a donor Tim. Just donate some money. I think they do that thing where they ask you to donate.
0:47:03 TW: No, that was kind of awesome, almost made me get within 27 miles of being cool to my daughter.
0:47:09 MH: And then the other show that really stood out to me was actually episode 122, which was the one we had with Astrid Illum on dealing with disparate stakeholders. And I just… As I scrolled through thinking about each episode and I was like, “Man, that one just stands out to me,” it was like the depth and quality of some of the insight that she shared on that podcast, I think span the years. There’s a book in there is what I think.
0:47:34 MK: And the fact that we were able to record with May somewhere in remote Italy with almost no internet connection still completely baffles me. And…
0:47:42 TW: That’s right, you were like climbing on the roof of the shed that was passing, it was the kitchen, looking out over the bucolic, countryside of… Yeah.
0:47:50 MK: That was good fun.
0:47:51 TW: Astrid could be the session I’m most looking forward to at Super Week ’cause she’s basically putting her futurist hat on, and thinking about analytics, so that oughta blow our minds for anyone who makes it to Super Week.
0:48:02 MH: Yeah, that is definitely a must see at Super Week. Register today. [chuckle]] Okay. This is gonna be a long ass episode, but we gotta keep going. Don’t wanna short-change the most important part which is… Now, I’ve talked about the industry, we’ve talked about the podcast. Now, it’s time to talk about us. What are we doing going forward? As an industry, personally what skills do you hope to learn next year? What do you think are some big things that are gonna happen in 2020? 2020.
0:48:33 TW: And for you, that means besides growing our LinkedIn group for the podcast and making it a…
0:48:40 MH: Baby steps. Baby steps, Tim.
0:48:42 TW: Is mine to be a less of an asshole next year, to truly grow my emotional intelligence.
0:48:47 MK: Goals have to be achievable, Tim. [laughter]
0:48:49 MH: Yeah, exactly. Thank you Moe.
0:48:53 TW: Are you talking about the LinkedIn group or my emotional intelligence?
0:48:57 MH: You decide Tim. It’s best if you just figure that one out yourself.
0:49:02 MK: So, I’ve got one. My role here at Camp has actually been kind of weird in that of the 12 people in data and analytics, everyone’s super, super technical, does a lot of data engineering, building data products, and I’ve just been this weird person since I started where I’m going around the business fixing problems and a lot of them is fixing data problems. And 2020 for me is really gonna be about building our data culture which is super important. But one of the things that my coach has talked to me a lot about is like, “Moe, you took this job because you wanted to grow your technical skills.” And I’m like, “That is 100% true.” And so what we’re trying to do each week is carve out some of my time to actually do deep technical work. And if… Maybe if I say it here, it will really force me to hold myself to account. But over the next year, I really wanna learn Python and I am part of this really amazing technical team. Everyone writes amazing code, there’s really good QA practices. So I feel like I’m in the right place to do that and my coach and I are really working on how I make sure I have enough time to do it. So, yeah, 2020, the year of data culture and Python.
0:50:15 MH: It’s interesting Moe. I completely support you in that. But I think not technical support, I’m sure he could Google Stack Exchange, but I support support Moe as a person, Tim. Whatever she chooses to do, I support it. And sure, come to me with all your Python questions, I’m really good at asking them again in Measure Slack or Googling for answers. So… No, but one thing I say to lots of people and I’m not saying it directly to you, but I’m gonna say it to all of the listeners and you can take something from it if you want, but I think there is sort of a thing we need to be careful of which is don’t be afraid to embrace being a generalist. There is a group of people who, being a generalist and not necessarily a master of every deep technical thing, that is a very legitimate thing to do. And it’s complementary to the analytics industry. And I only say this because I’m not deeply technical either. And so I struggled with this for years, like, “Should I be learning Python right now? Should I… ” And I always say to people, I’m as technical as I need to be. I’m never gonna say, “You do this for me.” I’ll roll up my sleeves and figure it out. But I know I’m not set up to be a developer, and that’s why I’m not a developer. I don’t know what I am. I am a digital strategist, analyst, whatever.
0:51:07 MK: But I would say though that being a generalist is not about. Not… Like for me, being a generalist means I don’t have to be the best person at Python.
0:51:48 MH: Yeah, exactly.
0:51:49 MK: But if that’s what my team is all programming in, I need to be good enough that I can coach people on my team or understand the code they’re writing and use and run the code they’re writing, you know?
0:51:58 MH: Absolutely.
0:52:00 MK: Yeah.
0:52:00 MH: And what I would say to a lot of people who are kind of struggling with that gap is sort of like keep working on your soft skills because maybe your job in the future should be managing all of those developers and leading that whole team, not doing the development work, personally, and so you just have to give yourself the room and again, if you love what you do, then keep doing it. If you wanna learn Python, learn it, go do it, whatever you want. But I think sometimes in our industry, we get a little excited about people who know all the details and not enough excitement around the people who know where all the details should go. And so, it’s crucial that all these things come together in a one unified whole to actually drive value, and so there’s a lot of different people. This is actually sort of like as I reflect on the future of analytics, I just feel like analytics is no longer one thing, it’s now multiple disciplines, lots and lots of different disciplines and so you can make a whole career out of any one of those. It’s kind of insane.
0:53:04 TW: But I think setting a big goal to learn something tangible and new, that there’s a lot of stuff that you’ll learn that you weren’t expecting to learn. Like my…
0:53:14 MH: Sure.
0:53:15 TW: My journey into R pretty fundamentally shifted my understanding of data and where it is comfortable to be kind of an incremental, if there’s not something tangible that you can kinda set as a something of a BHAG, then it is easy to say, “Well, I’ll incrementally improve on that next thing next week, I’m gonna keep doing.” So I feel like there’s value in study.
0:53:38 MH: What… It’s crazy to me Tim that you took what I said and meant it as don’t set goals or learn new things, [chuckle] ’cause I totally didn’t say that. You should totally do the things you just said, and I totally agree with you, but actually, I don’t think not learning things should be part of anybody’s strategy.
0:53:56 TW: Well, I’m just saying that learning a, learning something like Python or R or SQL or Tableau or Alteryx or Google AdWords, that those are, they have this nice thing and that they’re tangible and you can go from don’t know at all to bumbling around to feel reasonably comfortable with it and therefore those are easier new things to learn than I’m gonna get better at communication or I’m gonna get better at marketing strategy. If you’re doing those, then you really have to work to say, “Okay, how? What is my plan that is going to force me to do that?”
0:54:32 MH: Well, and I would say based on where you’re at in your career, you wanna build hard skills up into soft skills, right? Over time, so that makes sense.
0:54:41 TW: Yeah, I’ve given up on the soft skills. I have no aptitude for the soft skills.
0:54:45 MH: I think you could do something with them.
0:54:48 TW: Yeah, it’s not worth it.
0:54:49 MH: You have secret soft skills you don’t like to talk about, Tim. [chuckle] It’s why you’re so lovable.
0:54:58 TW: Oh, we’re gonna run way over on this.
0:55:00 MH: Yeah, it’s a long episode. Alright, who else is looking forward to the future?
0:55:03 TW: New job, Josh.
0:55:05 JC: Yeah, I got a starting a new job in January moving from agency side into a startup, so I’m entirely terrified, but new, exciting, scary is good.
0:55:19 MH: How is your SQL skills?
0:55:21 JC: A little rusty.
0:55:23 MH: Alright.
0:55:23 JC: They didn’t ask me about SQL, but I did talk a lot about R in my interview, actually.
0:55:27 MK: I’m like, but I know his R skills are good because he helped me fix something this year.
0:55:32 MH: Nice.
0:55:32 JC: Yeah, yeah. Yeah, last time I wrote SQL was actually inside R. There’s a package that lets you paste in SQL to run SQL queries on your data in R. So the last time I used SQL was actually inside an R script, so it’s kinda, to Tim’s point.
0:55:51 MK: It pisses me off, ’cause all the formatting is totally stuff though, which anyway, that’s a…
0:55:55 JC: Yeah, [chuckle] yeah, it doesn’t quite look right.
0:55:58 TW: To be fair, if you’re using dplyr in R, doing data frame manipulation, you’re using SQL concepts basically.
0:56:07 JC: Yeah.
0:56:07 TW: So, I mean there’s the… Well, yeah, we won’t get back into that. [chuckle]
0:56:14 JC: But yeah, and then just in terms of stuff I’m super excited for, it’s gonna be my first Super Week this year, so I’ve heard so many good things and I’m looking forward to being there and yeah, meeting some people face-to-face for the first time, such as you folks on this podcast.
0:56:31 MH: Yeah, actually it was Super Week where we all three, or the rest of us met the first time too, Moe, right? We met in person, two years ago?
0:56:39 MK: That’s right.
0:56:40 TW: All three of us together at the same…
0:56:44 MH: Tim, we met at an eMetrics, I believe. Okay, so I am looking forward to next year, too, because I have done something very foolish and quit my very nice job at Search Discovery and started my own company, and so I’m going through a little bit of a startup-y thing myself there, and so that’s why I’m not gonna focus too hard on the hard skills, this year, Tim. [chuckle] ’cause I’m focused very hard on one hard skill, which is trying to make a business work, and it’s fun. I’m having a really awesome time, and it’s been pretty cool to sort of do both sides of this again, helping companies structure analytics to make it actually work for them. And we’re early days yet, only a couple of months into this, but I actually just sent my first invoice out today, the day we recorded. So that’s a big step.
0:57:38 TW: Not as big as getting paid, right?
0:57:41 MH: Yeah, and getting paid for that was the next things, yeah. I know how it works, Tim, I know how it works, or I know how I hope it works. Anyway. No, but it’s pretty awesome and it’s been a fun experience, but 2020 is definitely gonna be a very exciting adventure year for me for that reason. What about you Tim, what’s your development plan for 2020?
0:57:43 TW: Yeah, this is, I’m just not in a good spot right now to actually figure out what that is, so I think I’m gonna have to take a hard pass on that, there are lots of things I want to pursue and I have not figured out how to successfully pursue the right one.
0:57:43 MH: I think I speak for Moe when I say have you thought about SQL or Python?
0:58:23 TW: I started pursuing SQL again and then got steam-rolled by some client work and other life issues and thought, “Damn it! I have to pull the cord on that.” Yeah, Python was it for a while, I just honestly don’t know, I’ve got a whole lot of really interesting and exciting things going on, but I can’t point to which ones are actually gonna grow me professionally.
0:58:49 MH: Yeah.
0:58:49 TW: Hopefully, the powers that be at Search Discovery don’t listen this far into the episode and call me on it, ’cause I’m gonna have to make up some bullshit things in our quarterly system on that front.
0:59:01 MH: Ghost, ghost OKRs, as I like to call.
0:59:04 TW: I set them every quarter and then horrendously fail to achieve them, so…
0:59:07 MH: Yeah, if they’re aspirational then that says design, right? So…
0:59:10 TW: Let’s not go down that path. [chuckle]
0:59:12 MH: Good. Okay, alright, okay, we need to start to bring it back in. Let me just say that, we’ve been doing this podcast for five years now, which is pretty incredible. And most folks don’t know how the ins and outs of the podcast work, but for almost all of those years, Tim Wilson has personally seen to the editing and the creation of the show links and all this different stuff and this year we brought on a producer in Josh, who has, I hope, I think changed Tim’s life in a very positive fashion and has actually been a pretty awesome guy to get to know this year. So, I just wanna take a minute and say, Josh, you don’t probably know the impact you’ve had on this podcast and on our community, but we are so glad, I am so glad that you are part of our show and geez, we should have done it three years ago, but maybe you wouldn’t have been around, so…
1:00:16 TW: If all the latent aggression intention you sense between the three of us, and you think, “My God, what was this like before I was here?” Well, it used to be just full on screaming matches. [chuckle]
1:00:27 MH: Did we ever yell at each other? Not…
1:00:30 TW: I think Josh has witnessed the only close to yelling that’s happened.
1:00:34 JC: Oh yeah.
1:00:35 MH: Oh okay.
1:00:37 MH: But that wasn’t during a recording.
1:00:40 TW: Right. Yeah, that’s what I’m saying, it’s the…
1:00:42 MH: Yeah, exactly. Was at the business side.
1:00:46 TW: I’d agree, Josh has been… It has been awesome to have… And that’s where, hopefully we’ve gotten feedback that people have enjoyed the multi-touch moments, and that’s not just because Josh is, you’re part of them, but that is actually, partly being ’cause it’s freed up capacity for us to even think about and do those sorts of things, so…
1:01:07 MH: Think of dumb stuff to say.
1:01:08 TW: There are things that are happening that aren’t just behind the scenes operational…
1:01:13 MH: Yes.
1:01:13 TW: Improvements, although those are keeping us sane.
1:01:16 JC: Oh, that’s awesome, thanks for, thanks for the shout out, you guys. I’m honestly having a great time helping put the show together, and it’s been great to get to know you guys, so…
1:01:26 TW: Plus it makes the, it’s all the news going on in Hong Kong. Like you joined just in time for it to be instead of a…
1:01:30 MH: Oh my god!
1:01:31 JC: Oh yeah.
1:01:31 TW: Instead of a passing news story, it’s like, “Get… Okay, Josh, are you still… Are you still far enough away from the… “
1:01:37 JC: Yeah. [chuckle]
1:01:38 TW: Yeah.
1:01:39 JC: Yeah, you guys have… You guys have live updates on the situation on the ground at Hong Kong.
1:01:43 TW: So I will, as kind of as my sort of big reflection and I sort of feel like this is a somewhat repetitive topic ’cause this is the fifth year end review episode we’ve done. No, things have shifted. I feel like every year I, when I look back on the year of the podcast, I’ve got like a series of those really cool interactions with listeners, people that I knew before, people that I didn’t know before, people who have said that they got something really useful out of the show, just people I’ve gotten to know and that was kind of the excuse ’cause it seems like we’re reasonably approachable. So getting to go and represent being at conferences, or even just being in the Measure Slack, and establishing those connections, it is very heart warming and rewarding to feel like I’m part of a community that actually cares and is growing and is trying to support each other and feeling like we’re contributing to that is pretty cool. And working with Moe and Josh on the podcast has been awesome. [chuckle]
1:02:49 JC: And not Helbs? [chuckle]
1:02:52 MK: I think that was implied.
1:02:53 JC: Oh okay, that’s the joke. [chuckle]
1:02:57 TW: I was just seeing if he was paying attention. And you’re great too.
1:03:01 JC: This is the why I’m usually not on the mic. [chuckle]
1:03:03 MK: It takes a while to understand Tim’s humour, I think.
1:03:08 TW: Although it’s gonna be weird. Like 2019 was, I think, the, really the only full year that we work, I guess most of 20, almost all of 20, well, maybe all of 2018, we were co-workers for two years, so we were only podcast collaborators for two years, co-workers and podcast collaborators. So, I’m not doing my math well, three years, not as co-workers, two as co-workers, and we’re gonna go back to not being co-workers and that’s gonna be interesting.
1:03:34 MH: It’s a huge load off, I’m sure. [chuckle] Yeah. I’m just… [chuckle] I can’t…
1:03:39 MK: I’ve already done my prediction, in five years’ time, 2024, everyone, the whole world is gonna know SQL and I’m gonna remind you all of it, in our year end review episode, ’cause they’re my favorite. [chuckle]
1:03:52 MH: So could I be a citizen SQL person? Is that a thing in 2024?
1:03:57 TW: You could be a SQL translator.
1:04:01 MH: No.
1:04:01 MK: Sure.
1:04:01 TW: A citizen SQL translator.
1:04:02 MH: Ooh, now you’re talking. No, I think it’s… I mean I remember the episode we had with June Dershewitz from Amazon and I would say she would agree that SQL is a necessary skill set for an analyst, so I think you’re good company Moe. Alright, so Moe, you have nothing more to add, no closing thoughts, comments, anything? 2020?
1:04:21 MK: No, I think I’ve wrapped the year, I’m ready for 2020, year of data code. [chuckle]
1:04:21 MH: Okay. We’re doing it, we’re doing it, it’s SQL culture time, 2020. Let’s go. Thank you all for listening. As always, we love to hear from you on the Measure Slack. We’ve got an exciting year of content kicking off with an amazing time at Super Week. So get there, it’s not kicking off with that, but that’s when we’re all be together. Get there, by any means necessary and we will see you in Budapest at the end of January, if you’re there. Okay, if you’re not there, you still wanna reach out to us, we have a LinkedIn group and we have Measure Slack and Twitter, and we love to hear from you. Okay, I think I speak for my co-hosts and our amazing producer, Josh, and Moe and Tim and maybe even all of our guests, I don’t know, I didn’t ask, but no matter what 2020 holds in terms of cookie deletion and ITP and GDPR and CCPA and women in analytics, and the struggles we have with more racial diversity in our field and all the things that we need to learn to be analysts in our space, whether that be SQL or Python or R, or whatever, one thing we can never stop doing is analysing.
1:05:51 Announcer: Thanks for listening and don’t forget to join the conversation on Facebook, Twitter, or Measure Slack Group. We welcome your comments and questions, visit us on the web at analyticshour.io, facebook.com/analyticshour or @AnalyticsHour on Twitter.
1:06:10 Charles Barkley: So smart guys wanted to fit in, so they’ve made up a term called analytics. Analytics don’t work.
1:06:18 Thom Hammerschmidt: Analytics. Oh my god, what the fuck does that even mean?
1:06:26 MK: It’s on our speaker mixes, guest mix, Jesus.
1:06:31 TW: Did not have him, did not have Jesus.
1:06:35 MK: No, we didn’t have him.
1:06:36 MH: Yeah, is he in the industry? [chuckle] Sorry, sorry, okay.
1:06:43 MK: That’s okay.
1:06:47 TW: You could, this is like, “Okay, Josh Jesus”, I was thinking the same thing.
1:06:52 MH: We’re all thinking it.
1:06:53 MK: I’ve been messaging him, but like heart…
1:06:57 MH: Oh, so I’ve been telling Josh not to talk, so sorry for the mixing up…
1:07:02 MH: Just kidding.
1:07:04 MH: Favourite podcast episodes. How do you get six, Moe? No, you get, you get 2.5. [chuckle] Well, we don’t share our numbers, and so [REDACTED] could go and jump off a cliff. [chuckle] Bitch. Oh, did you catch that? That’s great. Can you please, do not put that in the out-takes because I… [chuckle]
1:07:27 JC: Producer cannot be trusted. [chuckle]
1:07:31 MH: Yeah, and then we’ll be like, “Shut up Josh, we have something to say.” No, just kidding. [chuckle] Good stuff. What, no last call on the…
1:07:40 MK: No.
1:07:40 MH: Year end review?
1:07:43 MK: No.
1:07:43 TW: The whole thing is a last call. And Josh had a last call, that’s the thing to say, it was like the best last call ever.
1:07:49 JC: I… Yeah. [chuckle]
1:07:52 MH: Oh no wait, everyone sit down.
1:07:53 JC: Yeah, we’ll just put my one last call in.
1:07:56 MH: Yeah, that’s right.
1:07:58 TW: Rock, flag and navel gazing.