#134: These Are a Few of Our Favorite (Analytics) Tips

“QA and patience and reviews by a peer. Data viz testing, hold no chart too dear. Don’t be an asshole; automate ’til it stings. These are a few of our favorite things!” With apologies to Julie Andrews, on this episode, Moe, Tim, and Michael shared some of the tactical tips and techniques that they have found themselves putting to use on a regular basis in their analytics work. The resulting show: multiple tips, minimal disagreements, and moderate laughter.

Tools, Techniques, and Super Robots Mentioned in the Show

Episode Transcript

[music]

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.

[music]

00:27 Michael Helbling: Hi, everyone, welcome to the Digital Analytics Power Hour. This is episode 134. My name is Michael Helbling, I’m the owner of AJL Analytics. One of my co-hosts is Moe Kiss. She’s the Marketing Analytics Lead at Canva. Or, Moe, it’s Australia, so was it Canva?

00:46 Moe Kiss: It’s just Canva.

00:48 MH: Canva, okay. And our other co-host is Tim Wilson. He is the Senior Director of Analytics at Search Discovery and the Quintessential Analyst.

[chuckle]

01:00 Tim Wilson: Oh, we’re gonna…

01:02 MH: That’s correct. It doesn’t say that on LinkedIn, but that is the correct introduction, Tim.

01:07 TW: Well, I am… I think I have been recommended or endorsed for butter, like two or three times on LinkedIn. So, it’s pretty much the same thing.

01:15 MH: Because you’re smooth like that. Okay.

01:18 MK: Oh, wow.

01:20 MH: Let’s get going. We are doing a special episode, Tips and Tricks. We go into every day with some tools in our arsenal, and we went through and created a big old list. We rated that list about what was some of our best ones, and now we’re gonna talk about them with all of you. Alright, Tim, you wanna pull out the first tip or trick?

[chuckle]

01:44 TW: I feel like Moe should start.

01:46 MH: Okay.

01:46 MK: What?

01:47 TW: My tip is to let Moe start.

01:51 MH: Never start with the first tip or trick. That’s Tim’s first tip.

01:54 TW: There you go.

01:54 MH: Good one.

01:57 MK: So I’ve actually been getting asked a lot about how people can improve on their stakeholder skills, so it’s kind of a bit of a theme that’s coming up with a lot of my colleagues. So one of the things that I started doing a few years ago was that I would go to a meeting with a stakeholder who had a problem about something and I would set myself a goal of just asking questions. So I would basically try and avoid giving any opinions or advice, and let them know that I was kind of trying to explore the problem with them, and my goal was to walk out of the meeting having only asked clarifying questions. And one of the reasons that I find this really useful is because, number one, it gives you time after the meeting to go away and actually think before you give your advice, which is probably not a bad thing, but it made me a better listener, I think. Because I’m not thinking about the advice I’m gonna give them, I’m just listening, and then just asking more stuff. Does that make sense?

02:56 MH: Yes, I really like that for a couple of reasons. Because I think I have a tendency when I start to get the hang of what people are talking about. It gets exciting, and then I wanna jump in with ideas and start talking about the solution right away. And what I’ve learned over the years is just keep holding that back and keep probing. You get so much more value out of active listening for as long as possible, that then allows you to craft things. So I love that tip, Moe, I think that’s great.

03:24 TW: Well, and I’ll take it a step further. I think that oftentimes as analysts, whether it’s internally or externally driven, we have this idea that we need to show up and have the answers, and arrive and immediately have the answers. And so consciously and deliberately doing this. And it’s funny ’cause I’m literally on-site at a client this week doing this exact thing and it is… You feel the tug of saying, “Oh, but I have an answer.” And sometimes it’s the way that can be channelled, I think, is you sort of pivot it to, “Well, how do I need to probe deeper to really make sure that would work without going to, ‘Here’s the solution’?” But I also love that tip.

04:05 MH: And foreshadowing my last call, we’ll circle back to this.

[chuckle]

04:09 TW: Wow.

04:11 MH: Yeah.

04:12 TW: Okay.

04:13 MK: What about you, Tim?

04:14 TW: Well, let’s talk about spreadsheets. No, we’re not gonna talk about spreadsheets. [chuckle]

04:17 MH: Yeah.

04:20 MK: I really don’t want to.

04:20 TW: Actually, a quick little tangent. I’m curious, because… And I had a few spreadsheet tips, and we had a little bit of a pre-meeting discussion around them, but Moe, what’s the extent that you are in any form of a spreadsheet at this point in your career?

04:35 MH: Yeah.

04:36 MK: Yeah, well, so pretty much any time Tim raised something about a spreadsheet, I was like, “Veto, veto, we don’t need to talk about that.” And I think they can be a little bit dangerous, and the reason I think it can be dangerous is because, yes, I think spreadsheets are important as one of the tool sets that you have. I do still think lots of people in the industry are too reliant. I mean, I would probably open a spreadsheet, maybe two or three times a week. In terms of doing analysis. And it’s more because I’m being lazy, and it’s gonna take me longer to clean it up in R or and I know I’m not gonna have to do it again.

05:18 TW: I feel like I’m in Google Sheets constantly, but it’s not for analysis, it’s for doing things like making list of tips, and tracking them, and rating them. So it’s funny, as we were having that back and forth, I was like, “Oh, this actually… The things that I use spreadsheets for now are structured list-making and management much more than crunching data.”

05:37 MH: Yeah, than analysis.

05:39 MK: Yeah.

05:40 MH: It is interesting, ’cause I think that I now… As we looked at that specific one, and Moe, you were like, “Nah, not really,” and I was like, “What? Spreadsheets? Yeah, you gotta have them.” And I’m very curious now to kind of go into companies and sort of see, who’s using them versus who isn’t. And as things like Tableau and other BI tools, and stuff like that, have kinda taken over how much Excel or Google Sheets is just not showing up in the analyst toolkit anymore. And I have a feeling it’s probably not that pronounced. I think most companies are still using the heck out of Excel and Google Sheets.

06:00 MK: I think stakeholders are… Like, I’ll meet with stakeholders, and they’re like, “Oh, here’s this hideous spreadsheet that I maintain,” and I’m like, “Oh, that’s really dumb,” but I also don’t quite have time to automate that for you yet, so I’m just gonna be shocked and I’ll come back to you in a few months.”

06:00 TW: That’s not a good time for you to probe and ask more probing questions? Why? Why are you doing this moron-ic thing?

06:00 MK: It is.

06:00 MH: Yeah.

06:00 TW: How do you get value from this?

06:00 MH: Yeah.

06:00 MK: Oh, God. What I do find I’m doing more often, which completely shocks me, is that I’m dumping something into Data Studio if I wanna quickly look at it. And it’s because I just find I wanna do a couple of quick graphs and it’s just easier. I find the connector is really simple, and I know I could do that in a Google Sheet, or any… I don’t know why I’m doing that, but I am.

07:06 TW: Yeah, okay, so I’ll actually will throw a tip out. Probably the one that I would die the most if I didn’t get to plug it, and it’s kind of for years I’ve used the same one, it is to me the most profound data visualization tip, which is to maximize the data-pixel ratio, which is a… Often if nobody’s heard that, or doesn’t know what that is, then they’re like, “What are you talking about?” But it’s this really simple, but insanely powerful idea that every pixel on a screen that is not the background colour, is either representing data. So, it’s a number, it’s a chart, it’s a bar, or it is not representing data, which means it could be necessarily some structural pieces, or it could be just decoration and totally gratuitous, but the idea is you want to have as many of the pixels, or if it’s printed as much of the ink as possible. I didn’t come up with this, this was Stephen Few derived from Edward Tufte’s Data-Ink Ratio.

08:04 TW: But it is insane how much cleaner and easier to read and how much cognitive friction you’ll remove if you start lightening up or totally removing gratuitous pixels. And Stephen Few has an example, and I use it now when I’m doing training, where you kinda go through a default chart from a spreadsheet and you start removing stuff, and then you put them side by side, so it is a lot easier to see. To me, it becomes instantly apparent, and when people say, “Your visualizations look great,” I’m like, “I’m telling you, if you apply that one thing… ” Or as Michelle Kiss, Moe’s sister, used to say, like, “Why do you explain it as maximize the data-pixel ratio, why don’t you just say, ‘Pretend that your printer is running out of ink’? And therefore, be as stingy as you can, which means it will force you to just represent the data and the numbers.” And it will have you make things gray, that are kind of secondary, like access labels, that you maybe would have defaulted to black.

09:08 MK: Can I just summarize that?

09:09 TW: Probably, I don’t think you can make it any longer.

09:14 MK: Use the ink…

09:15 TW: Yeah, how can we use less ink to communicate this?

[chuckle]

09:17 MK: Use the ink for your numbers. Use the ink for your numbers. It drives me mad. And this actually is one thing that I really struggle to teach other people in the company, especially other data people, because people are like, “Oh, but I get charts.” It’s like, “No, not really. Because all of your titles are bold and size 16, and then all of your numbers are size 10 with like five decimal places, and this is ridiculously hard to read.” Or even just write a line and people will find it easier. And I sometimes feel like an asshole where I’m like, “Hey, have you thought about doing this?” I actually think it’s a hard… Once you get it, you get it, but to someone that doesn’t get it, I actually think it’s really hard to explain without sounding like an asshole.

10:01 TW: Well, and it is easier to do by… I guess that’s the thing, where it’s like, our tendency is to add stuff, not remove stuff, and things default… Even in R for the ggplot users, the light theme… The theme Light actually has stuff that I then override and remove. That’s my base that I start with, and then I turn off ticks, I turn off some of the grid lines. So to me, it’s a degree of getting… And you really only need to see it once or twice and then you can say, “What else can I take away?” And you take it away and say, “I’ll be damned.” And you say, “It didn’t make it worse.”

10:33 MH: Yeah. And as someone who is noted on the show for being aesthetically challenged, the way that I haven’t gotten to this, or gotten decent at this is, actually make a checklist of things to do to my charts or graphs to get them to the right place. So you go through and you do like, “Okay, do this. Okay, remove this. Take this out. Check your colors.” Or if you do that and just make yourself a little cell of steps, and you can always add more steps as you learn more things, your charts will pop more, they’ll be much more consumable and those kinds of things. So that’s a very good tip.

11:07 MK: I think it was Dona Wong, and maybe I’m misquoting, who wrote the infographics for The Wall Street Journal. Who had the tip of always starting your analysis in grayscale. And it’s something I really love. And it drives me mad that a lot of the tools… Like, when you create a graph in most tools, they default to colour. And I actually love that process, because if you make your graph in grayscale, and then you’re like, “What’s the point I’m trying to make here? So, June was the best performing month, I’m gonna now make June green, and leave everything else in grayscale,” you’ll also see how much more that makes it pop. Which I found it’s a really useful tip.

11:50 TW: Absolutely. I love that.

11:52 MH: Oh, yeah. Conditional formatting, it’s my nemesis.

[chuckle]

11:57 MH: No, I always screw up the formulas for some reason. I don’t know how to explain that, I just always do. But I’ll figure it out eventually.

12:02 TW: I feel like that’s a right of passage for the analyst, to like all of a sudden conditional formatting works. But we’re not talking about spreadsheets, so nevermind.

12:10 MH: Yeah, that’s right, sorry.

12:11 MK: I mean, you really… You’re passionate about conditional formatting. I feel like we should tweet some screenshots of some of our spreadsheets that we have for the show, so people can see how much time Tim really hearts conditional formatting, but I just don’t think it’s that essential to do your job. I think it’s like… Sure, it makes your life easy, maybe, but…

12:32 MH: You just basically described a scenario where you’d wanna use conditional formatting.

12:37 TW: What?

12:37 MH: Moe did. Yeah, so like, don’t hate on the thing you just suggested.

12:42 TW: Again, it’s for a list, especially a list that have drop-downs where you’re trying to get a quick visual pop of where things fall, and I’m… Just where I am in my career right now, I seem to run into that a lot. Yeah, when somebody says, “Oh, I’ve gone in and highlighted the rows,” I’m like, “Oh, why?” So, yeah, “Oops, I really was not trying to take it that way.”

13:06 MH: Alright. Let’s moved on. I’m gonna steal one of yours, Tim, which is, track all of your analytics requests somewhere. It gives you data about where your requests are coming from, and how many they’re coming, enables you to be proactive about notifying stakeholders, and those kinds of things, if you’re being delayed, or you’ve already done that analysis in another area, those kinds of things. You wanna talk about that little, Tim?

13:29 TW: I have a hard time trying to figure out how much of this is personal style versus how much is… I’ve watched organizations not do this and have it bite them in the ass, so I don’t know how much, but to me there’s… I learned 15 years ago that if it’s not written down in some organized manner, and we just rely on ourselves to remember it… And I had a co-worker, he was brilliant, and he was highly productive, but he basically was like, would never write anything down, and you just had to continue to remind him. I’m like, I feel bad about reminding him, but it’s because he wasn’t tracking it. But then if you take it to an organizational level, that whole a quarter or six months in, “Hey, what have we actually done?” So many little death by a thousand cuts, and you’re like, “Where did we actually spend our time,” and actually being able to say, “Oh, we actually responded to 32… closed out 32 requests. And you know what, 16 of them came from the same person. Hey, maybe that’s… What do we do with that?” So that’s actually spreadsheets being a potential place to keep that…

14:38 MK: Jira, Jira, or Trello, not a spreadsheet. This is not something that goes in a spreadsheet.

[laughter]

14:45 TW: It depends on the scale and the scope. I agree, again, same client we’re talking to right now, we’re like, we’ve got to get… They don’t have it anywhere, and we’re saying, “Use Jira.” Because they already have it. But if you go and try to stand up an entire new tool just to track analytics requests… And there is a cost to actually stand up that stuff. So if you’re doing nothing than a spreadsheet, you can be doing it in 10 minutes.

15:05 MK: Isn’t Trello free?

15:07 MH: It depends on your users. But I think it’s a user tool that’s gonna work in the flow of your own organization. That’s the important thing. So, there’s tons of them out there. But that’s so important. And not just, Tim, the reasons that you mentioned, but it’s also for historical purposes. Analysts come and go and if there’s something like that in place, there’s so much knowledge crossover that can happen, which will save people so much time. And nothing is more disheartening than going into an organization as the analyst and finding out that this amazing analysis you did was basically conducted two years ago, and nobody even thought, or cared, or remembers it.

[chuckle]

15:49 MK: Yeah, I don’t necessarily feel like the ticket tracking does that though. Because… We use Jira, and it’s pretty awesome. Everyone really does track what they’re working on and probably you know that I’m really losing my shit and stressed out when I start writing a paper to-do list, because that’s when I’ve got so many little things that I just rebel against Jira. And that’s not a good place to be.

16:17 TW: It’s funny, there’s a nice little transitional step, if you’re so desperate you wanna start writing it down, you could just fire up a spreadsheet and type them in there.

[chuckle]

16:26 MH: Great point.

16:27 MK: But the issue…

16:28 MH: Lots of great tools there.

16:29 MK: The issue I have with tracking your tasks is that I don’t think that it solves that problem of people being able to find analysis afterwards. It’s not good at that. But what I will say is the other thing that’s really dangerous about tickets is that lots of people ask for stuff that is, A, never gonna get done, or B, isn’t important. And what I do find it happens is that, I don’t think the analyst should be making the tickets. I think your stakeholder should be making tickets. And I train my stakeholders to do that, but the problem is, there are lots of like, “Oh, it would be nice to see these.” And next thing you know, over Christmas, someone put 12 tickets in my queue that I have no intention of ever doing, and so I need to go through and get rid of them nicely. You know how people always ask for stuff and don’t actually need it, and in a month’s time you’ll be like, “Do you still need this?” And they don’t.

17:20 TW: And, Moe, I agree with you that it’s not a good learning or insight library. I do think all too often it’s a missed opportunity to, say, at least record the link to the final deliverable. And then that gives you the opportunity for somebody to go through and mine it, or it’s a place that at least has that sort of full life cycle of the record. But I agree, it’s not… I hear people talk about that like, “Oh, then we’re gonna have all the insights in our learnings.” It’s like, that definitely not a Jira construct.

17:51 MH: Yeah, my initial reaction is, I don’t want stakeholders in control of those requests coming in. I would rather be out in front of that, and then I create them. But again, I’m weird like that.

18:02 TW: So, I’ll jump in with the next tip. And this one, I still struggle with, so I have to remind myself, but it’s basically when you’re done with a report or an analysis, pause. Usually you’re pushing to get it done, it’s taken longer than you thought. You’re excited, you’ve gotten it over the finish line, and there’s this desire to say, “Let me push it out, let me deliver it, let me put it aside, I’m done, I’m ready to go.” And I’ve learned the very, very hard way that, when I’ve made that big final push, I need to stop and take a deep breath, and ideally wait overnight, and come back and look at it again, fight the urge to say I’m pushing it out, just because there’s this desire to rush to make the stakeholder happy, to get it off your plate, and that’s a great way to miss something and push something out that’s not good.

18:58 MK: This is the toughest thing though. Because one of my tips is actually to run your work past a co-worker, particularly if you’re running a really complex SQL, which is the bane of my existence, I normally get someone to QA it. But it does add a good, I’m gonna say, half a day. And it’s really tricky, because you kind of… Well, I normally am already busting to get it done by a particular time, and then adding that extra time of review, or just letting it sit so that you can process. Because normally I’ll be laying in bed at 10 o’clock and I’d be like, “Oh shit, the numbers are wrong because I forgot this flag, or this thing.” But it is really tough, so I think that comes back to how you better estimate your time, which I’m completely hopeless at. So if someone wants to give me some tips on that, I’m all ears.

[chuckle]

19:50 TW: But that does mean you’re fundamentally reducing… I mean, I think I’ve taken the mindset that I’m literally gonna produce 20% less, and just get comfortable with that. ‘Cause I think we get caught up in… Like, that is true, but if you don’t do that, you’re gonna push stuff out that’s gonna take you so long to recover from.

20:09 MH: Well, and there’s often so much urgency in our work, people need stuff from us, and they’re asking, and they’re like, “Can you get me this information,” or, “Can you do analysis to find out why this happened?” And so, you also feel a pressure to really get back to people as fast as possible, and it’s really hard to combat that and sort of sit still with it for a minute, Tim, like you’re suggesting there. And, Moe, your tip that we’re now combining into this new Voltron tip, is also really great…

20:42 TW: I think they’re close cousins.

20:43 MH: They’re very close, but all the Voltron were like… Weren’t they like mechanical cats of some kind? Okay, I don’t know. Anyways, I remember when I was an analyst, we actually would do review meetings with just our team first, where we would present our tips or our analysis to each other. So, just like you are collaborating, I think what I’ve always observed is that analysis in collaboration has a 100% always been more powerful than individual analysis. And so, wherever you can find that, those two things mixed together, stop, go find a co-worker, collaborate with them, have them be like, poke the holes, and be like, “Okay, that didn’t make sense.” That’s gonna… You’re gonna lose some people with that. “Okay, well, let’s clean that up. How do I figure out how to create better information around that particular point, or simplify that part of the message?” So I think that’s a great tip, Tim and Moe.

21:41 TW: Well, but I think you kind of… You’re adding on to it and then…

21:44 MH: I am. That’s right.

21:45 TW: You’re reminding, so it’s Voltron triplets at this point, but…

21:49 MH: And I’ll form the head. There you go.

21:51 TW: But that’s also fighting that, or… That if you say, “I’ve done my best and it’s ready,” and if you go and you show it to someone else, close to 100% of the time, they’re gonna have input that is gonna require you to go back and do more work.

22:04 MH: Yes.

22:04 TW: And that’s… It is actually making your end deliverable better. But, as you said, there’s always kinda this urgency, and I think that’s another sort of skill that needs to be developed over time. What is urgency because somebody wants it as soon as possible? What is urgency in that it’s really going to… It’s kinda like getting something out at the very end of the day on Friday, versus by 10:00 AM on Monday morning. It’s the same. In most cases, right? Unless there’s a…

22:33 MK: Uhh…

22:34 S?: What? Really? Moe’s executive work on the weekends is what I just heard.

22:38 MK: I know lots of people now, and I think it’s the workforce that I’m in where lots of people work flexibly and I might duck out for a couple of hours on a Thursday, but I’ll be working on a Saturday. And I know lots of my stakeholders are the same, so I get your point, but…

22:55 TW: Well, okay. Then say this. Yeah, pushing it out at 10:00 PM versus saying, “I’m gonna sleep on it overnight, and I’m gonna do this first thing in the morning, and look at it again, and make sure, “Okay, there’s no… ” And if there is, even then, when you send it to them, you have to count… They’re working at may be odd hours because they’ve got a bunch of other stuff on their plate. They’re probably not sitting there saying the most important thing is that… And it does happen, there are times, but I will claim that we have a tendency to put more urgency on the work for everything, and it’s because we’re pleasers and we kinda want to… We wanna say, “We turned it around quickly for you. Look, we’re great partners.” But there are just… There are trade-offs.

23:37 MH: Expectation setting is everything in that context, right? So, yeah.

23:42 TW: Yeah. Who’s next?

23:44 MH: Well, I think this one goes hand-in-hand with the last one, which is, okay, well then, if your time is so constraint, how do you gain more of it? Maybe you automate everything possible in your day-to-day so that you create more space for analysis, which I think is a great tip. My favorite quote in this vein comes from my good friends Steve Shilling, who described to me in my first little bit of time at Lands’ End. He’s like, “Michael, what we’re looking for is smart lazy analysts. Smart enough to do the job, lazy enough not to wanna do it twice.”

24:17 TW: I feel like we discussed this on a past episode, and Moe’s gonna make the point that she made, that was some really good point that I’m forgetting right now.

24:24 MH: I don’t know, because I’ve internalized that message, Moe, and so feel free to make your point again, but I live by this.

[chuckle]

24:32 MK: I was gonna say, there’s two points that I make about automating everything. One, yeah, I do think you should automate as much as possible, but I think the thing that’s really challenging, and I know my team is facing this right now because we’ve just gone through our warehouse migration and so we’re rebuilding everything. To automate everything, you need to have time to automate everything, so you need to not be doing the three days of wasted time on a stupid spreadsheet…

25:00 MH: Oh, absolutely.

25:00 MK: In order to automate it. And so you need to actually carve out that time. And that can be difficult to find, and I find that lots of analysts, the only way they get time to do that, is to do some of the automation in their own time, which is bullshit and it sucks. The point that I made at the time was about, when you automate everything, you don’t tell your stakeholders, because then you actually carve out extra time.

25:22 MH: Completely agree.

25:23 MK: So they think that it’s gonna take you three days to do this report. Don’t tell them that you’ve automated it down to 10 minutes. Just now you’ve got three days to actually do some deep dives into stuff that you think will add value to the business.

25:35 TW: I’m struggling to figure out how… I like that idea in concept. I’m trying to think how… I feel like stakeholders often aren’t really at all cognizant of your workload. Although, no, I’m taking that back. If you’ve automated… If it’s three days to 10 minutes and it’s a monthly thing that you’re doing, they’re like, “Oh, we know we can’t bug Tim, the first week of the month he’s working on that big report.” And you just kinda sit quietly and chuckle.

26:00 MK: But it’s about ego though. You have to not… And I explained this to one of my old bosses. It’s like you have to… If you’re gonna do this, you have to not be so proud. Because most people when they automate something, they’re like, “Yay, I wanna tell everyone about how awesome this is. I figured this out. It was really hard.” And you have to not have the ego to wanna do that, you need to just be really quiet about it.

26:17 MH: I remember a story in an agency setting in a prior job where a story went around the organization about how the team had been really efficient and automated something and got in trouble for it because there were no longer billing as many hours to that project.

26:34 TW: That happened. That totally happened. And I did it, I managed to build stuff, and then because it was time and materials… I mean, the whole world of agencies…

26:45 MH: Talk about perverse incentives, yeah.

26:48 TW: Yeah. That was crazy. But, I think, Moe, to your point, trying to figure out what to automate. And I’ll get sucked into it. It’s this cool idea that if I write it, then I have the opportunity to pull it way, way more quickly in the future, even though no one’s asked me to. But I know that if they do, I can pull it very quickly, versus the, “I know that this thing is gonna have to be done on a recurring basis.” And then kinda doing that, “Am I spending two hours on it?” And it would take me 10 hours to automate. Like, “Well, that’s not… ” But, well, if it’s weekly, then two months from now, you’ve just kinda screwed yourself by not figuring it out how to automate it.

27:24 MH: And my dream for every analyst is that they get a chance to work inside of a company that celebrates when they automate things, and gives them space to do analysis, so they don’t have to play some of these games.

27:37 MK: Good. We’ve got jobs at Canva. Just reach out to me.

27:41 MH: See? Moe is hiring at Canva and she will celebrate efficiency with you.

27:46 MK: Actually, guys, I’ve got a really funny story for you. So, someone amazing in my team actually wrote this code called Slack Up, and it’s a Python code, and basically we have a channel where we tell our stakeholders what we’re doing each day, what we did yesterday, and the code pulls from GitHub, from Jira, from our calendars, so basically, it gives an update. So, each morning, I actually have a shortcut for it, so I literally just type Slack Up in my terminal and it gives me all the stuff I finished yesterday, all the stuff I’m doing today, and then I just paste it into Slack so all my stakeholders can see what I’m working on. And it saves me probably 10 minutes every day of going through Jira, and Git, and my calendar, but I accidentally let it drop one time in a stakeholder meeting and everyone in data wanted to kill me. Because, of course, they built this Slack Up code, but none of our stakeholders knew. ‘Cause they were like, “You guys always do such great slack ups each day. That must take you 20 minutes every day.” And I was like, “Oh, no, it takes me like two minutes.” And I let the ball drop. And so my team were not super impressed with that one.

28:53 MH: “Moe!”

28:54 TW: I will say there is a risk to automation, which I have definitely seen happen, where if it’s a risk to auto… If you’re automating something and it’s pushing stuff out, that you can be like basically spamming the organization, and not have any reason to go back and check in after a month or a quarter, and actually say… Evaluate. “Is this thing still valuable?” So it’s only for certain sorts of things. If you automate stuff that’s kind of coming to you, and it’s not directly going out. And I feel like I used to see this… Well, but to pick any of your web analytics platforms or the Adobe story, like, “Yeah, I push out this analysis work space every day.” I’m like, “Well, it looks terrible, ’cause it’s analysis workspace, and frankly, loading that into somebody’s inbox every day as a PDF, they’re gonna quickly check out on it. They might look at it for the first week, but why would you ever turn it off? Well, now you’re kind of a spam generator.” So it seems like we said, “Automate everything, and now here are the 17 caveats and challenges with it.”

29:58 MH: Sure. Every rule has its exception. So, maybe it’s automate within reason.

30:03 MK: I tend to go with, if it’s a once-off, I don’t automate it, but I might save the query that I built or whatever. But if it’s something I know that the team… And I will literally ask my stakeholder that. I’ll be like, “Is this something that you are gonna wanna look at again in a week, or in a month, or even three months, or is this something that you only wanna know one time?” And once we have the answer, that’s the answer. And that helps me decide.

30:26 TW: I wanna go with the Voltron cousin tip on that one, which is…

30:32 MH: Right tip.

30:33 TW: Yeah. [chuckle] Which is, documenting what you’ve done as you do it. So, I still remember when Donald Phips posted in Slack. He was like, “Oh my God, our notebooks have changed my life.” And I was still kind of ramping up on R. But I don’t know that… I haven’t written just a plain script file in like two years. Everything’s in a notebook, and even if I know this is purely just for me, I’m writing down why I did it. The same thing if I’m in a spreadsheet. The same thing, even if I’m having to go pull stuff from different sources, I’m still finding somewhere to log how I did it. ‘Cause I am… It is shocking to me how often a number gets shared, and there is no audit trail even back to the original analyst who pulled it two weeks ago and they can’t recreate it. Like, the number of analysts… And they’re like, “Yeah, but every step I took was right.” I’m like, “Well, but if you just write an email and don’t re-read it, are you gonna have typos in it?” Like, “You will, but you have nothing to re-read.” So that’s like, it adds a little bit of time, but you also kinda develop your own practices to say… To me, it’s especially kind of in the coding world when I’m working with data, it does give me the opportunity to say, “Let me write down my approach and now let me fill in and do my approach.”

31:46 TW: So, regardless of the means… I feel like that’s this weird area that learning R has kind of made me a better analyst. And it just… In general, I’ve gotten more comfortable with kind of a narrative of what I’m doing, why I’m doing it, where it came from, what decisions I’ve made, and then I have it. It can go in the appendix of something if I’m delivering it, it can just stay in the network folder. It can go in any number of places.

32:11 MK: But it makes your work more reproducible and understandable by another analyst. We have a technical test that we give analysts when they apply for a job, and the difference often between someone that gets to interview and someone that doesn’t is the comments they write. And it’s because you’re gonna have three people that are reviewing your code, and if it’s really hard to follow what you’ve done, you get to the end and someone will make a recommendation, and if there’s no comments, you’re like, “How did they get to this recommendation from these series of functions? I have no idea what made them think this.”

32:45 Announcer: Whereas you will see the really strong candidates, it’s literally talking through their logic. And, yes, I don’t think in a code base you should have that many comments, but in a piece of analysis where you’ve written your code, you should. I mean, we even have in our data warehouse and our SQL code base, if there’s something really funny, like, I’m treating this value this way because of this, we will put that in a comment in our code. Because otherwise the next person picks it up, and it’s like, “Oh, that’s a really strange approach. I have no idea.” And you’re the only person that has all this context about it. And ultimately, you need to make sure that… Like, if you get hit by a bus tomorrow, anyone can pick up your code and understand why you made the decisions you made.

33:25 MH: Yeah. I do feel buses get a bad rep.

[laughter]

33:31 MH: Sorry. No, I heartily agree. Alright, Moe, you wanna take us into our next tip?

33:38 MK: Well, I wanna talk about… It’s actually one of Tim’s. But when I saw it, I was like, “Damn, that’s kind of good. And I probably don’t do that enough.” So one of Tim’s suggestions was to try multiple visualizations when you are doing analysis. And just basically like having a play through and seeing whether the data looks different if you change the graph style. I think that’s something I could actually work on. But I think it would probably help clarify, like, how will people interpret this, and what is obvious to you when you look at it, and what does your brain jump to? And I guess try and put your mind in the place of your stakeholder and how they’re gonna interpret it.

34:17 MH: Yeah, I’m also gonna side with you Moe, this one really stood out to me as well. And I think primarily because I feel when I read it, I was like, “Wow, I don’t do this enough.” And I immediately get the sense, ’cause I… The cool thing for me is having kind of gone into what I’m doing now. I am getting a chance to actually do some analysis, and set some stuff up for people, and as part of my overall strategy work. And so I’m getting a chance to sort of get back into those. And I do find myself being like, “Alright, what would I take away from this? What’s immediately visible?” So that kind of analysis. But when I read that I was like, “Oh, that’s brilliant. Just give yourself a chance to go and do it a couple of times, find a visualization that will work well.”

35:01 TW: And this totally ties back to the… Showing the queries to others. And now I’m actually realizing that… I had kind of forgotten this, but not too long ago, Helbs actually pinged me on Slack, and…

35:11 MH: We don’t have to talk about that. Yeah.

35:13 TW: No, that was one where you were like… And it wasn’t… ‘Cause a lot of times it’s not like, “Oh, well, here’s a better way to do it,” like, “That’s another great sounding board.” No, you were like, “Hey… O” It was basically, “This visualization isn’t working.” Like, “Do you have any thoughts?” And we kicked stuff back and forth, and then you tried some other stuff, and…

35:31 MH: Yeah, we got to a much better place. I mean, who else would I turn to, but the Quintessential Analyst?

35:36 TW: Oh good fucking lord. I had another case recently where…

[laughter]

35:42 MH: Basically, why I do the podcast with you Tim, so I could ask you visualization questions. [chuckle]

35:47 TW: Keep that Slack team alive. But I had a case where somebody… It was a simple little thing, and it was in a spreadsheet, and somebody had done something. I’m like, “That visualization, I don’t think is really working.” But it was just a Google Sheet, so I tried a couple of others. And I was like, “Yeah, I kind of think this one’s better.” And then I’d gone off and done something else. And then a third person who was kind of involved in this looked at it, and he was like, “Wait a minute, did you do these other visualizations?” I’m like, “Yeah, I couldn’t really… ” And he said, “I looked at all three, and this one is clearly the most helpful.” Which was really nice, because he hadn’t developed any of them.

36:20 TW: And so that’s again, it’s… And I’ve realized that there are, as I am now kind of in more of a… I’m working with more analysts who are with less experience, and I realized that there was some degree of being like, “Wow, Tim, your visualizations are great.” And I’m like, “Well, let’s understand that it’s not like I just looked at the data, snapped my fingers, and… “I feel like we don’t acknowledge all the time, that, yeah, there’s a lot of care that goes into after I have technically represented the data in an accurate fashion, that a ton of analysts seem to say like, “Yep, I got all the… I had categorical values, and I had three different categories, and two different series of data, and I popped them on, and I got my second y-axis on.” And it’s like, “No, that’s not… The challenge isn’t to technically represent it correctly, the challenge is to communicate it effectively.” And sometimes it just takes another set of eyes to help figure that out.

37:17 MK: Yeah, but here’s the problem, right? I see this a lot. And this is often other analysts, or especially the finance team are like recurring perpetrators of this. You see them share graphs or numbers, and you’re like, “Oh, that sucks.” I am struggling to interpret that and I work with data. I don’t know how our stakeholders are gonna interpret that. How do you not be an asshole and tell them that?

37:47 TW: Oh.

37:47 MH: You just have to have a lot of empathy and humility like me, Moe. And…

[chuckle]

37:51 MH: No, I’m just kidding, I don’t know the answer to that question.

37:56 MK: Because… One of the guys I’m working with, he’s the finance marketing partner, so we’re starting to work really closely together. And the other day, we were presenting some numbers to the company, and I said to him… So he made his slides, and I said to him, like, “Hey, I’m kind of into slide design, and we work at a design company, do you kind of mind if I just have a bit of a play-around with your slides and see if I can improve them a bit? You can tell me to go jump off a bridge if you don’t think that’s helpful.” And he was like, “No, that’d be great, I’d really appreciate it.” And so I kind of played around a bit, and then said to him, “I think when you’re sharing numbers and definitions of calculations, it’s really hard when you have five of them on one slide. So just split them up and I’ve done these couple of little things. I hope that’s okay, if you prefer your original version, that’s fine.” But I just don’t… You don’t know if you’re gonna like… He was very receptive, and was like, “This is much better.”

38:45 TW: But I think you nailed it, this is the humility. Michael said it, and then you could just described humility in your…

38:51 MH: Yeah. That’s a great way. And I would even go a little higher than that and say, “Hey, I’ve been reading this book by Nancy Duarte, DataStory, that’s been amazing in helping me get more impactful with what I’m sharing with people. I’d love to share it with you.” ‘Cause I think what you can offer to them is not just sort of like, “Hey, I can help with some ideas,” but actually, “You can be a much more effective in your role by gaining these skills, and let me share what I’ve learned.” And then I always… The old adage that was ringing in my head as we started to talk about this is always, criticize in private and praise in public. And so if you think they have a really terrible or shitty design on something, you maybe do it outside the meeting in front of everybody. So that’s the only other thing.

[chuckle]

39:35 MK: I like that.

39:36 MH: Yeah.

39:36 MK: I’m gonna steal that.

39:37 MH: It’s an old adage, yeah.

39:39 TW: But I think also your point… Using, whether it’s Nancy Duarte, or Lea Pica, or Dona Wong, or Steve…

39:45 MH: Yeah.

39:45 TW: Any of those where you can actually say, “I tried this technique that I came across in a book or in a presentation, and I just thought I’d try it on your content. And here was kind of the rationale.” So you’re kind of like taking… You’re not like… Yeah, I think there are gonna be the jerks who really have too much personal stake, and are seeing it… That still get defensive, but I think eight or nine times out of 10, people are like, “Wow, you just made… ” Especially if you’re not taking credit, you’re not telling anybody, and you just made it way better,” and they’re like, “Well, awesome, you just made me look better, and you help me communicate more effectively.” But, yeah.

40:24 MK: I hope so.

40:25 TW: So that does kinda take me to my simple one of, “Don’t be an asshole,” but…

40:29 MH: Nice. I found it pretty rich that you suggested that one, Tim.

[laughter]

40:35 TW: And Michael, don’t be an asshole.

[laughter]

40:39 MH: That’s fair.

40:41 TW: But I think I recognize that analysts really are, as Jim Caine once said, “Analysts don’t do anything,” which is still one of my favorite, gets re-quoted, and that we are typically… We are serving others. We are serving our stakeholders. And that means the degree of its service which means not telling them how they’re stupid, or telling they’re wrong, or… Private or public. That there is… And again, I think we’ve probably all had the analyst we work with who… Like, “Oh, they just don’t get it.” They are being an asshole. That’s, I guess, a rule for life.

41:16 MK: And you have to be so careful in open offices now. It’s actually something I give so much thought to… And I actually did it the other day where I was really frustrated with someone, and you’re like, “Wah,” and you’re like, “Oh, freak, that was not the right place to have that discussion.” But it even comes down to when you’re talking about data, or you’re talking about some discovery you found, or whatever it is, you have to be so careful. Because if you’re sharing your concerns… Like my stakeholders sit in the next bay, so if I’m like, “Oh, I’m a bit worried about this data because of this, this and this,” it very quickly can spiral into like, “Oh, but the data is not trustworthy,” or, “It’s not right,” or, “Something like that.” And so, it’s something that I am giving a lot of thought to. It’s like, “How do you have those discussions with your team?” But you need to be super aware of where and how you’re having them, because the tiniest comment about data quality in an open office, can suddenly ripple through an organization.

42:15 MH: Yeah. I would even add on to that, so much of analysis and parsing through data effectively, and the tactics and methods we use, and the technologies, require so much intelligence, and discipline, and knowledge, that sometimes it can be when we’re not getting through to people, or people are not believing, or getting an understanding of what we’re trying to talk to, we can tend to wanna bully them a little bit with that information. And it’s something… It’s really hard to avoid, because everybody wants to feel respected, and have autonomy, and to have people understand, like, “Hey, I put a lot of effort, and you can respect this analysis, and you can respect the effort that I put in, and the expertise that I brought to this.”

43:00 MH: And it’s very hard when someone is like, “Well, I don’t know, whatever.” And then you could just be like, “Oh, really?” And then sort of crush them, right? So, it’s hard. It’s really hard. I also, a lot of times in my role as an analyst, I was reminded of that stereotypical IT guy kind of person who’s like, “Oh, your computers don’t work. Move out of the way. Let me do it,” and like, “No, I’m not gonna do that.” It’s just sort of really rough with people, and I was like, “Wow, I could see myself turning into that kind of person with data,” and I would be like, “No, that’s not how you do it.” And I was like, “Michael, look at yourself. Look how you’re responding to people.”

[chuckle]

43:38 MH: You have to not only master the data, but you have to master the win friends and influence people aspect of the job too, and putting those two things together is exceptionally hard. But the tip, “Don’t be an asshole,” you should probably just stick it up on your open-office cubicle wall, and keep it there, ’cause you’ll need that reminder again and again, I think. At least I do.

43:57 MK: And it’s so… I think a lot about trust. Trust from stakeholders is something that… ‘Cause I’ve had periods where it’s been really hard to earn that trust. And like it or not, one of the things I’ve noticed is that I guess likeability and being cordial with your colleagues does go a long way in helping develop that trusting relationship. And so I think that’s why not being an asshole is so incredibly important. Because if you have a good relationship with your stakeholders, they are more likely to trust you, and that’s ultimately what you need to get to, is that when you say something, you have some recommendation, that they listen to it, and believe you, and action it, and that’s really hard to do if you’re like, “Move out of the way. I know what I’m doing, and you’re dumb.”

44:43 TW: Plus you want them… And I can remember what word you just said… ‘Cause it was before you said cordial, which is kind of a… Likeability. That you actually do want your stakeholders to want to… We’re at work, and they don’t call it play, they call it work. I never really liked that attitude, but being likable means that when you do have to have a meeting, they actually want to be there because they enjoy you. And I feel like it’s even for introverts, even for… I don’t know. It is, you have to have that relationship, and you want them to be comfortable popping by and asking you a question. Or saying, “Oh, this is a meeting, I have two conflicts, which one I’m gonna go to?” They’re gonna go to the one… I mean if they’re roughly equal business value, they’re gonna go to the one that they would feel like they’re going to get a little more enjoyment or learn something out of. So, yeah.

45:41 MH: Yeah.

45:42 MK: And ultimately, that you need them to tell you their problems.

45:44 MH: Exactly.

45:45 Announcer: Which is not gonna happen if they don’t have a good relationship with you.

45:49 MH: It’s crucial you get invited into the meetings where you’re setting strategy and direction so that your analysis can map to it. Yeah. Okay. Well, I hate to be the asshole, but we gotta start to wrap up.

[laughter]

46:04 MK: Oh, man.

46:04 MH: I know.

46:05 MK: There’s so many left. We’ve got so many.

46:05 MH: There are.

46:08 TW: Well, if this gets a good response, we could do another episode.

46:11 MH: That’s what I wanna throw out to our listeners. We’d love to hear some of your tips and tricks. We’ll add up to our sheet, and maybe in a few months, we can do another episode on this, and we can get a couple of more of ours in, but we’d also love to include some of yours. So, send us your ideas, and we can loop them in as well. Okay. We do last calls of the show. It’s around the horn. We talk about something we found interesting that we think our listeners would enjoy, kind of a tip or a trick. It’s kind of weird and redundant in this episode, but gosh, darn it, the traditions must be observed. Alright, Moe, what’s your last call this week? Or this time, this episode?

46:48 MK: Okay, so I’m spending a lot of my life at the moment using RegEx for a whole bunch of stuff like messy URLs, and shitty campaign names, and device types, and all sorts of other random crap that are not going well. And the amazing Vincy who’s in my team, who teaches me stuff pretty much every single day, she’s a total rockstar, got me on to this site and it’s called Reg E-X-R, RegEr or RegExr.

47:16 TW: RegExr.

47:17 MK: I don’t know, it’s… Yeah, dot com. And it is freaking amazing. Because basically you can either use the text that they’ve already got there, or you can paste in whatever text you’ve got. If you’ve got a bunch of URLs. And then you can test how different RegExes work to find the weird characters or whatever it is that you wanna pull out. And I just… It actually is really changing my life, and Tim is…

47:41 TW: It’s actually bookmarked in… It’s actually… I have it in my tool bar.

47:45 MK: I too.

47:45 TW: Which is funny, ’cause I still feel like I go to RegEx 101 more often than not. Today I actually managed to write a little bit of RegEx that was just a little bit of a substituting thing, and I got it right on the first time, and it was not that complicated, I was like, “That literally never happens, outside of a dot star.”

48:00 MH: That’s awesome. In the words of The Mandalorian, “This is the way.”

48:05 TW: Oh my God.

48:06 MH: What? You don’t watch The Mandalorian, Tim? Come on, get with the program. It’s 2020.

48:12 TW: I’ve tried. I’ve at least figured out that’s where the Baby Yoda thing comes from.

48:17 MH: Yey, you can be taught.

48:18 TW: No, I had my 18… My middle child was home over the holidays and he basically… When I realized that I could have a free year of Disney+, and he was like, “I can get The Mandalorian.”

48:27 MH: Well, all I’m saying is this is a great right of passage in the analyst journey tangling with RegEx again and again, and being humbled by it, but finding good tools to help you through it. So nice one, Moe, thank you. Alright, Tim what about you?

48:44 TW: So, mine will be a little bit of a fun one. It is a podcast, I haven’t done a podcast recommendation in a while.

48:50 Moe Kiss: I thought you were about to say a four-fer. That is actually what I thought was coming, and I was gonna be like brain exploding.

48:56 TW: Funnily enough, I have four different ones on my list, but I’m only going to do one. And it’s a podcast called Cautionary Tales by a guy named Tim Harford who’s a British… The Undercover Economist. But what he does is he basically goes through and takes different tales from history. The analogy he gives is that when you’re a kid, you tell them fairy tales and the fairy tales or parables basically are teaching kids a lesson about being kind, or diligent, or not lying, whatever. And these are cautionary tales for adults. And so it goes through different episodes in history, and then the way the episodes… They’re like 30-40 minutes a piece, but it’s usually kind of some sort of bias, or just ways that we screw things up even when we’ve got evidence that’s telling us we need to change direction and we don’t.

49:47 TW: So it’s got one where the Oscars, when La La Land was misawarded the Best, when… This was a few years ago, when they were like, gave the Best Picture to the wrong movie. It was Warren Beatty and he had to then apologize. By the time they’re done, they’re going back. And he goes through three or four different examples, and then he ties it into, “This is how you can be aware of this in your life.” And one of the first ones is like, if you have a bunch of signals that are telling you to change course, but you’ve already in your mind committed to the course, how long it will take us to kinda change course. So there are, I don’t know, eight or nine episodes in the first season, and it was a delightful listen. So there you go.

50:32 MH: Outstanding.

50:34 TW: What do you have that’s actually more useful?

50:36 MH: Well, as I foreshadowed earlier in the episode, I recently read a book called Never Split the Difference by Chris Voss. It’s a book about negotiation, and I very much enjoyed it. I actually read part of it, used some of the things he suggested in a real world business scenario that day. Was so amazed by what happened in the result of that. I sat down after my day’s work and finished reading the book the rest of the day. It was intense. So I’m going back through it again now with pen and paper and writing notes, and it’s transforming the way I have business conversations. But the reason that matters is so often we’re always recommending things and trying to get people to embrace our point of view, as it pertains to an analysis or a decision to be made based on analysis, and I was just gaining a ton of insight into how to leverage those conversations more effectively because of that book. So I highly recommend it. Negotiation is something that is hard to do, but…

51:36 TW: Did you read that book instead of finishing the book on finishing things?

[chuckle]

51:40 MH: I have not finished Finish yet, I’ve put it down for a while. ‘Cause you know what, they teach you in Finish, Tim? Is, don’t be worried that if you don’t hit your goal, starting over is actually more worthwhile than hitting your goal the first time out. So I’ve given myself permission to stop reading that book for as long as I want, and then I’m gonna pick it up and finish it in my good day of time. Thank you.

52:04 TW: Good for you.

52:06 MH: I’m so well-rounded, it’s crazy. Okay, you’ve probably been listening and you are thinking, “Oh, that tip hits me right where I’m at,” or, “I’ve never heard of that before. I wanna ask a question about it,” or you’ve got one of your own, which I mentioned, we’d love to hear yours too. Reach out to us on the Measure Slack, or on Twitter, or on our LinkedIn group, we would love to hear from you. Happy to answer questions or provide additional commentary. And I think we should probably talk for a second about our producer, Josh Crowhurst. Just one word from each of you. Tim, one word when Josh comes to mind.

52:45 TW: Awesome.

52:46 MH: Nice. Moe, what about you?

52:47 MK: Rockstar.

52:48 MH: He is truly amazing, we really appreciate… The show really happens with Josh helping us out, so we’re hugely thankful for his help and support. And I think I speak for my two co-hosts, and I don’t know if it came through in their passion on these tips and tricks in this episode, but I think you know it’s true. And with all these tips and tricks, and everything you do everyday, remember, keep analyzing.

[music]

53:17 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 at AnalyticsHour on Twitter.

53:37 Charles Barkley: So smart guys want to fit in. So they’ve made up a term called analytics. Analytics don’t work.

53:45 Thom Hammerschmidt: Analytics. Oh my God, what the fuck does that even mean?

53:54 MH: You guys have AliExpress over there? Because you can probably find that cable for 25 cents. It probably won’t last very long, but if you’re gonna buy a bunch of them, you might as well go that route…

54:03 TW: Good, Michael, what don’t you propose we get shitty unreliable equipment to use as part of the podcast recording process.

[chuckle]

54:14 MH: I’m just trying to save people money. Listen, for five years, this $99 Blue Yeti microphone has been taking my amazing analytic insights to the masses. So that we’re recording.

54:31 TW: Yeah, I know.

54:32 MK: I’ve got a really good last call today, which I don’t know if Tim’s heard of, but it’s changing my life.

54:40 TW: Oh, you read my twitter stream?

[chuckle]

54:47 TW: I’m on fire right now.

54:48 MH: That’s just… You’re just hoping somebody does.

54:51 TW: Oh, man, I sure I am. I sure I am. Okay.

54:56 MH: I think we should probably talk about spreadsheets.

54:56 TW: Yeah. Okay. We’ll give it a good hard break. And then I’ll…

55:01 MK: Josh is gonna kill us.

55:05 MH: Rock flag and assholes, don’t be one.

[chuckle]

55:13 MH: This is great.

[music]

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