S2 E5: Bit - Behavioural design in analytics.

0:00Hello and welcome to the Datum podcast.

0:03This is season two, episode five, and I'm joined by my co-host Ravi.

0:07How are you doing?

0:07Hello.

0:08Um I'm well.

0:09I'm very well.

0:10Um we have a new name.

0:11We do, and and you got it wrong.

0:14I got it wrong, yeah, to start with.

0:16We didn't hit that face.

0:18But uh yeah, this is the Datum Podcast.

0:20We've we've kicked our new name into action.

0:22Um so we are now Datum Pod on Twitter and you can find us on Datum Pod.

0:29Cool.

0:29Yeah, no, so um no, I I quite like the root brand, the colours and the logo.

0:33If you spotted the logo last week, folks, it was on the album art.

0:36Of course it's going to be changed.

0:38on the actual podcast itself now.

0:40So you'll have a brand new podcast that might look a bit strange and new, but it's still us.

0:45It is a bit weird.

0:46But we're talking about behavioral design today.

0:48But one of those things in podcasts is like when the when they change their album art, it kind of

0:53It kind of shocks you, doesn't it?

0:54You kind of think, oh, hold on.

0:55This is this is new, this is different.

0:57So it's quite quite topical actually.

1:03Yeah, exactly.

1:05But before we dive into that, uh let's just do some follow-up on uh the previous episode, which was about champions.

1:11Um what did you think of the show?

1:12No, it was good.

1:12Um again, like I said, it's a passion um topic of mine.

1:15I really

1:16This these are the conversations I have every day in my day job, right?

1:19So this is the stuff sort of stuff I'm doing for our customers, um, helping them focus in on what they need to do to be successful.

1:27So it's really fun to talk about and think about in this

1:30Structured well I I say structured, but um a lot of this podcast comes off the off the cuff, right?

1:35So um yeah, exactly.

1:37But the feedback was good actually.

1:38I mean it wasn't it wasn't huge.

1:40Um we we

1:42did get a few positive notes.

1:43I think there was one one gent who's like actually this is exactly what I'm doing at work right now.

1:47I'm thinking about all this meta-level stuff.

1:50So yeah, hopefully um it'll it'll be useful um to come and

1:55Yeah.

1:55Hope uh I'm hoping that this w maybe it's it's definitely what topic we can come keep coming back to, right?

2:01Exactly, and some of this stuff is timeless as ever.

2:03I think uh uh I was telling you about uh another topic which I think we need to revisit having heard another

2:08other podcasts.

2:09So we'll come we'll come to that a little bit later.

2:11But um as ever please please send us feedback whenever we do a show you think something's missing.

2:17to take that feedback on board.

2:19Absolutely.

2:19Um right, so behavioral design.

2:22I mean the the the name of the podcast today is behavioral design in analytics, but I feel like we have to start first at

2:28What is behavioral design?

2:29Yeah, uh again this i if anyone watched my tableau fringe festival talk, it was on about behavioral nudges in design.

2:37um for dashboards.

2:38Um and and a lot of that comes back to my sort of roots in behavior economics.

2:42This is um we're gonna we're gonna touch on Tim's favorite topic when I'm gonna talk about the dissertation.

2:47um about about recycling habits and the the the habit habitual nature of of what we do and why we do it is definitely about what um where we come to with behavioral design because

2:59If anyone's read, or if you haven't read, Nudge by Thaler and Sunstein is a book that's fantastic for me.

3:07And it really encompasses this idea that you nudge

3:11different you use different aspects either in design or in life to nudge people in the right direction.

3:18It's a really good book actually.

3:19I I first came across it um

3:22Through a series of suggestions.

3:24Um actually I was I was at a quantified self meetup and someone talked about thinking fast and slow in relation to something I was talking about.

3:31about with music by uh Daniel uh Kahneman and then someone else suggested well have you actually read this uh book about nudge um it's actually a really good book I'll put a link to it in the show notes um it's actually about health and well being mostly but

3:45uh sort of the mechanics behind that actually and how we can sort of push people towards a certain choice that's actually good for them.

3:52It's good because we'll talk about some of the ethics of all of this stuff a bit later in the podcast, but um it really talks about that sort of thing because you're you're

3:59You're typically doing a nudge to drive a positive pro a positive outcome.

4:04Um, but of course it can be used for the opposite.

4:07Um

4:09Exactly.

4:09And in many ways, um this touches on a couple of the topics we've we've already talked about.

4:16We talked about champions last time around, which is really important because

4:19Your champions uh are most often actually tasked with this with this job of um you know thinking about design in analytics and so behavioral design would naturally fall into their their play uh sort of unknowingly in most cases

4:33And then the other side of this is obviously Viz literacy, which we've also talked about previously.

4:38It goes back to how how do people understand and interact with what they've been doing.

4:43presented with.

4:44Yeah.

4:44Yeah.

4:45And it's uh the the other the other stuff it's this sort of branches out into is um just just about I I want to say just about everything, but I'm going to call out two of the specific ones.

4:53First is like

4:54general user interface, so UX design.

4:57Uh and then the second is gaming.

4:59So for example, for user interface design, you can think about Tinder, for example, completely disrupted the dating game with an app because it was a simple

5:08um application which allowed you to swipe left or right like based on what you wanted and it was just a really simple here's your instructions here's your queue

5:17Do this, do this, and your reward is if someone likes you they'll pop up otherwise they they they're gone forever, basically, right?

5:24Um similarly, like if we think about the addictive social media applications, the reason these things are addictive

5:30is that they're designed in a certain way to either by algorithm or by visual design, all of these different things, to make sure that you keep on scrolling, right?

5:39Keep on scrolling past those adverts.

5:41Keep on

5:42being a consumer and in this world.

5:44And uh I mentioned with with that Tinder example, I mentioned the three steps and that comes down to this car model.

5:50Um it seems to pop up everywhere.

5:52It seems to pop up everywhere.

5:53Like I can't exactly find

5:55where it originated from.

5:57I found like The Power of Habit, which is quite a famous book for people that are looking for self-help, then like looking to

6:03do life improvements.

6:05Um but also in the in this um website that I love it's called boundlessdesign.

6:09ai they talk about this Q action reward and this can relate to a lot of different things and

6:17It like for example in retail when you're you I think this this is one of your specialist subjects Tim like when you're looking at um promotions and pricing um where things are placed like the gondola stand the uh ends stand

6:30Yeah, yeah.

6:30Where it is or in relation to like uh higher level or lower level.

6:34Uh these are all paid for because the retailers know that that that

6:39Positioning that design choice to put a product, to put a promotion at a certain place is more likely to drive a reward

6:47Right.

6:48Or do they?

6:49Right, exactly.

6:50That's another It's kind of half my what half my uh work has been actually.

6:54Um actually understanding, you know, do those behaviors actually materialize or are there other mechanics

7:00um sort of at work.

7:01Um and it's actually quite a common uh common challenge, whether it's to do with promotions or it's to do with uh sort of long long held myths about uh how certain uh behaviors manifest and

7:14in consumers or even at work, right?

7:16Mm-hmm.

7:16Yeah, exactly.

7:17Um like for for example, if you think about gaming, um I I've ri I saw this really great video about Fortnite, the the famous game where everyone learned to dab and floss, right?

7:28Um but in in this video the one of the designers talked about how they created and came up with the concept of Fortnite which made it easy and repetitive.

7:37Um and and in particular one of the things that interested me was like the design of the the HUD or the heads-up display, which is basically in our terms a dashboard

7:46'Cause if we go back to the term of what a dashboard is, you think of cars and a car dashboard gives the information at your fingertips, right?

7:54That's what we see as a dashboard, and then perhaps we can even link that back to what we do as a day job break term.

7:59Yeah, exactly, exactly.

8:00Uh uh I think um we we touched on this topic.

8:03There's actually a really good episode uh called the Dashboard Conspiracy.

8:07Uh

8:07It's uh Data Stories uh podcast episode one three five.

8:11It's actually a really good one.

8:12They go deep into the question of what is a dashboard.

8:14Yeah.

8:15Um which we won't do now, but it it it touches on a really interesting sort

8:19sort of thing about expectations and um behavior because in many ways uh what people call a dashboard is irrelevant.

8:27What is relevant is how they then end up using it and how they end up consuming the content.

8:32And in in your example with Fortnite, they managed to build something that could easily be consumed by a wide range of people.

8:39And it m and it's it's it's a mechanic that makes playing the game much, much

8:43much much more enjoyable, which uh I think in the car model is called a reward, right?

8:47Exactly, exactly.

8:48So the the the the cue would be that everyone's talking about it, the action would be you actually start playing it and the reward is

8:54You you kind of it it's just a simple game to just pick up and play, right?

8:57That that's the thing.

8:58Like um we'll talk about another example of it within gaming later on the podcast, but like with Fortnite, I think that the easiest thing is like it's just

9:05If you're gonna pay for more stuff, it's not gonna improve your gaming, but Exactly it's like suddenly people want the all these different dance moves, they all want the different kit, all this different stuff.

9:15just because they want to look good while playing it.

9:17But the actual game itself for everyone is the same, exact same thing.

9:21Um, which reduces the overhead.

9:23But th this isn't a gaming UX podcast.

9:25We're talking about behavioral design and analytics specifically

9:28Um Exactly.

9:29And I and I I think before we dive into it deep we go in hard.

9:33I think it's it's a really interesting thing because I

9:36I I I maybe I'm I'm I'm misspeaking here, but I get the sense that this is actually a new concept in analytics in the traditional

9:44i.

9:44e.

9:45in organizations.

9:45I don't think it's a new concept in uh app design or gaming or any of these sort of um uh you know industries which have actually had analytics embedded in them by the nature of what they do.

9:58Um

9:58uh per se.

9:59But if you think about uh you know users of Power BI, Tableau, ClickView, whatever, um we've we've had this term

10:07dashboards sort of thrown at us without much real conceptualization of what actually sits underneath that and when we when we build those dashboards when we build those views whatever you want to call them um

10:20w do we think about behavior as we do that?

10:22And I think it, you know, I said it we touch on visual literacy.

10:26Part of that is obviously, you know, building things that are easy to consume.

10:30But the other part of it, which we don't often think about, is

10:33is sort of the the end result.

10:35So once a users use something, do they do they what is their reward?

10:39What what is the benefit?

10:40Did it help them get to where they needed to go?

10:43And I think this is a very new area in analytics, which

10:46Um I think there are very few people who understand it to be brutally honest.

10:49I I I can't I couldn't easily find papers on the topic, but I think a lot of people would claim to touch

10:55uh on this topic in sort of one way or form.

10:57But I I also think they do, right?

10:58I think th that they absolutely do, but they just don't realise it in an explicit way.

11:02Like they won't say adding an eye icon to s find information or highlighting a text bit in red is is a nudge or

11:10intentional behavioral design, but it's something that it's almost like um uh in in good rati you have this term power of fashion

11:17Um you're literally parroting what someone else has done because you know it works.

11:21Like it's a tried and tested method, so therefore you're doing it.

11:24You're not thinking about why you're doing it.

11:26But I think the the nice thing about this in in how I I agree it has come out very recently

11:31Um it's one of these cool things that's like the cross subject area um thing, right?

11:38Because what what's interesting about this sort of thing is like

11:41Well if we think about photography, that that was a thing for a while in in visualizations, like everyone's thinking about a visualization in the same terms that think about photography with the nine segments, right?

11:51With with the foreground, background sort of relationship and all of these different things.

11:55Yeah, I agree, I agree.

11:56And I I think if you think about um companies like Tableau and um Power BI and um these companies that sell products off the back of an idea that this idea is that

12:09um you know analytics is accessible through uh sort of views or portals or you know call it portal if you think about things like tableau server um

12:19uh they've sort of built multi-billion dollar industries that's not well understood.

12:26And uh we're still kind of figuring it out to be briefly honest.

12:29I think if you look in the Tableau community, at least which we we know quite well

12:33Um, you know, people are still figuring out things.

12:35You know, new features come out and it changes the whole sort of paradigm of of of expectations.

12:41And yet this is a very I know visualization is a very well-known topic, you know, people are

12:46Like uh uh Thomas uh Edward Tuft.

12:48Is that Tufty?

12:50Tufty and um Stephen Fuch.

12:53Stephen Fu.

12:54I was about to say Stephen Tuft

12:57Unholy comparison, yeah.

12:58Oh wow, that would have been uh that would have gone down like a bomb.

13:01Um but yeah, uh you know these guys have been talking about this for a long time.

13:04Stephen Few will will probably have a very academic understanding of what a dashboard is

13:09Um would he agree with David McCannby's?

13:12Probably not.

13:12Yeah.

13:13But would um the users we build dashboards uh for call them both dashboards?

13:17Yes.

13:17Yeah.

13:18Right.

13:18And so that's a very interesting

13:20Now w what I I like about that sort of thing is the the concepts introduced by Tufty, by Few, by Cairo, you know, the the sort of the people we see as the godfathers of data visualization.

13:32Um a lot of those concepts are now almost outdated because the way we consume information has changed, right?

13:37Yeah, it has, it has.

13:38Because like if you think about the way we consume news, like articles now no longer you you're less likely to see a chart in a in a newspaper

13:45like physical newspaper now than you are on a image, on social media, on a website, on on a screen, right?

13:52You're more likely to see that.

13:54So perhaps again this is a completely different episode where we sort of tear apart the idea or dashboard.

13:59But it's it's less about the dashboard, it's more about like wha why why are we consuming information in this way and

14:08If we are, i are we getting the right information out.

14:10Now, for example, this isn't a dashboard, but I wrote an article about um scatterplots and a couple of people on football Twitter were

14:18writing creating these long elongated rectangular scatter plots and I was like this is just misinformation.

14:23Now I wrote this blog post and it's funny like a couple of feedback I got was really good article

14:29I learn a lot but I couldn't tell you what I learned.

14:31I was like, oh man, that's like a failure.

14:33Yeah, I've not conveyed the information.

14:35I've not taught the people anything

14:37It's yeah, and and this is this is really important because I think going back to you know our champions and so on, uh I think we think we're all doing a great job.

14:46We think we are uh, you know, absolute stewards, you know

14:49Uh doing the best we possibly can, um very well studied, you know, certified on complete information.

14:55Yes, yeah, exactly

14:57Um, but actually uh when I was digging into the sort of underpinnings of behavioural design, it was actually uh alarming h how little of this I know that I I actually apply and I want to start applying be

15:10Because when you think about it, it actually makes sense.

15:12It's very easy to sort of understand why people respond the way they do.

15:17So um maybe let's just uh touch on the underpinnings of it um by um

15:22uh in you know boundless ai have kind of put out in their document.

15:25Mm-hmm.

15:25So I think the first one, like the the the the the key one for me at least is the framework, right?

15:31Okay.

15:31The way we actually set this out and the way we actually come to an idea of what we're gonna create and and w how we're gonna

15:39sort of subvert that and sort of tweak it to make sure that the audience and the idea we're trying to put across is put across.

15:47Right

15:47Yeah.

15:47That that comes from the framework.

15:49We need to understand everything that there is from start to finish and we need to understand the the impact and the reaction people have to the the the set of information we're presenting.

15:58Right, right.

15:59And it's it's actually really important because that that frameworks forms the um it's sort of the catalyst for sort of everything else that comes along, right?

16:08Um

16:08And you without without that framework or without that direction, you don't really have any solid sort of basis to to put things forward to people, even try and persuade them.

16:17Right, exactly.

16:19Um I think the next one's about uh being deliberate, right?

16:23So I I find this uh it's quite it's not alarming, but it's so obvious, but it's obviously needs highlighting because it doesn't happen.

16:31And um occasionally I think people actually do uh want to be deliberate with their dashboard designs.

16:38The whole reason you build things is to to change behavior, you know.

16:41um to make an impact by people.

16:44Yeah, make an impact.

16:45But here what we're really talking about is actually something even more subtle than that, which isn't just making an impact, i.

16:51e.

16:51people walk away understanding your message.

16:53It's actually about making impact about the way the user uses your content, right?

16:58Yeah, it's directing almost.

16:59Uh you're meeting you're giving them a direction to follow in order to act off the information you've given them.

17:06Now

17:06Uh I quite like this one mainly because it's it c it harks back to a lot of the the sort of client people but people who are working in in sort of

17:16design of any sort of visualization or product that is UX based.

17:20Like I I think um if people if you haven't seen it, there's a great little article about like

17:25um speed versus qu uh quality, right?

17:28There's a horse that's half done.

17:30Like the bottom half is a fantastically shaded, contoured horse, and the second is like a child's drawing, right?

17:37Now

17:38That's important because I think that that touches on like the fact that we are so driven by stakeholders.

17:43Right.

17:43Right.

17:44And that that defines what we are allowed to be deliberate with.

17:48In many ways.

17:51the context kind of probably more often than not constricts what you can be deliberate with.

17:55And so you you're basically left with very little that you can actually have an impact and change with Yeah, exactly.

18:01Exactly.

18:02It's a

18:02Uh goes back to the the the the model we spoke about last week.

18:06Um I remember seeing a viz um on the tableau uh public gallery.

18:11I'm just I'm just scrolling the homepage now to try and hopefully find it before

18:15Um if we try and fill the air while I do this, I can't find it.

18:19I think it's moved moved links.

18:21But the point I was going to make was about um, you know, we if I take um in the Tableau world as this um

18:27competition called Ironviz.

18:29And this is a uh for people who don't know what it is, it's like a competition.

18:33Um is it a competition even?

18:35I don't know.

18:35It's it's kind of like um it's kind of like um I don't know how to describe this.

18:41uh to non tableau people.

18:43It's it's it's really difficult to to explain.

18:45But essentially they are feed arounds where people submit a vision

18:50Some judges select visas that are sort of best of the crop.

18:54Each round has a theme, so it might be, for example,

18:57quantified self, one theme, another one might be healthcare.

19:00Agriculture.

19:00And then the winner of each theme gets to go to uh the Tableau conference.

19:05Uh this year it's in Las Vegas and on on a stage in front of uh

19:10uh I don't know how many thousand people actually turn up.

19:12Um uh there's a competition and they have to build a viz.

19:16Now in reality they don't build it for the first time there.

19:19They've seen the data before, they get to practice it.

19:21It's kind of very well orchestrated to to sort of help showcase the product as it were.

19:27But the point I'm trying to make here is that um a lot of the sort of uh entries into this

19:34into this thing um aren't aren't very deliberate about their design.

19:38They kind of missed the point.

19:40And they they they showcase more skill than actual um

19:46you know, sort of deliberate design in in the sense that they don't necessarily make the user sort of um interact with the content in a way that leads them to sort of a better

19:57better understanding.

19:57It's more often than not you just get techniques that are being um pushed around.

20:02The most the the the one that always sticks out to me is anywhere I see a Sankey diagram.

20:07Well anything curvy, right?

20:08Anything curvy.

20:09Yeah.

20:10Well no, just the Sanky diagram is particular.

20:12I'm not I'm not going in on this chart just because I I don't like this sh

20:16It's just you always see it used when there's a flow of data from one place to the next, right?

20:21And it's as if there's no other simpler way that people just understand and can can see immediately.

20:27um that that can you can do it.

20:29You could even have like, for example, a tree diagram, which is much, much simpler.

20:33Equally technically difficult to do, but people don't seem to like want to kind of, you know

20:38um you know work with that and even set actions for example allow you to do interactions that show you how things go from one part to the next part.

20:45I think Bethany Lyons calls it

20:47proportional brushing.

20:48Yeah.

20:48Yeah.

20:49Those are more deliberate attempts to me than than than some of the sort of techniques you tend to see which are quite design centric.

20:55And

20:55Um in that sense.

20:56But I mean that's a massive tangent on deliberate design.

20:59But I I I I think I think you make some really good points there though.

21:02Like for example, like one of the I wrote a blog a few

21:06a y couple of years ago now about long form, right?

21:08Land long form as a almost a cheat because I always said like if you're creating a long form visitation, it's almost like okay, I've got my first screen display of information, but I've just run out of space.

21:21So let me add on a hundred, two hundred, three hundred pixels and keep making this longer or wider or bigger until I can fit all the charts, all the images, all the text on this, and suddenly it's storytelling.

21:32Right.

21:33Um and I'll I'm just like

21:35I'd rather I don't know it's it's sort of a like I think this comes back to the the modern day method of interact interacting with stuff, right?

21:44A long-form visualization as that allows you to follow that very traditional mobile level interaction with the visualization, right?

21:52Or an image.

21:53You're able to double tap into it, fills your screen, and then you swipe until you while you're consuming the information.

21:59Again.

21:59Yeah, exactly.

22:00Yeah.

22:00Again.

22:08Through formatting, through di deliberate design choice, through arrangement.

22:13But in terms of I don't know, I I feel like no one no one actively starts off with a canvas that's uh four hundred pixels wide and t two thousand pixels long.

22:22Right.

22:23But you don't start with that.

22:24You always end up with that.

22:26Exactly, exactly.

22:27And it's it's interesting because um the other thing is that i y it's it's very easy as the build of a dashboard to sort of get that get caught in in in in the uh excitement as it were if I

22:40say that if I say that rightly, right?

22:42Um there comes a point where uh and and it this actually does happen a lot in the business context where you're having to prove your skills as much as you are

22:50um, you know, fulfill a need for the business.

22:53So uh, you know, when you start off building a dashboard, especially if you're new and you're new to Tableau, um

22:59Let's be honest, the sort of the first examples of your work are actually just you proving a point, uh proving proving that you've got the ability to do something.

23:07And so those two things can very easily kind of get

23:15So this this idea that behavioral design is actually scientific field.

23:19Um

23:20And I think it's been made largely scientific because of the way that um our devices work today, you know.

23:26If I fast forward um

23:29uh a decade let's say I was listening to a podcast about um uh the way that the n uh internet has changed the way people interact and the analogy they gave is this

23:39Um you you've probably uh you know heard of flat earthers, right?

23:42So people think the world is flat, right?

23:45Now um imagine you walk past uh flat earther in the street a decade ago, right?

23:50You you you just walk past them and

23:52you'd you know, because you believe uh s of science, you believe their facts and you'd know the facts, but you don't necessarily stop to want to change that person's opinion, right?

24:00You just sort of let them get on with the day and you know, just walk on by.

24:04And maybe hundreds of other people do the same thing.

24:07Okay.

24:08Now in that in that one day, one person might stop to talk to them.

24:11And so if you were to do a straw pole, you'd say, okay, one in 2,000 people stopped

24:16To talk to this person.

24:17And so you probably think they're just, you know, the village loony or whatever you want to say.

24:21Okay.

24:22Now, here comes the internet.

24:24Okay.

24:25And the digital equivalent of this is that this one person is now talking to

24:29six billion people.

24:30Okay.

24:31So if you do one in two thousand of six billion people, you actually have quite a big critical mass, right?

24:36Correct.

24:37Whereas before whereas before you, you know, this this person was preaching to no one.

24:41Now he's suddenly speaking to an audience of

24:43of millions of people.

24:44Yeah.

24:46If anyone's if anyone's had a tweet go viral, the amount of your DMs blow up with like a couple of hundred people replying.

24:53But like imagine just on the scale of you know like you that there's there's a concept of the ratio on Twitter, right?

24:59When there's very few likes and retweets but like thousands of replies.

25:03Yeah.

25:04Yeah, exactly, exactly.

25:05And so

25:06I the nature of devices today is meant that we can measure all these interactions that are happening between people and they're amplified even larger.

25:15And so when they're amplified this way, we can even home in on what used to be really niche aspects

25:20of the way that um you know people work in the workplace or the communities consume information data.

25:27And so behavioral design has had a kind of had this sort of data driven injection and energy

25:32Um combined with um things like neural analysis and and behavioral analysis, uh the psychological and data science kind of melding part of

25:44Yeah.

25:44And I th I think th there's also the anthropological sense, right?

25:47And I think the the the point you make about the velocity of information is so important here.

25:52Like that that's why this this is why academics are focusing on this sort of thing.

25:56This is why uh when we think about systematic scientific design as a as a part of behavioral design.

26:03um that they're there homing in on it as these concepts that they can apply and sort of spot in nature a bit more, right?

26:10Or spot in human behavior a bit more

26:12And what's important is what they're they then are able to see is those levers, th those levers that you can pull on and start working with to actually change that behavior.

26:22Exactly.

26:22And this is kind of how the car model has actually come about, right?

26:25Because people have have built very sort of nice, clear understanding of you know, at a high level, we're we're not talking about if you dangle a carrot this

26:33is what will happen.

26:34We're talking about understanding exactly what people consider rewards to be, uh behavior to be, and habits to be, and being able to repetitively prove this sort of

26:45um interaction, right, and this cycle of behavior.

26:48Because ultimately we're trying to bring about change, which is actually the next point.

26:53Exactly.

26:54And and that that's that's where we come back to this positive point.

26:56This is the the thing that we it all our the best intentions of behavioral design

27:01should and lar by and by and large are to drive positive change.

27:05For example, the most like the one that I quote the most is probably about um drug the driving license in the UK.

27:11Um, you know, the fact that you're nudged to become a Blug and Order donor used to be opt-in, now it's opt out, so you're m less likely to think, hang on, I'm gonna opt out and not give blood away.

27:21I'm not gonna get share my organs once I've passed on.

27:24Um and that's a positive change, right?

27:26Things like look left on the on the street, that's a positive change to make sure that you are doing that thing.

27:31Mm-hmm.

27:32Yeah, exactly.

27:33Exactly.

27:34Um and and you know the the last thing here is is that um the environment and and it's so important.

27:41We talked about environment last week, how you know the same person in two environments um you know, last week, a couple of weeks ago

27:48even um the same person in different environments won't necessarily achieve the same outcome yeah uh because environment is so important it's fluid i exactly exactly and so the the biggest Achilles heel actually in this whole topic is

28:01uh misunderstanding your environment because you could you could have all the sort of you know good intentions and and direction and you know philosophy around this.

28:09But by not understanding your environment and and fundamentally not picking your moment and or people carefully, you can very easily find yourself sort of uh

28:17um n not actually having the successes you'd want and kind of misunderstanding people's behavior and then this can come back to bite you when we start to talk about uh uh sort of the ethical side of

28:28this because at the end of the day you are you're turning people's behaviors into a science and when you start to do that you start to play with something called trust and yeah and uh uh and when people trust uh when people start to trust your product

28:41And I'll talk about it as a product.

28:44And so when you start to talk about trust, you know, you know, people put people look at what you're doing as a product.

28:50product and when you start to sort of tweak with the way people behave and you start to do it in a scientific way, ethics start to play a really, really important part of this.

29:00Um one of the things I've I've talked about in the past when we talk about design is user experience, and I think this is where ethics kind of melds nicely with with

29:10What we're talking about.

29:11Um, and uh in a talk I gave I talked about uh a concept which is the levels of user experience.

29:18And it what we're really talking about is sort of something similar to Masro's higher hierarchy of needs, right?

29:23But

29:23but for user experience.

29:25And it starts off at the very bottom with uh safety.

29:28So fundamentally, um, you know, when someone starts using your analytics tool, they talk about um you know

29:34No, th they think about, sorry, uh whether this product sort of conveys safety.

29:39Does it convey trust?

29:41Is it um you know

29:42follow the brand guidelines?

29:44Is it something familiar?

29:45Is the data correct?

29:46And at the very fundamental level, if you don't get this right, people won't even go to the next question.

29:51which is it is it useful?

29:52Is it better than what I had before?

29:53Yeah.

29:55Before you move on, sir, I think I I think reputation comes into this massively.

29:58Because you you have a reputation

30:00Before you go in anyway, like this is the way we talk about like the f whole thing you taught as a kid about first impressions.

30:06That's where the reputation begins.

30:08Exactly and and if you've got a reputation or an inkling that you're not a safe safe product or brand

30:15Yeah.

30:16You don't want utility at all.

30:18Exactly.

30:19And in fact, people start to misconstrue your product as dangerous and they don't want to be

30:23Associated with it.

30:23I've s I've so many times.

30:25Self-driving cars ring a bell?

30:27Yeah.

30:27Exactly, exactly.

30:28They're actually safer than people, but

30:30uh the level, the bar of safety that they have to pass is much higher because there's no human being in them, right?

30:35Yeah.

30:36Um and so it's funny, I've been in so many analytics projects where, you know, with all good intentions, we followed the guidelines as, you know, uh

30:44as we were told we've been given the data by the business but because we can't reach the same level of certainty as the business had with their existing tool.

30:52It's just so difficult to get any sort of sentences anything else because the first thing people ask is is is the data correct?

30:58Is it right?

30:59And even if you prefess it with the data isn't right, but what we want you to do is look and see if you like

31:04like this format just so we can get past the format issue.

31:07Yeah we actually know what we need to build.

31:10And it's just impossible.

31:11I I th I think people all struggle.

31:13Well my my first my first role

31:15uh in my in my first placement at the daily school was um with a guy named Ben Strauss who's a fantastic manager to work for.

31:22And whenever a a a consultant we were working with said, I'd like to use dummy data for this

31:27Ben was like, I've got cold to it, do not say that word to me again.

31:30I was like, oh so I I sort of inquired like I was like dummy data makes sense, you know, you're using a rough data set and it's the numbers might not be right, but it gives you a flavor

31:37Yeah.

31:38But but the the key thing comes down to fundamentally people focus on the numbers than the design or than the product itself.

31:47Yeah, because that's where the reputation and safety is, right?

31:50And then, you know, if the numbers are correct, then the next thing you go to is utility.

31:54You know, does it actually do the job it's supposed to?

31:56And actually this is very quick and easy to evaluate.

31:58Because people don't get stuck on this.

32:00What people get stuck on next is is it effective?

32:03You know.

32:03Um, you know, you've gone through all this effort to give me something, uh, but is it actually better than what I had before?

32:09And if the answer is yes, then the next thing they default.

32:12is okay well fine.

32:14Um it's it's it's effective, it's it's it's you know the numbers are right, I can use it.

32:19Um is it efficient?

32:20Uh I don't know, you know I have to put in lots of stuff in

32:26Yeah, exactly.

32:27We're gonna have to outsource this ETL workflow.

32:29Uh I don't know, is that really more efficient than what we were doing before with Excel?

32:33files.

32:34Um and you know if you manage to overcome that hurdle, right, and the business all in, then it goes back to satisfaction.

32:41And this is the thing, this is the stickiest, this is the stickiest thing ever

32:45Because I've seen dashboards that do all the previous four things.

32:48Efficient, effective, well utilized, you know, very, very correct numbers.

32:53But

32:53Because people don't get the satisfaction.

32:56And by satisfaction I don't mean, you know, uh does it does it do something for them?

33:00I I I'm simply talking about their own sort of um personal development.

33:05Does it does it propel me forward in my career?

33:08Does it enable me to do something?

33:09What other questions can I ask of this data, right?

33:12Um and so you've delivered what they've asked for, but they're already thinking about the next step.

33:16And that's what they consider is

33:18uh satisfaction and it's only when you sort of go one step back and what you offer people is here here's a an analytic suite of products

33:26Can you then start to talk about, you know, fulfillment, which is, you know, this is fun, this is enjoyable.

33:31I really like using this.

33:32It helps me with my job and my work.

33:34I can

33:34see the numbers, it's timely, it's efficient, it's organized, it's safe.

33:38That is when you sort of reach the full circle.

33:40And that is so hard.

33:41So hard is never done with one tool.

33:42No, and I think that that self-fulfillment, I think the the only thing I can think of, the only concrete example I can think of where

33:48you'll ever get to that is if the CEO of the company right at the top, the person who owns everything, you know, the the big, big, big boss, if he's like, I like this

33:57then suddenly it f it's self fulfilling because it's like, oh yes, I've finally succeeded.

34:01Like it's never about the fact like it's never about intrinsic well in intrinsic support and in like your your own

34:08uh personal enjoyment, right?

34:10It's all about everything that you're almost showered upon you.

34:13Like that that satisfaction.

34:15Yeah, yeah, because if you were to take this to any other industry

34:17Let's say artist or musician.

34:19Um, self-fulfill fulfillment would be about expression and being understood, right?

34:23It's completely an art form, it's a completely different thing.

34:26Whereas you you go to work and actually self-fulfillment is a completely different

34:31sort of career oriented uh uh sort of high level thing.

34:35And um yeah, I'm not gonna go into sort of the psychology of this now or into other topics at this

34:40Right.

34:41Um but going back to ethics, it's so important you keep those factors in mind because as soon as you start to sort of

34:53And the ethics of the way that you're sort of handling the tool start to come into question.

34:58A good example is

34:59Tableau server has a Postgres database.

35:02This Postgres database collects analytics about which data sources, views are being used, when they're being used, who

35:08the authors are uh down to an email level so you could essentially see how often someone sees a dashboard and I always love people's reaction

35:17When I highlight that you can build a dashboard that shows their usage of a dashboard, right?

35:23Yeah.

35:24And it's and it's it's one of those things where no one will ever openly go

35:28I don't like that.

35:29But you can see that exact reaction.

35:31They start to pale.

35:35Yeah.

35:35They sort of s and scribble something down.

35:38And I don't think it's because of fear that, you know, s they're gonna be found out.

35:41I think it's it's 'cause fear of the opposite thing, which is here we are asking for something and for the

35:46the first time actually someone's going to be able to look and see how we use this thing.

35:51And it's a very, it's a very sort of interesting tool.

35:54And

35:54I think when you think about ethics, it goes back to things like that.

35:57You don't want to turn into a nanny state where you're sending out an email going, oh, uh top user was X, bottom user was

36:04was this, you know?

36:04You sort of you you need to be using that data at a high level, not really using it as like a whip as such, but more as a way of understanding behavior and trying to

36:13sort of say, well, hey, we've got this group of users who have access to the server, but they're not engaging with the content.

36:19Why is that?

36:20Not to go to them and say, why aren't you using it, but to to go to them and say, hey, how could we help you use

36:26So would that be like some sort of incentive or reward for using it, would you say?

36:30That's a that's a tough one because incentives and rewards aren't the same thing.

36:33I mean businesses are A-class examples of business.

36:38Right.

36:39I think a r a reward in the car model as I see it is uh is not necessarily even an incentive.

36:45It's

36:45Um, you know, I think we probably think of rewards in uh this particular use case as uh let's take something like, oh, the top user gets you know five pound Amazon voucher, right?

36:54Yeah.

36:55That's not a reward because

36:57Uh a reward is something where the expectation of what you get is lower than what you actually receive.

37:03Okay.

37:04So the very simple terms.

37:06If I uh uh if I'm the top user of an analytics

37:09And I get an email from the head of business intelligence saying, well done, you are the uh most frequent user.

37:15And then he sends us a t-shirt or something that I actually value.

37:18Um, even if I don't like the thing he sends me or she sends me, um that

37:22That is a reward because it's surprise.

37:24I wasn't expecting it.

37:25Now, if I then end up being the top user every single month, it stops becoming a reward and it starts to become an

37:32Expectation.

37:33Okay.

37:33And too many times businesses get it stuck in this way of describing rewards, which means that um you know they're not fluid, they don't move with the organization.

37:42After a while, they become an expectation

37:45Correct.

37:46Right.

37:46Whereas an incentive's more like um you're gonna get something if you do this today

37:53in five months time, if you get three more people, you get X, Y, and Z, right?

37:58It's sort of like delayed action.

38:00I think the the the other game I was gonna mention in in this sort of area about rewards is Flappy Bird.

38:05Do you remember that?

38:06Yeah dude.

38:09Yeah right.

38:10Flappy Bird was that that that weird game that had like two weeks of uh fame and then the guy like shut it down because he was like, I can't make money off like people being idiots

38:19Um because it was such like a basic game.

38:22It was it was if you don't remember this, this is a game where you tap it's like th that old helicopter game used to I I played in high school.

38:28or primary school.

38:29We like click.

38:30I put a link in the show notes.

38:31It's still on the App Store.

38:32Right, okay.

38:33So basically you hold down your you tap the phone and hold it down to make the bird go up and you have to dodge all the obstacles.

38:38Basically right.

38:40Now ev no one could get past like ten on Flappy Bird.

38:45Like you can't you could pass ten obstacles.

38:47Everyone getting stuck, right?

38:49And

38:50It's like that short-term intention basically it's like you it's a really simple game the concept's easy right that's your cue the action you do you you tap to make the bird fly up and down great the reward is a high score

39:04Now th the key thing here is that there's a shallow learning curve and there's instant gratification, right?

39:10Like th the the more you do it again, this comes back to Fortnite.

39:13It's a very shallow learning curve.

39:14It's a um it's a first-person shooter.

39:16You you basically don't

39:18trying not to die.

39:19Um I just died Ravi.

39:21I just died.

39:22I got I got past T.

39:23Right, exactly, right, exactly.

39:25And and this was just like because it's such a short, sharp game, you can just pick up and play

39:30Right.

39:30Like you've got that two minute gap when you're waiting for something, you'll just fire up Flappy Bird and play that.

39:35Or whatever.

39:35Fortnite's different because it's like a 20, 30, 40 minute game you actually end up playing.

39:40But that that sort of um Q action reward, the C A R model that we keep referring to, that that the aspect of the shadow learning curve and the instant gratification

39:49D does that sound familiar to you, Tim?

39:51Like that's exactly why we love Tableau.

39:53That's exactly why we love it.

39:55Because it's easy to pick up.

39:56You've got instant gratification in the building of the charts and the dashboards.

40:00But it's that cycle and the process that really helps drive that ethical the ethical thing because if you're able to control that and give that power back to the user

40:09And be very transparent with exactly what you're trying to do and that's obvious to the user as well, isn't it?

40:14Quite a simple thing to understand, then boom, you're you're onto a winner.

40:18Exactly.

40:19Exactly.

40:20Exactly.

40:20And it's it's so it's so um it's such a tough thing to do.

40:25I I think this is why this area needs more more research because um

40:30First of all, I think as we say organizations are different.

40:32But then secondly, I think um the way companies are set up to handle this.

40:37I mean analytics teams are by no means behavioral experts and actually

40:42What we're talking about here is a field that needs uh behavioral experts.

40:46You probably need quants as well, people who can get into the numbers and understand sort of what's going on.

40:52You need um data scientists to sort of take some of that behavior and start standardizing it um and and and try and sort of run a different type of analysis onto it.

41:00you can maybe hope to be a little bit more predictive about sort of where you're heading.

41:04And then the final aspect is obviously leadership because once you start to see these behaviors, there's the there's sort of the leadership bit, which is, well, do you want these behaviors to persist or do you not want them?

41:15to possess right there's sort of so many different sort of caveats to this and when you start tweaking these things it's a bit like an F1 car Formula One car and

41:24You know, the smallest tweak over here to the suspension can change the the level of wear and tear on your tires, which means that you have to do an extra pit stop which cuts you 20 seconds, which means that you finish uh 10 seconds behind the leader rather

41:37than f five seconds ahead, right?

41:39Yeah.

41:39Um and it's it's that kind of fine tuning that you start to really kind of get in line with once you understand the sort of the way these things work.

41:47Cool.

41:47Yeah.

41:48So the what's the now what then?

41:50What's our what's our the like takeaway for our listeners?

41:53I guess I guess if we start at the basics, alright.

41:55So

41:56I I I think I wanna emphasize this point very very hard and that is whatever you're building the product uh is is is the most important

42:04thing.

42:04So if it's an analytics product um and you set out to uh have a dashboard that um does X is the most important thing and keeping a focus that is the most important

42:15important thing because if you have a process which is led by anything else other than the goal, then you start to have sort of very unhealthy dynamics influencing

42:24influencing some of what we've talked about, especially behavioral design, right?

42:28Because um if I take a simple example, so often we build dashboards.

42:33and we get to sort of nearly going live and then marketing get in gets involved.

42:38And uh and I I don't mean marketing as in marketing the profession.

42:41I mean marketing as in

42:43um the the the manager or the lead of something in a certain way and wants a certain label here and the delivery.

42:53Exactly, exactly.

42:54The owner, that's the one the product owner as they'd call them in

42:57the agile methodology.

43:00Yeah, they that you know marketing starts to drive what the tool is and then you start loading your dashboard with all these things that it doesn't need and then the user gets it and then

43:10And they're like, oh my god, there's so much it again this comes back to the deliberate design.

43:14Yeah, exactly, exactly.

43:15You know, product must come first.

43:18Um and everything else comes after.

43:20Understand how habits work in your organization.

43:23I think this really does depend on organization.

43:26organization to organization, especially if you have a culture of analytics already.

43:30I think if you took someone from uh a startup sort of analytics team and you put them into uh an analytics team for a company that's been running for

43:38for the last hundred years, it'd be a very different sort of way of working.

43:42Um very different.

43:43And I think you it vastly sort of grain um uh

43:46sorry, go against the grain in that sense.

43:48Um tracking is absolutely essential.

43:51You need to track whatever you consider as engagement metric.

43:56It's interesting because I think people just track every metric under the sun.

43:59I think it's also identifying those success metrics.

44:02Like what is your actual metric that you're driving for that success, right?

44:07Yeah, exactly.

44:07I mean, is it just people turning up to the Viz?

44:10Or is it people returning to the Viz time and time again?

44:12Or is it people sending you emails to say, hey, I used this once, but it was great.

44:16Thank you very much.

44:16Goodbye.

44:17How can I export it?

44:18Um, you know.

44:22Um, you know, uh the there's so much there that is is funny.

44:26Uh on that export thing, I think

44:28People asking, I I love that as an example because it's just the one that comes up time and time again.

44:34You build uh what you think is a great dashboard.

44:37Um it's hard to say if it is or not.

44:39Uh you deliver it and then someone uses it and says, This is great, this is really fast, I love it.

44:45How can I export the data?

44:47Yeah.

44:47And that question drives home on two levels.

44:50It it drives home on one point, which is you misunderstood their need.

44:54Like just because they want to export doesn't mean they're wrong.

44:57Yeah.

44:59But but but the other thing other flip side is when someone picks up a dashboard and you've got like a big thing front and center, but the what they're really interested in

45:07is that tiny chart on the bottom left.

45:09Right.

45:09Yes.

45:10That's exactly the that's exactly the same.

45:12It's like you've missed the point because what the users really wanted was that bottom left chart.

45:16Not not this thing that you personally find interesting.

45:19Exactly.

45:20And so it's really interesting because so many people sort of critique that.

45:25Oh, why do you want an export?

45:26Look at this wonderful viz and stuff.

45:28And it's like, no no no, but you missed complete you entirely missed the point because what they gave you was an expression.

45:33You asked them what they wanted and they told you what they wanted.

45:36They told you literally exactly what they wanted.

45:38But uh if if if uh you know if you went back into the golden ages and said uh I want a faster horse

45:45A car would not have turned up, right?

45:46Yeah, right, exactly.

45:47That's that's the old Henry Ford example, right?

45:50Exactly, exactly.

45:51And so

45:53uh you know w we we kind of bang our heads on the table when when users do things we don't like with them but actually we've got to start learning to listen to that behavior and say okay you want an export okay let's see what happens when you do an

46:05export let's see where you come from here yes absolutely and and and uh you know in in if I take a very simple example in a taboo well it's uh I wouldn't actually give you an export what I'd say to you was you know instead of an export why don't you have access to

46:18this way of building your own dashboard so you can build your own views because the reason you want an export so you can go to Excel.

46:23So why don't I make that easier for you?

46:24Yeah and make it easier for you to build stuff.

46:26Here's a data source rather than

46:31Yeah, no, it could be good.

46:32Yeah, I I was gonna say this might be preempting what you're gonna say, but the other thing is people wanna see that raw number and they want to do that quick calculation themselves for their own sanity.

46:40Um exactly, just to check.

46:42Exactly.

46:42Now I think what you're saying there about you teach them, right?

46:47You teach them how to change it.

46:48You say, what are you doing?

46:50Let me help you.

46:51That thing is so important.

46:52Like that is where you create new habits.

46:55That is where you can create this new culture.

46:57The stuff we talked about last in the last episode about champions.

47:00Right.

47:00Right.

47:01This is how you

47:02train and develop and you you sort of educate people.

47:05You don't you don't push them away and sort of ridicule them.

47:08You don't say, ha ha ha, you used a pie chart.

47:10You sort of you talk about what they're actually doing and then you go from there

47:15Exactly.

47:16And and uh, you know, once you start to do the basics right and you start to understand these things, then you can start to kind of understand at a little bit higher level what best practice is.

47:25And I think

47:26This is actually something that I mean level one, I think a lot of companies I have to say give credit to this do do this to an extent.

47:32They do track these metrics.

47:33They do understand what's going on in the organization.

47:35organizations that might not be able to articulate it and they might not be able to sort of s point at it and put a finger on it and say, hey, this is what's happening.

47:42But

47:43they understand how small changes to their products will will impact their users.

47:48And that means they're ready at the sort of second level, which is about cultivating a culture.

47:52And I think

47:53Uh i I think sometimes it's it you can sort of take this too literally.

47:57When you're cultivating a culture, it doesn't necessarily mean that you've established it.

48:00It just means that you're building it and letting it grow and letting it happen.

48:03But it doesn't mean that it has to be

48:05Set in stone, right?

48:07Yeah.

48:07And um uh the you know that allows people to try new things um and and to and sort of push things in new new ways.

48:14And as you're doing that, because you're measuring, you can obviously always

48:18uh see how people engage with it, see how people react.

48:20What catches fire, catches fire and you sort of let it run.

48:23And what doesn't, well you you go back to those things and you start to understand, you know, w what's going on.

48:29I think one of the best use cases I've seen of this is

48:31and a client which I've worked with recently who, you know, they have about 40 analytics products on their Tableau server.

48:37And they've built like a um a little report that says, you know

48:41which ones are being used or not.

48:43And you know that they've built 40 products for various people.

48:46And for the first time they've looked at the Postgres database of

48:49of dashboards um and from their perspective all 40 dashboards have needed maintenance up until I showed them this Postgres database.

48:58and the analytics behind it.

49:00And you know, some of the charts on there were saying that, you know, two people have looked at it in this month.

49:05And so they realized as a team they're spending a whole load of time maintaining stuff.

49:10That's just

49:10It's just being serving like four people.

49:13Yeah.

49:14Yeah, exactly.

49:15And then and then they don't realize that.

49:16They or or they just don't look, I think is the the better way of putting it right.

49:21Yeah, exactly.

49:22Exactly.

49:23Exactly.

49:23Um and then last one is is obviously if you're if you're real uh if you're at a real baller level with all of this, then you could even start to, you know, predict and

49:32understand what happens if you're Google level with this.

49:35So you know if you move this button over here, you know, people won't click it and this is what will happen because you fully understand sort of what's going on.

49:42And you you can sort of map behaviors to actions and actions to be

49:46behaviors.

49:48Yep, exactly.

49:49I think that's a good podcast, unless you have anything else to add or finish up on top No, no, no.

49:54That's but it's very it's a very interesting topic.

49:57Um I love it.

49:57I think we're gonna have to revisit aspects that we

50:00Oh god, yeah, there's so many little nuggets everywhere.

50:02Like three or four pod mini mini podcasts spawned off there.

50:07Gotta love editing this one, trying to keep it concise.

50:10Right, right, exactly.

50:12Absolutely.

50:13Okay, well thank you.

50:14Thank you for tuning in once again.

50:16And thank you for bearing with us as we've uh you know recently changed our branding.

50:20Um let us know what you think about that, by the way.

50:22I would kind of just impose it on you.

50:24We didn't do like a a focus group as they typically do with these things and ask you which one of the tem logos should we go for.

50:32Maybe we should do like an Evernote style blog about how we didn't change our legacy.

50:35Yeah, yeah, yeah.

50:36The original one was great, right?

50:38Yeah.

50:39Exactly.

50:41Absolutely.

50:41Okay, mate.

50:42Uh take it easy.

50:43I'll catch you in the next one.

50:44Nice one.

50:44Take it easy