Brent Dykes_mixdown.mp3

Brent: [00:00:00] An insight that's hard to understand or hard to process, it could be complex Data, where it's a very intricate kind of analysis we've done, and maybe the Data is unfamiliar to the audience. And so in those situations, we would want to invest extra time to tell the Data story. Often, when we have information that is counterintuitive, maybe it's bad information, like not bad information, but hey, that program that you rolled out for the last six months, I've analyzed it and it was not as successful as we'd hoped.

Harpreet: [00:00:40] What's up, everybody, welcome to the artists Data Science Podcast, the only self-development podcast for Data scientists. You're going to learn from and be inspired by the people ideas and conversations that'll encourage creativity and innovation in yourself so that you can do the same for others. I also host open office hours you can register to attend by going to Bitly.com/adsoh forward slash a d s o h i. Look forward to seeing you all there. Let's ride this beat out into another awesome episode, and don't forget to subscribe to the show and leave a five star review. Our guest today believes in the power of Data and its ability to elevate and transform what we can achieve both individually and collectively, and that doesn't matter if you're optimizing marketing initiatives, streamlining production cost or enhancing sales performance. He believes there are no limits to what we can do with Data. In his nearly two decades long career, he's worked in enterprise analytics as an analyst, consultant, manager and evangelist. [00:02:00] Through this experience, he's gained deep insight into what is needed to be successful with Data, both from a strategic and a

Harpreet: [00:02:08] Tactical

Harpreet: [00:02:09] Perspective. He's got a demonstrated ability to distill down complex concepts into content that resonates with the broader audience and has had his work shared at some of the largest industry conferences

Harpreet: [00:02:22] Around the globe.

Harpreet: [00:02:23] Today, he's here to talk to us about the importance of effective Data storytelling over the course of this interview. He'll equip us with the knowledge we need to make sure our good insights don't go to waste because when the right narrative and visuals are paired with a compelling insight, our Data Communications can inspire change

Harpreet: [00:02:44] And drive value. So please help me in welcoming our guest today. A man

Harpreet: [00:02:49] Who firmly believes the ability to tell stories with Data is an essential skill in our growing

Harpreet: [00:02:56] Data economy.

Harpreet: [00:02:57] The author of effective Data storytelling, Brant. Brant, thank you so much for taking time out of your schedule to come on to the show. Really appreciate you being here.

Brent: [00:03:08] Yeah. Thanks, Harpreet. Thanks for having me on the show. Wow, what a what a introduction. I hope I can live up to the setup you gave me.

Harpreet: [00:03:14] So oh absolutely. I know. I know you will. I've thoroughly enjoyed going through your book here. As you could see, I've just got notes that needs to get transferred into my digital cast and soon. But really, really enjoy this book and I can't wait to dig into it and share some of the insights that you've got in this book with the audience. But before we do that, when we get to get to know you a little bit, I talk to us a bit about where you grew up and what it was like there.

Brent: [00:03:37] Yeah, I'm the son of immigrants, so my my father is actually from New Zealand, my mother is Australian and they immigrated to Canada, had me there. And so I, when I was an infant, they lived there for a couple of years. Then they went to England and then they went back to New Zealand. And then when I was eight, I actually moved back to Canada for good this time and grew up in Victoria and North Delta [00:04:00] that's on the west coast of Canada, British Columbia. So that's kind of where I grew up in the last almost 20 years. I've lived in Utah.

Harpreet: [00:04:08] Yeah, I love Vancouver. Vancouver is an amazing place and specifically North Delta. I've got family that lives there, so I've been going to a north delta since I was a young boy. I was actually in Delta just the beginning of the month and beginning of September 2021 here. So that's that's awesome to hear. That's where you're from. All right, cool. So growing up in North Delta, that is definitely an awesome place to grow up. A lot of lot of good beer in Vancouver. I don't know if you're a fan of craft beers or not, but a lot, a lot of good stuff out there that I that I enjoy. But so growing

Harpreet: [00:04:39] Up in in

Harpreet: [00:04:40] Vancouver, what

Harpreet: [00:04:42] Did you think

Harpreet: [00:04:43] Your future would look like

Brent: [00:04:45] Growing up in the eighties? I thought I was going to be a computer programmer. I was convinced I was going to be a computer programmer. However, obviously life took me a different direction.

Harpreet: [00:04:53] So in a sense, I mean, not necessarily computer programmer, but you're still involved in the technology field and and still involved with, you know, Data in a sense. So is life really different than what you imagined it might be or is it kind of.

Brent: [00:05:08] No. I mean, I always did well on my math classes. And then when I was in college, I was

Brent: [00:05:14] Debating between marketing and accounting. I was getting good grades in accounting, and a lot of people would say, Oh yeah, definitely go that route, get get your accounting degree and then you're set for life once you become partner. I have a brother who's an accountant, but I decided, you know what? I'm just not as passionate about counting other people's money as maybe doing the creative side of marketing. However, I think when I eventually, when I was thinking of doing an MBA, I was like, You know what? I still miss the numbers, and I didn't really get as much exposure to the numbers on the marketing side, at least marketing communications. And so when I did my MBA, I was able to get back into the numbers and the quantitative side. And then my first job out of my MBA program was actually at an [00:06:00] enterprise analytics solution called Omnicare. And then I went into consulting from there and and that's really where I was able to. We were working with marketers on their analytics, but I could also, you know, obviously do analysis and kind of flex those muscles that I wasn't getting when I was just in pure marketing role.

Harpreet: [00:06:20] And so at what point was that you realize that that you can actually do a better job communicating Data when you use stories was. It's just a culmination of all the different interests that you had up to. Up until that point, well, what was that light bulb moment where like, OK, yeah,

Harpreet: [00:06:35] My story's

Brent: [00:06:36] So funny story was I was really interested in PowerPoint. I was really good with PowerPoint, started a blog called PowerPoint Ninja and did like one hundred blog post there.

Harpreet: [00:06:47] It's still up. I haven't

Brent: [00:06:49] Contributed to it in like probably 10 years, but but that kind of, you know, that kind of flex those

Brent: [00:06:54] Presentation muscles and stuff. But as a consultant, as a manager, I saw a lot of consultants struggling with communicating insights, you know, and even clients struggling to communicate insights. And that's where I kind of those two worlds kind of came together where I could take my analytics background with the presentation side and say, you know, look, there's got to be a better way to to present and share insights. And that's where I stumbled across Data storytelling. And I actually pitched it. The company that I was working for omnichannel was acquired by Adobe in thousand nine and in like twenty fourteen. We're coming up to twenty fourteen and I was like, I want to do a session like a breakout session at our customer conference on Data storytelling. And so I pitched it to the the event organizers, and they thought it was a great idea, ended up being a really popular session. And that just kind of opened my eyes to wow. There's not only do I love this and I'm super passionate about it, but other people are really interested in as well. And so from that point on, I just started presenting on it a lot and developing my ideas and putting my ideas into application. And [00:08:00] and yeah, and then I got to a point in twenty sixteen

Brent: [00:08:03] That I decided, you know what? I need

Harpreet: [00:08:05] To. I need to start

Brent: [00:08:06] Working on a book. I can't just keep this in my brain. I need to get it out there. And so that's and it took me three years to write the book. So it was it was a long process of writing and going through that. And yeah, no, it is quite the journey. But I'm excited by, you know, today, now

Harpreet: [00:08:23] I'm I've kind of

Brent: [00:08:24] All all, all chips in. I'm basically gone solo and this is what I do full time. So this is, you know, in terms of consulting and stuff that I'm focused on Data storytelling.

Harpreet: [00:08:35] So before we get into the new indicating or talking or informing what is there, subtle differences are glaring difference. Talk to us about that.

Brent: [00:08:43] Yeah, I mean, I think a lot in the analytics space. I've worked in analytics a long time and I think one of the things we're trying to do a lot is just providing information right where we're trying to inform people so they can make better decisions. And there's actually a quote, a great quote, and I'll just kind of summarize it. But it was by a journalist by the name of Sidney J. Harris, and he basically summarized information is about giving out and communication is about getting through. And and for me, that really resonated with me, I associate storytelling more with communication in the sense that we're really trying to get our insight

Brent: [00:09:21] Shared out to people in so that they can understand it like we do. Whereas I think like reporting and informing is more like, OK, we're pushing information at people. And and then it's up for them to to then just make sense of it. And we're not really communicating and insight, necessarily. And I think that's that's where communication and storytelling come together. Obviously, there's certain advantages to storytelling. I mean, we've we've we're storytelling creatures. We as human beings. That's part of our defining characteristics that we really seek out and try and

Brent: [00:09:56] Make sense of the world through the narratives that we form in our mind. And we're [00:10:00] trying to make sense of the world around us. And the magic of Data storytelling is often what we if you just give somebody a fact, they may not know what to do with it. They may not. It may not fit into their worldview or how they are currently thinking about whatever the topic is.

Harpreet: [00:10:17] And so by

Brent: [00:10:19] Pairing that factor that insight with a narrative,

Brent: [00:10:23] We're helping to explain it and we're also help. We're giving that individual something that they can then OK, fully grasp and integrate into their into their knowledge. So it's it's very powerful that way. And so I basically to answer your question, I think storytelling communicating one in the same or basically storytelling is a form of communication that's very effective.

Harpreet: [00:10:45] So let's get into it now, let's get into to to Data storytelling, and very early on in the book, you talk

Harpreet: [00:10:50] About the

Harpreet: [00:10:52] Elements of a Data story. So so what are the elements

Harpreet: [00:10:55] Of the Data

Harpreet: [00:10:56] Story and how how is it that they interact together to to create something that's compelling that can drive action or change?

Brent: [00:11:04] Yeah, I mean, I know surprise if I told somebody, OK, well, Data storytelling, it's comprised of three key elements. So you have Data narrative and visuals, and probably everybody. Yeah, that's a no brainer, Brant. But what I do in my book and what I've done in articles is I have kind of like a Venn diagram where I have each circle is for each of those elements. And then I look at the intersections of those because I think it helps us to understand the power of Data storytelling. So if we take just the Data bubble and we say, Hey, we're going to share some information with somebody, here's a spreadsheet. Here's a Data table.

Harpreet: [00:11:39] Here you go.

Brent: [00:11:41] And then I hand that to you and and there's a good chance you may not have the full context like I do. There's a good chance you may not come to the same conclusions. You may interpret it differently. That Data. And so what do we do when when we pare the Data with the narrative? And that intersection of narrative [00:12:00] and Data is really about explaining, we're adding the narrative to kind of make sure that people understand the data that we're sharing, the insights that we're sharing. We hold their hand through the numbers. We guide them, we give them the context, we give them the meaning behind those numbers. And so that's that's a really critical intersection of those two bubbles. And then if I look at the other bubble, the visual bubble and how that connects with the data, again, going back to sharing a data table again, there may be patterns, there may be anomalies in that data. There may be trends that are hidden in the rows and columns of the of that data table. And so it's only when we visualize that data that we can all of a sudden see, Oh, we start to make connections, we can start to see things and see things in the numbers.

Brent: [00:12:46] And so the combination of visuals with data is really about enlightening the audience to things that they wouldn't see otherwise without the visuals. And then the last two bubbles intersect. Interesting. So the narrative and the visuals, because as human beings, we love storytelling. We love visual storytelling. I mean, that's that's why probably many of us were up late last night binge watching the new Netflix or Hulu shows because we can't get enough of this connection. This this combination of visuals and narrative, it's really engaging for us. And so that all kind of brings together if we can get the right data, we combine it with the right narrative and the right visuals. All of a sudden we have something that's very powerful, something that actually can change how we view the world, how we behave can really have a huge impact. And so that's the power of Data storytelling in those three elements.

Harpreet: [00:13:38] Binge watching is true. That is what I was doing last night. I was watching. I think I watched like three episodes of this Netflix show called Squid Games. It was quite,

Brent: [00:13:46] Oh yeah, I've heard a lot about

Harpreet: [00:13:47] That. Yeah, it was quite quite interesting. And you know, you talk about you talked about how Data storytelling is kind of meant to to enlighten our audience. And, you know, speaking of enlightenment, I like that to you included some teachings [00:14:00] from Aristotle in your in your book. You know,

Harpreet: [00:14:03] I'm a

Harpreet: [00:14:04] Big fan of philosophy. I love philosophy, and Aristotle is definitely one of my favorites. So I'm wondering what can Aristotle teach us about persuasion and storytelling?

Brent: [00:14:13] Yeah, no. It's funny. When I started looking at Aristotle, I was like, Oh man, he was on to something here you. And I think there's the there's the common things that we associate with with his, with the three appeals that he talks about. So there's ethos, pathos and logos and so ethos just for people who don't know ethics is really the speaker's credibility. And so if we think of Data storytelling, that's really important that we have credibility ourselves. We've done due diligence on the Data, we've done due diligence on the Data. We we care about the

Harpreet: [00:14:49] Numbers and we are going to

Brent: [00:14:51] Inspire people to trust us in our stories.

Harpreet: [00:14:53] And then there's the

Brent: [00:14:54] Pathos, which is the the emotional appeal. That's where the narrative comes in. Emotion is really tied to narrative

Harpreet: [00:15:01] And then the

Brent: [00:15:01] Logos. Obviously, that's that's the logical appeal. That's what we do all day with the Data and the insights that we share. And there's actually two other appeals that don't get as much recognition, but I think they're also equally important to Data storytelling and being persuasive with numbers.

Harpreet: [00:15:17] And that's Telos.

Brent: [00:15:19] And so that's the purpose in which we're communicating our our our information. And so what I like to say a lot about Data storytelling is you. It's not like dumping a bunch of different insights. No, we're going to have a central insight. We're going to focus our attention. Our story is going to be focused on one central insight.

Harpreet: [00:15:39] And so that becomes our purpose. We want to fix

Brent: [00:15:42] This customer service process or. Want to fix how we market to our customers or whatever it is that we're analyzing and you have an insight. And then the last appeal that that Aristotle kind of highlighted was Kairos, and that's really the opportune moment. And a lot of the times when we're telling [00:16:00] Data stories, you know, we may have a very good Data story, a very powerful insight, but maybe something like COVID happens and then all of a sudden, you know what?

Brent: [00:16:09] That's not the right time to share this insight because everybody is focused on something else. And so, you know, finding that opportune moment is also a key part of storytelling Data story that's talking to something that is of the at that moment, the company is very focused on. Then you've got something that's going to be super well received and it's going to be super powerful. So absolutely Aristotle and all of his persuasive appeals are very relevant to Data storytelling.

Harpreet: [00:16:36] And you mentioned, you know, he mentioned logos and there now as logos guessing that that equates kind of two to logic ish in a sense. But like, why is it that most of our decisions aren't actually based on logic and and and if most of our decisions aren't based on logic, then what does that mean for us as storytellers? Why is that something

Harpreet: [00:16:57] That we should, you know, have in

Harpreet: [00:16:58] The back of our mind?

Brent: [00:16:59] Yeah, I know it's something. When I started out into analytics in the beginning of my career, I thought, if I do really good analysis, I come with all the data and facts, and I present that to a decision maker.

Harpreet: [00:17:11] They're going to be

Brent: [00:17:11] Able to make the logical, well-reasoned decision and pursue that and. You know, coming out of college,

Brent: [00:17:19] I didn't really know how human beings actually work, maybe as well. I mean, you have your group projects and stuff in school, but you know, you thought, Well, you know, that's they're just students, you know, in the professional world. People base their decisions on logic and reason. And and then I quickly discovered, no, you know, a lot of decision making is emotional. And and and that's something that even neuroscientists have found that actually emotion plays a big decision. It plays a big part in decision making. And there's

Brent: [00:17:51] Actually I talk about this in the book, but there is a guy by the name of Antonio Damasio,

Harpreet: [00:17:56] And he's a

Brent: [00:17:56] Usc neuroscientist, and he was working with patients [00:18:00] that basically had damage to their emotional centers of their brain. So basically,

Harpreet: [00:18:04] They

Brent: [00:18:05] Had no emotion. They they operated without any kind of emotional part of their decision making. And the interesting observation that he made when he was talking to these individuals is he would try and set up like a lunch appointment with with them.

Harpreet: [00:18:20] And then and then he'd

Brent: [00:18:22] Say, OK, what? Where do you want to go on Tuesday for lunch? And these he'd watch these patients

Harpreet: [00:18:28] Go back and forth trying to

Brent: [00:18:30] Make a decision on where to go to have lunch. They'd kind of say, Well, the sushi place. I think they have the special I like on Tuesdays. But then again, the Italian place is actually easier for parking. But then again, I really like the servers at the and they're like going back and forth. So decision that you or I, if we said, Hey, where do you want to have dinner in Vancouver? We could probably come to a decision in a minute or two, whereas these individuals would spend 20 30 minutes trying to come up with a decision. And so that really highlighted to this professor that a lot of our decision making is based on emotion, and sometimes that emotion is flawed. If you've read the book by Daniel Kahneman thinking fast and

Harpreet: [00:19:14] Slow, you know he talks about

Brent: [00:19:16] System one and System two, System one has a lot of people who haven't read the book system. One is basically our intuition. It's our unconscious processing of information and it it really has a sway over us. And that's really the emotional side of us that it really influences how we make snap decisions and how we come to conclusions. Because it's again, it's trying to make sense of all the stimuli that's coming into it and then provide the system to which is our analytical brain with kind of a recommendation.

Harpreet: [00:19:49] So it's

Brent: [00:19:50] Interesting. The human mind is, you know, we think it's like it works like clockwork and it's, you know, it's all logical. No, it's there's a lot of we have human [00:20:00] bias, we have cognitive bias. We have logical fallacies and things that we do as human beings. So.

Harpreet: [00:20:07] And you cover a lot of them in your book Effective Data storytelling, which I encourage all the guys to pick up, like a lot like like everything that I enjoy reading on my spare time. Like all this behavioral science and logical fallacies and biases and things like that, you pack them into this book and it

Harpreet: [00:20:24] Just, you know, before I used

Harpreet: [00:20:25] To think storytelling is, you know, what is storytelling is something that artists do. It's something that you know, either can do or you can't do. But no, it's a learned trait if you understand how humans react to information and how humans process information. So definitely recommend you guys checking out this book. And by the way, if you are looking for a place to eat in Vancouver, might I suggest meet MIT and Yale Town? I was hanging out with George Farrakhan there at the beginning of the month. They took really, really good care of us meat, so just shout out to them. So I'm glad we talked a little bit about System one and System two because it kind of keeps me up for the next question here. And that's, you know, if most of our decisions are

Harpreet: [00:21:02] Very emotional,

Harpreet: [00:21:03] Then how is it that we can make better decisions in spite of this emotional nature that we have?

Brent: [00:21:11] Yeah. I mean, it's so I think one of the things that is important is to read these books

Harpreet: [00:21:17] Like, you know,

Brent: [00:21:19] Daniel Kahneman's There's I have other books that I've read predictably irrational the the name of the author's escaping now.

Brent: [00:21:27] So all of those kind of books. And I think what's really important because there's there's two factors here in terms of how this plays out, there's our own biases and our own emotions and our

Brent: [00:21:38] Fallacies and stuff. So we need to manage that from our own perspective. Being aware of maybe what we might have a cognitive bias, you know, maybe we do have confirmation bias when we're doing our analysis

Harpreet: [00:21:50] Or we're trying to prove

Brent: [00:21:52] That we were right.

Harpreet: [00:21:53] And you know, and and so we're,

Brent: [00:21:55] You know, being self-aware, I think it's really important. Can we completely remove [00:22:00] all

Brent: [00:22:01] Of our biases? No, no, we can't. But we can manage them. We can try and mitigate them as much as possible. So that's one half of the coin. The other half of the coin is looking at our audience and how can we help them? They're going to have certain biases they're going to have. Flawed reasoning that they're going to use, and so often the great thing

Brent: [00:22:22] About visualizing our Data stories is that when we use charts and graphs, a lot of the times, it really helps the information to be really clear for the audience because one thing that can happen is as people there, they have something called motivated reasoning, right?

Harpreet: [00:22:39] Where they're they're kind

Brent: [00:22:40] Of they have maybe they hear a fact that that doesn't agree with their viewpoint and they're going to struggle with accepting

Harpreet: [00:22:47] That.

Brent: [00:22:47] But if we put that information into a chart and it becomes very clear, it's much harder for those individuals to misinterpret the Data or even kind of fight gates the Data that maybe they don't like. And and that's a common thing. We we don't like

Brent: [00:23:04] Numbers that that conflict with our viewpoint. We're going to we're going to be much more. And here's the it's a double standard because information that we

Brent: [00:23:13] Don't like, we're going to be much more on guard, much more analytical, much more skeptical. Where is it when we get some data

Harpreet: [00:23:21] Point that that reaffirms our opinion?

Brent: [00:23:24] We don't even check the source. We don't, you know, it's like, Oh, I see, I knew it. I was right. And we don't even verify anything. So it's almost like it's like an open door on one side for information that we like. And then and then there's all these like barriers and obstacles that we put up for information we don't like and so we can get screwed on either way. Like when we when we don't have an open mind and are open to new information that maybe we don't like to hear. But then also we we should also be verifying information that that maybe does validate our opinion. [00:24:00] But what about the source? Where is this coming from? Is there any bias in the information?

Harpreet: [00:24:06] And you wait just for anyone listening that's not aware of that term already motivated reasoning. What is it that that that you know how? How would you define that? What does that mean?

Brent: [00:24:15] Yeah. So it's when we have a viewpoint on something and we hear some conflicting data. So basically, our system one kicks in and says, Oh, don't worry about that, you know, it basically rationalizes our position. And so then what happens is there might be an initial kind of reaction like, Oh, I don't want to hear that there's I have an opinion on a on a political view or something like that, and I get some data

Harpreet: [00:24:41] That conflicts with my

Brent: [00:24:43] Political opinion. What happens is the the brain will basically rationalize that information and actually you get like

Harpreet: [00:24:50] Endorphins kick in or we

Brent: [00:24:52] Get almost

Harpreet: [00:24:52] Like this positive

Brent: [00:24:53] Reinforcement like, no, no,

Harpreet: [00:24:55] You're OK. Like that,

Brent: [00:24:57] That that that Data is wrong. Or I'm sure it's it's questionable or you're right, and this is all happening unconsciously. So we don't even, you know, we're not mentally like analytically thinking it's all just system one this this unconscious part of our brain that's that's trying to rationalize and and make us feel OK. So that's what they call it motivated reasoning because we we have a position already, and when we get this conflicting data, it's almost like our brain smooths it all over and it's our coping mechanism. And the actually the interesting thing is is that when neuroscientists looked

Harpreet: [00:25:34] At how we

Brent: [00:25:36] Receive a, you know, if you have a strong opinion on something and you get a conflicting data point that conflicts with your viewpoint, the human mind when they stand it, the same

Harpreet: [00:25:48] Reaction we have to that

Brent: [00:25:51] Factor figure that we don't like is the same as if we were in the wild and we ran into a bear predator. That same kind of reaction of of kind [00:26:00] of like something's going to cause us physical harm. The same reaction in our body occurs when we get Data or facts that that we don't like. And so we're we're very defensive and put on guard by new information we don't like.

Harpreet: [00:26:17] And so this is where the combination of narrative and visuals helps kind of get through that right. It helps us kind of cut through the motivated reasoning so we can no longer hide from the truth.

Brent: [00:26:27] Yeah, I mean, it's one tactic that can get through. Obviously, it's not always going to work, even if we tell a really good story. People can be very entrenched in their positions, but it may be the only way to get through that combination of narrative and visuals to kind of explain a different behavior. And some of the research that I found that was one of the some of the few things that would get through. And is it a silver bullet? No, it's not going to work every time, but it may be our best

Harpreet: [00:26:56] Shot at

Brent: [00:26:57] When we have information that's new and

Harpreet: [00:27:00] And maybe not

Brent: [00:27:03] Like we're going to the to a a team and saying, you know what, that campaign you just rolled out, it's not going so

Harpreet: [00:27:09] Good.

Brent: [00:27:09] And let us let me walk you through the numbers and show you that's not where they're going to want to hear. And so they're going to push back on that. But but again. Our only shot at maybe getting through to them is with a narrative that has visuals to kind of support our points.

Harpreet: [00:27:24] So I guess what are the differences in in the ways that facts and stories activate our brains? But you know, you mentioned how God's system one system, two going on, that's kind of our instinctual and system would be that instinctual way that we react to new Data system to. It's like, OK, we have to pause and think and kind of like, let me analyze that.

Harpreet: [00:27:45] But I guess what

Harpreet: [00:27:47] Are some other differences in the ways that you know, facts and stories that activate our brain?

Brent: [00:27:52] Yeah. Like so if I look here at our book in my book, if anybody has the book, it's on page sixty nine. I go through how to react to stories [00:28:00] and fiction differently. And so one of the things one of the things that we're going to our brains are really going to fight against new Data. We're going to we're going to try and not

Harpreet: [00:28:15] Accept new facts.

Brent: [00:28:17] And so one of the key things some of the benefits of stories is stories. Basically, when they were looking at the scans of the brain, when people would share just facts and figures, there are a couple of regions of the brain that would light up and they were just associated.

Harpreet: [00:28:32] Yeah, just associated

Brent: [00:28:34] With processing language. However, when somebody told a story, what they what they saw was other regions of the brain would light up. And that is because the audience would experience what the storyteller is sharing with them. And so you engage more of the human mind when you're sharing stories. The other thing is, in other research, they found they did a study where they they had noticed that the brain waves or the brain patterns of the listener and the storyteller actually started to align. And so there is some there's a great TED talk. His name is Yuri Onon. And basically, he talks about his research into this, where there's a there's a neural coupling they talk about between the the listener and the storyteller. And and so we can form a very different kind of connection with our audience when we're telling a story than if we're just sharing facts and figures. And then the other there is some research by a researcher by the name of Paul Zak and he he looked at how people responded to narrative stories as opposed to facts. And he found that there is more. Elevated levels of cortisol and oxytocin, and so cortisol is kind of a stress hormone, and that what that does is it gets the attention of the audience. So when we hear a story where we're wondering where the story will go, what's [00:30:00] going to happen next, and so our attention and this cortisol levels go up as we're listening to a story. And then also there's an elevated levels of oxytocin, which is

Harpreet: [00:30:10] Our love for role.

Brent: [00:30:12] But it's also we're more willing to do things for people. So it's almost like we make our our insights more actionable by just telling a story around it because people are going to be more open to accepting and and also running with with an insight. And and and there's even examples of where psychologists have looked at how people respond to narratives in the sense that they almost go into a trance like state. When we're hearing a story and we're less likely to pick on the details of a story as as we would with just straight facts.

Harpreet: [00:30:49] And so as we go

Brent: [00:30:50] Into this almost like hypnotic state listening to a story. These are reasons why why would we not leverage these, not not to manipulate people or. But there's as I talked about in my book, there's there's almost like this expressway. It's like the carpool lane in the brain, and that's where the narrative goes. Why would we want to get congested in the slow lanes where you get all the traffic

Harpreet: [00:31:17] Backed

Brent: [00:31:17] Up as a brain's trying to process information? If we can go in that express lane and get our ideas quickly to the people in a way that

Harpreet: [00:31:24] They're they're very

Brent: [00:31:26] Open to and actually

Harpreet: [00:31:28] The brain system, one

Brent: [00:31:29] Actually wants to hear stories. Why would we not leverage that?

Harpreet: [00:31:34] So I think we're perfectly set up now we've got we got a bit of the brain science going on, what's going on in your audience's minds as you're communicating your stories. We've talked about the importance of Data why narrative is important, but we haven't really talked about what a Data story actually is yet. So let's get into that now. So what is a Data story is like? Isn't it just the same as a dashboard with visuals? Or am I missing something here?

Brent: [00:31:57] Yeah, no. I think there's some characteristics of of things [00:32:00] that kind of separate a Data story from from just a dashboard or a report one. So I basically in my book, I talk about six key elements. So one is obviously a Data story, has a foundation and Data. We're not just creating some kind of narrative and then sprinkling in a few data points to kind of back us up. No, we're actually doing analysis. We've we've found insights and now we're building on that foundation of Data, as I mentioned earlier. Another key element is you've got to have a main point.

Harpreet: [00:32:30] And if you think about a

Brent: [00:32:32] Data story, it's got to have a destination. Where are you taking people? You know, it's not just an assortment of

Harpreet: [00:32:38] Kind of like, here's here's

Brent: [00:32:40] Oh, here's something interesting, and here's something interesting. And here's something you know, it's there's a main insight. Obviously, there could be supporting details to kind of help us understand that. But there's a main insight that we're sharing with the

Harpreet: [00:32:53] Audience and a lot

Brent: [00:32:54] Of the communications that we get the most that we can get out of a dashboard is really observations. We can make observations with a dashboard. And maybe those observations then lead to an insight later on as we do deeper analysis into the into the problem or opportunity. But when we talk about Data stories at the core of a Data story is an insight. We're not just if all we have is observations and no insight. You don't have a Data story in my mind. The third point about a Data story is it's explanatory in focus. So if we contrast that with a descriptive approach, which often reports and dashboards that describing the Data what's happening, it's providing a summary of what's

Harpreet: [00:33:40] Going on, not more

Brent: [00:33:42] Focused on the what rather than the why. And I think a Data story really focuses on the why. Its goal is to really explain to the audience, Hey, we have a problem here in our in our with one of our processes and our manufacturing plan, and we're going to walk you through why [00:34:00] it's a problem in all of the all of the information. You need to understand why there's a problem. And then hopefully, you know, what are we going to do about it, you know? And again, that's kind of a differentiating factor for for Data stories. And then a forced key thing

Harpreet: [00:34:15] About that is unique

Brent: [00:34:17] To Data stories is they have this linear

Harpreet: [00:34:19] Sequence.

Brent: [00:34:20] It's not just again, a random assortment of of of Data or observations or insights. We are taking you step by step through this process, and that's what stories do. There are a series of events and and things that happen.

Harpreet: [00:34:35] A causal relationship goes through them. And the same thing with

Brent: [00:34:39] With our Data stories, we're stepping people through this, this connection. That's the fourth point. The fifth point is we can just like a normal story. You know, if you think of film or or books, there's a lot of things that we can borrow

Harpreet: [00:34:54] From the fictional

Brent: [00:34:56] World to include in Data stories. And so you may think, well, we don't have characters like a story. Well, are you analyzing customer data? Are you analyzing employee data? You have. You have a characters you have. You're doing this analysis of your employees, so you definitely have characters. And then we can mimic some of these other obviously with a story before you get into story, there's a setting and there's background information. The same thing happens with a Data story. We're establishing the status quo. This is what we typically would expect to see. And then, boom, we saw this happen. This metric shot up, or this metric went down,

Harpreet: [00:35:35] And then that

Brent: [00:35:36] Launches us into a story. And so we can borrow a lot of elements from traditional storytelling and bring those over into the Data story as well. And then the last element is are the visual elements know and Mark Twain. I have a quote in my book where he's he's he basically

Harpreet: [00:35:53] Was telling

Brent: [00:35:54] Writers like, you know, rather than putting the fat lady on this on the stage, [00:36:00] you bring her on the stage and letters screen, you

Harpreet: [00:36:03] Know? And I think the way I

Brent: [00:36:05] Apply that to Data storytelling is, you could say, yeah, our revenues went up 50 percent. Ok, that's great. Show me. Show me that. Show me that pattern. Show me how the revenues went up 50 percent and and we can do that with the data visualizations we have. That visual element is that that sixth element that kind of brings it all together. And so those are, you know, those are six things that I look at in a Data story. There is a lot of confusion out. I think a lot of people are confusing, maybe a dashboard with a Data story or a report with a Data story, and that's I would say, no, those aren't the same if they don't have more of those, those features that I just mentioned

Harpreet: [00:36:48] Way the book is chock full of amazing quotes I loved. I loved all the quotes that you were able to source and add in the book. And for anybody that wasn't listening carefully, the elements of the Data story that was Data Foundation, the main point explanatory focus, the linear sequence, the dramatic elements and then the visual anchors. So you mentioned something in there and

Harpreet: [00:37:10] It was insight,

Harpreet: [00:37:11] And I don't think we really actually got a definition of that. So, you know, you talked about the fact that we can just say revenues are up 50 percent. Is that considered an insight or how how can we make that into an insight? Like what needs to what are the elements of an insight? How do we go from fact to insight?

Brent: [00:37:28] Yeah, I mean, one of the I think there's a lot of confusion around what an insight is, and we use it kind of loosely in a lot of ways. And even I was using it loosely before I wrote this book, and I had a couple of readers who viewers who are reading my book and they're like, Brant, you talk a lot about insights, but you don't really define what an insight is. And I think that will be important to other readers. And so I I was like, Oh, you're right, you know, I need to do that. So I went I went back to the first chapter and as I was looking around at different definitions, [00:38:00] I was really struggling because they were just kind of really loose and not really that helpful until somebody pointed me to a quote and how it just spaces me. Let me just pull it up here. And I thought, Well,

Harpreet: [00:38:15] Well, you do that. Just that. We are also live on on LinkedIn a lot of great comments coming in from people. There's about 25 people listening in. People are loving the love and the insight and the the wisdom you're sharing with us here. Brant, thank you. There are some great comments coming in from Christine and Meredith and Armand. Kate Strachan is also joining us on the live stream as well.

Brent: [00:38:35] I am looking for my. So basically now the name is going to come to me. Basically, he said, an insight is an unexpected shift in the way we understand things, and that for me, really resonated because I was like that. That is a really great way of understanding what an insight is, because if you think about, OK, so I go into the Data, I have an understanding of our customers and that means, wait a second, there's there's an opportunity here. We have a group of customers who are very interested in this.

Harpreet: [00:39:08] And then the other thing about

Brent: [00:39:10] An insight is, is it's something we

Harpreet: [00:39:12] Typically will want to

Brent: [00:39:13] Share with others, right? So that's where the Data story comes in.

Harpreet: [00:39:16] Because if I can just take

Brent: [00:39:18] Action on that and I can address that, that whole, I can get the product to those customers on my own without anybody else. Hey, then, no Data story is needed because I can act on that myself. But in most cases, when we're working with the business or working within our organization, we're going to need to get buy in from other people. We're going to need to get budget resources approval,

Harpreet: [00:39:39] Maybe

Brent: [00:39:40] Get people to coordinate with us from other teams. And so that's why the insight then needs to be communicated in an effective way. So we can we can actually get the action to occur because it can't just live with us. We need to get other people on board.

Harpreet: [00:39:55] And I've definitely been there in those situations where I'm like all in the Data, like I'm getting [00:40:00] in there and I find myself in a Data labyrinth. So that Data labyrinth. There's a lot of like facts and there's a lot of things that look like insight. Is there like a distinction between just the old fashioned insight and like an actionable insight? How do we distinguish the two?

Brent: [00:40:16] Yeah. So I what I what I do in my fifth chapter, I go into that and I talk about how we can kind of really identify actionable insights. And I borrow something from I don't know if anybody is familiar with Avinash Kaushik. He's he's kind of he works at Google very smart guy. And he shared kind of like three things that we need, almost like a so what test for our insights. And so the first one is why should you why should your audience care and what should they what should they do about it? And then the third thing is what's the potential impact? And then what I did in my book is I kind of applied a formula that I had looking at each of those. So under why should your audience care? I think there's got to be two key things that are important for answering. That question

Harpreet: [00:41:06] Is do we have a

Brent: [00:41:07] Valuable insight? Is there? Is there some kind of positive return or perceived return that we can get from our insight? Is that clear? And then is it relevant? You know, obviously, if I'm I'm coming to an audience with something they're not even thinking about

Harpreet: [00:41:22] Or not even focused

Brent: [00:41:23] On. There's probably going to be less interest in acting on that. So I want I want to have why should your audience care valuable

Harpreet: [00:41:31] And and

Brent: [00:41:32] Relevant? And then what should they do about it and in there, we need to get into what we need to be practical and specific. And so again, yeah, like I could I could tell the company if you only

Harpreet: [00:41:45] Spend three hundred

Brent: [00:41:47] Million dollars, we can generate,

Harpreet: [00:41:49] You know, maybe

Brent: [00:41:50] That's not practical for the business, especially if their revenues are much lower than that. So we have to, you know, we have to kind of look at the solution, what's the what's feasible? What's [00:42:00] realistic? If we have a more feasible and realistic solution or an insight that potentially the business could go after, then that's going to be more actionable than one that feels a little bit far off. Or we're not ready to kind of pursue that, that insight and then very specific, the more specific we can get on. Ok, so here we have this insight what do we do about it? And then if we can articulate specifically the steps or the actions that we need to take again, that's going to make that insight more actionable than an insight that doesn't have a lot of specificity around it. And then when we get into what's the potential business impact, I bring up two key points here. We want to make it as concrete as possible. So usually that means quantifying it, monetizing it, putting it in some dollar figure, if that's if that's appropriate to really kind of shine a light on this, like this is a quarter million dollar opportunity

Harpreet: [00:42:55] For our team.

Brent: [00:42:56] If we can, we can seize this and then the next thing is contextualizing the the opportunity as much as possible. So if we can say, Hey, I think we can generate this many leads and oh, and by the way, last year we did a similar initiative and we were able to generate X amount of leads. And so here we are. It's completely feasible. And just by contextualizing our recommendations, contextualizing what we're talking about, it helps people. It makes the

Harpreet: [00:43:27] Insight more more makes

Brent: [00:43:29] People more at ease. And we're comfortable with with the insight when it when it's contextualized.

Harpreet: [00:43:34] So those are all the

Brent: [00:43:35] Factors that I obviously in the book, I get into more detail, but actionable insights. It's great if we have insights, but the more actionable we can make them. Obviously, we have a higher likelihood of driving value

Harpreet: [00:43:47] And the book. For those that do not know yet, it is effective. Data storytelling by Wiley publications and excellent, excellent book. I highly recommend guys checking it out. So this is all Data need a story?

Brent: [00:44:00] Yeah, [00:44:00] no. And that may be one of the things that people come to me and say, Well, Brant, do I need to turn everything into a Data story? And that's where I say, no, no. Like, I'm trying to be pragmatic with my Data storytelling. I want to be as pragmatic and practical as possible because honestly, it can take some effort to create a Data story. You know, it goes above and beyond just slapping a couple of charts in a in a in a in some slides and then sending it on to your manager and hoping for the best. No, we're crafting this. We're honing all of the visuals. We're building a narrative structure around this and that can take some effort. And so I have in the book I talk about, I have this, there's a story zone. And so basically it's a typical kind of four by four quadrant analysis. And so that the two axes that I have one access is is just the value of the insight is at a low value insight or is it a high value? And so that one, obviously, we're going to want to focus on high to medium value insights. We don't want to invest a lot of time in low value insights.

Harpreet: [00:45:07] So we wouldn't we

Brent: [00:45:09] Wouldn't tell a Data story. Or at least we wouldn't invest as much time in a Data story for a low value insight. And on the other axis, I talk about the type of insight and how easy or hard it is for the audience to accept or understand the insight.

Harpreet: [00:45:26] And I'll give you some

Brent: [00:45:27] Examples of maybe an insight that's hard to understand

Harpreet: [00:45:31] Or hard to process.

Brent: [00:45:32] It could be complex Data, where it's a very intricate kind of analysis we've done, and maybe the Data is unfamiliar to the audience. And so in those situations, we would want to invest extra time to tell the Data story. Often when we have information that is counterintuitive,

Harpreet: [00:45:48] Maybe it's bad

Brent: [00:45:49] Information like not bad information, but hey, that program that you rolled out for the last six months, I've analyzed it and it was not as successful as we'd hoped. And so whenever we have a situation [00:46:00] where maybe the information is,

Harpreet: [00:46:02] Is is

Brent: [00:46:03] Unfamiliar, it's it's, you know, information that's counterintuitive, information that's hard for the audience to receive because maybe they they are invested in the success and hearing

Harpreet: [00:46:14] That things didn't

Brent: [00:46:16] Go as well as they could have. It's going to be bad news. And but that's when a Data story is required, when we have information that is pleasant, when it's very straightforward or not counterintuitive. And if it's if it's even if it's high value, do we need to invest? Much time because going to the team and saying, hey, that new product you launched the product launch was a success. Yay. You know, it really doesn't require much of a story because people are already on board. It's when people aren't on board that that's when you need to tell a Data story. And that's so

Harpreet: [00:46:51] Basically the the

Brent: [00:46:52] Hard insights to process and understand. And if they're medium to high value, that's the story zone where I really feel like storytelling is is needed. Now you could use storytelling outside of those zones, but but then that's that's where if you have the time and you feel like it would add some value, then you can do it. But it's not required.

Harpreet: [00:47:13] But it's it's it's

Harpreet: [00:47:15] The for the framework. Oh yeah. Talk to us about that. And where does that kind of fit into

Harpreet: [00:47:22] The the Data

Harpreet: [00:47:23] Story kind of process?

Brent: [00:47:26] Yeah, yeah. Yeah. So for Dee, I've actually heard some other

Harpreet: [00:47:29] People use for

Brent: [00:47:30] Pt and other, but my forte is really about the audience. So I say there's four main main dimensions that we need to think about

Harpreet: [00:47:38] When we're looking

Brent: [00:47:39] At an analysis, whether we're looking at a dashboard or in this case with Data storytelling. And now obviously, it kind of starts with the analysis because if we're already off track when we begin our analysis, then we're not going to have what we need for a Data story. So the four DS, the first dimension is the problem, and the problem is really important to understand because the [00:48:00] only way if we don't understand the problem of the audience and it's going to be very hard for us to really get focused on finding potential causes or really getting into what's going on for that audience that they care about. And if I had an example of a marketing team where they're struggling with generating leads, I'd want to dig into what are the problems? And they might say, Well, we're our biggest problem is we're

Harpreet: [00:48:22] Just we're getting a lot of complaints

Brent: [00:48:23] From our sales team that we're just not generating enough leads for them. And so, you know, we look at our sales leads and it's they've been going down over the last six quarters or six months. And so that's the problem. And then and then the next dimension is OK. Well, if that's the problem and that's where you are today, where do you want to get what's your future state look like? What is what is the outcome you want to drive? Are you maybe you're already driving towards that outcome? And so this marketing team might say, Well, we want to double the number of leads that we're providing to our sales team. Ok, great. Now I know how far where are you right now

Harpreet: [00:49:01] In that goal? Well, we haven't really achieved.

Brent: [00:49:03] Ok, so you had a lot of work to do or or no, we've we've made some changes and we're halfway there to our goal. We just need to get the last. And so that's kind of establishing kind of how far they've come, where they need to get to. And so that's good. Now we got these two two perspectives on the audience. The next one is the actions. And so the actions are the activities or strategies that they're using to move from the their current state to the future state. And and this is important for us to understand as we as we go into the Data and as we do our analysis because obviously we going to have data on all kinds of things. But if we know that they're investing time and effort resources on certain activities and actions, we can then target those for our analysis. Those are the areas where we

Harpreet: [00:49:51] Dig in and

Brent: [00:49:52] Those are going to be areas that the audience is going to care about. Because what they're spending money on it, they're they've got people allocated in doing it. And if we're [00:50:00] doing our analysis to understand

Harpreet: [00:50:02] How

Brent: [00:50:02] Successful or potential opportunities in those areas to the marketing example, maybe they're they're looking at shifting a lot of their offline kind of activities to online virtual. And so we could do some analysis around how those initial virtual campaigns are going.

Harpreet: [00:50:20] Maybe they're they're

Brent: [00:50:22] Experimenting with some new agencies to kind of roll out some new creative or something like that to kind of generate some more leads. So, OK, let's let's start analyzing how those different campaigns are going. Those agencies, how are they doing?

Harpreet: [00:50:35] And so we're very

Brent: [00:50:36] Targeted on what what's going to be top of mind and important to the audience. And then the last dimension that we look at is the measures. And so those are the KPIs. Those are the, you know, at the end of the day, what are the metrics that this audience cares about? It may be a number of leads. They're generating cost per lead conversion rate on their campaigns. Those are the things that we are going to then use to evaluate the actions, understand the outcome that they're driving towards. And I kind of look at this as a yes, like we talk, I talk about the data being a labyrinth and we can easily get lost in that labyrinth. If you don't have kind of like a plan or if we don't have kind of some guidance to kind of guide us through the Data. And so the the Ford, I look at the Ford that I just outline.

Harpreet: [00:51:25] This framework is

Brent: [00:51:26] Very helpful to keep us centered and focused on going into the labyrinth to coming

Harpreet: [00:51:31] Out with with.

Brent: [00:51:32] Valuable insights that are going to help

Harpreet: [00:51:34] The business rather than

Brent: [00:51:36] We can go into that labyrinth and then, oh, look, squirrel, squirrel, squirrel and we start going and then we come out of there a little bit like, where did why did we go in originally? What were we trying to find? Did we know without that kind of mooring or that kind of concentrated focus on what's important to the audience? I think that's where we can waste cycles [00:52:00] and things that don't really matter to the to the company or to the audience that we're trying to help.

Harpreet: [00:52:05] And so far, just to recap the 40 framework that's looking at the problem, the outcome, the actions and the measures, Brant goes into great detail on that framework in his book Effective Data Storytelling, which again, I highly recommend you guys check out. So sometimes you might have like an awesome story put together. You got your presentation, you got your visuals, and you just be ready to go in and share these insights. But you might have an audience member that's a key audience member, and they just want the facts. How do we how do we handle that situation?

Brent: [00:52:41] Yeah, so I I have a whole framework that I share in the narrative chapter where I go into how you set up

Harpreet: [00:52:47] A Data story and

Brent: [00:52:50] A lot of people are like, Oh, that's great bread,

Harpreet: [00:52:52] I love it. But what happens

Brent: [00:52:53] Is when I am presenting to executives, they're really kind of conditioned to kind of just expect a summary and just the numbers. And really, it would be kind of a shock to them to kind of get a story. And so maybe before I get into my strategy around working with the I need to kind of back up and explain my my narrative kind of approach here because I think that'll give context before I get into the

Harpreet: [00:53:18] Hack that I use

Brent: [00:53:19] In those situations. So if you're if you're telling a Data story, there really should be a structure to it. And when I was researching Data storytelling, a lot of people would say, Well, this story has a beginning, middle and end. And I found that actually comes from Aristotle. It's based on I mean, he didn't say it that way, but people took his his analysis of Greek tragedies and applied

Harpreet: [00:53:40] That every

Brent: [00:53:41] Story has a beginning, middle and end. But I found that kind of lacking. I didn't really find that it was that helpful for me because you could point to a report and say, Oh, it has a beginning, middle and end. It's a story. No, it's not a story.

Harpreet: [00:53:55] So that that model

Brent: [00:53:56] Didn't really work for me. And so I kept looking. And then I came across a guy who was a German [00:54:00] playwright from the eighteen hundreds by the name of Gustav Fraid Tech, and he had this. He he basically looked at Shakespearean plays. He looked at the Greek tragedies like Aristotle did,

Harpreet: [00:54:09] And he

Brent: [00:54:10] Kind of and he analyzed them for basically he found that they all had a story arc. Which has been called freight tax pyramid, but basically I took his model and I applied it to Data storytelling,

Harpreet: [00:54:22] And so I

Brent: [00:54:24] Kind of see some key key things in a in a storytelling arc for four Data stories. And the first thing is establishing the setting, right? So when we're going into, we're going to talk about, let's say, call center Data and we're going to establish here are the

Harpreet: [00:54:39] Typical response

Brent: [00:54:41] Times, the typical kind of behaviors we see from

Harpreet: [00:54:44] Customers, and we're

Brent: [00:54:45] Establishing giving the audience some context into what we're going to get into. And then there's a hook, and the hook is really just a an observation, an observation and an interesting observation we've made in the Data that, oh my gosh, something happened on this date. When people making this up on the fly, they're calling about a particular product. We saw that the response times went up significantly. Oh, OK, so now we've got something that's going to draw the audience in. We've established the setting. We've got this hook or something. Just this response. Times went way up and that's costing this money, right? And so then what we do is we start unpacking that. So we start to do some analysis, OK, what's going on here? What's causing this? And then we we build it to an aha moment, which may be if we don't address this problem for this reason, this reason, this reason we're going to be, you know, we're going to have we're going to double our call center costs over the next two quarters or whatever.

Harpreet: [00:55:49] Again, I'm

Brent: [00:55:49] Making this up. So now we're like, Oh my gosh, this is this is going to get more and more serious. It's going to cost us more and more money. And then the last step. So that's our climax, right? That's our aha moment. [00:56:00] And we're basically connecting our hook

Harpreet: [00:56:02] With

Brent: [00:56:03] If there's one or two insights or maybe there's ten insights or observations we need to make to get up to our big aha moment. That's fine, but then we're not done. Once we've got our aha

Harpreet: [00:56:14] Moment, we then need

Brent: [00:56:15] To say, OK, how are we going to address this problem? We've identified that this is a serious problem that if we don't address this going to cost us x amount of

Harpreet: [00:56:24] Dollars, what can we do?

Brent: [00:56:26] And that's where our job is the analyst or or is the manager. We go in and do some more analysis to kind of say, OK, here's here are the three options we can do this this and this, and that's option A. We can do this, this and this and this Option B and then Option C, and we recommend Option A because it's the biggest impact for the least amount of cost. And what we've done is we've taken all of our findings and our analysis and packaged it into something that mimics a typical story. Now, going back to your original question is what do I do when I can't tell that full story? You know where I have the setting, the hook and the rising insights leading up to my my big aha moment? And then the next step and say, What do I do in that situation? Well, I kind of modified it and said, What you want to do is you want to you want to. Data trailer. I call it a Data trailer. So think of it like a movie trailer, but it's like the worst movie trailer in the world because it actually gives away the climax of the story of the movie.

Brent: [00:57:28] And basically, what I do is if there's these four stages of a Data story, I say, What are you going to want to do? Is You want to take the hook and you want to take the AHA moment and maybe a little bit of setting to set up the hook. And that's where you put into your Data trailer. And so you say, Hey, we notice the patterns on response times. With this, we saw this massive spike. And oh, and by the way, if we don't address this in two quarters, it's going to cost us X amount of dollars. That's the Data trailer. So we've kind of crammed it down into [00:58:00] that. And then at that point, what we're seeking to do is that manager may then say, Tell me more. Like, I'm curious, how did you get to the X amount of dollars or how do you what's going on with that? Now you have permission to tell them the rest of the Data story. So and that could go one of two ways they could say,

Harpreet: [00:58:18] Tell me more. And then you

Brent: [00:58:20] Get into actual storytelling or it's like, Oh, OK, yeah, I'm not worried about that. Ok. All right, then I'm not worried about it, either. Then, and I don't need to tell a Data story and I'm not wasting their time. I'm not wasting my time. So I see that Data trailer as the solution to kind of modifying our approach, but hopefully encouraging. It's like we're enticing people to hear the rest of the story, and that's what we can do in those situations

Harpreet: [00:58:48] Nicely with with a question that that that I had prepared. So the question coming in is from from Christine. She wants to know, can this story take away from the actual

Harpreet: [00:58:58] Science in the

Harpreet: [00:58:59] Problem solving process? And my question was going to be, what's the difference between a Data story and a Data forgery? So I'm wondering if there might be a way to answer both of those there?

Brent: [00:59:08] Yeah, no, totally. So I think one of the things sometimes when people

Harpreet: [00:59:13] Look at like we see

Brent: [00:59:14] Maybe a presentation. That's got a bunch of Data in visuals, and we say, Oh, that's a Data story. And then I say, Ooh, have we really told a Data story? And and I call those Data forgeries. And so if I outline the process that we need to take with a true Data story, it should start with the Data, right? You're starting with the Data. We're doing some analysis. Maybe we have a hypothesis that we're testing. We validate that hypothesis. And then we then we have our insight that we want to share. And then the next step is to then visualize the Data build, the build, the visuals that support our Data story and then they're tailored to the audience. So that's kind of how a Data story should come together. [01:00:00] Now there's three forgeries that I talk about in my book, so the first one is everything follows the right process. We start with the Data. We do some kind of analysis, we find an insight. And then what happens is rather than tailoring our deliverable to the

Harpreet: [01:00:17] Audience, we just kind of

Brent: [01:00:19] Share exactly what we what communicated to us, we assume, will also communicate to the audience. We make no edits. And I call that the Data cut that kind of like a director's cut of a movie, right? Every director is like, Oh, this is how the movie should be seen. But often what I've seen is when I watch the theatrical version, I'm like, Oh man, that's amazing. And then I go, I want to see more. I love this movie so much, and then I want to see the director's cut. And then I go and watch the director's cut, and I'm like, No, no. That scene was kind of lame, but I don't know where that was going. I can see why the ED cut made the cuts that

Harpreet: [01:00:54] They did, and the same

Brent: [01:00:56] Thing can happen to us, especially analytics professionals. We assume, you know, it's kind of like the curse of knowledge where we assume that people can will embrace the Data and consume it the same way that we do. And often that's not the case. We need to edit it.

Harpreet: [01:01:11] We need to provide context.

Brent: [01:01:13] We need to hold their hand through the Data and so that that last second step of actually editing ourselves is really important. So that's the Data cut.

Harpreet: [01:01:21] Now, the one

Brent: [01:01:22] That will will be relevant to the

Harpreet: [01:01:24] Question is the next

Brent: [01:01:26] One where basically what happens is it starts. And this is usually a situation with the business side saying, Hey, I need to show that my marketing campaign was successful. And so we start with the story. In this case, it's not a hypothesis. It's actually no. I need to show that my campaign was successful. And so you need to go find me Data or help me find Data that that shows that my campaign was successful. And and then what happens is,

Harpreet: [01:01:54] And I call this one that I won't

Brent: [01:01:56] Get what it's

Harpreet: [01:01:56] Called yet. But basically what happens is we then select [01:02:00]

Brent: [01:02:00] Data from the Data. We select Data points that that

Harpreet: [01:02:04] Support that the campaign was

Brent: [01:02:06] Successful

Harpreet: [01:02:07] And we

Brent: [01:02:08] Either inadvertently or on purpose ignore data that shows maybe some problems with the campaign. And then we we visualize it all. We tailor it to the audience. So everything looks really nice. But the basic, you know, we're basically just sprinkling in some data to support our argument or our agenda that we have and that that kind of speaks to the question that that's the danger when we start with the story. And then we're trying to mold the data to the point we're trying to make or that's less effective. Now you can have a hypothesis, you can have a hunch, you can test that. But as long as you remain open to maybe the Data saying something different and then you're going to, I can't tell the story I want to tell because that's actually not accurate. And and that's the danger, you know, whenever we. Get into the scenario where we have to kind of prove something, you have to show

Harpreet: [01:03:00] Something, then

Brent: [01:03:02] We will select the Data that and then we're not in my mind. That's not a true Data story.

Harpreet: [01:03:08] And then the the third Data

Brent: [01:03:10] Forgery is one where we

Harpreet: [01:03:13] Typically look at some really pretty visualizations that have been created.

Brent: [01:03:17] You know, we're like, Oh, wow, this is really interesting. And then we start to scratch at it and we see, wait a second. What is the point of this like? There is no insight. There is no main takeaway. It's almost like the creator of the visualization is hoping that somebody will find something of interest of note. And and that's I call that the Data decoration. We we basically and I don't think I gave the name to the second one. The second one, I call it Data cameo, kind of like again, a movie reference where the data is just inserted as a cameo, but it's not really driving the story. And then the third one is the Data decoration. The visualizations look pretty, but it's kind of hollow.

Harpreet: [01:03:58] There is no main takeaway. [01:04:00]

Brent: [01:04:00] There is no main insight driving that that Data story. So that again, is Data forgery. So basically, if we look at it, the three elements Data element, the narrative

Harpreet: [01:04:11] Element and then the

Brent: [01:04:13] The narrative, the narrative, the visual in the Data. So the the Data cut is is a Data problem where

Harpreet: [01:04:20] We haven't edited the Data the the

Brent: [01:04:23] Second one, the Data cameo is kind of a narrative problem where the narrative is becomes overbearing. And then the third one is the visual problem where the

Harpreet: [01:04:30] Visuals become too dominant, and we haven't really put a

Brent: [01:04:33] Lot of effort into the real insight behind it. So that was a long answer.

Harpreet: [01:04:41] Also, talk about in your book Cognitive Biases, Logical Fallacies, I just real quickly, what are these and why are they important to watch out for? Why should we keep an eye out for these things?

Brent: [01:04:53] Yeah, I mean, I think as I was mentioning before, it's kind of like it's on us as the analysts and as a storyteller to make sure that we're not tripping up our own Data story.

Harpreet: [01:05:03] You know, our cognitive

Brent: [01:05:05] Biases are not getting in the way of us telling our Data stories effectively. If we come into it

Harpreet: [01:05:12] Where we're

Brent: [01:05:14] Either in a couple of examples that I use in the book and there's the one of the sharp I do have sharpshooter, but it's the survivorship bias and that's with Abraham Walt. And he was probably pretty. Everybody probably heard of it. But basically, to summarize real quick, the American Air Force is basically losing a number of its bombers and its crews. They're getting shot down. And so they were wondering if they should put more armor in certain places and they were looking at the the planes that were coming back and they were doing an analysis of where the bullet holes were. And they found there are certain concentrated areas where they are getting more damage. And so they went to Abraham Wald, who was a team of he was on a team of mathematicians and statisticians during [01:06:00] World War Two and in and they basically said, What is can you do an analysis of our data and tell us, are we making the right decision here that we want to put the armor plating in these places where the bullet holes are? And then he actually came back to them and shocked them, and he said,

Harpreet: [01:06:16] No, you should absolutely

Brent: [01:06:18] Not put the armor in those places. And he introduced this concept

Harpreet: [01:06:23] Of survivorship

Brent: [01:06:24] Bias. They were looking at the planes that were returning safely, so it didn't really matter how many

Harpreet: [01:06:30] Shots they'd taken.

Brent: [01:06:32] Those were two non-essential parts of the plane, and they survived.

Harpreet: [01:06:36] He was saying,

Brent: [01:06:37] We really need to understand what was shooting down like, where would the planes that were shot down? Where did they take damage? And so it was almost like the inverse. We need to look at the places

Harpreet: [01:06:46] Where these

Brent: [01:06:47] Surviving planes didn't receive a lot of damage because we know that if they

Harpreet: [01:06:52] Did on the

Brent: [01:06:53] Engines or the back of the flew the fuselage or in the cockpit, those are the places that are probably causing these other planes to go down. And and the reason why these ones survived is because they didn't take damage there.

Harpreet: [01:07:06] And so that that really

Brent: [01:07:07] Kind of like, Oh, and that was a bias that they had the

Harpreet: [01:07:12] American Air Force,

Brent: [01:07:14] That that Abraham Wald had to kind of wake them up to. And so similarly, there's all kinds, I think in Wikipedia, there's like one hundred and eighty

Harpreet: [01:07:21] Different cognitive

Brent: [01:07:22] Biases that we can fall victim to. And I was actually teaching my class about cognitive biases, and we were going through a bunch of the last class and in it's eye opening to realize how much our brain can can conceive us. And so as analysts, as we analyze our data, as we go to build Data stories, we need to be cognizant of where we can trip ourselves up so that we don't, you know, a

Harpreet: [01:07:48] Cognitive bias kind of

Brent: [01:07:50] Blinds us to a perspective on our Data and we build this beautiful Data

Harpreet: [01:07:56] Story. And then somebody

Brent: [01:07:58] Is like, Well, what about this? I mean, it looks [01:08:00] like you kind of ignored that. And then you're like, Oh my gosh, I I was. So, you know, the cognitive bias took over and I went down a path that that kind of led me astray. So that's I think that's important. And again, like what I said earlier is that it's hard to train out of us. And so it takes discipline. It takes maybe sharing our ideas with other people and sharing our work to get feedback and maybe even acknowledging what our biases are before we start doing any analysis or as we're building our Data story, how can I strive to be more objective? It's it's hard to completely be objective, but we can at least strive to be.

Harpreet: [01:08:43] And you in the book Effective Data storytelling, great book, you should get it. You talk about a number of different cognitive biases. I'm wondering if there's one that's, you know, you see a lot of the professionals kind of, you know, commit most frequently talked about survivorship bias. But is there one that you know, you've seen happen a lot recently or one that you just see happening over and over?

Brent: [01:09:06] I mean, the one that happens a lot is this confirmation bias, right? So we were just we already have a viewpoint where we kind of know what we feel. And I've seen that with as even as I've done analysis, I'm like, Oh yeah, this this campaign's going to this campaigns would have failed or this this marketing channel is, you know, I have a marketing analytics background. So that's why I have a lot of marketing. But this marketing channel is garbage never works. And so all of a sudden, I'm going to be analyzing that with that chip on my shoulder, where I'm going to be like, Yeah, it's almost like, I'm not going to be.

Harpreet: [01:09:42] I'm going to be

Brent: [01:09:43] Looking for ways in which that marketing channel has failed. I'm going to be looking for ways in which it's a terrible investment for for marketing dollars. And and that's what you've got to be careful of. I think because I think think about analysts and data scientists were all very [01:10:00] smart people. You know, we have opinions, we have perspectives. And that's the dangerous part that we're going to go into whatever analysis is, and we're already going to have an opinion on something and then we're going to inadvertently potentially support you or confirm our bias that, oh yeah, I knew that was going to fail or I knew that that was the right thing to do. And you know, and we'll we'll trip ourselves up. And so I think I think I would say confirmation bias, and that's that's also for also our audience as well. They're going to have confirmation bias as well. So that's that's a very common one that that people run into all the time.

Harpreet: [01:10:39] Let's have one final formal question before we jump in Twitter. Really quick random round and it is this it's one hundred years in the future.

Harpreet: [01:10:48] What do you

Harpreet: [01:10:49] Want to be remembered for?

Brent: [01:10:51] Oh boy. Yeah, I don't. I don't know if I could be like Aristotle. You know, like he was from like twenty three hundred years ago, and here we are. We're still using some of his principles. I mean, that's that's crazy to think somebody lived that long ago, and we're still leveraging his his work. Hey, if there's some value out of effective Data storytelling or any of my other

Harpreet: [01:11:12] Future work that that

Brent: [01:11:14] Resonates with people in the future, I look to people like Hans Rosling and

Harpreet: [01:11:19] Others.

Brent: [01:11:20] Even though Hans Rosling has passed his, his work will always be remembered as as a a very amazing Data storyteller. And so I hope that maybe in the future that people will remember

Harpreet: [01:11:33] Me as

Brent: [01:11:35] I'm not going to put any

Harpreet: [01:11:36] Shade on Hans or

Brent: [01:11:38] Even compare myself to Hans Rosling. But you know, like, hopefully if I'm I'm sharing insights or ideas that are helpful to people and help them to become better Data storytellers and tell really powerful Data stories. That's great. That's that's all I can ask for.

Harpreet: [01:11:53] I know you're well on your way there because this book is amazing. I really, really enjoyed it. I've learned a tremendous amount by [01:12:00] going through the book and just for the audience. Hans Rosling, if I recall correctly, you can find a video of him on YouTube where he's talking about population size and these bubbles growing and stuff like that. It's really fascinating to watch. Really good way, a good way for you to see Data storytelling like in action, right? So let's go ahead and jump into the random round. First question is what are you currently reading?

Brent: [01:12:25] I am reading a bunch of books. What I'm reading is actually pretty good.

Harpreet: [01:12:30] It's learning to see Data

Brent: [01:12:33] And spy Ben Jones of Data. Ben's a really smart guy, but yeah, I've enjoyed his book.

Harpreet: [01:12:39] I'm about two

Brent: [01:12:40] Thirds through it. But it's good. Yeah, enjoyed it.

Harpreet: [01:12:43] What song do you currently have on repeat?

Brent: [01:12:46] I was thinking of that. I think I've been on Spotify. It keeps giving me songs by Beck and It's Hyperspace album, which I hadn't really got exposed to before this year. But it's been. It's been repeating a lot of his songs from that album.

Harpreet: [01:13:03] So Beck is Beck's cool man. He's one of those people who was always changing up his style, not afraid to, you know, go back down the mountain and take a different path just to reinvent himself.

Harpreet: [01:13:13] I really admire

Harpreet: [01:13:14] His chameleon like Major Beck is awesome. We are going to go

Harpreet: [01:13:19] To a random

Harpreet: [01:13:20] Question generator. This will be a lot of fun here. First, random question we got for you here, Brant, is if you lost all of your possessions, but one, what would you want it to be?

Brent: [01:13:34] I would want to keep my

Harpreet: [01:13:37] Incredible Hulk one eighty

Brent: [01:13:38] One. It's a comic book. That's the first appearance of Wolverine, and I got it when I was a teenager. And yeah, that would be my one position I'd want to keep. What's your worst habit? I do not get enough sleep. I need to get more sleep.

Harpreet: [01:13:55] What's the baby, candy?

Brent: [01:13:56] Oh, I like hard [01:14:00] candy, I like a niece, so it's like it's like a Greek hard candy, other chocolate bars I would go with, I'd probably go with 80 dark chocolate, dark chocolate. It's a big thing for me.

Harpreet: [01:14:12] What's one of your favorite comfort foods, Greek food?

Brent: [01:14:16] I love Greek food. So like a Greek chicken souvlaki? Yeah. Love it.

Harpreet: [01:14:22] Nice. We'll do one more from here. What's something you learned in the last week?

Brent: [01:14:26] Yeah, actually, that's that's something as I was preparing my talk for Data Kate's conference that's happening next week, I was I'm preparing a talk and I talked about the difference between Data telling and Data storytelling. And it was interesting to kind of put pen to paper and really think through the differences between what we may perceive as Data telling and Data storytelling.

Harpreet: [01:14:52] Right. How can people connect with you, what can they find you online?

Brent: [01:14:56] Yeah, a couple of places so effective Data storytelling. That's my website for my book, and you can reach me there if you want to contact me.

Harpreet: [01:15:05] I'm going to

Brent: [01:15:05] Be adding a bunch of services, pages and stuff. Still working with my designer on that. It should be happening next week or so. And then the other best way would be LinkedIn LinkedIn Brant dikes just connect with me. If you're passionate about Data storytelling, I'd

Harpreet: [01:15:19] Love to connect with you.

Brent: [01:15:20] Or if you'd like to get passionate about Data storytelling, then definitely. Let's connect because I can. I can. I'll be, you know, I'm constantly sharing content and ideas through my LinkedIn channel. So yeah,

Harpreet: [01:15:31] I'm looking forward to seeing your presentation at the Data Cated Conference, which is happening on Tuesday, October 5th. You and I will be presenting on the same day. I'm really looking forward to that. So, you know, if you guys are listening live here on LinkedIn do connect with Brant. I will be sure to add his I'll tag you in the post. We had such good, positive feedback from from the viewers. Brant, thank you so much for taking time out your very busy schedule. To be on the show with me today. Appreciate having you here.

Brent: [01:15:58] Thanks, Harp. Appreciate it. [01:16:00]