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Data Storytelling: When and how to communicate your data in stories

Updated: Mar 20, 2023

MindSpeaking Podcast Episode 4 - Brent Dykes, Author, Founder and Chief Data Storyteller at AnalyticsHero

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0:00:00 Introduction

0:00:24 Introduction of Guest

0:02:11 Brent in high school

0:03:36 Marketing: Fluffy Business Area?

0:06:56 Influence with Storytelling

0:08:19 How Data Professionals Foster their Curiosity

0:11:37 How to reach senior people

0:15:53 Data Storytelling

0:20:50 Mindset Shift

0:31:18 Benefits From Data Storytelling

0:39:44 Role of Presentation Skills in Data Storytelling

0:47:26 Brent's Book

0:55:34 Rapid Fire Round

1:02:13 Where to follow Brent Dykes

1:04:10 Conclusion

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👨🏻‍💻 Gilbert’s Linkedin

Introducing Brent Dykes

Gilbert Eijkelenboom: Hi Brent, welcome! I'm so excited to talk to you again. Because we share a passion in data storytelling. And of course, that's what we're going to talk about today. But I also want to know a bit more about you, because I think that's also what people are interested in. And before we dive into your career, I want to go back a bit more going back to your childhood. And I'm curious because we speak about it a lot about development, personal development on this podcast.

What type of person was Brent Dykes in high school?

Brent Dykes: I was probably a nerd. I was probably socially awkward. I really just wanted to survive high school. I didn't really enjoy high school I you know, I did okay, in my classes, I got these. I didn't really apply myself. And I really just wanted to move on from high school so I don't have fond memories of high school. I think the more I survive, I just don't stand out. Don't don't do anything. You know, silly don't do anything that's gonna get you picked on or anything like that. Just survive, you know, and so I I did a lot of computer gaming. I liked you know, playing with my Commodore 64 And, and that was probably a big thing. I enjoyed skiing. So I go skiing. I grew up in Vancouver, British Columbia, Canada. And so often we go skiing. I love hockey. I wasn't a hockey player though. I wish I could say I was a hockey player. I did not get tall until I was in 12th grade. So that didn't really help my channel.

Marketing: Fluffy Business Area

Gilbert Eijkelenboom: So and and after you you started to your dad, you started your career. Now you talked a lot about data storytelling. But actually your background is in marketing, right? You you write to your LinkedIn profile that you're deep down, you're still a marketer. And what I find interesting about that is what what I would like to understand is because many people in day two, I think marketing is a fluffy business area or it doesn't really matter. I've seen those comments in the past on LinkedIn and other areas. What are your thoughts on that?

Brent Dykes: Yeah, well, when I started when I was in the last, you know, year or two of my, of my studies, studying business administration, at Simon Fraser University in Canada, and I was deciding between accounting and marketing, and I was good at accounting, which for most people, that would be Oh, that you definitely go into accounting because there's to save career. You're not going to have too many issues finding a job. Whereas I think that perception that marketing is a little bit more fluffy, a little bit more squishy, and probably not as safe and option but I really wasn't passionate about counting other people's money. And so I decided to go into marketing because I really, the one thing that I really enjoyed I joined a lot of my psychology classes and I liked how psychology overlaps with marketing and consumer behavior. And they apply a lot of these psychology kind of principles there. And so that really appealed to me. I love that that part of it.

My dad was in public relations, and so I got a little bit of exposure, indirectly to marketing. And at the time, honestly, data wasn't really a big thing with marketing. The only discipline within marketing that you could actually play with data was in market research. And I was talking to another person who graduated with a marketing degree at the same time as I did and her professor told her how do you want to make the least amount of money in marketing go into market research? And yet with that was probably I would say, that's pretty, pretty fair assessment of where dated marketing was at the time.

However, I would say once I got into marketing, and I did an MBA, I got into digital analytics or web analytics as it was called at the time. And that was really where marketers now had lots of data on their campaigns, lots of data on their SEO, lots of data on all of the marketing channels. And even today, I mean, marketers have so much data, so much, so many numbers to play with and to analyze and hopefully tell data stories. But that was that was a transformation for me because I could apply all of the stuff I love around marketing with confidence. And so getting into marketing analytics or digital analytics for me was was a godsend because I was able to pair those two interests together and then that's what started me down the path of data storytelling, because at the end of the day, yeah, you can have an insight but if you're not able to communicate that insight effectively, or clearly, then that's, you know, no action will be taken on that.

Influence with Storytelling

Gilbert Eijkelenboom: Psychology interest and knowledge you've built over the years. can also come in handy while telling stories with data and talking to stakeholders to understand how to make their decisions and holiday. How you can influence them with with storytelling.

Brent Dykes: Absolutely. I would say when I started getting into to analytics I may have looked past a lot of the psychology of decision making and how that influences us and how we look at data and process it and so it was almost like a renaissance or you know, a rejuvenation of the psychology aspects because as I was writing my book, I realize a lot of people would say, Oh, do this or do that. It because it works. In my mind, I think I'm curious, but why why does it work that way? And that was part of you know, what I wanted to get into with my book is I want to understand why these things work the way they do. Why is it good to tell stories wise, why are visuals effective? Why do we sometimes ignore the data, just trust our gut, in a wire these things? Why do we work this way? And I think that was an important thing to look into and understand because at the end of the day, we want people to take action on our insights and we can't commit connect with them or if you can't communicate your ideas effectively. Then, again, like I said earlier, our insights will go.

How Data Professional Foster their Curiosity

Gilbert Eijkelenboom: I like that you mentioned curiosity that you're curious person. Do you think on average data professionals are curious enough or how can they can they foster their curiosity or bring it to to the to the workplace, how can they put it in practice, so to say?

Brent Dykes: Yeah, I mean, I think that there are some people that are naturally just more curious than others, but I think in general, all human beings are curious by nature. Especially if we can get our if somebody can pique her interest, and hold it potentially. I worked with a lot of internet analytics professionals over the years and sometimes I've seen on the reporting side, and maybe a little bit on the on the data, setup side, maybe data engineering or other professions. Sometimes it's more just taking a number, short order cook, filling that order, and then moving on to the next one. And there's no curiosity.

There's no question Why are you asking for that data? Why do you want to know that number? And I think that's an important thing to do as analytics professionals or as data professionals, because sometimes you'll get a prescription from the business, right? They'll say, fill this prescription. And then you're like, but why do you need this payment? Why do you need these payments? Well, it's because you know, I've got this pain in my back. And then you know, and then you turn them around and they've got something sticking out of their back, escape. I can give you this medicine or we can just remove this. Stick that sticking out of your back. I mean, that's kind of a terrible analogy. But basically, sometimes what happens is the business comes to us with I need this data. And we don't ask the question why we just, oh, okay, here's the data. And I think that's the wrong approach.

I think we we also should say, Well, why do you need this data? What are you trying to solve? What are the questions you're trying to answer? And it may be like actually, that data is not what you need, you need this data, or we don't even have that data. We need to go collect that data for you. or different things like that. I think that the curiosity starts right there. And then obviously, if you have the data, then you know i It's hard to it's like the curse of knowledge. Right? If you if you are somebody who's curious, it's hard to not be curious, but if I'm looking at data i Get curious, I want to know what's you know, what's happening, what's causing it? What is it contributing to what are the other factors?

And so I just naturally get curious. But that that is something I think, is a skill that we need to develop in people and I think stories data stories, go back to data stories, I think for getting people's interest in the data, and in the business, increasing that that curiosity because as a shared data story, they'll say, Oh, that's interesting. I wonder what's happening in my part of the business or I wonder what's happening with this. And what stories can we tell on that part? You know, if we looked at one customer segment, are there other things that we can do with other customer segments to understand their needs and their interests and then I think that I think you will.

How to reach senior people

Gilbert Eijkelenboom: Outweigh when you were talking, I was thinking, Oh, I would like to know how you can make stakeholders who are not as available, who may be more senior or far away from you are hard to reach, but eventually make the decisions that you're that you're trying to improve or help with, with your data. How can you reach them or how can you get curious with them? How can you understand their perspective? But maybe you answered this question already by saying, You need to tell stories, so you get their attention. Is that right? Or do you have more ideas how you can do that? How you can reach these more senior people or people who are far away, where eventually making the decisions based on your data.

Brent Dykes: Yeah, I think an important step in that process is to understand their business, their needs, what are they trying to solve? In the book I talk, I have a model that they introduced called the four D framework, and it's really based around audiences and I say there's four key dimensions you need to understand for any audience to really connect with them. And the first one being, okay, I want to understand what the problems are that they're facing. Is there a top of mind problem or series of problems that they're trying to address in 2022? And then the next thing is with that paired with that is okay, what outcomes are you trying to drive? You know, maybe they have a problem.

Let's take a marketing example. They're struggling to generate leads for their organization, as a marketing organization in a b2b marketing organization struggling to generate leads. Okay, well, what is the outcome you're trying to drive well, in 2022, we want to double the number of leads that we're generating for the business. Oh, okay. So that's you're going from 500 a month to 1000 a month or whatever that is. And then the other thing that the other the third dimension that I want to understand is what actions or activities or strategic initiatives do you have in place to get you from your current state where you have this problem to your future state? And so okay, what are we doing as a marketing organization?

Well, we're changing some of the channels that we use, we're shifting more to digital, or we're going to be doing more virtual events. And so Okay, so let's, let's evaluate how they're performing what what are their opportunities to optimize those are there other things you could be doing in those areas? So I want to understand that and then the fourth dimension is the metrics that the the key we often call them KPIs or key performance indicators, but what are those key metrics that that audiences using to measure themselves by and measure the activities that they have?

And so I think, you know, obviously, the stories you're going to connect with people, but if, if we don't have a good grasp of what the audience is caring about, obviously want to have stories that are going to be meaningful to them that are going to connect with them. And that's where if we can understand what problems are trying to solve, what outcomes are trying to drive, by activities, they're investing time and resources in and what metrics are being held accountable to that gives us a really great approach that we can take to kind of build meaningful data stories, because that's, I talked about in my book that it sure lots of businesses are collecting all kinds of data.

And it's kind of like a labyrinth, right? We go into that labyrinth, we may or may not come out with something meaningful. And having a framework like what I just talked about, obviously, it's a simple framework of having those four dimensions. It feels like we're handed a GPS we're handed a map or focus and go into that labyrinth and find meaningful insights that we could then bring out of the data and share.

Data Storytelling

Gilbert Eijkelenboom: I think that's, that also sums up what we in data. Data professionals can learn from people in marketing, because people are marketing all they do all they start with. They always start with asking questions about who's who's the customer, right? What are their frustrations, what are they trying to achieve? And I think with this marketing, or Google radiosity mindset, however you want to call it, I think we could benefit greatly.

We touched upon storytelling already a bit what I'm curious about this because I've I've seen storytelling data storytelling everywhere in the last years. It's kind of a hype, right? Everyone talks about data storytelling, but from my perspective, there are a lot of misconceptions about what data storytelling is about how the term is you miss used and misused. So can you share your thoughts about it?

Brent Dykes: Yeah, one of the things one of the frustrating things for me is that I do see data storytelling being more than a buzzword more than just jargon. And I've seen a lot of vendors and other people talk about data storytelling, kind of using it as a buzzword. And, and I think there's a lot of power behind that whole principle of telling stories with our numbers or with our data. And so one of the first misconceptions I think that's out there is that a lot of people just associate data visualization with data storytelling, and that it's a sentiment or maybe good data visualization. That's all it is. And really, that overlooks two other elements that in my book I talked about, there are three key elements to data storytelling. That we have data narrative visuals. And yes, visualizations are a big part of data, or data storytelling, to the point that a lot of the data that we're sharing is very complex. There's a lot of complexity with the numbers. And so when we visualize the data, we help the audience to see things in the numbers that they would miss otherwise, because they wouldn't be able to see the anomaly or they wouldn't see the patterns or trends.

Now, I've had some people come back to me and say, is that even an essential element because they've heard good podcasts. You know, where people are sharing data stories with no visualizations. It's all audio based. And so I would say, I think visuals are still important. Are they essential?

Well, actually, you could probably tell a data story without any visuals. Now, with that said, the again, I'll say a lot of times you're sharing a lot of very complicated, intricate information, and it does, it can be assisted by visualization. But really where a data story comes in is obviously having the right data and having a framework like for D to kind of help you identify the right Insights is crucial, but then the thing that I think gets overlooked a lot of the time is the narrative element.

And I was actually thinking of writing a post or a blog post about the difference between narration and narrative. And I kind of look at narrative as being much more than just narration. When you hear about data storytelling, some people just assume, Oh, I'm telling a story with my chart, I've added some annotations, or I've got an explanatory title on it. And now my chart is telling a story.

And I've even heard other people say, Oh, every chart tells a story. You know, that. I think that really relegates or undermines really the power of storytelling. The storytelling goes beyond just what I would call a scene, which is one data chart. In my framework, I kind of view that as a scene in a story. You know, so that can be very very compelling, very powerful. We've all watched movies where they've had these really amazing scenes, but is it an entire story? It's not. Now. Often what I find is I'm going to have to use several visuals and different data to really tell a complete story.

Storytelling goes beyond just what I would call a scene, which is one data chart. In my framework, I kind of view that as a scene in a story. Yeah, so that can be very, very compelling, very powerful. And we've all watched movies where they've had these really amazing scenes, but isn't an entire story. It's not now, often what I find is I'm going to have to use several visuals and different data to really tell a complete story. And so I think that's one of the misconceptions that's out there that yes, you know, people would equate it with data visualization, but then also some people equate it with just adding in some text, and some annotations and calling it good and you've told a story. No, there's a whole structure to how a story makes the story a story. If we think about it in terms of the like an arc A story arc, you can create the story arc for your for your data findings, and form it into a story format, which then connects to people on a much deeper level emotional level, potentially, that you just can't achieve with just facts alone or just..

Mind Shift

Gilbert Eijkelenboom: That's also the biggest misconception, I see that people assume that their storytelling is data visualization. But indeed a just a graph and with some annotations, it's not necessarily your story. I think. Where starts to be become a story is when there's a problem, right? Or a character or at least those are elements of the story. And it's quite hard to have that in one scene in one frame. Or one visualizations, even if you add these annotations. You also mentioned about a blog post and also, I want to ask about another blog post you mentioned in a blog post, you talked about why data storytelling requires a mindset shift. You talk about story framing versus storytelling, and reporting versus storytelling. Talk to us about that. And yeah, tell us what was the the essence of that blog post?

Brent Dykes: Yeah, I mean, I think a lot of people will also associate another misconception. I think it's out there is that people associate dashboards as data stories and and I worked at a company Domo, you know, where they they basically are a cloud BI solution and provide dashboards to companies. And I always struggled with that notion that we're telling stories and dashboards, it really comes back to that whole. It's a different mindset that we go through a lot of what we've done today and BI and analytics is we've focused on generating reports and dashboards. And, and there's even some vendors and other people out there that are saying dashboards are dead, you know, kind of being provocative that way. I don't, I'm actually not. In that camp. I do see a role for dashboards and reports and I think it will continue into the future because at the end of the day, I talk about creating an insight funnel, okay. And at the top of this funnel, is really where the dashboards and reports sit. We're basically observing what's happening in the business, right? We're monitoring what's happening and we create these reports and dashboards to help us explore the numbers. And so I call that the story framing. Because at the end of the day, it goes back to if I set up a dashboard, all of a sudden I'm choosing the metrics. I'm choosing the dimensions. I'm starting to target where we're focusing our attention on hopefully we're focusing on the most important things to our business, and they're tied to the priorities of what the company is focused on. But we're not, we're not bringing in all of our data into a dashboard.

Now we're hand picking the metrics and the dimensions that are meaningful to the audience that we've targeted data. And so that's kind of the first step we start to. That's why I call it story framing. We're starting to reduce all of the metrics of data that we can look at, and really focusing on the ones that are really critical to the business. Now from that we might then see a spike in a particular metric, or a decrease in particular metric or something that's happening. And then that gets us curious. And then we start to ask questions, well, why is that happening? And maybe we can, you know, double drill into that information in the dashboard or maybe at that point, we need to kick out and go to an analytics tool and then we need to work with an analyst or data scientist to explore that problem further. And then at the bottom of that funnel is when we have an insight that we want to share with other people. And we need their buy in we need their maybe we need resource we need budget from them.

That's when we form a data story. We have an insight, and we take that insight and craft an explanation of what's going on and also what we recommend that we do with that insight. And that's where we shift from being exploratory at the top of the funnel to actually being explanatory. And the goal at that point is we're trying to move away from just observations to a real insight that then will then drive a decision or chord or change something and that that's, that's something I've also been talking a lot about lately. I think sometimes we use that term insight very loosely. And when I was writing my book I found I needed to I had reviewers who gave me feedback said you're using insight a lot what does that What do you mean by insight, and I started to look at like dictionary dictionary definitions of what an insight is, and they were okay, but they really did it to help me understand really what an insight was until somebody shared with me a quote or a definition by Gary Klein is a psychologist, author. And he basically framed an insight as an unexpected shift in the way we understand.

We understand something. And for me that was that's what it is because then all of a sudden it's like okay, let's take an example. Maybe it's a manufacturing example. Oh, this process we thought wasn't working because of one thing that we've been trying to optimize on that one step but there's some analysis or something we did, and it shows that was it isn't that step. It's this other step that we have. That's really causing other problems. Well, what does that mean? That means, oh, we've been focusing on the wrong area the whole time. We need to we need to fix it ASAP, and optimize it. And so that that could be we're going to have to do changes within the organization and have to do things differently and that any insight will then inspire change automatically, or the demand potentially, whereas an observation is just, oh, here's something we you know, this this metric went up, it spiked up.

Okay. That's very interesting and unusual. But we don't know why. We just have to what and so sometimes I think we equate observations with as we're mistaken observations for insights when really they're, they're not as actionable as an insight that our understanding we have an urgency to change the dressing.

Benefits From Data Storytelling

Gilbert Eijkelenboom: According to that definition that you're just mentioning, in your book, The unexpected shift, then we have way less insights because not all those patients or parents are actually insights right? And you talk about what's the difference between reporting the dashboarding and, and then storytelling at the bottom of the of the funnel? What What are your thoughts about you know, having a predictive model or creating an algorithm and then presenting that to a group of people who have business people? Can we use data storytelling? If yes, how?

Brent Dykes: Yeah, I think so. I think we can still use what, what went into that model, what what were the how do we design that followed by enough context to understand it, and then how would we apply it how what are the insights or what are the benefits that we get from that model? So I think we can take that approach and apply data storytelling might be slightly different, where there's an action that we're trying to drive or something like that, but it's just like, we need to rely on this model and and this is this is something that we're trying to do and a lot of times, you know, when I talk about data, storytelling, data storytelling, I don't think you necessarily need to do data storytelling for everything.

When do you need to tell the stories and I was actually talking on another podcast with another speaker. And in my book, I have this quadrant where I say, basically, there's there's this one quadrant where you definitely want to tell the story. And on the bottom axis I had is that high value or low value in terms of the the impact of the insights that's coming out and then the other axis I had, where I said is what what type of insight is it is that a difficult or hard to follow or understand insight, or is it easy to insight or process? And then I said basically if if an if an insight is candid, give value. And it's also hard to understand a process and that could be for different reasons. It could be because it's counterintuitive. It could be because it's bad news. It's like, oh, we spent all this money in this campaign, and it's all been wasted. That's gonna be a tough message. So there's, you know, there's some complexity as opposed to where maybe an insight is easier to understand.

So we did this campaign. It was a huge success. And we're going to be reporting back to the marketing team, hey, all that money you spent was a success. I mean, that's going to be a harder step. It's gonna be easier sell right. And then what the, with the other podcaster noted is when there's stablished narrative in the mind of your audience, and your information just complements that it just adds to the existing narrative. You don't need to tell a story. You're just adding new information to what they already believe. It's when there's an existing narrative that oh, we're really good at or that campaign was successful.

Or our customers like feature a, and we come back with like, no, actually, they like feature B or that we are not as good at marketing as we thought we were. When we have a conflicting narrative. Our data shows that we have we need to form a more accurate narrative this conflicted with the existing narrative. That's when you need to tell a data story. And so it's, it's really when you need to shift the narrative in people's minds. And that's when we engage so they came up with that model example.

If it's, if it's a model that everybody's expecting will work fine, and they're excited about the model. Do we need to really do a big elaborate industry for it? Probably not, because people are going to be on board with it. It's only when it's like, the existing model or the existing way that we've done things sucks. And the only way we can move forward is if we embrace this new model. That's when you do need to take the time to really build the case, right? You have to build a story around why that model is going to change the way we you know from a customer service perspective are going to help.

Role of Presentation Skills in Data Storytelling

Gilbert Eijkelenboom: You mentioned a Quadrant by value and difficult hard to follow, difficult or hard to follow any are easy to process and talking about conflicting narratives in COVID. I don't want to make this a political debate. But what I'm curious about this, there are a lot of different narratives in among people and take a very black and white start to narratives, right? You shouldn't be vaccinated or you should not be vaccinated. How do you think how do you think the government do you ask government or, or how do you see otter dealing with this and do you think they would benefit from from adopting more storytelling? What do you think because clearly, they tried to make people adopt a certain narrative, namely, be vaccinated. How do you how do you think they're doing or do you think they could benefit from more storytelling?

Brent Dykes: One of the interesting things that as I was writing my book, I found some work by some climate change. May they've done some analysis or research into what makes people considered new perspectives. or conflicting perspectives. Because at the end of the day, from a psychology perspective, I come to you with let's say, You're not You're gay climate change, you know, you think all of it's just fluff and I came with some data and dropped it on your lap and said see Gilbert, climate change is real. You're, you've got it. You're so You're so crazy. Unless that's never going to work. Because just dropping facts on somebody is not going to change their perspective.

What you have to do is you have to not only include those facts, but you have to package them in a story because you're going to have anybody has an existing narrative. And the psychologists in the neuroscientists found a lot of times is when maybe one fact in their, in their narrative gets by somebody. But what happened is that residual narrative that they have in their brains, that they'll just start, oh, well, maybe that data is, you know, I can't trust that data. It's, it's from, you know, songs or whatever.

Now, revert back to the narrative that makes them comfortable. And so it's really how can we build a compelling narrative with our facts and really complete the whole story so that people can embrace not only that narrative that goes with it? And the interesting thing is that in some of the research that I that I found that people found, that visualizations are actually very effective at persuading people with very different political views or, you know, they use it for climate change.

They use it for different parties in the US. And they a visualization was actually one of the few things that got through to people where they could they couldn't deny the data. They couldn't, they couldn't reject it outright. And so it's a delicate thing, and especially with politics and how people approach it. Everybody has an existing narrative if you think about conspiracy theories, right? There's so far they have to preserve the narrative, and they'll just embrace anything like it's, it's funny to like, again, I just started it's very interesting conflict because the thing is, is when we get laid as supports our narrative, you don't scrutinize it.

They just say, oh, yeah, there. There's more that supports my narrative, you know, and we don't even think about it unconsciously we do that. Whereas if it's anything that conflicts with our narrative, sudden we're very skeptical. We're off guard, we don't want to be tricked or deceived. And so once we, when we when we shift into that analytical boat, we're going to be much more closed minded, and people psychologists even when you have a threat to your ideas or your viewpoints they looked at the reactions that we have in our bodies and found the same way we react to a conflicting idea or perspective, is the same way we react to if we ran into a predator in the wild, the same defensive mechanism that we have in our brains. For us physical threat is the same way of react to a, a a threat to our ideas or our values or viewpoints. And so it is very tough to just break through with data.

And I think that's where a story is one of the only ways we can really get through to people. And again, you know, it's it's no guarantee there's a lot of people are entrenched in this and their viewpoints, but it's, I would say it's one of the few ways that we can actually be crafted in a right way. And with empathy and with compassion and understanding. Maybe we can break through to people who, you know, are that information, they're, you know, they're being fed just, I mean, it's, it's really and that was one of the challenges as I was writing my book, and I've seen all this play out, like the concept of alternative facts was something that didn't exist you know, before I started writing my book, and in the middle of my book, I'm like, Oh, my gosh, like, alternative facts. Are you kidding me? And so I you know, there's a little bit of that in my, in my book, but this is all unfolding.

I always, as somebody who grew up in data, and always aspired to make decisions based on data, and then seeing all of these actions and in movements kind of undermine all of our progress that we made with becoming a more fact science based, data driven, community or culture, and then falling back into these days and misinformation. It's crazy.

But I think again, I think data stories are a way to get through to people. And if we do it the right way, and we tell these stories in an effective manner. I think we can get through to people at least way more effectively than just hoping that seems to be.

Brent's Book

Gilbert Eijkelenboom: This counterintuitive thing done many people in data they prefer to data right to prefer to rational facts. They should speak for themselves. But of course, in reality, they often don't and I think we should adopt and agree and embrace the fact that emotions plays such a big role in decision making. And by understanding and paying attention to other people's emotions and your own emotions and your own biases. You're much more likely to come up and get your get your point across and yet coming back to your story about dropping facts.

I also remember a story of my cousin when she was 16 years old. I was three years younger, so 13 back then, but I remember the story vividly because my cousin she was 16 years old and she was smoking as she was smoking early and her mother didn't like it, and every other week my aunt read an article in a newspaper saying how bad smoking is with a lot of facts, how many people died, how bad it is for you and how bad it is for your health.

So every time she cuts the news, Dixie got the article and laid it on the bed of my cousin. So every time when she came home from school, there was another article full of facts why smoking is bad. And of course, like you just mentioned to see that she never adopted the narrative, right? Which is more facts and facts. And I don't think our mother tried to understand her perspective, ask questions, started with empathy and, and using a story maybe to get her on the other side.

So I think this shows how ineffective just dropping faxes then absolutely. We talked about data storing and telling a lot and we also talked a bit about presentation skills to be thinking about presentation skills and in data storytelling.

Brent Dykes: Like to share? Yeah, I mean, there's there's different scenarios. There's the scenario where you're, you've got an insight, you build a presentation or a data story and you're sharing that in person with your audience or via zoom or whatever, but it's an in person kind of communication. Now, a very common scenario is I don't have an opportunity to share it with the people I have to send it to them in an email, or I have to basically put it up on an intranet site that way, so there's there's two challenges there. Sometimes people have to do both and I've talked to different analysts. And it's like, not only do I have to present a person, I also have to email it out to everybody else who wasn't at the meeting for them to kind of process it. And I think one of the dangers that we have in that scenario is we get you know, we're trying to optimize our time.

So we're like, Okay, well I'm going to take the version that I would email out to everybody, and I'm just gonna present that to people directly. And one of the challenges that that that creates is because you've got all of your sins and all of your descriptive language and everything in the slides that makes for a horrible presentation. Because what happens is people will naturally start reading your slides and meanwhile, you're talking over and saying exactly the same words. And so that would be one of my recommendations to people to be very careful about that, that they don't present, the version that they're getting email to everybody. You do need to have annotations.

You do have to have notes or whatever to explain the slides or the information to the people who aren't able to hear you in person. But that that is a danger zone when you make that mistake of because at the end of the day, if you're just loading in too much information into your slides, and you're presenting it to people, you're going to lose your audience. They're going to they're going to start to multitask.

Now because they just overwhelmed with too much information. So I think that's one key thing. Now if you're presenting information, and it's something that I've learned in my career, and if you say you have a really big presentation where you've got this really great insight and you're presenting it to the C level executives or the VP level at your company, and you're excited about where this insight can go and interpret things. I think it's important to rehearse your presentation. I think it's important to get feedback from other people on you know, here's my slides.

Let me present it to you. Give me feedback, you know, you're not going to do that for every presentation. But I think if there's a critical presentation, where it's important to career are important to the organization, it's worth that extra time to, to refer to get it down. So you're you can do it cold and you're very familiar with it. It's going to give you more confidence. It's going to position you for success presenting that information. But then also sometimes we're so far in the weeds, and we were looking at our presentation, we're looking at our story.

And then if I share it with you, Gilbert, and then you say well, why did you use this color? Blue for this but then you switched it to green? On these other slides. Oh, I completely missed that. I I'm so focused on the narrative are so focused on making sure everything's perfect, that I miss those little details or maybe have Hey, Brad, have you thought of adding a Client Testimonial, and you talk a lot about the value? That's right. It'd be great to have a qualitative accent, you know, little things like that can add a lot of value. I love getting feedback from other people presentation because it's going to round off those rough edges. And often I get great ideas or great suggestions that you know, take something from being an eight out of 10 to a nine or 10.

Rapid Fire Round

Gilbert Eijkelenboom: Thanks for sharing those steps. And they made them make a big difference. I I totally agree. And going back to your first point about the different versions and presenting something and emailing the same slides I've never met anyone who said I like text on slides, but still, especially in corporate settings. Many slides are full of words. Why do you think that is? Why Why haven't we changed yet? Well, every everyone adopted the same narrative the only correct narrative you have he asked me slides are not supposed to be full of words. But still, in my experience, 70% of the slides are full of works. Well why do you think that is? Why can we adopt this different narrative or put in practice put in practice what we think?

Brent Dykes: I think a lot of it's just easier. I think it's easier for people to bang out their words, you know, explain something with bullet points or write it, write a paragraph. It's like, that's easy to do it actually to actually refine it and get it down to a succinct, concise, impactful, that's gonna take more work, right? It's kind of goes back to that. I think it was Pascal who said I would have written you a shorter letter, but I didn't have time. You know, something I'm paraphrasing. Like, it's the same thing with a lot of the presentation slides. Like they have enough time to really put the effort into it, but they at least want to share the information. Right? So they'll, they'll hammer out a bunch of paragraphs or bullet points, lots of texts, and then they you know, there's the information. I've got it, you know, is it perfect now, but it's it's there. And, and I think that's the problem and we too now I've got back in the day when we could present at conferences. I remember, I would go by conference room after conference or waiting for my turn to present my content.

And I just see these walls of text or ITBS data from L and what data pipelines going everywhere and I'm just like, oh my gosh, like these people don't understand. Like, they're, they're putting their audience to sleep. They're gonna they're gonna pretend that 2% of what they said, and the 2% being who they presented, you know, maybe the topic and that's about it. But it's it's a real problem. I mean, I think there's we we see a lot of complexity, and a lot of the just the general data presentations that I see. And that's again, that's not thinking of the audience. That's, that's making my life easier. I can just data dumped in the information, the text and then deliver it and that's that's all you're doing. You're just informing, you're not communicating.

You're not helping the audience understand what your ship because if you really truly wanted the audience to understand what you're communicating, then you would not do a wall of text. That is not an effective way you know, especially if you're presenting it. That's just but it's, it hasn't changed in the 20 years that I've been presenting at conferences and I don't I don't know what it's going to take but but you know, I one by one if I can convince at least one person not to do that. You know, spend a little bit more time to make something that's actually going to communicate effectively and connect with people. Good, then I hope you're gonna count that as a small.

Different Data Storytelling Framework

Gilbert Eijkelenboom: We, we talked about a lot about your book, which is excellent, a lot of great frameworks, and one in particular, and I was always wondering, what do you think about other storytelling or data storytelling frameworks, and for example, when you think about the pyramid principle, let's start with the key message or the key insight first, and then build the arguments after? What do you think about that? For for use for telling stories with date?

Brent Dykes: Yeah, that's one of the challenges I've run into because I think a lot of times I have people who now listen to how does the data story work? Or how does the story work? You build up to a climax, right? That's basically what you're not giving away at the beginning, the climax of your story, and that's essentially what you do with the inverted pyramid approach. You're basically giving away and so what do you lose? What is what is it that you give up? While you, you lose all of that emotional kind of build up into suspense? There's a lot that you give up and some people even call that inverted pyramid approach, the anti story, because you're basically you're losing a lot of that power.

Now, I also had people who came up to me after I presented on my state data storytelling, and said, I love this, but I I'm not sure whether my executives will embrace it because they're just doing executive summary and then going that way. And so I looked at my model I said, Okay, here's my work. I call it the data trailer. And it's like a movie trailer. But it's the world's worst movie trailer.

Because what I do is I basically say, Okay, there's two elements you take from my framework, you take the hook, which is maybe you've noticed in your it's a major assumption that you've noticed in your data where there's like, oh, this metric went up, or this metric went down. So you're gonna get you're gonna pique their interest with that. And then we're gonna jump to what I call the aha moment where the main insight that you have and so you share that at the beginning in a very concise, quick way.

And the goal of that is not to give them the entire story. It's actually to pique their interest in the rest of the story. So like a movie trailer gives away some of it in this case, it gives away more than just the teaser, it's giving away the the whole climax but but at that point, then you have an executive or somebody who says, well tell me more, and then you tell the rest of the story. And so then you get into the other details of the solution or recommendations that you have. But it's it's a way of it's kind of a way of working around this common approach today because I think I was, I was thinking about why is it that we have executive summaries? Why is it that executives rely on an executive summary so much, it's because we haven't told data stories? We've done data dumps, right? We've done these data dumps, we've dumped a bunch of data, then the executives like So what do you want me to do what you want me to make a decision? What?

Give me the executive summary because I don't have time to go through all of these numbers. And so we've ended up with this kind of executive summary kind of approach, but that is not storytelling. We've neutered the potency of storytelling when we do it as executive summaries.

And so my capitulation or my workaround is the data trailer, that we pique their interest we It looks like an executive summary, but then it draws them into a storytelling framework. And so that's the best I could do. You know, I think that's going to be a common challenge. And in some cases, you know, we don't need to tell again, it goes back to my model. We don't need to tell data stories. Sometimes it's fine to just, here's the information that confirms everything you already knew. Great. You know, there's no there's no conflict. There's no problem there that needs to be resolved. It's like it's just pre mind.

Stimulation in the use of data storytelling

Gilbert Eijkelenboom: We need to change perspectives, right to change their narrative, and then it's more, more useful. And I think we all agree that storytelling and data storytelling is really important. How, how can you stimulate the use of data storytelling or, or foster a culture of data storytelling, if you will, in their organization?

Brent Dykes: Yeah, I'm gonna be rolling out a white paper this year, I got some of the initial ideas, but how do you build a culture around data storytelling? And I think there's there's a number of different layers, but I'll just give some of them. So one is obviously enabling people to have access to data, right? If people are not able to access the data for themselves and we talked about self service with a SIM in different things, but if people are not able to get access to the numbers and the data that are relevant and meaningful to their roles or their teams, that's a first kind of problem that we have because how can you tell stories if you can't access a word, get into it? And then from there, the ability to be curious? Because at the end of the day, honestly, the stories don't happen unless somebody's analyzed the data. If somebody if nobody's analyzed the data, nobody's been curious found something interesting that they wish to share with other people, then there's really not going to be a data story. And so those are, if I'm looking at from a leadership perspective, do I have people are they able to access the data?

Do they have the skills, the knowledge, the ability and sometimes I look at analysts and that analyst role shifting in today's environment, because in the past, what would have with an analyst you say here, I need you to go analyze this, go go, go find me the answer, you know, and that still happens today, but I think that has to shift a little bit to where an analyst is more like a personal trainer.

They're working with these people, coaching them on Oh, yeah, correlation is not causation. Or it could be like little things like that, but they're guiding them to become self sufficient, to some extent, again, I'm not not envisioning everybody becoming data scientists or master analysts or anything like that. But I think there's some coaching mentoring that is now part of the analyst role. And so if you have the ability to access the data you have the tools, you have the bodies to kind of help nurture them.

And then I think giving people an opportunity to present data starts. So that might be on a weekly basis monthly, basically, whatever it is for your organization, but say, hey, I want to learn more about our customers. I want to learn more about our business processes. I want to learn more about what these areas are and inviting people to tell stories to I want it you know in these are opportunities for everybody to learn more about the business learn more about prospects, customers. what's working, what's not working. And so I think it just elevates every week. from a leadership perspective.

I think it's giving people the tools, the people and then the opportunities that the you know, to go up on stage and present stories to the rest of the organization. And then from there, I think it just kind of become secular in the sense that Oh, I hear this religious story that makes me curious. Now I want to go explore this other part of the business and see what I can find and see what stories I can tell on that. And I share those by somebody else.

And the last question is work if they leave you of course, I have this book here. I would highly recommend everyone to get it. It's a small investment, but it's totally worth it. I read it more than once and I use a lot of concepts in my in my training in our workshops. It's a really good book. So that one and apart from your book, what's what else would you like to share about your activities your you turned into an entrepreneur? Where can people follow connect with you?

Where to follow Brent Dykes

Gilbert Eijkelenboom: And the last question is work if they leave you of course, I have this book here. I would highly recommend everyone to get it. It's a small investment, but it's totally worth it. I read it more than once and I use a lot of concepts in my in my training in our workshops. It's a really good book. So that one and apart from your book, what's what else would you like to share about your activities your you turned into an entrepreneur? Where can people follow connect with you?

Brent Dykes: Yeah, there's two places probably the best places. So one is on LinkedIn. Definitely follow me on LinkedIn connect with that I love to connect with people who are passionate about data analytics and data storytelling. The other areas I have a website effective data And so they are I've got some I'm just starting to get some blog posts out there. I've got a few on there already.

Gilbert Eijkelenboom: And then I also offer services like workshops. I speak at events in different things. So I'm always looking for new opportunities to help different organizations with their data storytelling skills. So that's what I've been focusing on over the past five, five months of being an entrepreneur. freshly minted. so it's not about you know, talking a lot about entrepreneurship. But we had such good conversation about data storytelling, and COVID and how we can change people's narratives or just give data if they the story is telling us not necessarily. I think people can take away so much from this episode, and I also learned a lot so thank you for being on the show. Being on the mind thinking podcast, really enjoyed it. And looking forward to speak soon, Brett. Thanks, Brent.

Brent Dykes: Thank you for the opportunity. Gilbert. It's great to be here. Thank you.


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