68. Connecting the dots between data and insights through storytelling in finance | with Brent Dykes, Chief Data Storyteller, AnalyticsHero

Hannah Munro: 0:48 

So, hello, everybody, and welcome to this episode of CFO 4.0. Now, I'm very excited to say that we've got Brent on today. So, Brent is a bit like me, a bit of a, I wouldn't say a data geek, but certainly a data storyteller, so, much so, that his title is Chief Data Storyteller at Analytics Hero. He's also a published author, but I'm going to ask him to tell you about what in a little bit. So, welcome, Brent. Amazing to have you on the show. 

Brent Dykes: 1:17 

Thanks, Hannah, for having me. 

Hannah Munro: 1:19 

Fabulous. So, tell us a little bit about your journey. How did you end up with such an amazing job title as Chief Data Storyteller? 

Brent Dykes: 1:30 

Well, that comes from starting your own company. So, when you start your own company, you can give whatever title you want to yourself. So, no, my journey started in marketing. So, that's my background. I started in marketing and then got into the marketing analytics space, which was very good because originally, I was debating between going into accounting or going into marketing. And a lot of people would say, oh, you know, if you're good at accounting, Good with numbers, you should just go the accounting degree and you'll be set for life kind of thing. But I was very interested in the behavioural, consumer behaviour side of marketing and enjoyed probably my marketing projects and classes more than I did my accounting classes. So, I went the less popular route and went into marketing. And then after doing marketing for several years, got my MBA. and then decided, you know what, I can't give up the numbers. I really enjoyed the numbers. And at this time, this is back early 2004, There was a company that was hiring, and it specialized in marketing analytics or digital analytics. And so, I was able to join there and then did eight years of consulting, working with a lot of Fortune 500 companies, consulting on their digital analytics strategies and helping them to deploy different solutions. And then I published my first book, which was called Web Analytics Action Hero. And then... From there, I went into an evangelist role for four years at Adobe. So, I was working for a company called Omniture, which was acquired by Adobe. And so, a total of 12 years at Adobe. And then after that, I did four years at a cloud-based BI solution called Domo. And then after that, I did a year at a company called Blast Analytics, a consulting company out of California. And then I published my book called Effective data storytelling. I started focusing on data storytelling. I was very good at PowerPoint. I actually have a website called PowerPointNinja.com. where I do a bunch of... I haven't touched it in a while. So, if anybody goes there and complains that it's not up to date with it. But there's over 100 articles there. So, I was very good at the PowerPoint presenting. And then I noticed as a consultant, when I'd look at clients or I'd look at my fellow consultants, I realized that a lot of times people struggle to really share insights. And that's what got me into data storytelling. And I actually... proposed to every year Adobe would have a customer conference. And so, I proposed to do a session, a breakout session on data storytelling. And this is back in 2013, 2014. And I had to pitch it to them, and they said yes. And then it ended up being one of the most popular sessions at the conference. And that kind of showed me that there's something to this. And then I continued to present at the conference each year for the next two years. And then I realized, you know what, I need to turn this into a book. I need to write my book. So, I spent in 2016, I started writing, you know, all of the different presentations and the things that concepts and frameworks that I developed over the years and turned it into a book and then published it early to 2020. And then just last August, I decided I want to do this full-time and concentrate on consulting and training and really evangelizing data storytelling. So, that's when I went out on my own and gave my title of Chief Data Storyteller. So, that's the journey. 

Hannah Munro: 5:25 

I love that. I've obviously missed a trick, though I definitely need to revamp my title if that's one of the perks. Yeah. Definitely got to think about that. But no, I think it's a really great point because I speak to so, many finance directors that are looking, obviously having the conversation about wanting to shift out of that sort of day-to-day processing role into more of an insight driven role, but actually like connecting the dots between data and insight, and actually communicating that out to the wider, the team and the organization, it can be quite challenging, can't it? And actually, getting your point across and what you found, because it's not just about putting numbers in front of people. 

Brent Dykes: 6:07 

Yeah, I mean, I think that's one of the challenges. I think that there is a certain responsibility that we have in different functions, especially in finance to provide regular reporting of what's happening in the business, right? And that could be through reports that you're generating on a weekly, monthly, quarterly basis. You're going to be building dashboards to kind of help executives get access to that information. But there are going to be those moments where you have a key insight. And I think that's really critical. I define an insight. Sometimes we use that term insight very loosely. And I think that's a problem because really, if we look at what is an insight, an insight is not just an observation. It's not just, hey, revenue was up 23% last week or last quarter. Okay, why? What was causing that? What was driving that? And really what an insight, and as I was writing my book, I had some reviewers come back to me and say, Brent, you use the word insight a lot in your book, but you haven't really defined what it is. And I was like, oh, okay. And I assumed that it was pretty straightforward what an insight was. And then I started looking at the definitions from dictionaries and different things. I was like, no, none of this feels right. None of this feels like it captures the essence of what an insight is. Until somebody shared with me a definition that was generated by Gary Klein, who's a psychologist and author. And he said that an insight is an unexpected shift in the way we understand something. And for me, that was what it is. Say we're looking at the business and we see something in the numbers, something unusual that we are unexpected, that we didn't anticipate, that shifts our understanding of that topic. So, maybe I'll give you an example. Maybe this is a software company, and they think that all of our customers, they buy our product because of feature A. That's why they buy our product. And so, we've invested in feature A. That's what we go to market with. And yet we've done some kind of study with customers. We find, actually, they like feature A, but why they come back to us as a tool or a software vendor that they trust and use is because of feature B. And now we have an insight. oh my gosh, we've been investing in feature A, but all along customers actually want feature B. And so, now with this insight, the shift, now we're like, okay, we have to change what we invest in in terms of our engineering and product resources, our go-to-market strategy. We've been promoting feature A to all of our prospects, and we've completely missed out. We haven't been promoting how valuable feature B is and that changes our marketing. So, as you can see, when we have this shift in our understanding, which is something that we need to jump on. It almost compels us to act because all of a sudden now we're out of alignment with what we thought the world and how it should operate. And so, it's in those moments, you know, if you're in finance and you have one of these discoveries, you have one of these insights, how are you going to, are you just going to leave that in the dashboard and tell somebody, Hey, go check out the dashboard and maybe dig around and you'll see the, no, we're not going to know. We want to, we want to communicate that insight to the audience so, that they can understand it, that they can fully appreciate it and make, A decision, take action on it and change something within the organization. 

Hannah Munro: 9:49 

So, how do we communicate that insight in a way that grabs people's attention or allows them to understand the impact of what they're seeing? Because like you say, stuff can get hidden, can't it? Somebody produces so, much data at the moment. Is there a framework that we should be using to share this insight? 

Brent Dykes: 10:09 

Yeah, I mean, one of the standard ways of communicating information today, and this is very common in finance, is the pyramid principle, right? Or the pyramid approach where you come out with the insight, you share the insight upfront, and then you dig into the details later on. And so, this is typically a method that's designed for executive summaries. You know, we give them the information upfront. My only concern with this approach is it can be very efficient, and I'm not downplaying that it doesn't play a role in our communications. But when we have one of these significant shifts, I think we need to take a different approach. And if it's appropriate, and usually, when do you tell a data story? You build a data story when you need to shift the narrative. If you're just supporting the existing narrative, you don't need to build a data story. You're just providing complementary or additional information that already supports the existing narrative that people have in their minds. But when we need to shift the narrative, that's where we need to create a data story. We need to create a new narrative for people to fully understand. So, what's involved in that? In my book, I talk about a framework So, when I started going down the path of data storytelling, I was like, what can we borrow from the existing kind of frameworks around storytelling? And one of the most familiar models comes to us from Aristotle. More than 2,300 years ago, this Greek philosopher, he studied Greek tragedies, and he looked at the arc that they went through. He basically said that there's the three... Actually, he didn't say that, but people have interpreted it that way. What he actually said is there's a complication. There's something that happens in the story. And he compared it to tying a knot in a thread. And so, the knot is tied. And then that leads up to the climax, right? And then the rest of the story is unravelling that knot and then concluding the story. And so, a lot of times when we talk about data storytelling, it's in the sense of a beginning, middle, and end. But as I was building my methodology and looking for guidance, I was like, that doesn't really help. I mean, I could point to a report, and a report has a beginning, middle, and end. So, I felt like I needed something more substantial, and I kept looking. There's another model out there that's very popular. It's called The Hero's Journey. It's by Joseph Campbell, who is actually, he was a mythologist, and he studied legends and fables back in the 1940s, 50s. And he came up with, it's kind of more of a circular journey that the hero goes through, where they go through this transformative kind of process. And George Lucas says, actually used that model for his first Star Wars movie. So, Luke Skywalker went through all of these kind of stages that mirrored Joseph Campbell's hero's journey. But from a business context, originally when Joseph Campbell designed it, it had 17 different stages and some people have simplified it down to 12 or 8. But still, in terms of applicability to a business scenario, I didn't I didn't really find it that useful. And so, I kept looking. And then I came across a model that was by Gustav Freytag, who was a German playwright back in the 1800s. And he studied Shakespearean plays. He looked at the Greek tragedies. And he also found that they had this arc, this story arc. And in his model, there's five hacks to it. And when I looked at that model, I said, you know, this is something that I could apply to business storytelling or to data storytelling. And basically, the way the way the art works is the first step or stage is to really establish the context, right? So, we're establishing, what are we looking at here? What is this data we're looking at? What are the expected or normal patterns or trends or behaviours that we see in the data? And so, we established that up front with the audit. So, we put them in. We're going to talk about this. And here you can see, let's say, retail example. We can see that there's certain retail patterns that we see in our data. But and then we get to the first, and typically what people call this is an inciting incident in this model. But in our case, we don't have, you know, we're not talking about a fictional story here. So, we're using nonfiction, we're using data. But in our case, what is that inciting incident for us? It's that first observation, that major observation that we see where, oh my gosh, there's an increase in our conversion rate or there's a decrease in our conversion rate. Something unexpected has happened in the data. We don't know what's causing it, but It's something of interest. There's something going on here. And then from there, then we start to drill into, well, what's causing this change in our conversion rate? What's contributing to it? And then we start to share more data and more data and more examples building up to our climax, which I call the aha moment. And this is the main takeaway that we want the audience to take away from our presentation or from our analysis. And this is If they don't remember anything else, we want them to remember this key point. And so, we build up to that from what I call the rising insights. We build up to our aha moment. And then typically in a normal story, you'll have this resolution, and everything will kind of come. Well, in a business context, the resolution is that we know how to act on that insight. And so, we, our analysis isn't done. Just here's the insight. Good luck, you know, executives make a decision. Oh, we have to then inform and guide that decision-making process. And so, we may go in and actually, you know, explore the different options that they have. You know, here are three options. We could do this, A, B, or C. And we've analysed, you know, what is our recommended approach? And then we provide that to the audience. So, we could, we can mirror this story arc process in how we present our findings, how we present our insights. And the goal is to a couple of things. One is to help the audience learn about the business, right? We're talking about a process. We're talking about our customers. We're talking about our product. These are things that can go and help them learn more about the business so, that they can be smarter and hopefully over time make better decisions. However, in this specific case, what we're doing is we're actually looking at driving a particular action. We're taking this insight that we've had, and we want to drive action and drive change. Because ultimately, as I write for Forbes a lot and I obviously publish a lot of content on LinkedIn, one of the things I really hearken upon is all of this investment in analytics and data If we're not acting on it, if we're not taking action on it, we're not going to drive any value. And so, I see data storytelling as a mechanism for driving action, for informing decisions, obviously, driving action, and then obviously realizing value from all of these investments in this data that we're collecting. 

Hannah Munro: 17:46 

Yeah, I know, because data collection is just the start of the story, isn't it? I have this conversation a lot. I'm like, collecting all this amazing data is brilliant, but if you don't do anything with it, you know, you're not adding value to the organization. And I have a lot of these kind of conversations. People get so, wrapped up in, you know, is every T crossed and is every I dotted? But the piece that it does come back to is, you know, what does that mean for the business? What is the step that you think we should take with this? So, I love that framework It's a really great. So, if I just summarize that step. So, obviously inciting moments, you know, or, you know, you know, recognition of the fact that there's, you know, something coming out. Then obviously the steps into the aha moment and what that means. And then obviously coming up with then the solutions. And I guess your conclusion and final recommendations for how you would take that forward. Have I got that right? Have I missed anything in terms of steps? 

Brent Dykes: 18:42 

Yeah. No, no, that's it. And in the book, I call the inciting moment... Obviously, the inciting moment comes from the literary version. I call it the hook. So, we need a hook. And that hook is really... And here's the interesting thing. When I talk about this with different people, I sometimes say, if you're in finance or you're an analyst or something like that, the business may have... The executives may have come to you with the hook already because they look at a dashboard, they look at a report and they say, hey... What's going on here? Why did this go up, you know, 30%? Or why did this go down 50%? They've already given you the hook, you know, because that's what's caught their interest in the data. Now, obviously, your job is to go in sometimes and explore, okay, let me take some time and understand why that went down or why that went up. But your audience may have already given you the hook. That's the interesting thing. And then in that case, you're like, remember when you asked about why our returns were up 25% last quarter. Well, I've looked into it and here, you know, and here's the story. And then, you know, here's the action we need to take. And, and then, you know, it goes from there. So, I found that this model can be very helpful. Now I've had some people push back and say, Brent, I love this model, but you know, I, I think my executives, they, they want something, you know, more like the pyramid principle. They want it very quick. And, and so, in that case, I I've, added something to the toolbox as data storytellers. And this is something you can pull out in these situations where you have maybe an impatient executive who just wants the numbers. And I call it the data trailer. So, the data trailer is a modified version of a data story. It's not the full story. In fact, if you think of it in terms of a movie trailer, it is the world's worst movie trailer. Because what we're going to take is we're going to take the aha moment and we're going to take the hook and maybe sprinkle in a little bit of context, and then we give it to them that way. And our goal by giving them, we're essentially giving away the climax of the movie or the climax of our data story with the aha moment. And the hook is to pique their interest, to hear the rest of the story. And so, that's a modified version of storytelling where in some cases we're not really storytelling, we're breaking the model of storytelling. Because storytelling is really about building up the tension, the conflict, the interest, the emotion to that aha moment. In this case, with a data trailer, we're sort of deviating from that plan and giving them the highlights right out of the gate. But our goal is to tell them the rest of the story once they hear that data trailer and, you know, get curious and they want to learn more. 

Hannah Munro: 21:28 

So, how would you share that data trailer with them? Like what of the, you know, the different framework that we just talked about, the parts that make it up. So, how, what would you include? Would you include any of your recommendations and conclusions or would you just literally go sort of inciting moment and then aha moment and then hope that that's enough to get them to actually read? 

Brent Dykes: 21:48 

Yeah, then it starts a conversation or it's like, oh, I mean, there's one of two reactions we'll get. We'll get, oh, that's interesting. Thanks, but no thanks. Not interested in learning more, right? Or it's like, well, wait, how did you get, you said we're going to save $2 million by making this change to our recruiting policy? Explain that. How did you get there? And then it's like, okay, all right. Now that I know I've got more than two minutes, I've got now maybe 10 minutes or 20 minutes to go into the rest of the story. Now I've kind of hooked them, right? So, I can unravel. And at least we're having a conversation at that point. But that's the shift that we're just going to give them the hook We're giving the aha. And then what we're leaving out is all what I call the supporting details between the hook and the aha. So, they're going to ask that probably. Well, you said that you noticed this metric dipped. And then how do you get to that conclusion that it's going to cost us X amount of dollars? or pounds or whatever. And so, then we're starting a conversation, we're getting them curious, and then hopefully we can then go into the rest of our data story that we've prepared. 

Hannah Munro: 23:08 

So, we've talked a lot about the concept of a story, but we haven't actually talked about how we convey that story. So, how do you think information and stories are best told through pictures, through bullet points, through actual narrative? What's your recommendation when putting these data stories together? 

Brent Dykes: 23:29 

Yeah, I think that obviously there's three core elements of every data story I talk about are data, narrative, and visuals. And the interesting thing, and we can't do this, it's harder through a podcast, but let me see if I can descriptively do this. So, there's this, you have three bubbles, right? And it's kind of like a Venn diagram where they're overlapping. And if we look at the overlapping between the narrative bubble and the data bubble, Okay, so, if I were to give you a spreadsheet or a report and just said, here you go, Hannah, can't you see that there's this great insight here that I've uncovered? And you could look at that spreadsheet and you could say, yeah, I'm not seeing what you're seeing. And I don't have the context. I don't understand this data. And so, what do we do? We have to pair the narrative with the data. And so, we have to help explain that. That's what we're doing with that narrative going with the data. I'm going to walk you through the numbers. I'm going to give you the context. I'm going to give you the meaning behind the numbers. And so, that's kind of like the first intersection of those two bubbles. Now, the other thing that we do a lot, the intersection between the data bubble and the visualization bubble or the visual bubble is often when we look at a spreadsheet, we miss things. And I know, obviously, from a finance background, You guys are very comfortable with using data tables. But there is a place and there is opportunities to use visualizations. And often we can't see anomalies or patterns or trends in the data as clearly without the help of visualization. And so, visuals are often when we're working with very complex data systems. visualization can get to the main point much more quickly than if we actually go through the rows and columns of data and try and tell the story that way. And so, that combination of visuals with data is enlightening to the audience. It's going to enlighten them to things that they would perhaps miss if we didn't visualize the data. And then the last two bubbles and the intersection between those are the narrative and the visuals. And the reason why we all binge watch our favourite TV shows, and our streaming services is because as human beings, we like to have a story. A visual story is very compelling. It's engaging to us. And so, that combination is very powerful as well. And so, if I combine the right data with the right visuals and narratives, all of a sudden, I have something that can be very powerful, that can change the way we see the world and open our minds to new perspectives and new insights. And so, what are we doing in this case? We are taking visuals where appropriate. We are adding that commentary, the meaning, the context behind the numbers, and then using the right data, right? That's another thing that we... I talk about data being the foundation of every data story. And often that means being very selective and very strategic and very targeted with the data that we choose to put in our data stories. Because ultimately, our audiences will only care about certain data information. And if we're telling it, it could be an amazing story, very, very fascinating insight. But if it's not tied to their business priorities, their goals, objectives, then they're going to pat me on the head and say, Brent, that was very interesting. You've just wasted 30 minutes of my time or 10 minutes of my time. Because I'm not worried about that. I've got these three goals over here that I'm trying to drive. And you've just told me a story that that is very fascinating but completely useless to me in this moment. And so, you know, we always want to make sure that we... And that's another key thing. We want to understand our audience. We want to deliver data stories that are meaningful, impactful to them. And that's going to start with understanding our audience and understanding... What's important to them? What are the areas that they're focused on in the business? And then from there, once we have that understanding of the problems, the outcomes, or the activities that they're focused on, then we can have really good insights that go into our data stories. And we're going to have meaningful, compelling stories to tell them. And so, Yeah, that's kind of the crux of it. Those three elements coming together to really help us tell or impact how we share our insights in a meaningful way. 

Hannah Munro: 28:09 

Yeah, and I think that's a great shout out because, yeah, obviously working with a lot of finance people, we are very, very comfortable with long rows of numbers. I think it comes back from the days of doing T accounts, right? So, everyone is quite comfortable with massive amounts of data, but the rest of the organization isn't. Like you say, you can quite easily become number blind, can't you, when you're looking at data and certainly massive spreadsheets of information. So, I think it's a really good point. And I always say visuals are for bringing attention is kind of how I talk about it. And I love that concept. And then, like you say, the context and the backup, because you've always got to have the numbers to back up what you're telling and saying to the organization. So, that's a really great framework, I think. And it's a great framework food for thought for our listeners. So, in terms of what you see, like what are the biggest mistakes you see when people go to communicate insight, go to communicate what they found? What are some of the mistakes that you often see within organizations? 

Brent Dykes: 29:15 

One of the, you know, if I look at the functional areas like finance and like analytics and the areas where they have, they're accustomed to using and working with a lot of numbers and data is the curse of knowledge. And so, the curse of knowledge is where it's hard for us to not know what we know, right? And so, we expect people to see it the way we see it. And that goes back to my earlier comment about the audience and understanding our audience and showing empathy, taking it from their perspective. They haven't spent hours or weeks or days in the numbers like we have. They may not have the full context into what we're seeing. And so, that's where we have to kind of, and in the book, I talk about, there's two phases that we go through when we're doing any kind of analysis. The first phase is the exploratory phase. And that's where it's just about us, right? We're just using different data sets. We're visualizing the data for ourselves. We may have a hunch or a hypothesis of what we're looking for in the numbers. At this point, we don't have a story to share. And when we find that insight, there’s a shift that must occur. And then we need to take it from, it's not about what works for us and what communicates to us, but how do I then convey the same information to other people who haven't spent as much time in the data or maybe aren't as familiar with where the data came from, what it means and all these things. And probably they're not going to sit down with us for five hours and go through all of the nitty gritty of what we found. And so, it's kind of, okay, how do we then, we need to manage that shift effectively. And I think that's the disconnect. A lot of the time, I think a lot of, it's a combination of that curse of knowledge where people who are very comfortable with working with the data and know the data inside and out, then struggle to then communicate it to other people because they can't not know what they know. And that's the challenging part. They need to have empathy for their audience. They need to step back and say, okay, I don't need to share all of this information. That's one of the first things you could do. You could just say, do I need to share all 10? Say we're looking at 10 countries. And at the end of the day, no, I don't have to share the data for all 10. Yes, I looked at all 10 countries when I was exploring the data, but our insight was really related to two of those countries. So, all of a sudden, I just said, you know what? It's not like I'm showing how hard I worked or how smart I am. Look, I looked at all 10 countries and then I was able to, no, nobody cares. Just tell me about the two countries where there's actually an issue going on and the story. So, it's like the ability to edit ourselves. If we think of movies, right? So, sometimes you see that with different directors. They're given too much license because of you know past successes or just they're really successful and so, the studios will say okay well you know maybe they're not as aggressive on editing and then and then ultimately the director feeling like they you know they've got everything perfect they end up with this monstrosity where if people have just gone in and actually done a good job editing they could have saved that movie it could have really communicated really well to the theatre audiences. And so, the same thing applies to us. Sometimes we're not able to, or we don't take that step to edit ourselves and really step back from what we're doing and say, how is this going to connect with other people who aren't like us, haven't spent all this time and maybe even don't have the technical skills or the analytical skills to really appreciate everything that we've looked at. But at the end of the day, we're trying to drive action. We're trying to equip them with the knowledge and the insights and the information that they need to make an educated, smart decision. And so, I think it's that we need to be aware and we need to make sure that what we use in our exploratory side isn't the same material that we just hand off to other people. We need to edit it. We need to curate it. We need to go through and really structure make our key points really stand out. Going back to what I said about the 10 countries, we remove the data for the eight countries that aren't relevant. We don't need to leave that data in there. And then by doing that, we sharpen our focus, we strengthen our story, our insights come out more clearly, and then the audience benefits because they're going to get really useful information that's going to help them to manage the business and make smarter decisions. 

Hannah Munro: 34:12 

And is there a case then for actually an editing and review process internally around the story that you're actually telling? Like, do you recommend people have some sort of editing format that they follow once they think they're where they need to be and they think they've said the check? Almost just like with a fresh pair of eyes. Does this make sense having got the context from somebody that hasn't been playing in the data? 

Brent Dykes: 34:38 

Yeah, no, I, I think that's a good, I mean, we can, we can try and do that ourselves, but another really good, uh, approach is to ask a coworker, ask a colleague. I mean, I've even seen some people ask their spouse or their partner, um, you know, who maybe has no context to do the business or, or, you know, what, what point you're trying to make, but, but that's a good test to see, you know, it are my key points coming across, which, which of these, um, charts or visualizations were helpful. You know, did I word this the right way? Is, is it clear what the takeaway is from the slide? You know, those are all questions that we can get from, from getting an outside voice, getting a, you know, like we, that's part of the challenge is sometimes we're so, in the numbers, so, in the weeds that pulling ourselves out of it can be challenging. And so, I think it is, I think it is a good step to kind of do an Especially for an important presentation where it's like, you know, there's some, I've invested a lot of time in this analysis, building this presentation. This could have a big impact on my career, or this could have a big impact on the business. Making sure, validating that and checking with other people. I mean, often I've done that in my own work and have gotten amazing feedback, you know, where it could, maybe it might be where I, completely missed something. You know, I was completely blindsided or, you know, I was railroaded into, I was very fixated on one particular thing. And then somebody comes in with an external perspective and say, well, why didn't you talk about this? Oh my gosh, I completely missed that. Or even like, I just, I don't understand what you're doing here. You know, this doesn't make as much sense. And so, then I'll iterate, and I'll say, well, how about this? Oh yeah, that's way better, you know? And so, that process of getting familiar feedback from other people is really beneficial as well. So, I would definitely encourage that as part of the process, definitely. 

Hannah Munro: 36:34 

And one of the challenges here is that, you know, certainly if we're talking through it, it sounds like an elongated and a long process that you go through. And obviously one of the challenges that we have at the moment is how do we get data in front of the right people fast enough? So, is there any tips you can share about obviously doing the right level of depth of storytelling and making sure we've got everything right but balancing that with the need to get insight out to the business quickly. 

Brent Dykes: 37:01 

Yeah. In my book, I talk about there's two, you know, I've had people say, do dashboards or reports tell data stories? And I would say most of the time they don't, but that's okay. They're important. Again, going back to your point, we need to get information out there. We need to get that into the hands of people. We need to provide monitoring of business performance and results. And so, I see it as kind of like a funnel. I talk about it being the insight funnel. The top of that funnel, what we do is I call it story framing. So, we take the reports, the scheduled reports, the dashboards, the more automated ways of getting information to the hands of people. And what are we doing? We're not providing all of the data on the business to everybody. No, we're targeting it down to the key performance indicators, looking at the data from the perspective of the goals and the priorities, the strategic priorities that the business has. And so, that is the top of the funnel. And so, we want to get that out there. We want to provide that to people. And in some cases, that's sufficient. I might build a dashboard for somebody and it's an individual contributor, and they can manage their aspect of the business from that dashboard. They don't have to share anything with anybody else. They can just look at their dashboard and make decisions on whatever it is within their scope of work. Now, where storytelling comes in is when you have an insight that requires action from a group of people or a decision from a group of people, that's where storytelling comes in because now I have to share the information with them in a way that is explanatory, helps them to make a decision. And so, if we were looking at that funnel, I think the wider part of the funnel is going to be those dashboards and reports. That's going to do the bulk of the information sharing. It's only when we have an insight that needs to be analysed or we have a group of data that needs to be analysed, we see an observation in a dashboard, and now we're like, oh, wait a second, what's going on here? We do some analysis and then we report back on the findings of that analysis and the recommendations that we have. And so, I see it as we're doing a lot of that regular reporting and that's going to be happening on a recurring basis. We definitely don't want to just hoard information until we have enough to share a story. No, I see it as we're going to be sharing that information constantly. But then in those strategic moments where we have an insight that is critical to the business, that needs to be shared with a bunch of people to get their buy-in or get their approval or get budget or resources or what have you, then those are the times we're going to have to craft a data story. And so, it complements all of the other work that we're doing. But it's another tool in the toolbox and it's used strategically when there is that bigger decision that must be made and maybe it is related to a shift in the narrative that needs to occur. 

Hannah Munro: 40:13 

So, I know probably a lot of the CFOs listening to the podcast are going, this sounds brilliant. You know, I've got a team, you know, where we're looking to shift from traditional sort of bean counter and more transactional accounting into more finance business partnering, where we're working with other areas of the business to help them understand and deliver insights. So, you know, assuming that they've got that team ready, that they have time and capacity, what are your top tips for getting them into the right habits for data store storytelling and how do they get started? What would you recommend as an approach? 

Brent Dykes: 40:49 

Well, a key thing is obviously you've got to have curiosity into the data. And I think one of the challenges I've seen is a lot of people are accustomed to generating words and dashboards. And that's kind of a different mindset. It's a reporting mindset. And the data storytelling mindset is dependent upon analysis. And so, one of the things you obviously have to be curious, and you have to allocate time. And so, one of the biggest challenges I've seen with a lot of teams is like, this is great, Brent. I love the sound of telling data stories, but I'm already maxed to the hilt already with reporting requirements and ad hoc reporting and different things. How am I going to find time to do storytelling? And so, I often push back on them and say, have you automated as much as you can of the menial, labour-intensive kind of tasks that you have in terms of reporting and distributing information? And often the answer is no, we haven't. It still takes us a while to prepare each report. And so, I would say you want to free up time by automating and improving whatever you can on that front from a technology perspective or outsourcing perspective or whatever makes sense because you want to free up your strategic resources to really focus on doing data storytelling. And that starts with allocating time for analysis and the deep dives. And really data storytelling only comes in when you're, once you have these insights that you want to share, how do you do that in an effective way? How do we communicate them in a way that's going to resonate with people? And so, I think that first step is to obviously automate as much as you can on the menial tasks allocate time for analysis. And then you have opportunities for data storytelling. Now, one of the things I've also found is that you have these cadences of sharing reports and things over time. And often I was talking to one guy, and he shared how his company would have this big meeting where they'd bring together all the divisions. And it was a great opportunity for his analytics team to kind of show all of the data that they are collecting and different things, but he wanted to move away from that. He wanted to tell more data stories, but he also knew that there was an expectation about this reporting. So, I suggested to him to insert, obviously you're not going to go away from something that's successful if their recurring reporting is important to the business, but what you might start to do on that, if it was a monthly cadence, you might want to say, oh, here's the monthly reports, here's all the updates. oh, and by the way, now we're going to start to share with you one data story per month, you know, if we find something of interest. And so, then what they could start to do is, you know, they cover all the reporting, but then they insert, you know, we took a look at this process, or we took a look at this part of the business, or we took a look at this function, we did a deep dive, and here's an insight, or here's a data story that we've found that we want to share with you. And I think as you start to share these data stories and having a platform or an opportunity to share data stories, we love, as human beings, we love to hear stories. As I talked about, we binge watch TV shows. We share stories with our colleagues at work. We share stories with our families and friends. I mean, we are storytelling creatures. And so, I think providing an opportunity for people to share stories We'll do a couple of things. It'll enhance people's data literacy because as we tell data stories, we're exposing people to data. We're also enhancing their knowledge of the business. And I think it will also pique their curiosity because as we share these stories and people are like, oh, I wonder what's happening in my part of the business. That was interesting what they did for that part of the business on the B2B side. I'd like to see how we perform on the B2C side. or vice versa, or, you know, oh, that's great, that works, that's interesting, sorry about the UK market, but I wonder what's happening in France, or I wonder what's happening in Germany. And so, you know, that's what I think the benefit of storytelling is, is it obviously elevates everybody's data literacy, but also gets data curiosity, and then, you know, it's easier that, you know, we're bombarded with information all the time, but if we put it into a format, into a structure that as human beings really connect with us, our data and our insights are going to go so, much further. 

Hannah Munro: 45:39 

No, absolutely. And I love that. Creating a tidal wave of curiosity and requests for insight and requests for data stories going the other way. So, I literally think I could talk to you about data and stories for hours, but I'm not going to. So, just to wrap up. So, if anyone would love to learn more about yourself, Brent, and what you do, or perhaps read one of your books, what's the best way for them to find you and find your material? 

Brent Dykes: 46:09 

Yeah. So, my book is, you can find it on Amazon, a lot of other online booksellers. It's called Effective Data Storytelling, How to Drive Change with Data, Narratives, and Visuals. You could go to the website for the book, which is effectivedatastorytelling.com. And there you will find links to the book and also, I offer services as well. So, training, workshops, virtually, hopefully in person sometime in the future once COVID kind of goes away. But also, I offer consulting, speaking engagements. If your organization wants to get excited about data storytelling or exposed to data storytelling, that's another thing that I often do. And coaching as well. There may be teams out there that are just starting to dip their toe into data storytelling, but don't have a lot of mentors or coders who can help them to kind of ramp up their skills quickly. And that's another offering that I provide. And I also have, you can also, sorry, the other thing I would mention is I'm also a Forbes contributor and I have over 40 plus articles. So, if you do a search for Forbes and Brett Dykes, you can read a bunch of articles that I have there. 

Hannah Munro: 47:22 

Yeah, if anyone that's listening, I will put the links to, to Brent's book in the show notes and the website. And because it was actually a Forbes article that I found Brent through, actually, it was a great article. So, you know, I think I shared it in our monthly CFO update. So, for those that are interested, I will put those links into the show notes. And yeah, I just want to say thank you so, much, Brent, for joining us. It's been a fantastic session and it's been great to hear your insight. 

Brent Dykes: 47:55 

Thanks, Hannah. Thanks for having me on. It's been fun. 

Hannah Munro: 47:58 

It's been brilliant. And so, if you have enjoyed today's session, I would love to hear from you. So, messaging myself, or even better, if you leave us a review on this episode on the podcast, it helps us to basically understand whether we're doing a good job, whether this podcast is resonating with you. And if you'd like more on this topic of data storytelling, please do let me know either way for directly through my LinkedIn or through leaving us a review on any of the main platforms, more than happy to take that feedback on board. And again, we're going to be having more conversations on data, on insight. So, stay tuned. And if you have any thoughts on potential episodes moving forward, then let me know. And I want to say thank you again, Brent. Great to have you on the show and looking forward to catching up with you guys next time.