Alter Everything

AlteryxMatt · ‎01-03-2024

Sometimes, data needs more than just an eye-catching dashboard. Collecting the data is only half the battle. Guest host Kate Strachnyi talks with Data storyteller Kat Greenbrook about how you can effectively weave the story your data tells those who may not know all the details. Kat gives some tips and tricks for data storytelling to others, and how to tailor your insights to a broader audience. Interested in sharing your feedback with the Alter Everything team? Take our feedback survey here

Panelists

Host: Kate Strachnyi - Contact
Guest: Kat Greenbrook – LinkedIn

Topics

Ep 149 (YT thumb).png

Topics

Episode Transcription

Ep 149 Data Storytelling

[00:00:00] Megan: Hi everyone. We recently

launched a short engagement feedback survey for the Alter Everything podcast. Click the link in the episode description wherever you're listening to let us know what you think and help us improve our show. Welcome to Alter Everything, a podcast about data science and analytics culture.

Today, I'm passing the mic over to our guest host, Kate Straschny from DataKated.

She talks with Kat Greenbrook, founder of RoadPenguin, about data storytelling best practices, pitfalls, and more.

[00:00:35] Kate: Hello, everybody. This is Kate Straschny. I'm the founder of DataKated, and I'm super excited to host Alter Everything today. With a very special guest, Kat Greenbrook, a data storyteller. Kat, welcome to the show.

[00:00:48] Kat: Thank you so much for having me.

[00:00:50] Kate: Absolutely. I'm really excited to chat with you. And I think a great place to start is a quick introduction.

So why don't you tell folks all about yourself?

[00:00:58] Kat: Hopefully in a short amount of time. Okay. So I am a data storyteller. I live in Aotearoa, New Zealand. I have been in this space for decades. I got into the field through analytics. I think it's a very common pathway for a lot of people doing data storytelling today, is come through the analytics field, through data visualization to get to data storytelling.

That's not the only way in. So I started my career in a reporting analyst type of role. I graduated university with a science degree in genetics and biochemistry and decided I didn't want to be a scientist. So I fell into business analytics and I've done all sorts of different analytics roles from your reporting analyst, insight analyst through to your more productive modeling data science kind of work.

And I grew increasingly disheartened by the field. I was building these predictive models and they weren't, they weren't doing anything, they weren't going anywhere. And the companies that I was working for, they wanted to be part of this, you know, big data, data science wave, but they weren't necessarily at the point where they could operationalize any of that.

And so they were creating all this amazing modeling and insight, and it just wasn't really creating the impact that I was hoping to create in the job that I was doing. So long story short, I decided I wanted to get out of the field and I took a study in design. So I had this idea that maybe I'll just go and be a graphic designer.

I'd always loved design. So I was working as an analytics consultant and studying part time. And so I graduated with a design degree. And this was around about the time that Tableau was introduced in the New Zealand market. Power BI came a couple of years later. Seth launched Visual Analytics. And this whole wave of data visualization just entered into analytics.

So my whole plan of leaving the field turned into a bit of a, Hey, I'm at the right place at the right time to really lean in quite hard to the field of data visualization. So data visualization was my way into data storytelling. I think the longer I was in data visualization and trying to use that as a way to engage people with analytics.

The more I realized that you need more than just a pretty visual. And that's when, for me, this idea of story became so important because it was that, that added extra that you could use to engage people with analytics. And so for me and the roles that I was doing to create the impact that I wanted. Data Storytelling, that was the icing on the cake.

And so that's where I stayed.

[00:03:46] Kate: Amazing. You know, sometimes when you ask people, you know, what is data visualization? What is data storytelling? A lot of times they'll say, Oh, it's there's, it's an art and a science. And it seems like you've got a degree both in art and science. You've got the perfect recipe to be a data storyteller.

Now you don't, you'd normally see little boys and girls sitting around telling their parents, I want to be a data storyteller when I grow up, right? So I love hearing your evolution of how you ended up getting there. And I think for, for folks listening who might have not have a clear crisp definition of what a data storyteller does.

I'd love for you to just give your version of what is a data storyteller actually do.

[00:04:23] Kat: Yeah. So for me, data storytelling, it's a process. It's a, it's a process to create an effective way of communicating your data insights. And so data storytelling happens after data analysis. I think data analysis is a separate process.

The output of data analysis is hopefully some, some data insight, and then the way that you would communicate that data insight to people, maybe outside of that data team, you can use data storytelling as one of the ways to effectively communicate that. So data storytelling for me is a, is a process of making that information resonate with people who.

Um, Necessarily technical people or don't have the background of the people that found the insight, uh, and it's a way to get them to, to understand and engage with those insights and hopefully go on to create some sort of business impact from that.

[00:05:15] Kate: So should a data story typically be a presentation and email or what does that actually look like?

[00:05:22] Kat: Yeah, good question. A data story can be any way of typically communicating as we do today. So if you think of all the different ways we communicate within a business, yes, we email people, yes, we do presentations, we create visualizations, they're all forms of communication. We can stand around waiting for a coffee and tell a data story.

When we think of data, a data story or data storytelling is just a form of effectively communicating those data insights. You can do it in any way that you communicate in businesses today.

[00:05:53] Kate: Great. And would you say that everyone let's say in the corporate world has to be good at data storytelling? Is that like a necessary skill these days?

[00:06:01] Kat: I don't think everybody has to. I think that's probably a leap too far. Uh, but I do think anybody working with data, if they have to communicate those data insights, they will want to know a little bit about how to effectively do that. I mean, data storytelling is one of the ways that you can communicate those insights.

Dashboards are another way. They're also the difference between dashboards and data storytelling. They're meant for very different audiences. And so when you create a dashboard, you're doing it for an audience who has a grasp of what those numbers mean. They understand the significance of a high or low number.

And so they don't need all that background and that context and that story. But when you're communicating to people who don't necessarily have all that background, you do need to weave some sort of context and explanation and meaning into the way that you communicate those numbers. And that's, that's what data storytelling is.

[00:06:55] Kate: Yeah, I love that. And so for when we add context to a story, let's say we have an audience that is not familiar with the data or the dashboard that they're looking at, is there a personal preference that you have for adding that context verbally? Or would you just type it in as a text box? Actually adding text to the dashboard of explaining things?

Or do you think it's it's more effective to explain it using your voice?

[00:07:19] Kat: Yes. Yeah, I mean, I think it's down to, at the end of the day, your audience, how they would prefer you to communicate. I don't see dashboards necessarily as data storytelling tools because they are designed for two different audiences, but I do think a data story can complement a dashboard.

So if you've got an audience that doesn't necessarily understand the dashboard. When they first see that, if you lead them into it or explain it using a data story, it can help engage people more with that dashboard. So they don't feel like that everything is unknown when they look at that dashboard, because they've had that context explained to them.

So that can be either in the form of a text above the dashboard to help explain it, or it can be in the form of a presentation before giving somebody a dashboard. It's completely up to the audience and how they prefer to be taught that.

[00:08:08] Kate: Yeah, absolutely. So my next question is a bit subjective, but I'd love to hear your opinion on what do you think makes a good data storyteller?

[00:08:17] Kat: So I'm going to go against a trend, I think here, because a lot of the time people think data storytellers have to be good at designing visuals. And I don't think that's true. I think if you want to be a good data storyteller, you have to be, first of all, the good communicator. You have to understand the technical side of things, you don't necessarily have to understand it in detail, but you do need to, to grasp those technical concepts, and then you need to be able to put them in a format that somebody maybe who's not technical will be able to understand, and I think that's the whole bridging the gap between technical versus business.

And in order to do that, you need to speak technical and you also need to speak business. You need to have that business acumen because that's, that's the bridge that you're creating. So I think to be a good data storyteller, you, you do need to have a foot in both worlds, but not necessarily visual.

[00:09:14] Kate: Yeah, that, that makes sense.

I think a lot of people do think that you need to be a designer data visualization expert to be a good data storyteller. Right. But it does have this. large component of being able to communicate and think through how the audience will want to consume the information and format it specific for that audience, because everyone is different and they have, they have preferences.

So I do want to get into tools because I'm very curious when, when you tell a data story, what tools do you use?

[00:09:42] Kat: Yeah, so I have my own personal preferences. I prefer visual storytelling just because of my design background. So the tools that I use to tell my stories are usually design focused. So I use Adobe Illustrator and Photoshop and those kind of really.

design tools, but that's just my personal preference. So I do a lot of training and the tools that people are using could, could be anything from Excel, PowerPoint, your basic, basic tools. But the thing is you don't need to have a really. Um, big expensive tool to do data storytelling. And if anybody sells you on that, I think they don't truly understand what it is in some ways.

Because data storytelling, it's a process. It's not a tool. And part of that process, uh, it's very, very manual. It's very human. And that doesn't necessarily require a big expensive tool. I, there are some tools that will make it easier to, to tell those stories. And so when you're communicating what you, what you've created, the story you found, there are some tools that will make it easy for you to present that, but it's not going to do it for you.

You still need to understand the process and what's involved in actually creating that story in the first place. I think a lot of the time when people do data storytelling is they miss the, the key aspect, which is the data story. They go straight to the visuals and they, they don't truly understand the message that they're communicating.

And, and that's the main part of data storytelling. You need to understand the data story before you're, you can tell it.

[00:11:18] Kate: Absolutely. And so you mentioned that data storytelling is a process. You said that a few times, so very on board with you that I do. I agree that it's a process and the process typically comes after data analysis.

So I wanted to hear at a very high level, what does that process look like for you? So the data analysis is done over to you, Kat, what's your next step?

[00:11:38] Kat: Yeah. So it's, we're talking about a form of communication, right? And so with any form of communication, we need to understand the goal of that communication.

And what are we trying to achieve here? Is it that you want your audience to understand the insights that you found through that analysis? Are you trying to influence some sort of action by sharing those data insights? And so understanding, first, what it is that you're trying to achieve. The next step is understanding who you're communicating with.

So who is going to help you achieve the goal that you've set out to do. So that's your audience. And so understanding who they are, what motivates them, what are things that you can incorporate into your story that are more likely to resonate with your chosen audience group to really get them on board with, with being engaged in what you're saying.

So when you understand, when you understand your why, when you understand your who, and then it comes down to what is your message? Because you want to be able to tailor your message to your audience. This is not about making up a story because those insights are already there. It's about putting them into a structure, into a narrative that's going to engage with that particular group of people you're, you're talking to.

And so this is about really understanding what is your communication, what is your message? And for me, I like to actually write that down. I write that down first and just piece of paper, a pen, that's all it takes. But get really, really clear on what it is that you're trying to say with your data insights.

How are you, how are you structuring that narrative? And then, and only then, do you think about how you're going to tell that story? Now, most of the, the data stories that are told within a business context are visual. So we, we present our data stories in a visual way. And I think this is why the two terms, data visualization, data storytelling, they get confused or people think that the same thing it's, it's because most of the ways that we tell our stories are visual.

And so data visualization does play. A big role in how we tell our business stories, but we need to understand what that business story is first. And so end to end, it's the goal, the audience, the message, and then how do we tell that message?

[00:13:43] Kate: Yeah, absolutely. So for a story to be a data story, does it have to have a chart?

[00:13:51] Kat: No, no, no, I don't think so at all. The thing is, it doesn't even have to have data, which sounds crazy, but we're talking about how do we communicate a message that has been derived from data. And so for some audiences, they don't want to have a whole lot of data thrown at them. They, they actually just want to know what, what it means to them, and they might not appreciate having charts and, and even statistics and numbers thrown at them, but you can understand truly what it means to, to the business, but you don't necessarily have to include a whole lot of numbers and how you communicate that message.

[00:14:29] Kate: Yeah, I think that can actually end up confusing people, right? If you end up adding too much data, statistics and tables into your story, people might get stuck in there, get confused by it. So I agree. It doesn't have to have a chart. I just wanted to ask that question. So moving on. So not every. Person is a great data storyteller, but I think we can all take necessary steps to just get closer to being better every day.

So I wanted to ask what some of your tips were for folks who want to level up their data storytelling skills.

[00:15:01] Kat: Yeah, uh, I think it is the part of the storytelling process that I, that I do think people need to get better at is that, that message that identifying what it is that you're actually wanting to communicate from your data insights.

So if you, if you are an analyst or anybody analyzing data. Generally, the output of your analytics process is a whole lot of different metrics and numbers and how do you figure out what a message is from that can be, it can be a really difficult thing because a data analytics project can, can generate many, many stories.

And so part of the struggle, I think, for people in these roles is to try and pick just one story and tell that well. Uh, and so there are certain building blocks that you can identify within your analytics, within that output. And so you can understand what insights go in what story. I think a big mistake I see people making when they do data storytelling is they try and tell too many stories at once.

And so then try and incorporate a whole lot of different data metrics in there that don't necessarily belong together. And they're just trying to communicate all that they found, but they're putting it into the same story. And whereas actually identifying that, hey, this is a story and this is another completely separate story.

Is a good starting point. Uh, I have a, a canvas that I like to use in my process, which is about how do we just get the right building blocks for the right, for the one story. And it just helps to set the scope a little bit more, but it's about framing a story around just one, one particular data metric.

So pick the data metric that's the focus for your story. You may include other metrics and how you tell it, but if all data stories, I think, revolve around one metric, one piece of insight. And that insight can shape whatever it is that your, your story becomes. And so if you have just one really important insight, see if you can craft a message around just that one, one metric and see, see how you go from there.

[00:17:03] Kate: Yeah. Why do you think people struggle with identifying that one story? Do you think it's because there's like a lack of clear? Understanding of what the issues are that they're trying to solve for, or is it the lack of guidance from stakeholders? What do you think is driving that obstacle of people not being able to tell that one story?

[00:17:22] Kat: Yeah, I think some of it is around, as you say, lack of, lack of guidance and that comes down to identifying the goal at the very beginning. So if you don't identify the goal, that can be really hard to figure out that one, one story. And audience as well, if you have an understanding of your audience, you will know what, what they care about.

And so be able to shape your, where you go as well. I think another part of it is though, that we do want to share what we found and everything that we found. And I'll also go as far as to say, we want to share how we found it. Which is neither a good thing. People don't want to know how you found it. They don't want to know what algorithm you've used.

They don't, they don't want to know that information. But I think sometimes we want to share what we found and how we found it because it shows And in the eyes of the people who are doing the analysis, it shows how valuable they are. And that's a really hard thing to, to break out of and to lose and just to drop that information.

And because you're essentially not telling people. How amazing you are because you've been employed because you have these skills, but you're not shouting about them. And we've got to realize when we're doing data storytelling and we're communicating these insights, people don't necessarily want all that detail of, of our methodology.

They just want our results.

[00:18:44] Kate: Yep, they don't want to know how the sausage is made. They just, they just want it on their plate and in their mouth. That's it, right? They don't want to know what you had to do to get there, the data cleaning process, the going back and forth with IT or whatever you have to do.

But yeah, I think it's human nature to want to say, Hey, I went through all this trouble to get this for you. And we need to just stop that and focus on delivering the insights. Now, one way that I level up skills is I read, I read a lot last year, I read over 60 books and I just absolutely love consuming information in that format.

And I heard that you've got a book coming out, so I'd love to hear more about why you're writing a book and what is this book you're writing?

[00:19:23] Kat: Yes, it's very exciting. It has been so long in the making. Oh my goodness. Ah, I think I had the first idea about six years ago and it's just been off and on and off and on.

So I do, I run data storytelling workshops and I've run these first for six years. And the book is a, it's a handbook. It's called the data storyteller's handbook. And it's everything that I include in these workshops and that I've learned throughout my years of teaching. That will enable somebody to tell a data story and it goes through the whole process, my end to end data storytelling process, how do you identify the goals and what you're trying to achieve and the impact that you're hoping to achieve within the business.

How do you understand your audience better? How do you pick out the right building blocks from your analysis? How do you structure these into a narrative? And then how do you use visuals to help tell that? So it's a whole end to end process. And it's just been something that I have been wanting to put out into the world for a very long time.

And the workshops have really helped to shape where that book has gone.

[00:20:26] Kate: Yeah, that's, that's amazing. I know it's, it's a huge accomplishment and I'm very, very happy for you. Very proud of you. Who, who is the book written for? Who's your target audience?

[00:20:35] Kat: Yeah, so it's for anybody who is struggling to communicate their data insights.

So I've mainly written this with a focus on people doing the analysis. And so a lot of the people that I train, data analysts, data scientists, but I'm also I've seen in the last, maybe the last two years, there's been a real increase in the number of people attending my workshops who not necessarily technical.

So these could be from communications teams, design teams, marketing teams. It just seems to be a whole lot more job titles out there that are having to face this problem of how do we communicate data? And so yes, this book is written for, in mind with those, those analysts, but it's definitely anybody who has to communicate data can, can get something from this.

[00:21:23] Kate: Absolutely. So since we're talking about stories, I want, I was wondering if you have any stories about how a data story has transformed a business. If you have any examples that you want to share about a case study where a data story has actually helped a business.

[00:21:38] Kat: I'm going to reshape this question because I do get asked this question a lot.

And I think if we turn it around and say, do you have an example of how. Effectively communicating has helped shape a business because that's what it is. And if we think of it in those terms, I mean, it's every single day we are hopefully effectively communicating to other people within a business. And now that data has become such a big part of business operations, business strategy.

This is essentially, we're all doing this every day. And so yes, you have, you have examples. Like I have examples of using a data story as part of a business case to help get a million dollar budget. But. The majority of use cases for data storytelling are going to be in those really, really small moments.

They're going to be in, in the opportunities that you get just to, to talk to someone, to share with someone how data is shaping whatever it is that you're doing. And so this could be that you've done an analytics project and you've got some data insights and you wanting to communicate that in the form of a report.

You can use data storytelling to do that. Or if you've got a presentation coming up and you want to share the impact that your work creates on the business, you can use data storytelling to do that as well. So this is not a, you know, a really specific use case for data storytelling. It does relate to so many different opportunities.

And I don't think people realize just how often that it's already occurring that they're already doing this.

[00:23:13] Kate: Yeah, I guess we're just labeling it now. As data storytelling, but we're all doing it when you said effectively communicate. And I'm like, yeah, every email I sent to my clients better have some sort of positive business impact.

And yeah, I do. I do use data to write those communications. So it definitely makes sense. Final question here. I wanted to pivot into AI because I think especially generative AI has just been such a hot topic. I can't cross the street without hearing about it or talking about it. So I wanted to know what impact do you see from generative AI onto data storytelling?

Is it going to make it easier, more difficult? Is it going to impact it in any way in your opinion?

[00:23:50] Kat: I think eventually it will take my job. I say eventually because I think there's a lot of other jobs that will take before mine. But if we, if we look far enough in the future, it will get to a point where even business analysis is at risk.

I don't know how far in the future that is, because at the moment it's nowhere near where, where it needs to be in order to do that. At the moment, it's still a very human process, but I do think that anything that you can follow a process in, is able to be automated or taken over by. Generative AI and data storytelling is no exception.

It's a process and it, it is at risk of being able to be done by someone other than a human. But I do still think that it is a very, very far in the future because we need to understand, we need to learn how to, I think, ask the right questions first. I mean, even just talking to somebody, if you ask somebody, Hey, can you tell me, How the work that you are currently doing creates business impact, it might take them a while if they could even answer that question.

In some cases, this is, this is what I ask people to do at my workshops and it's surprising how, how few people can actually answer that question with tangible results. And so I think, yeah, just, we need to be able to, to truly understand that first before we, before we can automate that kind of thing.

[00:25:16] Kate: Absolutely. And you know, you say at risk, I think it's at opportunity. It, we are at risk of being replaced, but I do see it as an opportunity because I don't enjoy working all day. So whatever Chachi PT can help you with, or mid journey can help you with, go ahead, hang on, help me out. A lot of times it does a better job than I do.

So, or just. At least it gives me ideas and sort of gives me this almost free collaborative partner that is in a lot of ways just has so much more information and ideas in their head. But you're right. It's definitely not there yet.

[00:25:49] Kat: No, it hallucinates. And I love it when you say collaboration because that's, that's what I'm currently using it for.

So I do find it really, really helpful if I have an audience that I don't necessarily understand a lot about. I'll ask chat GPT, you know, what is, what is this audience struggling with? What are the challenges that they would face in that role? And it's a great way just to, to get initial understanding of an audience that you don't necessarily know much about.

And I think it's really helpful in terms of reframing narratives and writing. It can be helpful, but I do find that chat GPT, it can give you something that sounds good, but doesn't necessarily say. Anything helpful. And so it's got, it's got a way to go, but I do think it will get there. And I love that opportunity because yeah, it's, it's who knows, who knows what the future is going to be in the space.

And I think that's what makes it exciting.

[00:26:37] Kate: Yeah. And I mean, I especially can see, for example, for customization of advertisement based on who's watching, right. It can change the messaging based on your gender, your generation, your where you live. It can just, it's going to get crazy. It's already crazy.

It's going to get even more insane. And I'm. I'm here for it. I love seeing all the, all the innovations, but can anything else you want to share about data storytelling before we wrap any last thoughts, hopes for the future, best practices, should people go buy your book where, where can they reach you, any, any final thoughts?

[00:27:08] Kat: Yeah, so absolutely. They can reach me at rogue penguin. co. nz is my, my company website. The book will be available on Amazon. I think final parting words, I think you've just got to. Be open to data storytelling, be open to communicating your insights. I think when you're working in these analytics roles and these technical roles, none of the work that you do, I hate to say it, but none of that matters unless you can communicate that or somebody else within the business who can create that business impact.

Understands it properly. And so it doesn't matter how amazing your models are or how insightful the data is that you're analyzing. None of that matters. And none of the infrastructure and the money that's gone into that matters, unless those insights are. Driving some sort of business impact. We don't, I think, necessarily think enough about what is that business impact that we're hoping to achieve when we're working in these technical teams.

Uh, and so I think a little bit more thought in terms of. Hey, we're, we're all in this to create business impact. That is why we're employed. Needs to, needs to be thought about.

[00:28:25] Kate: I love these parting words. Kat, thank you so much for being on Alter Everything. It's been a pleasure chatting with you. Thank you so much.

[00:28:33] Kat: You too.

[00:28:35] Megan: Thanks for listening. To check out topics mentioned in this episode, including Kat's new book, head over to our show notes on community. altrix. com slash podcast. See you next time.

Ep 149 Data Storytelling [00:00:00] Megan: Hi everyone. We recently launched a short engagement feedback survey for the Alter Everything podcast. Click the link in the episode description wherever you're listening to let us know what you think and help us improve our show. Welcome to Alter Everything, a podcast about data science and analytics culture. Today, I'm passing the mic over to our guest host, Kate Straschny from DataKated. She talks with Kat Greenbrook, founder of RoadPenguin, about data storytelling best practices, pitfalls, and more. [00:00:35] Kate: Hello, everybody. This is Kate Straschny. I'm the founder of DataKated, and I'm super excited to host Alter Everything today. With a very special guest, Kat Greenbrook, a data storyteller. Kat, welcome to the show. [00:00:48] Kat: Thank you so much for having me. [00:00:50] Kate: Absolutely. I'm really excited to chat with you. And I think a great place to start is a quick introduction. So why don't you tell folks all about yourself? [00:00:58] Kat: Hopefully in a short amount of time. Okay. So I am a data storyteller. I live in Aotearoa, New Zealand. I have been in this space for decades. I got into the field through analytics. I think it's a very common pathway for a lot of people doing data storytelling today, is come through the analytics field, through data visualization to get to data storytelling. That's not the only way in. So I started my career in a reporting analyst type of role. I graduated university with a science degree in genetics and biochemistry and decided I didn't want to be a scientist. So I fell into business analytics and I've done all sorts of different analytics roles from your reporting analyst, insight analyst through to your more productive modeling data science kind of work. And I grew increasingly disheartened by the field. I was building these predictive models and they weren't, they weren't doing anything, they weren't going anywhere. And the companies that I was working for, they wanted to be part of this, you know, big data, data science wave, but they weren't necessarily at the point where they could operationalize any of that. And so they were creating all this amazing modeling and insight, and it just wasn't really creating the impact that I was hoping to create in the job that I was doing. So long story short, I decided I wanted to get out of the field and I took a study in design. So I had this idea that maybe I'll just go and be a graphic designer. I'd always loved design. So I was working as an analytics consultant and studying part time. And so I graduated with a design degree. And this was around about the time that Tableau was introduced in the New Zealand market. Power BI came a couple of years later. Seth launched Visual Analytics. And this whole wave of data visualization just entered into analytics. So my whole plan of leaving the field turned into a bit of a, Hey, I'm at the right place at the right time to really lean in quite hard to the field of data visualization. So data visualization was my way into data storytelling. I think the longer I was in data visualization and trying to use that as a way to engage people with analytics. The more I realized that you need more than just a pretty visual. And that's when, for me, this idea of story became so important because it was that, that added extra that you could use to engage people with analytics. And so for me and the roles that I was doing to create the impact that I wanted. Data Storytelling, that was the icing on the cake. And so that's where I stayed. [00:03:46] Kate: Amazing. You know, sometimes when you ask people, you know, what is data visualization? What is data storytelling? A lot of times they'll say, Oh, it's there's, it's an art and a science. And it seems like you've got a degree both in art and science. You've got the perfect recipe to be a data storyteller. Now you don't, you'd normally see little boys and girls sitting around telling their parents, I want to be a data storyteller when I grow up, right? So I love hearing your evolution of how you ended up getting there. And I think for, for folks listening who might have not have a clear crisp definition of what a data storyteller does. I'd love for you to just give your version of what is a data storyteller actually do. [00:04:23] Kat: Yeah. So for me, data storytelling, it's a process. It's a, it's a process to create an effective way of communicating your data insights. And so data storytelling happens after data analysis. I think data analysis is a separate process. The output of data analysis is hopefully some, some data insight, and then the way that you would communicate that data insight to people, maybe outside of that data team, you can use data storytelling as one of the ways to effectively communicate that. So data storytelling for me is a, is a process of making that information resonate with people who. Um, Necessarily technical people or don't have the background of the people that found the insight, uh, and it's a way to get them to, to understand and engage with those insights and hopefully go on to create some sort of business impact from that. [00:05:15] Kate: So should a data story typically be a presentation and email or what does that actually look like? [00:05:22] Kat: Yeah, good question. A data story can be any way of typically communicating as we do today. So if you think of all the different ways we communicate within a business, yes, we email people, yes, we do presentations, we create visualizations, they're all forms of communication. We can stand around waiting for a coffee and tell a data story. When we think of data, a data story or data storytelling is just a form of effectively communicating those data insights. You can do it in any way that you communicate in businesses today. [00:05:53] Kate: Great. And would you say that everyone let's say in the corporate world has to be good at data storytelling? Is that like a necessary skill these days? [00:06:01] Kat: I don't think everybody has to. I think that's probably a leap too far. Uh, but I do think anybody working with data, if they have to communicate those data insights, they will want to know a little bit about how to effectively do that. I mean, data storytelling is one of the ways that you can communicate those insights. Dashboards are another way. They're also the difference between dashboards and data storytelling. They're meant for very different audiences. And so when you create a dashboard, you're doing it for an audience who has a grasp of what those numbers mean. They understand the significance of a high or low number. And so they don't need all that background and that context and that story. But when you're communicating to people who don't necessarily have all that background, you do need to weave some sort of context and explanation and meaning into the way that you communicate those numbers. And that's, that's what data storytelling is. [00:06:55] Kate: Yeah, I love that. And so for when we add context to a story, let's say we have an audience that is not familiar with the data or the dashboard that they're looking at, is there a personal preference that you have for adding that context verbally? Or would you just type it in as a text box? Actually adding text to the dashboard of explaining things? Or do you think it's it's more effective to explain it using your voice? [00:07:19] Kat: Yes. Yeah, I mean, I think it's down to, at the end of the day, your audience, how they would prefer you to communicate. I don't see dashboards necessarily as data storytelling tools because they are designed for two different audiences, but I do think a data story can complement a dashboard. So if you've got an audience that doesn't necessarily understand the dashboard. When they first see that, if you lead them into it or explain it using a data story, it can help engage people more with that dashboard. So they don't feel like that everything is unknown when they look at that dashboard, because they've had that context explained to them. So that can be either in the form of a text above the dashboard to help explain it, or it can be in the form of a presentation before giving somebody a dashboard. It's completely up to the audience and how they prefer to be taught that. [00:08:08] Kate: Yeah, absolutely. So my next question is a bit subjective, but I'd love to hear your opinion on what do you think makes a good data storyteller? [00:08:17] Kat: So I'm going to go against a trend, I think here, because a lot of the time people think data storytellers have to be good at designing visuals. And I don't think that's true. I think if you want to be a good data storyteller, you have to be, first of all, the good communicator. You have to understand the technical side of things, you don't necessarily have to understand it in detail, but you do need to, to grasp those technical concepts, and then you need to be able to put them in a format that somebody maybe who's not technical will be able to understand, and I think that's the whole bridging the gap between technical versus business. And in order to do that, you need to speak technical and you also need to speak business. You need to have that business acumen because that's, that's the bridge that you're creating. So I think to be a good data storyteller, you, you do need to have a foot in both worlds, but not necessarily visual. [00:09:14] Kate: Yeah, that, that makes sense. I think a lot of people do think that you need to be a designer data visualization expert to be a good data storyteller. Right. But it does have this. large component of being able to communicate and think through how the audience will want to consume the information and format it specific for that audience, because everyone is different and they have, they have preferences. So I do want to get into tools because I'm very curious when, when you tell a data story, what tools do you use? [00:09:42] Kat: Yeah, so I have my own personal preferences. I prefer visual storytelling just because of my design background. So the tools that I use to tell my stories are usually design focused. So I use Adobe Illustrator and Photoshop and those kind of really. design tools, but that's just my personal preference. So I do a lot of training and the tools that people are using could, could be anything from Excel, PowerPoint, your basic, basic tools. But the thing is you don't need to have a really. Um, big expensive tool to do data storytelling. And if anybody sells you on that, I think they don't truly understand what it is in some ways. Because data storytelling, it's a process. It's not a tool. And part of that process, uh, it's very, very manual. It's very human. And that doesn't necessarily require a big expensive tool. I, there are some tools that will make it easier to, to tell those stories. And so when you're communicating what you, what you've created, the story you found, there are some tools that will make it easy for you to present that, but it's not going to do it for you. You still need to understand the process and what's involved in actually creating that story in the first place. I think a lot of the time when people do data storytelling is they miss the, the key aspect, which is the data story. They go straight to the visuals and they, they don't truly understand the message that they're communicating. And, and that's the main part of data storytelling. You need to understand the data story before you're, you can tell it. [00:11:18] Kate: Absolutely. And so you mentioned that data storytelling is a process. You said that a few times, so very on board with you that I do. I agree that it's a process and the process typically comes after data analysis. So I wanted to hear at a very high level, what does that process look like for you? So the data analysis is done over to you, Kat, what's your next step? [00:11:38] Kat: Yeah. So it's, we're talking about a form of communication, right? And so with any form of communication, we need to understand the goal of that communication. And what are we trying to achieve here? Is it that you want your audience to understand the insights that you found through that analysis? Are you trying to influence some sort of action by sharing those data insights? And so understanding, first, what it is that you're trying to achieve. The next step is understanding who you're communicating with. So who is going to help you achieve the goal that you've set out to do. So that's your audience. And so understanding who they are, what motivates them, what are things that you can incorporate into your story that are more likely to resonate with your chosen audience group to really get them on board with, with being engaged in what you're saying. So when you understand, when you understand your why, when you understand your who, and then it comes down to what is your message? Because you want to be able to tailor your message to your audience. This is not about making up a story because those insights are already there. It's about putting them into a structure, into a narrative that's going to engage with that particular group of people you're, you're talking to. And so this is about really understanding what is your communication, what is your message? And for me, I like to actually write that down. I write that down first and just piece of paper, a pen, that's all it takes. But get really, really clear on what it is that you're trying to say with your data insights. How are you, how are you structuring that narrative? And then, and only then, do you think about how you're going to tell that story? Now, most of the, the data stories that are told within a business context are visual. So we, we present our data stories in a visual way. And I think this is why the two terms, data visualization, data storytelling, they get confused or people think that the same thing it's, it's because most of the ways that we tell our stories are visual. And so data visualization does play. A big role in how we tell our business stories, but we need to understand what that business story is first. And so end to end, it's the goal, the audience, the message, and then how do we tell that message? [00:13:43] Kate: Yeah, absolutely. So for a story to be a data story, does it have to have a chart? [00:13:51] Kat: No, no, no, I don't think so at all. The thing is, it doesn't even have to have data, which sounds crazy, but we're talking about how do we communicate a message that has been derived from data. And so for some audiences, they don't want to have a whole lot of data thrown at them. They, they actually just want to know what, what it means to them, and they might not appreciate having charts and, and even statistics and numbers thrown at them, but you can understand truly what it means to, to the business, but you don't necessarily have to include a whole lot of numbers and how you communicate that message. [00:14:29] Kate: Yeah, I think that can actually end up confusing people, right? If you end up adding too much data, statistics and tables into your story, people might get stuck in there, get confused by it. So I agree. It doesn't have to have a chart. I just wanted to ask that question. So moving on. So not every. Person is a great data storyteller, but I think we can all take necessary steps to just get closer to being better every day. So I wanted to ask what some of your tips were for folks who want to level up their data storytelling skills. [00:15:01] Kat: Yeah, uh, I think it is the part of the storytelling process that I, that I do think people need to get better at is that, that message that identifying what it is that you're actually wanting to communicate from your data insights. So if you, if you are an analyst or anybody analyzing data. Generally, the output of your analytics process is a whole lot of different metrics and numbers and how do you figure out what a message is from that can be, it can be a really difficult thing because a data analytics project can, can generate many, many stories. And so part of the struggle, I think, for people in these roles is to try and pick just one story and tell that well. Uh, and so there are certain building blocks that you can identify within your analytics, within that output. And so you can understand what insights go in what story. I think a big mistake I see people making when they do data storytelling is they try and tell too many stories at once. And so then try and incorporate a whole lot of different data metrics in there that don't necessarily belong together. And they're just trying to communicate all that they found, but they're putting it into the same story. And whereas actually identifying that, hey, this is a story and this is another completely separate story. Is a good starting point. Uh, I have a, a canvas that I like to use in my process, which is about how do we just get the right building blocks for the right, for the one story. And it just helps to set the scope a little bit more, but it's about framing a story around just one, one particular data metric. So pick the data metric that's the focus for your story. You may include other metrics and how you tell it, but if all data stories, I think, revolve around one metric, one piece of insight. And that insight can shape whatever it is that your, your story becomes. And so if you have just one really important insight, see if you can craft a message around just that one, one metric and see, see how you go from there. [00:17:03] Kate: Yeah. Why do you think people struggle with identifying that one story? Do you think it's because there's like a lack of clear? Understanding of what the issues are that they're trying to solve for, or is it the lack of guidance from stakeholders? What do you think is driving that obstacle of people not being able to tell that one story? [00:17:22] Kat: Yeah, I think some of it is around, as you say, lack of, lack of guidance and that comes down to identifying the goal at the very beginning. So if you don't identify the goal, that can be really hard to figure out that one, one story. And audience as well, if you have an understanding of your audience, you will know what, what they care about. And so be able to shape your, where you go as well. I think another part of it is though, that we do want to share what we found and everything that we found. And I'll also go as far as to say, we want to share how we found it. Which is neither a good thing. People don't want to know how you found it. They don't want to know what algorithm you've used. They don't, they don't want to know that information. But I think sometimes we want to share what we found and how we found it because it shows And in the eyes of the people who are doing the analysis, it shows how valuable they are. And that's a really hard thing to, to break out of and to lose and just to drop that information. And because you're essentially not telling people. How amazing you are because you've been employed because you have these skills, but you're not shouting about them. And we've got to realize when we're doing data storytelling and we're communicating these insights, people don't necessarily want all that detail of, of our methodology. They just want our results. [00:18:44] Kate: Yep, they don't want to know how the sausage is made. They just, they just want it on their plate and in their mouth. That's it, right? They don't want to know what you had to do to get there, the data cleaning process, the going back and forth with IT or whatever you have to do. But yeah, I think it's human nature to want to say, Hey, I went through all this trouble to get this for you. And we need to just stop that and focus on delivering the insights. Now, one way that I level up skills is I read, I read a lot last year, I read over 60 books and I just absolutely love consuming information in that format. And I heard that you've got a book coming out, so I'd love to hear more about why you're writing a book and what is this book you're writing? [00:19:23] Kat: Yes, it's very exciting. It has been so long in the making. Oh my goodness. Ah, I think I had the first idea about six years ago and it's just been off and on and off and on. So I do, I run data storytelling workshops and I've run these first for six years. And the book is a, it's a handbook. It's called the data storyteller's handbook. And it's everything that I include in these workshops and that I've learned throughout my years of teaching. That will enable somebody to tell a data story and it goes through the whole process, my end to end data storytelling process, how do you identify the goals and what you're trying to achieve and the impact that you're hoping to achieve within the business. How do you understand your audience better? How do you pick out the right building blocks from your analysis? How do you structure these into a narrative? And then how do you use visuals to help tell that? So it's a whole end to end process. And it's just been something that I have been wanting to put out into the world for a very long time. And the workshops have really helped to shape where that book has gone. [00:20:26] Kate: Yeah, that's, that's amazing. I know it's, it's a huge accomplishment and I'm very, very happy for you. Very proud of you. Who, who is the book written for? Who's your target audience? [00:20:35] Kat: Yeah, so it's for anybody who is struggling to communicate their data insights. So I've mainly written this with a focus on people doing the analysis. And so a lot of the people that I train, data analysts, data scientists, but I'm also I've seen in the last, maybe the last two years, there's been a real increase in the number of people attending my workshops who not necessarily technical. So these could be from communications teams, design teams, marketing teams. It just seems to be a whole lot more job titles out there that are having to face this problem of how do we communicate data? And so yes, this book is written for, in mind with those, those analysts, but it's definitely anybody who has to communicate data can, can get something from this. [00:21:23] Kate: Absolutely. So since we're talking about stories, I want, I was wondering if you have any stories about how a data story has transformed a business. If you have any examples that you want to share about a case study where a data story has actually helped a business. [00:21:38] Kat: I'm going to reshape this question because I do get asked this question a lot. And I think if we turn it around and say, do you have an example of how. Effectively communicating has helped shape a business because that's what it is. And if we think of it in those terms, I mean, it's every single day we are hopefully effectively communicating to other people within a business. And now that data has become such a big part of business operations, business strategy. This is essentially, we're all doing this every day. And so yes, you have, you have examples. Like I have examples of using a data story as part of a business case to help get a million dollar budget. But. The majority of use cases for data storytelling are going to be in those really, really small moments. They're going to be in, in the opportunities that you get just to, to talk to someone, to share with someone how data is shaping whatever it is that you're doing. And so this could be that you've done an analytics project and you've got some data insights and you wanting to communicate that in the form of a report. You can use data storytelling to do that. Or if you've got a presentation coming up and you want to share the impact that your work creates on the business, you can use data storytelling to do that as well. So this is not a, you know, a really specific use case for data storytelling. It does relate to so many different opportunities. And I don't think people realize just how often that it's already occurring that they're already doing this. [00:23:13] Kate: Yeah, I guess we're just labeling it now. As data storytelling, but we're all doing it when you said effectively communicate. And I'm like, yeah, every email I sent to my clients better have some sort of positive business impact. And yeah, I do. I do use data to write those communications. So it definitely makes sense. Final question here. I wanted to pivot into AI because I think especially generative AI has just been such a hot topic. I can't cross the street without hearing about it or talking about it. So I wanted to know what impact do you see from generative AI onto data storytelling? Is it going to make it easier, more difficult? Is it going to impact it in any way in your opinion? [00:23:50] Kat: I think eventually it will take my job. I say eventually because I think there's a lot of other jobs that will take before mine. But if we, if we look far enough in the future, it will get to a point where even business analysis is at risk. I don't know how far in the future that is, because at the moment it's nowhere near where, where it needs to be in order to do that. At the moment, it's still a very human process, but I do think that anything that you can follow a process in, is able to be automated or taken over by. Generative AI and data storytelling is no exception. It's a process and it, it is at risk of being able to be done by someone other than a human. But I do still think that it is a very, very far in the future because we need to understand, we need to learn how to, I think, ask the right questions first. I mean, even just talking to somebody, if you ask somebody, Hey, can you tell me, How the work that you are currently doing creates business impact, it might take them a while if they could even answer that question. In some cases, this is, this is what I ask people to do at my workshops and it's surprising how, how few people can actually answer that question with tangible results. And so I think, yeah, just, we need to be able to, to truly understand that first before we, before we can automate that kind of thing. [00:25:16] Kate: Absolutely. And you know, you say at risk, I think it's at opportunity. It, we are at risk of being replaced, but I do see it as an opportunity because I don't enjoy working all day. So whatever Chachi PT can help you with, or mid journey can help you with, go ahead, hang on, help me out. A lot of times it does a better job than I do. So, or just. At least it gives me ideas and sort of gives me this almost free collaborative partner that is in a lot of ways just has so much more information and ideas in their head. But you're right. It's definitely not there yet. [00:25:49] Kat: No, it hallucinates. And I love it when you say collaboration because that's, that's what I'm currently using it for. So I do find it really, really helpful if I have an audience that I don't necessarily understand a lot about. I'll ask chat GPT, you know, what is, what is this audience struggling with? What are the challenges that they would face in that role? And it's a great way just to, to get initial understanding of an audience that you don't necessarily know much about. And I think it's really helpful in terms of reframing narratives and writing. It can be helpful, but I do find that chat GPT, it can give you something that sounds good, but doesn't necessarily say. Anything helpful. And so it's got, it's got a way to go, but I do think it will get there. And I love that opportunity because yeah, it's, it's who knows, who knows what the future is going to be in the space. And I think that's what makes it exciting. [00:26:37] Kate: Yeah. And I mean, I especially can see, for example, for customization of advertisement based on who's watching, right. It can change the messaging based on your gender, your generation, your where you live. It can just, it's going to get crazy. It's already crazy. It's going to get even more insane. And I'm. I'm here for it. I love seeing all the, all the innovations, but can anything else you want to share about data storytelling before we wrap any last thoughts, hopes for the future, best practices, should people go buy your book where, where can they reach you, any, any final thoughts? [00:27:08] Kat: Yeah, so absolutely. They can reach me at rogue penguin. co. nz is my, my company website. The book will be available on Amazon. I think final parting words, I think you've just got to. Be open to data storytelling, be open to communicating your insights. I think when you're working in these analytics roles and these technical roles, none of the work that you do, I hate to say it, but none of that matters unless you can communicate that or somebody else within the business who can create that business impact. Understands it properly. And so it doesn't matter how amazing your models are or how insightful the data is that you're analyzing. None of that matters. And none of the infrastructure and the money that's gone into that matters, unless those insights are. Driving some sort of business impact. We don't, I think, necessarily think enough about what is that business impact that we're hoping to achieve when we're working in these technical teams. Uh, and so I think a little bit more thought in terms of. Hey, we're, we're all in this to create business impact. That is why we're employed. Needs to, needs to be thought about. [00:28:25] Kate: I love these parting words. Kat, thank you so much for being on Alter Everything. It's been a pleasure chatting with you. Thank you so much. [00:28:33] Kat: You too. [00:28:35] Megan: Thanks for listening. To check out topics mentioned in this episode, including Kat's new book, head over to our show notes on community. altrix. com slash podcast. See you next time.

This episode was produced by Megan Dibble (@MeganBowers), Mike Cusic (@mikecusic), and Matt Rotundo (@AlteryxMatt). Special thanks to @andyuttley for the theme music track, and @mikecusic for our album artwork.

Alter Everything

Episode Guide

149: Crafting your message with Data Storytelling

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This episode was produced by Megan Dibble (@MeganBowers), Mike Cusic (@mikecusic), and Matt Rotundo (@AlteryxMatt). Special thanks to @andyuttley for the theme music track, and @mikecusic for our album artwork.