Data visualization field is rather diverse. There are people working as journalists, creating data stories, then there are graphic designers creating beautiful infographics, also we have business people making presentations and dashboards, and finally, we have scientists making scientific charts. All these types of visualization are quite distinct and have different requirements.

While it is OK to put some artistic flair into an infographic, it might be frowned upon in a dashboard or scientific visual. They also differ technically – infographics are static visuals, Scrollytelling – is one long story, where presentations and dashboards are sequences of pages. But then presentations are shown by someone else, while dashboards are navigated by readers themselves.

According to surveys run by Data Visualization Society – BI tools like Tableau, and Power BI are among the most popular ones. (Source: survey results from 2023 visualised) And yet, everyone, regardless of what field are they in, seem to be excited about data storytelling!

There are multiple brilliant books about data storytelling like “Storytelling with Data“, “Effective Data Storytelling” or “Data Storytellers Handbook“. The first one focuses on presentations, the second one explicitly tells that you cannot have storytelling in a dashboard, and the third one reaffirms that message. Storytelling is a very specific, skill and while it is useful for a variety of business, creative, and life situations, but it’s use for dashboards is limited.

Saying that you can do storytelling in a dashboard is like saying that you can travel from Lisboa, Portugal to New York on a bus. Of course, you can put a bus on a boat and cross the Atlantic Ocean while sitting in a bus. Technically, you did what you claim, but obviously that was a hack. The only way to have storytelling in a dashboard is to create slides in Tableau or Power BI. Technically, you did what you claim, but obviously that is not a dashboard – those are slides.

Why people keep telling that you can have storytelling in a dashboard then? Well, the reasons are two – either they are trying to sell you something, or they have no idea what they are talking about. “Storytelling” is a big buzzword, here is an article analysing the whole hype cycle for this one (peak storytelling), so, “storytelling” sells. I am personally guilty of this, I did numerous Power BI trainings called Visual Storytelling.

So, why cannot we have storytelling in a dashboard, and what is that often overlooked critical skill specifically benefiting dashboard creators?

Why can’t we have storytelling in a dashboard?

First, let’s define a story. I’m not looking too far, just quoting Effective Data Storytelling: “The general definition of a story is an account of a causally related or connected series of events.” In other words, a story is a connected sequence of events. And storytelling is telling this sequence of events in one way or another.

You can tell a story like Christopher Nolan in Memento or Gaspar Noé in Irreversible – do it backwards. Or you can tell the middle first, then the beginning and finally the end. This is my favourite way of reading trilogies. Or you can just do the normal way, following the actual sequence by which things happened.

There are multiple storytelling frameworks how to put that sequence of events into something that captures and holds people’s attention. This is not relevant here, you will learn a lot by just reading previously mentioned books. The point is that for having a story we need a sequence of events. Without sequence, there are just random facts.

And here we are having our first problem with storytelling in a dashboard:

1. Dashboards are not linear

Dashboard is everything everywhere all at once. You may say that an infographic or a page of a book has this same property that everything is presented at once in a page. However, it’s obvious how to read the text in a book – the direction is based on the script that was used. Same with a comic book – the sequence of reading is defined by the cultural idea of direction, and this is it.

Infographics and dashboards both have to guide the user through the content – What should I read first? What next? What if I skip things? But in an interactive dashboard which might have several pages users navigate the content themselves and can easily skip parts – guiding them and indicating what is related to what – that is definitely a different skill to master than storytelling!

And problems do not end here, here is our second problem with storytelling in a dashboard:

2. You have no idea how the story ends

In all the books about storytelling, the author of a data story leads the reader through a well-prepared narrative towards a very distinct insight, which calls for a very specific action. How to craft such a story when the insight is unclear?

Insight of the dashboard might be unclear because data is simply not there. How often I had to create a dashboard based just on a snippet of the data, like 1000 rows generated randomly just to fill the table with something.

Or the data might not be full, due to performance reasons – data engineers load first 100000 rows to the development environment instead of full table with 1000000000 rows. There is no way you can have serious insights based on data which is not full.  But the whole dashboard will be created having only development data.

And finally, insights have to be revealed, they do not just pop out from a dataset. You need to dig into numbers to find the story. It is funny that most Data Analysts working with BI tools are actually not analysing any data – they create dashboards which are interfaces for others to analyse that data. Yes, you could analyse data first, find a story and then create pages revealing that story. But it is not how dashboards are developed. Those are presentations.

Since the user is the one who will be using dashboards to find the story, it is important to assist them by organizing and providing relevant information in the right format, with tools to dig and filter. And this is a different skill to master than storytelling. This sounds more like a cartography where you put all those roadsigns, mark objects, and then users guided by the map discover or create stories on their own.

And this is the final problem with storytelling in a dashboard:

3. Every time there is a different story

This month we might find that sales in region R are decreased. Next month, we might find that sales of product P have skyrocketed. The following month, we find that costs C have doubled. Every time there is a different insight, and no one is remaking the dashboard to reveal that one specific insight every month. If you are not remaking the dashboard after every refresh – then you are not doing storytelling.

And then we have different people. There might be one management level dashboard on sales, but the manager of product P is interested in his product P, and the manager of region R is interested in his region R. Finally, we have top management. They might have a different question every time they open the dashboard. Storytelling, on the other hand – leads to one specific ending, one specific insight. Dashboard can lead different people to different places.

While storytelling helps to define the audience and make the whole experience specifically tailored for that audience, for a dashboard we also have to accommodate this branching of information, where different people might want to dig into different topics. Creating this navigation logic and means to do it is a different skill than storytelling.

OK, so storytelling isn’t helping much for dashboard creators. Now what?

It’s UX

The first skill that should accompany data visualization for dashboard creators has to be User Experience (UX) design.

Dashboards are interactive interfaces, they look like and work like websites. But UX is not only about digital products. Users use the dashboard, have experience with it. The experience might be pleasant, and might be frustrating. Loading too slow? – frustrating. Cannot find the number I need? – frustrating. The dashboard is so bad that I have to export to excel? – frustrating. UX principles apply to every product that creates the experience of using it. No one does not care about UX.

There is a massive body of knowledge regarding UX gathered through millions of years of product design evolution and finally – the internet. Applying this body of knowledge to dashboards will improve the experience users having with data.

 Topics that covered by UX are broad in scope because UX has a complete cover on all the aspects of the usability of the product, for example:

• Alignment between business objectives and user needs. What is the purpose of this dashboard in the first place?
• What features have to be there and what is the technology behind it. Whether the report is slow due to slow database or not following best-practices of data modelling – both causes a bad user experience.
• What information is relevant. Or in other words – what data has to be there and in what format – absolute numbers, deltas, growth rates, indexes?
• Interaction. Buttons, passing filters between pages, cross-highlighting – how that makes the life of users easier?
• Amount and organization of content. One page per KPI or one page per time perspective? Is it clear what is related to what?
• Navigation! Side menu pane is enough, or do we also require buttons? How many menu elements should be visible? Do we have sub-pages?
• User interface. What is the right mix between charts, texts and tables? What colours to use? Is the interface intuitive enough, does it guide the user?
• And many more…

Concepts used in UX design for product development are also very relevant in dashboard design.

For example, wireframing – when a rough sketch of a product interface is created without any colours and other design decision. Is it easy to get in what sequence should we read this? Does the information even fit into one page? These are very relevant questions in dashboard development.

Another example is User Acceptance Test or UAT – giving an unfinished product for users to try and see if they even understand how to use the product. Usually, we just drop a dashboard and sit there being sure that users will understand how to use filters, but in the end, approximately 3/4 of all complaints about dashboard end up being that visuals are empty. The reason for this is simple overfiltering – non-compatible filters applied (like current-week in previous-year) which render visuals empty. Stupid users, don’t know how to filter, right? It doesn’t matter, because everyone had a bad experience – user had to complain, product owner got a complaint, you got a complaint. UAT would help to prevent such cases.

Of course, I am not saying that storytelling for data is irrelevant at all. It is the most relevant in cases like presentations or data journalism, if you are in those fields, definitely spend some time with the books listed at the beginning.

Furthermore, I am not saying that storytelling for data is irrelevant for dashboards. It is relevant because it emphasizes some important concepts about understanding your audience, and tailoring the message for them. But for dashboards, UX is more relevant than storytelling.

We can say that some storytelling is still happening in dashboards. If we compare a dashboard to a map which draws the landscape of data, then people by navigating that create their own stories of data adventures and discoveries. We could think of dashboard something like an open world game as Grand Theft Auto, where users roam through the city, having adventure on the way. There are stories in the dashboards, but they have to be uncovered by the user using the interface, not crafted in advance by the developer.

It is sometimes called “storyframing“.

What‘s next for you

So what should you do (if you’re involved in dashboards)? Stop learning about storytelling and start learning about UX. Any UX course with enough stars on any platform would be good introduction if you know nothing about it.

If you do know something already, I would encourage you to check those data UX specific websites where you can find ideas tips and tricks on how to use UX priciples for dahboards:

• MoonStory
• Dataviz Clarity
• Valerie Junk
• Julien Charles-Donatien

If you are not convinced that UX is important, try this evil demo: userinyerface

And of course, keep sharpening your data visualization skills!