Okay, be honest with me – how many hours have you spent the last week watching movies or series on the television or reading novels? Your answer will properly exceed more than one hour and likely much more than that. So let us agree on one thing – stories are great! We love to relax hearing or watching stories. Even kids growing up with tablets, streaming television and 24-hours cable still loves the old-fashioned bedtime story told by parents, grandparent etc. Why is that? I think there are multiple reasons for that, like the special bond created between reader and listener. However, more important is the fact that the listener doesn’t hear the story but is experiencing the story. Imagination kick-starts our brain and the neurons inside our brain acts as they are actually reliving the story. The brain love fiction – the brain love stories
I think the community around Business Intelligence (BI) for many years forgot how powerful human story telling are. BI is all about delivering insight based on vast amounts of data in a way that support decision-making. We have to exploit data-driven story telling much more actively in our projects and recognize the fact that story telling is useful and powerful.
In this blog post, I will try to map the theoretical concepts of storytelling with Microsoft Power BI products.
Storytelling brings insight
My thesis is that storytelling brings insight and insight leads to better decisions. To support this thesis I have defined to following three headlines:
- A story brings life and meaning into your data
- Narrative visualization enhances your story
- Structure makes your story understandable and leads toward the decision
A story brings life and meaning into your data
We are humans not robots – yet. So when presented with lots of data and facts it can be very hard to digest it for a human. How should I interpret a dashboard with multiple values, different charts and KPI’s? Are there a correlation between values? Which measure should I look at first? What we need is a context based on the decision we need to make – a story can make that context. A story will not only describe the result but also describe the processes leading to the result.
Where in the BI value-chain should we consider using storytelling? The BI-chain that I am referring is based on the following flow: we take data and transforms it into information, which gives the end-user insight to make a decision that brings value. The leap from information (like charts and key measures) to insight (Okay, I get it!) seems easy when you look at a drawing with the BI-chain. In real life and with the vast amount of available information today, it can be a very difficult task to navigate. What makes that particular step so difficult? It’s because you move from ‘machine’ to ‘human’ and we need to make the information digestible and understandable in a given context for a human brain. A story arrange facts and events in an order that establish a connection between them and in a logical and maybe causable chain – a story that our brain can try to relive.
Narrative visualization enhances your story
Over the last years visualization tools has evolved dramatically. The market offers many technologies to visualize data in multiple ways. When you combine the discipline of storytelling and the possibilities in data visualization, you get a very strong and usable toolset – also known as narrative visualization. For many years, the Swedish professor in international health Hans Rosling has been a master in that discipline. The simple visualization of complex datasets using GapMinder combined with great narrative skills has made him known around the world – and sometimes referred to as an ‘edutainer’. If you haven’t had the possibility to view some of his presentations, then take the time to do so and see how easy he guides you through huge datasets using storytelling. 3
Segel and Heer of Stanford University described in their paper “Narrative Visualization: Telling stories with Data” some different ways to understand narrative visualization. They divide the discipline into “author-driven” and “reader-driven” stories and describe seven different genres of narrative visualization. An author-driven story is when the author controls the flow of the story and interactivity is limited. This could be a typical slideshow, a lecture or a delivered chart where the author has a clear message to communicate. On the other hand, a reader-driven story is controlled by the reader and will typical have the purpose of data exploration using a visualization tool.
Power BI and storytelling
Many vendors offers tools for both author- and reader driven storytelling including Microsoft with their Power BI suite. Power Map is great to make visualizations for author-driven stories – primarily when your data is geographical based. As a free add-on to Excel 2013, it’s very easy to attach the geographical canvas to a Power Pivot data model and visualize comprehensive amounts of data. The built-in MP4 movie export makes it easy to export the visualization and integrate it into a Power Point presentation.
With Power View you can make highly interactive dashboards based on Power Pivot models or enterprise-level models using SQL Server Analysis Services. Power View provides a series of different visuals ranging from simple text to charts and maps. All elements are interrelated which makes cross-filtering possible. Cross-filtering means that if you select an element like ‘year’, other elements on the dashboard will filter on that year. Power View is an excellent tool for reader-driven stories exposed through Excel, SharePoint or Power BI in the cloud.
Structure makes your story understandable and leads toward the decision
“Once upon a time…” that’s the first sentence in almost every fairy tale by H.C. Andersen. When talking about data-driven stories we also need structure and here you can find great inspiration in the old fairy tales. They all starts with setting the scene, moving to the main story and finishing up with a close-down. “..and they lived happily ever after”. Author-driven stories can adapt this approach.
But how do you tell an author-driven story? One way is to just point the reader to the visualization tool like Power View, but an even better approach is to guide the reader a little bit – setting the scene. That approach requires that you combine the author-driven and reader-driven disciplines. One way to illustrate that is by using the Martini Glass model.4 The model illustrates that you start with a narrow author-driven story introducing the subject in the story. When the stem of the glass ends, we move into a reader-driven story that can move in any direction through data interaction.
Microsoft BI supports this scenario in multiple ways, but one elegant solution is to integrate Power View into a Power Point presentation. If your Power View is exposed through a SharePoint Server you can export it into an interactive slide in the Power Point presentation. In that way, you can perform reader-driven story telling without leaving your Power Point – and your context.
Structure is important and most be integrated into every story, both author- and reader-driven. However, the structure must be based on the decision scenario. Which insight is necessary?
Storytelling is very powerful and combined with modern visualization tools as the ones in Microsoft Power BI you can provide even better insight into your data. We are still humans with a complex brain, which loves to understand context and try to relive the stories. So with that in mind, remember that stories needs data, but the data also needs the stories.
Power Point presentation: (in Danish):