31 October 2016
This article was originally published on Digital Arts
After the flood director Max Gadney wrote the below article for Digital Arts on October 4. You can read the article in situ here.
Infographics are failing us—as we need to add meaning to data rather than just order or simplicity, explains Max Gadney from After The Flood, which has created big-data-driven projects for UEFA, the BBC and the government.
There’s a deluge of data in the world. Doctors need to explain complex results to patients. Sports scientists optimise player performance in real time. Airline operators diagnose delays and communicate that information to passengers. These operations require explanation: finding the patterns in the data, extracting insights from the actions, and presenting them with clarity to the people who are not experts.
This is where designers step in. Designers today are working with more data, more channels and a wider breadth of user expertise. They’re data mediators, responsible for taking that complex data, digesting it, and outputting clear, unambiguous information that anyone can easily understand.
However, there’s a perceptible problem in the interpretation of this data. A dominative narrative is emerging of visually complex ‘data-vis’ infographics bursting with exciting visuals, but containing little meat in terms of real insight.
When designing with data, what is actually required is a considered process behind the scenes—long before visuals are even considered. Designers need to understand the end user, their needs, the business, and how it is distinct. Only then will the story within the data—and its uses as a building material—start to become apparent.
So, once you’ve gathered this data, what do you do? For starters, don’t make the mistake of showing all of the data that you have. Designers enjoy complexity and visual chicanery: to create something complex is often to create something of value in the eyes of their peers. But this is far from the right way to treat data projects.
This doesn’t mean just to focus on simplicity, but to wring out meaning from the data available. The answer to ‘what is the most valuable thing we can show?’ is the designer's responsibility. The designer must borrow from the storyteller’s rulebook—show, don’t tell.
80% of the time, the client will make the wrong assumption regarding what the users need to see or what the data needs to do. They may overvalue technical features, but chances are these will leave the general viewer confounded. Instead, the data designer must get to the heart of the problem that needs solving—and then decide whether the data available can achieve that goal.
Good designers have always done this. It’s just that the design materials have updated.
Readers of Jesse James Garrett’s still-excellent The Elements of User Experience will know that a designer’s real job is to mediate between the strategy and and the surface of a problem.
Some designers are happier doing surface work—they are visual/graphic designers. But it’s those that gravitate towards strategic planning, and understanding what the data does, that will have the most success. The wrong data will not help to achieve business goals – it won't matter what the front end looks like.
Lorem-ipsum dummy copy won’t help you in the 21st century. If you don’t work to understand the quality of the data, you can never design for it. Treat the data like a carpenter treats different types of wood. Some data is structured and robust—financial market data, for example. Other data, such as developing world government statistics, are patchy—you’ll need to build in a method of explaining gaps.
Quite often the client will understand what the data is, but not how the end users will use it. At After the flood, we turned down a global NGO who wanted daily updates through an app, but only had quarterly data. It wasn't that we disagreed with a subjective direction they had for a logo or ident, but that as carpenters, we couldn’t make a table from the wood with which we were given.
The designer needs to understand the materials they’ve been given, and to determine how they can be utilised. Only then can the indigestible be made digestible.
Once you have established the unique needs of the client, their users, and the most important elements of the information that needs to be conveyed, you will need to ensure the data provided is appropriate before making any first steps on interface design. The data is likely to be averagely structured and is not likely to provide answers to the users.
You can do this by making new data for the client—a new layer on top of what they already have that carries a bespoke weighting and new meaning depending on the unique values they want to show.
For example, in our Player Barometer project [for the Euro 2016 tournament], UEFA wanted to show more in-depth information about player performance. By arranging the readily available data into a new type of ranking, and labelling and packaging it as such, we made the data more understandable and shareable for a wider audience.
Netflix did something similar with movies; rather than simply grouping films by traditional categories, they made 75,000 smaller categories and subcategories – such as “uplifting sports dramas” – which they knew had traction with certain sets of viewers.
Another example: if your client was a kids’ video-on-demand service, is there any way you could create a ‘favourites list’ function that analyses what children in the same age group watch on YouTube? This is the kind of real value that is often found below the interface; in the mechanics that decide what to present to the viewer, not so much what the interface itself looks like.
So, are you a designer with data as your material? Work to understand it. Think beyond how things look, and consider how they work. Designers have always been mediators, and the results are often beautiful. But today, we’re working with more complex and intelligent information. The way it is handled makes all the difference.