in practice, an informed theory
InformForm is an international platform for information design, which celebrates and explores both practical and theoretical experimentation within the field of design. It prides itself on showcasing relevant examples of work by students, for students. Read More
Transfer Window - an interactive visualisation using live data from European football transfers and the impact this has on clubs' league position
Signal Noise is a London-based information design agency founded by Hem Patel, Matthew Falla and Christian Thümer. Signal Noise work for clients across industries helping them to understand, analyse and communicate complex data and narratives.
What made you set up a studio together? The name sounds intriguing! Is there a story behind it?
Matt: Signal and noise are concepts from information theory. The signal is the message sent over a channel, and the noise is the unwanted information that reduces the chances of the message being received. Our purpose as a studio is to help our clients make sense of their complex worlds, and to find the signal in an increasingly noisy environment.
Chris: Our separate work involved a lot of information visualisation and diagrammatic work for big corporates. It was a real eye opener for us. We realised that there was a need for that sort of visualisation. And we all had different core strengths as graphic designers, which seemed to be complimentary.
Matt: Setting up a studio is never easy, but we’re fortunate that data and the discipline of visualising it is becoming ever more important. After learning this we pooled our clients and skills in graphic information and interaction design.
Hem: I think it’s important that we all have slightly different roles. As well as design, I focus on new business development and building relationships. I work with our clients to define the creative brief and ensure the smooth delivery of our projects. I also work on the Signal Noise team by nurturing and growing new designers and developers. These are all key aspects to running a studio.
Information design is often about visual storytelling. Do clients come to Signal Noise with data or an idea of a story? Perhaps it’s both? Do you find there is a regular starting point for dialogue?
Matt: It does very much depend on the client. Sometimes clients don’t have any data and only an idea of what they hope to communicate. In those situations we have to source data, analyse it and clean it up ready for use. Others will deliver the data, user stories, key insights and detailed brand and UX guidelines.
Chris: You can really feel a shift in client expectations. Five years ago we had to educate clients about how they can or should use their data. It now feels like the world has found its feet a little bit with the world of data visualisation. Clients understand the value of data, and how to use it becomes more obvious. These changes are reflected in the briefs.
Matt: The most satisfying projects for us are when the visualisations can reveal an aspect of the data that nobody knew was there.
Data is essentially meaningless. It’s only through the assignment of meaning that it becomes information. What are Signal Noise’s thoughts on this in relation to how you approach client projects?
Chris: It’s absolutely vital to understand the end user. Without that, we might miss some of the most important aspects of the visualisation.
Matt: Designing data can be as emotionally manipulative as designing any advertising campaign. We’ve all worked on projects where the client realised that their data didn’t tell the story that they expected once it was visualised.
Sometimes demonstrating that a client has access to a large amount of data is the story. This kind of metadata around the data is also just as important as the data itself and it shouldn’t be overlooked.
Chris: We work on understanding what data we need to combine or compare, which can really influence how the reader understands the information presented to them.
Understanding process and its application is essential when you’re studying information design. What are your thoughts on the idea or definition of process in a professional context?
Matt: We find ourselves working in different ways depending on the project. Sometimes a very structured waterfall approach is the way to go, other times a truly iterative and agile way of working will give you the best results.
What role do you feel technology plays in your work? Particularly in relation to an audience and the user experience?
Chris: We embrace technology and it’s a core part of what we do at Signal Noise. Technology itself has brought a lot of the complexity to the world, but equally it enables us to help simplify such complexity.
Matt: Technology is extremely important in terms of our workflow. We’re lucky to have a great development team who quickly turn ideas into live code, which is the best way to see whether something is working. Having said that, there’s nothing more important in our design process than hand sketching and heated debate!
In terms of audiences, the vast majority of the work we produce is consumed on screens. This means that we can achieve more than we could in print or static formats, but it can also be quite constraining. On small screens you’re limited by pixels and bandwidth and on large screens the challenge is more about letting multiple people interact with the work.
Capturing our own analytics is a key area of technical focus for us. We’re trying to practice what we preach. This means understanding how people are interacting with tools and content, and allowing this data to inform or drive dynamic changes to what’s on the screen.
Where do you think information design and data visualisation as a practice is heading? What is the future?
Matt: People are often overstimulated and short on time. They want insight spoon-fed and want the right piece of information at exactly the right time. In the future, data will be consumed in ‘glanceable’ ways, with connectivity and context becoming as important as content. The days of ‘sci-fi’ style complex visualisation interfaces are definitely numbered.
Chris: In terms of the industry, mathematics and statistics will become more important to future data design practice. Mathematics is helping to write algorithms and extract meaning out of billions of data points, which is currently a highly specialised skill. I think it will be more about the quality of the data than the ability to see the data.
Matt: But data design will also become much more important as data is used by more and more ordinary people. Resource shortages like water and energy will mean more of us keep a close eye on our consumption and costs. We’ll all become CFOs of our households!
Here at InformForm we think learning never stops. What are some of the most important things that you have learned since you have graduated?
Chris: Failure is necessary. Don’t be afraid of criticism and keep trying different things. Collaboration is essential, delegate tasks to those who are better than you. Explore other industries and try to understand their language – this will allow you to translate some of the design ethos into other worlds.
Matt: Work with real data as soon as you can. You can get a great return on investment from finding the time to work on your own projects – clients respect it and you will thrive on it. People will still ask for an ‘Export To Powerpoint’ button no matter how great the tools you build are.
Finally do you have any advice for students studying the subject?
Matt: One of the interesting things about information design and data visualisation is that it can directly connect with other people at a deeper level. Spend as much time as you can understanding where data comes from in the real world.
Who is using it? How are they using it? Why does it have value? Who does it impact? What does it mean for society in general? This takes effort – reading up on finance, business, healthcare and politics. But this kind of study will give you much more context and help you to become a much better visual communicator.
It’s not enough to see data as abstract numbers that can be made to look pretty.
Chris: Consume and learn as much as you can from existing examples. I think it is vital to analyse existing work and to really understand why certain representations are the way they are. Explore different ways to show the same thing, and understand why certain methods work better than others.
Make sure you understand what is needed for the data to be truly useful.