Design, data exploration and the future

A software designer’s self interview

I have a hard time communicating what I do to people not well travelled in the land of software design. Which is most people. So I decided to interview myself to answer some of the questions I get a lot, and some questions I wish I got. I divided this interview into three parts. Each part describes a fictional character, the person conducting the interview, more or less inspired by real conversations.

• Part 1 is about my role as a designer.
• Part 2 is about Clarify and why it exists.
• Part 3 is about society and the future and stuff.

Perhaps this text is an act of shameless self-indulgence, as I bla-bla-bla about my experiences and how relevant they should be. Or perhaps it is an act of profound philanthropy, as I prepare the ground for a deeper conversation about the responsibility of designers, the future of collaboration, data and society. The truth, boringly enough, is probably somewhere in the middle.

Part 1 — The one unfamiliar with computer science (or design, for that matter)

• So, what do you do?
• I make software that lets people explore data.
• Okay.. what kind of data?
• Industrial data. Mostly time series data. Think of a graph plotted with time along the x and value along the y. We gather the data sources of a company in one place. Kind of what Spotify does with music. Putting a lot of songs from different artists into one playlist.
• Ah…
• Then we let people comment and discuss on top of the data.
• Okay, so.. you design the graphs that people see?
• Well, it's more about everything that happens around the graphs.. but yeah, I do that too.
• … so, you are like, a frontend designer?
• Actually, no. I'm part of the design team. We deliver specifications to the frontend. Which they turn into code.
• But I thought you studied design?
• Yes. Industrial design. Specialising in interaction design.
• What is interaction design?
• Think of it as a conversation between a computer and a person. You say something, then the computer listens, thinks for a bit, then responds. My job is to make this conversation meaningful.
• But how do you define what is meaningful?
• That's the question. It depends on who you are talking to. It's about understanding what they are thinking, what they want to achieve. That simple, and that hard.

User Experience (UX), User Interface (UI) Interaction (IX), Human Centered (HC) — there are a lot of abbreviations to choose from. To most people, I just introduce myself as designer, and watch their increasingly perplexed faces as I explain what I actually do.

Part 2 — The one who is here to network

• ..so, why did you decide to make Clarify?
• Before I started, in the beginning, it was a consultancy. Hands-on experience from customers and different industries indicated the need for a platform that could handle data for the entire company, and make it available to all employees.
• But aren't there solutions for that already?
• Not really. You have your data analysis platforms, which are great for digging deep into the statistics. Then there's your dashboards, great for giving you situational awareness. Both are important, but the data is limited to certain roles. We want everyone to extract value from data in their work, and decide how to use data for themselves.

Understanding Clarify: the alignment between people, data and company

• Okay. Cool. But how do you explain this to potential customers?
• Well, I'm not a sales person.
• Fair enough. But how would you pitch Clarify, hypothetically?
• It's obvious to most people that data will be extremely important in the future. But despite the promises of AI and machine learning, the most important asset has always been, and will always be, people. Clarify creates a positive feedback loop between people, data and company. If you manage to turn data collaboration into a habit, you can increase your understanding of the past and present. To make better decisions today, but also qualified predictions about the future.
• Can you give an example of how this works in real life?
• Let's say you're a farmer. Let's say you have a bunch of sensors that track the health of your animals and crops as they grow over time. Perhaps you want to find out how much feed you should buy in the next month, or compare the nutritional value of the crops in different parts of the soil. You want to gather all the relevant data sources in one place. And you want to add your own insights, come up with possible explanations and find opportunities for improvement. As data accumulates, you can start making informed decisions about how to improve the harvest in the next season, or reduce the risk of crop failure.
• I see. But how can ordinary people access that data?
• The first step is gathering data sources in one place where everyone can find them. But more importantly, data should be so easy and intuitive to work with that people can apply it in their everyday work life. We want people to use data the same way a farmer uses a tractor.
• That's a nice metaphor.
• Thanks. Also, we need to move the important discussions around data out of silos.
• And how do you suggest we do that?
• It's about having a shared source of truth. If I am the one delivering feed bales to your animals, then you could take my word for it, trusting that each bale contains grass of top nutritional value. Or even better, you could view the nutritional values yourself. That way you would know your animals got the right amount of nutrition at the right time. It's about finding meaningful ways to collaborate with data.

I never asked to be a socialite, a rhetorical oracle or a lyrical miracle. But every time I’m in a social, networky setting, inevitably, at some point, the subject turns toward where people work and what they do. Why would you expect me to perform a convincing pitch on the spot? I'm genetically predisposed to stand in the corner and observe. Leave me alone. Please.

Actually, I like it a little bit. To be around people, to take the pulse on current events, to feel the buzz. But mostly I sit in front of a computer and move pixels around. And I'm fine with that.

Part 3 — The one who thinks about society and the future and stuff

• What do you think about the role of AI and machine learning in the future?
• Oh, that’s really not my expertise. But I heard a quote recently, that went:

If it is written in Python, it's probably machine learning. If it is written in PowerPoint, it's probably AI *

• Cool.. What does that mean, though?
• I think it means we need to get off the hype train saying AI will fix all our problems. In stead, we should start using data to increase our understanding and improve our decision making. We need to communicate the value data can have in our everyday lives.
• Right. What are the biggest challenges to communicating the value of data?
• We have all this god-like technology at our hands, but we need to turn that into worthwhile experiences for humans. As natural storytellers, we tend to see the world in terms of causes and effects. We do it subconsciously, all the time. We assign meaning to events, making sure our view of the world is consistent with our experience. I think we can take advantage of that to extract meaning and value from data.
• Okay.. care to elaborate?
• Data can be so much more than just facts and figures. Why is it that we remember stories better than statistics? We sympathise with the characters in a novel, see things from their perspective, and ask «what would I have done, if I was in that situation?» Using elements from storytelling could be one way to make data more relevant and accessible.
• Interesting. Perhaps one could take the best from both worlds, and make a data story of some sort?
• Perhaps. But just because a story is catchy, doesn't mean it's correct. Having the facts to back it up is equally important, and often overlooked.
• Speaking of which.. How can we create meaningful social interactions online?
• Some of the most popular social platforms attempt to remove the complexities of life by portraying it in a headline, a tweet, a like. And what do we get in return? A culture that rewards extreme viewpoints, self-righteousness and groupthink, and punishes conflicting views, nuanced debate, and profanities like «I was wrong» or «I don't know».
• So, what should one do?
• I don't know.
• Any idea where to start?
• I think recent events has shown us that there are meaningful ways to connect, despite physical distances. Creative solutions are born out of necessity. We need to keep iterating on ways to work together. And we need to bring more diversity into the equation. Diversity in views, interests and experiences. After all, you don't know what you don't know.

The end.

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P.S.

If you are still here, you probably have some questions. For context, I work as a designer at Clarify, a tool for companies that have a lot of data. We want everyone in the company to explore that data, to use it as an everyday tool to solve problems and make better decisions. If you want to learn more about us, check out: https://www.clarify.us

References
* The quote was originally made by Mat Velloso, according to this talk: https://www.youtube.com/watch?v=Mukpy1QjVn8&index=8