The Rise of the Data Literate Designer
Admittedly, I’m a chemistry PhD dropout, but I love science so I spent over a decade in the biotechnology industry, most of which was a product manager. In the midst of all that science and product, without realizing it, I stumbled into design and design thinking. Inspired to take a human centered approach to things, I decided to pursue a career in that direction. There have been moments along the way where I wish I studied graphic design, industrial design, or architecture as an undergrad, however in hindsight, I’m incredibly grateful I majored in science (biology major, chemistry minor).
I’ve mentioned the term “designtist” during a few talks I’ve given over the past few years. It often gets a chuckle or a head-nod and that’s because, I think, we’re seeing the two disciplines coming closer and closer together.
A New “T-Shaped” Level of Talent?
Early in my career, prior to my product management days, I worked as a hybrid scientist/bio-engineer. The company I worked for acquired an engineering company that had little experience in the biotech sector. The engineers were a smart and talented bunch, although they hadn’t taken a biology class since their high school days and some never studied chemistry. Avagadro’s number? They had never heard of it. How a DNA backbone was structured? Nope. How two strands of DNA formed a double helix? Not that either. Since the products they were to design and engineer ultimately would be placed into molecular biology, biochemistry, and pharmaceutical labs, I created a three part science-for-engineers seminar to teach the basics of molecular biology. Would it create a new T-Shaped individual? Maybe. Learning science is like learning a language. The concepts are not all that difficult, sometimes intuitive and sometimes unintuitive, but the terminology can bite you in the ass. (I learned a similar lesson in business school with my Economics, Accounting, and Finance courses).
Turned out the engineers loved the course as it helped them think about the problems they were solving a little differently. They weren’t experts after three one-hour sessions, however the newfound knowledge of how DNA gets amplified via polymerase chain reaction (PCR) helped them better understand the system for which they were developing. As a result, they made more relevant design and engineering choices due to that knowledge.
It’s Not About Code
This is not another version of the “should designers code” argument. My answer to that one is simple: Heck yes. Yes, but… Designers do not need to write production-level code. They need to understand how code works enough that they can write some of it and more importantly, design within the constraints. After all, interactive designs do not live forever in Photoshop, or Sketch, or Illustrator, or __favorite tool here__. Those designs get coded to become a digital product. The same for designing with data.
In 2016, the discussion about designers learning to code is the wrong discussion, instead we should be talking about designers becoming data literate.
What does it mean to be “data literate?” Designers who understand data will be the designers who make the bigger impact with their work. Design solves problems. Data helps inform the choices you make to solve those problems.
We hear it in the news: “Data science is the sexiest new job.” And I chuckle, as it’s all about branding. Job titles like Data Analyst or Statistician have been around for decades, and they appear to have a negative connotation. Suddenly a name change that adds “science,” and people are all excited.
Consider these two phrases:
STAND BACK, I AM ABOUT TO DO SCIENCE.
versus:
STAND BACK, I AM ABOUT TO DO STATISTICS.
In the past few years we’ve seen the rise of design in organizations as a significant creator of value. We’re seeing a similar argument for data science. A 2015 PwC survey of 1,300 CEOs in 77 countries, ranked data mining and analytics as the second most important digital technology and organization capability.
CEOs now value data and analytics technologies just as much as they rely on their customer relationship management systems when it comes to their ability to meet a wide group of stakeholder needs
What if I substituted “design” into that sentence: “CEOs now value design when it comes to their ability to meet a wide group of stakeholder needs.” Since a designers job is to create a solution that meets a customer’s, stakeholder’s or user’s (insert favorite term here) need, is makes sense that these are complimentary. Smart, experienced designers dig into the problem first before generating any kind of solution. What better way to understand the problem than with data? The more a designer can understand how this data was collected, and analyzed, the smarter design decisions they can make to deliver a compelling solution.
Data modeling, simulation, and other digital tools are reshaping how we innovate. — Bob McDonald, CEO at Procter & Gamble
Innovation has been linked to design, many times over in the past, so it makes sense that the data literate designer will make the “right” design choices for their product. But here’s the rub: Most designers are not trained in statistics, um, I mean, data science. There are few programs out there that integrate a form of data education to designers: MICA’s Information Visualization (disclosure: I attended this program), Parsons Data Visualization, as well as programs like NYU’s ITP and MIT’s Media Lab who offer courses such as Machine Learning for Artists. From their web-catalogue, I see no data or stats classes listed at Stanford’s d.school. (Yes, I realize I’m cherry picking here, so keep that in mind, fellow data-nerds) I don’t have a nationwide design degree curriculum database in front of me, but I’d bet a lot of money that the majority of top design schools do not require a course in stats or data.
Just as my former engineering colleagues newfound knowledge about molecular biology allowed them make better decisions for their products, data literacy is how designers will make better product decisions for the deluge of data our society continues to create daily.
A version of this article originally appeared on the Fresh Tilled Soil blog.
Big thanks to: Austin Knight and Angela Bassa for their review and feedback, as well as Chris Wilcox and Emily Powers for editing prowess.
