On March 9th, Architech will be hosting a session at Dx3 2017, Canada’s Leading Technology, Digital Marketing and Retail Event. The session will be led by Molly Puddister (Designer) and Jan Scholz (Data Scientist), focusing on the intersection of data and design and how these two seemingly opposite disciplines come together to inform user experience.
IoT, machine learning, and advanced analytics have driven organizations to a data-tells-all-mentality. At the end of the day, what does the data mean for decision makers and what role does design play in those decisions? During this session, we’ll explore the relationship between what the numbers say, the importance of design, and how both influence the way consumers interact with a brand.
In anticipation of the Dx3 talk, we thought we’d help our audience get to know Molly and Jan a bit better.
Q: Molly, tell us a bit about your education and previous work experience
Molly: Well, I spent a year studying at Guelph University before I made the switch to study graphic design at Humber College. Once I made the shift, the focus there was primary print design with some focus on interaction design and the animation/basics of web design.
Q: How did you make that move? Why Sociology to Design?
Molly: Originally, I had planned to go into social work. I really loved learning about it but I felt like I needed the space to be more creative in my career. I wasn’t sure I had the guts to handle a social work position. So, I started thinking about what else really moved me and landed on design – a natural evolution from my Fine Arts background in high school.
Q: Did studying Sociology prepare you in any way for working in Design?
Molly: Psychology and Sociology are the study of people and the way they think. Understanding psychology at a basic level helped me think about interaction and human-centred design in a different way. Understanding Anthropology did help bridge the gap between design and data – but, this only occurred to me later as I explored Neuroscience and Neuropsychology and started to understand the connection point between biological data and behavior. I think this really links back to understanding motivation and user behavior which is so important to good design.
Q: What came next after school?
Molly: After I graduated, I did two internships – one at Rogers and one for a motorcycle social network. My work experience before Architech included front-end development and web and mobile design.
Q: Jan, tell us a bit about your education and previous work experience
Jan: I started off in cognitive science – psychology, linguistics, computer science, AI, and neuroscience. What excited me about this area is understanding how humans perceive and interact with the world. Ultimately, being trained across a broad range of topics now helps me understand how to build and design better. The more we understand about how we make decisions the better equipped we are to improve our experience when interacting with the world around us.
Q: What came next after school?
Jan: I have my PhD in Neuroscience from Oxford University. After my PhD, I spent 5 years working at the Hospital for Sick Children in Toronto in Neuroscience research.
Q: Jan, did Neuroscience prepare you for data science?
Jan: I view data science as a very essential tool – similar to writing and now programming – that can help you to get ahead in many if not most jobs . You can’t be a scientist without being comfortable with analyzing large amounts of data. So, yes, neuroscience helped me become comfortable with large data sets.
Molly: That’s exactly why data is normally such a difficult concept for designers – we’re not inherently comfortable with large amounts of data.
Not knowing what you’re looking for, and seeing all these numbers, and knowing you’re supposed to distil this information to drive what you’re doing is daunting. It can create a kind of paralysis.
Jan: I don’t think that data science is only for PhD’s and people who are comfortable with large amounts of data. It is often already helpful to understand the big picture without knowing all the details.
Q: Molly, how have you learned to overcome that “data paralysis”?
Molly: I’ve learned that when you’re looking at data, you need a hypothesis – a theory about a question you want to answer or explore. You need to let the data speak for itself but you also have to make sure you’re looking at it with a purpose. That purpose is to prove or disprove your hypothesis. You can’t be biased about the results, but you do need to dive into the data with the intention of uncovering insights about a specific issue or question.
Q: Jan, does anything about Design overwhelm you or feel daunting?
Jan: Design has an emotional component that scientists intentionally try remove from science. Instead, we work to present a view that is as objective as possible without curating it. But, I understand that in order to design well, you must be in touch with your audience and its emotional experience. This is daunting for data scientists because there is often no clear answer. In Design, there are so many possibilities. Making decisions about how people perceive things which can’t be validated in advance requires a lot of experience.
Q: So, what or where is the intersection between Data Science and Design?
Molly: I would say that it’s the people and the users that are at the intersection of Data Science and Design. We look at them from different perspectives but both fields look to this source for insight.
Jan: Exactly. I see like this: Design is the channel used to deliver the user experience that’s been developed using data analysis. Ultimately, it’s the lens through which we adapt, pivot, and update. Really, to be able to deliver the best user experience, you need data science and design working in collaboration because feedback from all points must inform the next iteration.
Hear more from Molly and Jan at Architech Dx3 session on March 9th.