Going deep vs. Going wide

I spent most of today learning more about the various schools of thought around design thinking, reading Tim Brown's Design Thinking blog, writing up a short case study about designing for a circular economy, and thinking more about the intersection between data science and human-centred design. In a perfect world I would be paid to do this all day, every day.

One blogpost; The Career Choice Nobody Tells You About,  really resonated with me. It's short and contains a simple message, but it was a nice reminder for why I wanted to "leave" astronomy research and pursue new opportunities.

Going deep requires incredible focus, lifelong commitment to a single cause, a willingness to be patient towards achieving success, and the confidence to follow a path others may not understand or value...

Going wide, on the other hand, is about making connections between what you already know and what you’re curious about discovering. It requires systems thinking in order for the whole to be greater than the sum of the parts. It means developing the skills to collaborate for the purpose of learning. It’s about seeing the creative possibilities in breaking down boundaries and describing the world, your organization, the problem in new ways.
— Tim Brown, CEO of IDEO

Data science offers researchers in academia an opportunity to go wide, to explore problems across all sciences, the arts, across business and technology, and even the not-for-profit social sector. While many researchers leave academia because of negative experiences or job insecurity, I suspect that most (like myself) leave because there are just so many more equally exciting things in the world to discover (or make, or teach) and a whole new community of amazing people to learn from.

Personally, committing a lifetime to academic research wasn't enough for me. Although my research was exciting and I had the opportunity to work at world-leading academic institutions, with incredibly clever and talented and researchers, there was always something missing. Perhaps it was a fear of missing out on all the other wonderful things people were doing?

Fortunately I've managed to have found a way to find aspects of astrophysics research where i can make significant contributions, and in the meantime work with data and technology within a completely different industry. There is a stigma around leaving academia so choosing how and why you leave matters.