During my tenure as an academic developer, I was tasked to build several programs to support professional and career development initiatives. It was exciting because I was finally doing something to help people, not by proxy through research, but real people with whom I worked. When the excitement subsided, I realized that I had no idea how to proceed with the project. I had an intuition of what needed to be done and how the final result should look like, yet how to get there was a mystery. As usual, I did what any respectable scientists would do – went through the literature to dig out evidence and best practices related to the researcher development area. Used to Biomed research, I expected a wealth of data; instead, I discovered an informational desert. While the importance of having researcher development programs had been discussed at length in my professional network, there was no substantial research to back it up.
At this point, I decided to take the matter into my hands and conduct my own “experiment” called “Irina’s first program.” The experiment consisted of the following steps borrowed from the old-time favorite scientific method:
- Observation of current environment & services
- Hypothesis: if I create ___ program, then ___ outcome will happen.
- Experiment: implement the program, collect data via a survey
- Results: analyze results
- Conclusion: confirm or reject the hypothesis
- Observe/Optimize – do it again
In the beginning, I thought this method worked. And why not? I solved the problem, and I obtained some evidence to improve the program. However, I felt like my results were process-focused based on the past instead of people-centered facing forward. I was satisfied as a researcher, but I wasn’t sure if my target audience would be happy with the service.
With this in mind, I searched for an alternative way, and soon I found design thinking (DT). In many respects, DT is similar to the scientific method (SM), especially when forming and testing a hypothesis. What makes DT different is the incorporation of qualitative data analysis to uncover unique users’ needs and wants before crafting a hypothesis. When SM employs objectivity, DT offers subjectivity and empathy. For me, DT expands the scientific method’s observation step, resulting in focused services tailored to a specific audience. It is a more holistic and humanistic approach.
While several DT approaches exist out there, in the next few posts, I’d like to share my experience with the dschool framework that I learned when I went to “Design your Life” training at Stanford University, USA. Since 2019, I’ve applied this versatile tool to create career development programs as well as to build institutional services. Moreover, I successfully used some or all the DT steps at work, home, and in my training & coaching practice. Stay tuned to discover the 1st step coming in December!
Irina