Wednesday, March 4, 2015

Learnings from teaching of “Design Thinking” course at IIM Bangalore

I got an opportunity to teach “Design Thinking” at IIM Bangalore in terms 5 & 6 of the academic year 2013-14 (roughly from Sept 2013 till March 2014). This was part of a course on innovation I co-taught along with my friend Prof. Rishikesha Krishnan. Term-5 course was for PGSEM students (working professionals with average 7 years of experience) and term-6 class participants included both PGP (full-time, flagship program) and EPGP (full-time students, average 9 years of experience). In this article, I would like to present my top 4 learnings from this teaching experience.

Ground rules: The DT course followed the iterative process: Empathize, Define, Ideate, Prototype and Test. It was emphasized that the process is more important than the outcome.  This was elaborated with following three ground rules: (1) Insights gathered from the field research will be given more weightage than those gathered only through secondary research (2) Customer validation is more important than excel validation and; (3) Iterative experimentation is important and no penalty for failed experiments.

Here are my four learnings:

1.      1. Passion trumps in challenge selectionIn a class, we applied pain, wave & waste tool to generate challenge options. One team selected the area: pain of riding a two wheeler in rain. They wanted to create a car-like comfort while riding a two-wheeler in rain. I asked the team members if they were mechanical engineers or had design background. The answer was negative. So I warned them that just showing PowerPoint suggestions will not take them far in the course.  The team indeed ended up prototyping options using tent rods (see picture). It was a pain area all the team members could relate to and that made a difference. There were passionate about the challenge area and that made a big difference. My learning is that passion as a parameter is most important parameter to look at while selecting a challenge area.

2.      Depth of immersion matters: As the first course progressed, I realized that the quality of data gathered, the challenge framed and the subsequent solutions created depended a lot on the depth of immersion i.e. the number of interviews, the amount time they spend in the field, the different stakeholders they talk to etc. Finding time for this activity could be a challenge given that the participants were working professionals. Hence, it was suggested that the team picks up problem areas which are in or around campus or easily accessible to all the team members. Students were also given specific targets on the minimum number of interviews (say, 10), talking to different stakeholders and making other contextual observations.

3.      3. Experimentation needs rigor: As the mid-term presentations began in term-5 course, I observed a lack of rigor in the measurement and analysis. For example, a team was experimenting with approaches to improve waste segregation on campus. They had pasted signs that may improve the segregation. When the results were presented, data about exact people passing the dustbin, people doing it right, not doing it right wasn’t available. This was an important learning for me. It meant I had to improve how I taught experiment design which I did subsequently. I introduced randomized control trials in term-6 and some of the teams used the technique.

4.      4. Presentations in every class helps: In term-5 we had two rounds of presentations. In round-2, we observed that there was a wide gap between the number of iterations and learnings of the teams. I also got a feedback from students that they would have done better had they seen how some of their peers were progressing through the course. I introduced one more round of presentations in the term-6 batch. This was useful in giving feedback on next rounds of experiments. Besides, a few students talked about how their project is doing towards the end of almost every class.

Overall, I felt Design Thinking offered a complimentary perspective to students who are good at using quantitative techniques in developing new ideas.

Image source: student projects

No comments:

Post a Comment