Weighted Decision Matrices and the Happiness Question

Weighted Decision Matrices and the Happiness Question

Weighted Decision Matrices and the Happiness Question

How I decided to come to MIT

March 18, 2019 | Mary T.

Deciding to pursue a Ph.D. and finding appropriate programs was straightforward for me; choosing where to go was much more tortuous. Even before I had received any acceptance letters, I fretted over the question: “How will I choose?”. Should I choose the most prestigious school? The cheapest city, so my stipend will go further? A less grueling program to protect my mental health?


Now, you may be thinking to yourself: Mary, just find the right research fit and everything else will fall into place. Not so easy! My research goals were so amorphous at the time that prioritizing research over everything else didn’t help. I wanted to study microscale phenomena in a lab that would lead me to industry research positions after graduation. However, microscale systems is an incredibly broad category. For my goals, working with the most prestigious and prolifically publishing professors wasn’t really necessary. I felt that only prioritizing research would lead to burnout and unhappiness. I wanted to be as happy as possible in grad school. For me to be happy, there had to be time for friends and relaxing, a sense of being valued and respected at my job, and explorations of the world, my city, and my school.


To decide, I needed a system. I needed structure. I needed a weighted decision matrix! Weighted decision matrices, or decision matrix analysis, is a tool that I learned during my undergraduate mechanical engineering program as a way to balance priorities in design quandaries. In this approach, you make a list of priorities, and then a list of all your solutions (here, “solutions” are schools I was accepted to). You rate each solution from 0 to 5 in terms of how well it addresses the associated priority. Then, you rank how important each priority is to you again from 0 to 5. Next, you multiply the solution rating and the priority rating for each school and sum them together to get a holistic score for each solution. In many ways, the result is like a more thought-out coin flip experiment–you see the answer you created, and your feelings about the answer tell you more than the number itself.


My initial result looked something like this:


This version of the matrix didn’t take into account the specific professor I’d be working with. That needed to be rectified. First, however, I needed to find professors who would be a be a good fit with me.  At each visit, current students would ask me what kind of lab I was looking for, and on a whim, I began asking “Which lab that works in the microscale has the happiest grad students?”


It can be easy to imagine that no one is happy in grad school. Even the most positive work environments can be demanding and exhausting. Sometimes I hear my friends complaining about research more than praising a PI for prioritizing mental health, advocating for the students, or encouraging socializing. Nonetheless, the current students always thought of a few professors that meet my criteria. Then I’d meet with those advisors, and often, it felt like they were the best fit for me at that university. It started to feel a bit like a magic question.

In hindsight, I think my happiness question was a bit odd because it seems most people look for research first and happiness second. I’ve certainly never heard another student state criteria for finding a PI in this way. But knowing my mental health resilience level, it was the right prioritization for me. After visits, I refined my decision matrix to evaluate particular professors and projects, and I was able to see more clearly which lab was the best for my priorities. MIT stood out above the others. Not only was MIT the most prestigious, but I had found a professor who worked in socially-conscious microfluidics applications, and I could see my future work transferring easily to the healthcare industry.

However, the “answer” from my matrix led me to question myself further. Could I handle the intensity of a school like MIT? Did I want to? On the other hand, a Ph.D. was going to be hard anywhere. Why not do it at a school that offered so much opportunity? Some of my friends couldn’t believe I was even debating going anywhere but MIT because it’s so legendary, but I really wanted to give myself the best shot at finishing this degree without losing my mind.

Speaking to current students in my now lab was the final thing allowed me to trust my matrix. They spoke glowingly of our advisor and his expectations for grad students. It was clear that they were happy in the lab.

So here I am! I am very glad that I used my happiness question and decision matrix to feel confident in my choice of MIT. If I hadn’t taken the time to elucidate all the factors of what would make a program successful for me as an individual via the weighted decision matrix, I might have ended up prioritizing my ambition over my happiness. It can be hard to resist the draw of spectacular research, even if all the current graduate students warn you to stay away from a PI. Having a set of priorities and a math-y structure to my decision was the right way for me to make my decision. How will you decide?


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