Guest Blog by Mauro Goncalves Filho, LEG ’22
First of all, this program reminded me of the importance of defining the problem well. I started with what I thought was a well defined problem, but turns out it was, at best, an idea of a possible solution for a small portion of the problem. Related, I learned to recognize complex and complicated problems, and I left the program convinced that the two types of problems require fundamentally different approaches to tackle them.
Second, I got quite a few additions to my problem-solving toolkit. The growth diagnosis tree and the differential diagnosis heuristics were my favorite on this front. I keep spotting “Camels not Hippos” and “Hippos in the desert” across several areas of my professional practice. Turns out that spotting successful outliers can be as revealing of constraints as spotting patterns.
Third, I learned to analyze economic complexity and to unpack its implications (and the implications of the lack thereof) on understanding the presence/absence of know-how as well as other factors and public goods that may be the binding constraint, preventing further growth. Besides, I learned to correlate changes in economic complexity with good governance and with the presence of a good PDIA approach to solving growth problems.
Around week 4, I didn’t think I would make it through the end. I started with a problem that wasn’t a problem, and with a geographic definition that was too broad to be workable. As I understood that part and evolved the problem statement, I struggled with my limited knowledge of the subset of that geography (Kenya, instead of sub saharan Africa), its institutions and key people – after all, my vantage point is from one single firm. But, as I got more familiar with the toolkit and leaning heavily on the amazing support I got from both my peer learning group and my TA, I managed to turn it around.
I credit, above all, the set of very clear and practical frameworks such as the fishbone, the growth diagnosis and the differential diagnosis – when I combined those three and took a deep-dive on the Atlas of Economic Growth combined with some economic data readily available online, things started to make sense and I got to a plan I feel good about. It was quite the journey.
Serendipity has it that I will be in Kenya in the next few days to run a workshop seeking to understand drivers of the digital divide, and what technologies, if made available, could help address. I will definitely use a lot of what I learned – fishbones, methods to identify the binding constraint, a systematic approach to crawling the solution space.
In addition, I have started using some of the frameworks I learned in contexts that are completely outside of the realm of growth problems. Recently, I needed a framework to classify possible solutions in the context of product development – which features to include or not include on a specific design. Turns out that looking at candidate features in terms of their ability to solve the problem and in terms of our confidence that they will work is a pretty neat approach to screen out features, as it is a fairly concrete way to describe potential return (“solve the problem”) and risk (“works”).
I am still very curious about the various possibilities to fund some of the changes needed to unlock growth acceleration, especially when it comes to public goods and infrastructure items that used to be public goods but have recently seen more and more participation from the private sector. I believe my next exploration will be “Infrastructure on a Market Economy”.
The three stages of my fishbone diagram ((1) clueless, (2) getting there, (3) pretty comfortable):
This is a blog series written by the alumni of the Leading Economic Growth Executive Education Program at the Harvard Kennedy School. 71 Participants successfully completed this 10-week online course in May 2022. These are their learning journey stories.