The 3 I’s: When good intentions build bad policy

It took me almost two years, but I finally finished reading Poor Economics by Abhijit Banerjee and Esther Duflo. In one of the last chapters, they discuss a concept that really resonated with me. It’s called the three I’s, which stand for Ideology, Ignorance and Inertia.

Essentially, someone creates an initiative or policy based on an ideology of how they think things should be, but they are ignorant of how things actually work within the population this policy or project serves. But what they have created continues to exist and wastes time, money, and resources due to the inertia of not properly enforcing the policy or evaluating its effectiveness.

I’m sure each and every one of us can easily come up with many examples of bad policies due to the three I’s, but I am going to share some solutions!

Solving the pitfalls of Ideology

You would be surprised at how many stakeholders I work with, who are so in love with the process that they have thought up, they have forgotten about the problem they are trying to solve. However, I have helped them gain a clearer perspective by working with them to create a logic model.

A logic model is a visualization of the theory of change that plots out a map from your resources to your desired outcomes. As you fill it out you keep asking yourself “so what?” until you have created a chain of logic to your program plan or policy.

If nothing else, at least it makes your ideology explicit (e.g. if nurses are always present, then more citizens will have more access to care. If more citizens have greater access, then the community will be healthier etc.)

With that logic: if you have an explicit understanding of your ideology then you have a better chance of…

Minimizing your Ignorance

This is because you have the means to identify all your assumptions. You can look at your if/then connections and stress test them by talking to subject matter experts, front line workers and other stakeholders in the project. You can also look for case studies or other research that operated under your if/then assumptions.

If you have turned into one of those people who uses chatgpt for everything, prompt it to identify the assumptions for you and ask it to offer suggestions on how to validate them. Take some time to think critically about its output (like what it could have missed) and then do the legwork to validate your assumptions. Make sure you talk to people. I am emphasizing these points because when you avoid doing human tasks, you are not…

Combatting Inertia

Most assumptions need to be tested consistently. This also goes for policies and programs. Some initiatives exist to serve a purpose and then need to end as situations and needs change. Therefore, having a strong evaluation cycle is crucial to creating a generative system.

Lucky for you, you’ve already created a logic model when examining your ideology! That means you can look at the pieces of the logic model (which also happens to illustrate all the major components of your program) and identify the key points that are worth evaluating. From there, you can very easily figure out what success looks like, what metrics you need to measure success and what mechanisms you should put in place to collect those metrics.

Now, you can set up the infrastructure to monitor your program and quickly identify when things are working and when things need to change. So, what would have been a crappy and useless waste of time and resources has transformed into a solid, generative system!

Getting to Action

This whole process is simple, but hard. And I realize I glossed over some of the details on how to get it done. However, I am more than happy to provide more guidance on this process in a working session for a specific project you may have - all you need to do is set up some time with me.