Measuring Secondary Effects: Drops and Ripples


What really counts? I would say that the things that count the most are the things that are hardest to measure.

I agree with the statement that says, “not everything that counts can be counted.” But maybe we should change it to “Not everything that counts is being counted.” Every time we have any kind of impact on a person or community it is like a drop of water hitting the surface. A lot of times we just measure the little area where the drop hit and how high the water level rose, but we don’t always measure how far the ripples went and what they did along the way.

Here we get into the “Secondary Effects.” For example, the drop might be a micro-loan. The easy things to measure are: How many loans were given out to women in a struggling community, or even the percentage of them that paid it back. These seem like great indicators of success on the surface level but what about the ripples?

How to do you count or quantify the number of people whose lives the loan actually improved? How many of them were able to use the loan in an effective way that allowed them to create an opportunity that they previously would not have had? What effect did it have on their health, economic wellbeing, education and long-term livelihood? Did it change their living situation? Were they able to control the money and the property and goods acquired through it? Was there increased conflict in the marriage or family? And the list goes on…

“Everything that can be counted counts”… I would say no. Although it is a good place to start. You have to start with the drop (things that are easy to count) and then work your way out through the ripples (secondary effects). Another example: Humanitarian aid and giving. A huge natural disaster just happened and people are in desperate need of food. Donations are flown in and thousands of pounds of food are provided for the starving people. It’s easy to count the number of meals served and the number of people directly reached but it’s harder to measure the long-term effects of the donations… In the end did it help or hurt the people? What effect did the free food given out have on local street vendors and small enterprises that were then forced to compete with the handouts?

It’s the same principle with the Tom’s B1G1 model. It’s easy to measure that there were 2 million pairs of shoes given to barefoot children, but it’s not as easy to measure the secondary effects: Did the free handouts compete with and undermine local markets? Did it create lasting change and improve the “shoe-wearing culture”?

Impact, Social Return on Investment, Quality of life, Lasting Generational Change…  These have to be some of the hardest things to measure in the developing world. Everything we do in development and social entrepreneurship is ultimately based on people and although we can count the number of people we have reached or directly affected, we can’t always easily count (or quantify) how their quality of life increased and all of the secondary effects that our drops of water are having.

There is a lot to think about when we are measuring impact and although it is hard, I would submit that we have to try to think ahead and measure the secondary effects (the things that are hardest to count). This will never be easy so we have to be creative in how we can obtain the valuable information that tells us if what we are doing is having a real impact.