Whenever I picture social impact in the past I would think of teaching children in a classroom, talking to the elderly in a nursery home, and cooking food in a food kitchen. I would think of people working with people, “touching lives”, “creating connection”, and working “on-the-ground”. To a certain extent, I even think that I subconsciously perceived this type of work as the only “true” social impact work.
But there is a whole different side to social impact work, that is not on the ground and not in the classroom. It is in tracking numbers, in the Excel sheets and in meeting rooms. And this place comes with completely different skill sets and challenges.
During my time at Tortoise, I worked with the latter. Rather than being on the “frontline”, I worked on redesigning the data storage that held everything the organization knew about their community partners. I analyzed the engagement behavior of our community partners, to see what made them stick around, what type of events was best attended, and what they reportedly got most out of. I also analyzed the diversity of our community partners. Where is the pool of people that we worked with somehow influenced by our own biases? Were there populations that we were missing? I looked at for instance, where in the UK our community partners were located and what type of social work they did. I found that we had a complete overrepresentation of some social issues, for instance, youth political empowerment, compared to other issues that we hardly engaged with, for example, racial equality. It was not until I had completed most of my analysis that I realized, just how much social impact is shaped not by what happens on the frontline, but what happens in the control room. I realized how many numbers and decisions go into every single event/program/project. You see, it was not because our organization did not care about racial equality, and was only focused on youth political empowerment. This disparity was simply something that had happened as a result of who was in people’s network, which organizations were easiest to get into contact with, and who kept engaged with our events.
Another part of my realization was how much bad data management is taken as a given in a lot of social impact work. Data is not a priority. It is just something that must happen, and as a result, smaller nonprofit/social impact organizations rarely have decent data infrastructure, processes, or even consistent storage. This was not something that I necessarily took away from Tortoise. At Tortoise we were redesigning the data infrastructure because there had been 2-3 previous employees to the current manager, in a rush that had not allowed for establishing any consistency in the data management. And that prompted me to think about the nonprofit organizations that I have worked more closely with in the past, as well as the countless experiences I now remembered hearing from my friends who worked in the same space. You see it is not that inconsistent notation of addresses is the issue. Inertia is a given with any type of data work. However, non-profits tend to have a much higher turnover rate, and especially in smaller ones, the people responsible for data management are often also responsible for many other areas of the business and rarely have either the capability or capacity to perform harder but valuable data science tasks.
To take an example, if we were operating a soup kitchen that was open 3 days a week, we have a massive amount of data available that could make the operation more impactful, if it was tracked and processed. To name just some of the things we ought to track would be the amount of food donated by our grocery/hotel/restaurant partners on each day of the week and its type (perishable versus non-perishable), the number of people coming on each respective days, and whether this number fluctuated with other factors such as rainy weather, holidays, time of the month, season. Using this data, we would be able to make much more qualified decisions on how many people to staff each day, when to anticipate needing more food, and when we can spare either.
As I realized in my time in Tortoise, the people who are making the decisions in “the control room” are guided by the data they have (or do not have). For instance, if we had not analyzed the diversity of our community partners both geographically and in social causes, then we would not even have known that we were drastically leaning in one direction. Often our perception is formed wholly by what touches our desk repeatedly, and often does not represent the reality of the organization. In other words, better data means better decisions. And better decisions mean better social impact work.
I think having a data scientist/manager/analyst/call-it-what-you-want is currently considered a luxury in non-profits, but I believe that in imagining a positive future for social impact it should be considered a necessity.
This was one of the biggest discoveries I take away from the Laidlaw programme after two summers. I have learned not just about social impact and leadership as reflected by this blogpost, but discovered more about my own place in creating a better future, and the strengths and insights I can contribute with in my journey beyond the Laidlaw experience into social impact work.