Analyzing data for social change

Andrew Means

Andrew Means is head of Beyond Uptake, the philanthropy innovation arm of Uptake, an industrial analytics company based in Chicago. Means also cofounded the company called The Impact Lab, and founder of Data Analysis for Social Good.

When you were young, what did you want to do when you grew up?

Means: When I was a kid, I wanted to be a pilot in really remote parts of the world. I had this vision and dream of flying into remote parts of Africa or South East Asia and delivering humanitarian supplies.

What did you become?

Means: Through college and out of college, I was a youth worker. I worked with middle and high school students. I became obsessed with this question of how do we know what works when it comes to social change and innovation? I went and studied data to become a data expert.

What is social innovation?

Means: Social innovation is hard to pin down. I think the thread that ties it together is this: we have to think differently to solve the biggest problems our world faces.

Can you tell me a little about the role of experimentation within that?

Means: Experimentation is really important because you have to test things to know what works and what doesn’t. If you only do the same thing again and again, you never learn anything. Innovation thrives on learning. Experimentation is a vital part of the social innovation space — or should be a vital part of the social innovation space.

We exist to solve problems, we should solve problems, we should know if we’re solving problems, and we should solve problems better.

Can you give me the data perspective on experimentation — how it allows things to scale up?

Means: Data professionals love experimentation. It gives us the confidence to infer insight from an activity. Typically your data person is going to be advocating for more experimentation. Within social innovation, in particular, data plays a really unique role. Data wears multiple hats in this work. It can tell us if what we’re doing is working. So it has an evaluative role within social innovation that I think is really important. If we’re truly doing social innovation, it should be about solving problems that we need to solve. Data can help us evaluate our ability to do that. Also, when we store things on servers and in binary code, it also changes the way we operate. It changes the possibilities. We can now run interventions and perform interventions that we couldn’t have without this kind of digital technology.

What’s the mindset of a social innovator?

Means: I think the mindset of a social innovation data nerd really comes down to what drives them. In the social innovation and data space whatever that overlapping category is I think what drives us is both an intellectual curiosity. They like to learn, they like solving complex difficult problems that have stumped other people, but they do it for the good of humanity. A desire to actually make a difference in the world. To apply their drive and intellectual abilities toward the good of someone else, or the solving of a problem that they care about.

Is there something particular about the way that you see the world?

Means: I’m very much driven by rigor. I’m driven by a desire for evidence to actually solve the problems we set out to solve. I don’t really have much time to deal with politics, and I don’t think non-profits exist to fundraise, and I don’t have much time to talk about that. We exist to solve problems, we should solve problems, we should know if we’re solving problems, and we should solve problems better.

It’s hard to take social innovation to scale. We just don’t have the same financial incentives as the private sector.

At the same time, I’m perfectly fine saying there are some things that we can’t and should not measure. That there are some things that are intangible goods, that some non-profit organizations are doing that should maybe remain a little intangible. I sit on the board of an arts education funding organization in Chicago, and some of the groups that I’ve been exposed to take kids to the museum or to the symphony, or to see a show.  I think that’s really important work. Those experiences were really valuable and important to me as a kid, but am I going to go to any one of those organizations and say, “Is who he is today because of that one time he got to the Chicago Symphony Orchestra when he was seven?”  We need to be able to say there are some things that we’re not going to be able to evaluate, but where we can, we need to evaluate well.

Data is a very valuable tool, but that doesn’t mean it can solve every problem. It doesn’t mean that it’s the only thing that matters because we happen to be excited about it right now. We need to use it for what it can do well, and not use it when it can’t do things well.

How does social innovation move from an idea to substantial change?

Means: A big part of it is seeding a lot of ideas, trying lots of things, experimenting early and often, and then turning down the ideas that aren’t working, turning up the ideas that are. And just continuously and iteratively doing that process. In the private sector, there are really nice mechanisms for that kind of growth. There are capital incentives and financial incentives to basically get your capital to grow, that we don’t actually have in the social innovation space. This is the hardest thing about social innovation. It’s sometimes really hard to attract capital in two ways. It can be hard to attract capital when you first begin — to get that early-stage high-risk funding. Once you’ve proven your idea, it’ll be just as hard to get capital because a lot of people that invest in newer, innovative things like to be in the riskiest tranche, and so, once you’ve kind of proven it, they say, “Alright. Good luck.” It’s hard to take social innovation to scale. We just don’t have the same financial incentives as the private sector.

What gives you hope and what motivates your work?

Means: The thing that gives me hope is the progress that we’re seeing. Five years ago, we wouldn’t have 300 people next door in Toronto talking about data, and the world of data sharing and data technology.

We’re seeing enough people move beyond that to actually building tools, to offering services in new ways; non-profits doing things in new, innovative ways; partnerships between government and civil society — and that’s what’s promising. There might just be blades of grass right now that are poking up above the surface, but they didn’t even exist a few years ago.

The other thing that gives me hope is that I really do believe that technology can help us solve problems. We have limited resources with which to address huge problems; we don’t have time to waste, we don’t have resources to waste. There’s just this drive inside that says, we can absolutely make the world a better place in a way that wasn’t possible maybe even 20, 30, 50 years ago. And I will do whatever I can to make that possible and make that kind of future reality come true.