Modern technology developers often use terms such as minimum viable product and iterative development. Startup companies popularized these lean startup approaches to develop products while conserving resources and achieving product-market fit. Under these management approaches, developers release small products and then rapidly make incremental changes based on market feedback and adoption. This process saves time and money while ensuring that new features correspond to real user needs.
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Although minimum viable products and iterative development originally took hold among startups, today, virtually every innovative technology organization I speak with uses this approach. Conversations with chief information officers and chief digital officers routinely turn to incremental development based on customer feedback and rapid turnaround times. even chief marketing officers talk about marketing projects in these terms.
Despite the extent to which business and government organizations have adopted rapid prototyping and development, applying these principles to non-profits is still relatively new and not always easy.
Non-profits face a different set of challenges than profit-making businesses. For example -- and this is but one example among many -- businesses can see a direct and often immediate link between product changes and user behavior: Instrument your app or website, make a change and observe the clicks to see user impact. In contrast, many non-profits measure results over time in terms of broader social benefit rather than clicks; obviously, this is much harder to measure and iterate quickly.
Despite the challenges, there is great value in applying iterative techniques to non-profits. To teach non-profits how to accomplish this goal, the former chief innovation officer of USAID, Ann Mei Chang, wrote a new book called Lean Impact, which presents advice on how to apply lean startup principles to social impact and non-profit organizations.
The clear importance and value of applying these principles to non-profits led me to invite Ann Mei to be a guest on episode 313 of CXOTalk, a video and podcast show that offers conversations with the world's top innovators in business, technology, and health care.
During our conversation, Ann Mei explains principles of the lean startup movement, on which her book is based. She then describes how non-profit organizations can apply these principles to their own operations.
Ann Mei is uniquely qualified to speak about these topics, given her unusual background, which equally spans business and non-profits. She currently works as executive director of Lean Impact at the Lean Startup Company, founded by Eric Reis, whose books lay the foundation for lean startup principles.
This episode of CXOTalk offers a unique and clear look into how organizations focused on social impact can apply the techniques of lean startups.
Watch the entire video embedded above and read excerpts below. You can also read the entire transcript over at the CXOTalk website.
Ann Mei Chang: It was really an evolution. There are not that many people who span both worlds. I spent so much of my career in the tech sector that lean startup was essentially in my blood. In fact, when I first went into government, it was a big shock in a way because things worked so differently in government than they do in Silicon Valley. One of those things was that, in government, we like to plan in a lot of details for years in advance and then execute on those plans because we're very risk-averse; we're a very planning-oriented culture.
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What I found myself doing was really encouraging people to plan a little less, do a little bit more, and really get out in the field and try things, learn, and iterate. It was sort of like just the instinct that I had. At the time, I hadn't picked up The Lean Startupyet. I was in D.C., and it wasn't as much a thing there yet, and so I didn't necessarily have a language for it. When I found out that Eric had written this book, The Lean Startup, and started learning about it, it gave me a language to talk about these concepts that I was really trying to explain to people and didn't really make sense to them up to that point.
Coming from Silicon Valley and into this world of global development that I was in, everybody wanted to approach me and talk about technology and talk about, could I build an app, a website, or so forth? I certainly tried to help where I could, but what I started to believe, as I learned more and more about what was going on, is that while technology could make a big difference in many of the things that were being done, that a different way of working, a different mindset, a different approach that was exemplified by The Lean Startup, could help us just produce far greater impact at far greater scale.
Ann Mei Chang: Maybe I should back up a little bit for the parts of the audience maybe who aren't yet familiar with lean startup and talk a little bit about that. The Lean Startup is a book that was written by Eric Ries about seven years ago. It captures the best practices of how innovation happens in Silicon Valley.
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Eric talks about the lean startup as a methodology for building products and services under conditions of extreme uncertainty. This is certainly true for startup companies who are trying to create products and services that no one has ever done before, and so there's a lot of uncertainty there. In this world of uncertainty, rather than trying to think we have all the answers and come up with a great plan that we can invest a ton in that plan, I think we need to be a little bit more humble and really understand where our assumptions are, understand what the risks are, and test for them.
In essence, lean startup, I think of it as an entrepreneurial version of the scientific method that you have a hypothesis about a solution that will hopefully work to solve a certain problem. You build what we call an MVP (minimum viable product) to test that assumption. Then you measure the results. You gather data on what happened. Then you learn. You learn that it worked exactly as you hoped, and you can double down, or maybe you learned that it didn't work as you expected and you either need to tweak your solution or pivot and take a completely different path.
Ann Mei Chang: That's a great question, and that's one of the many challenges that make innovating for social good harder. The minimum viable product is essentially trying to come up with the smallest, quickest, cheapest way to learn about something where you have a high degree of uncertainty. Again, in the social sector, we often are trying to solve problems that are long-time, intractable, and in conditions that are highly dynamic, and so there is a lot of uncertainty, and there's a lot that we need to learn.
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The question to ask is, what is the cheapest, quickest way we can learn whether something will work? Just as an example, in Africa, different companies offer home solar systems using a new business model. With mobile money, people can pay a few cents every day to purchase their home solar system over time because they don't have the upfront capital to be able to pay for these solar systems upfront.
One way you might do this is to build out these new systems with all the technology, manufacture them, and then hire a whole salesforce and distribute them. A company called Off-Grid Electric, that I spoke to, thought this was a great idea, but they knew it needed to be tested.
Theysent a person from village to village to collect money, manually, first, to see would people buy a solar system and pay it off over time. Is that something people would find valuable enough? Would they keep paying the money? Only after they showed that people would do that did they manufacture the systems and deploy them in a way that could really be scaled.
It's just one example. The MVP could be as simple as a flyer, which they also used to test out to see, hey, what kind of bundles would people be more interested in? Would they like to have a bundle with just some lights, is a radio important, or maybe even a TV? Would they be willing to pay more?
The goal is looking at the simplest, quickest way that we can answer those questions. That's a minimum viable product.
Ann Mei Chang: I get that question a lot. We are equally trying to solve tough problems at large-scale, but when we're tackling social challenges, we need tools to innovate. It's also a lot harder, honestly. There are a number of reasons.
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One of the biggest reasons is the nature of funding. If you're a tech company or even any business, you usually have a customer that you're trying to serve, and you build a product or service for them. The customer pays for that product or service, and so there's a direct feedback loop. If people don't like your product, they aren't going to pay for it. You learn very quickly if you're on the mark or not.
When you're talking about social good, a lot of times who are paying for your product is different than the customer, and so you have already this complication where your feedback loop involves two very different parties who have maybe two very different interests. And so, that complicates things. It makes it harder to drive your feedback loop.
On top of that, funders in the social sector, especially funders for non-profits, tend to be very restrictive. They want to know your whole plan up front and then see you execute on that plan. They're often also very risk-averse. They're looking for immediate results. That also makes it hard to innovate. It makes it hard to pivot, experiment, and take risks. Some of these systemic constraints make it very difficult for non-profits to do the sort of testing and iteration that's needed to innovate.
On top of the funding side of the equation, there's also some innate challenges. It's harder to measure social impacts like, are you breaking the cycle of poverty? Are you making a society more resilient and democratic? Are you developing? Are you helping kids get better education?
These are things that take time, often, to answer, much harder than, for example, seeing if somebody makes an e-commerce purchase. These kinds of challenges exist in the social sector that don't exist in the tech world or even in the business world.
Also, I think we need to be much more thoughtful and careful when we're experimenting with people who are vulnerable already. We can't do the Silicon Valley thing of move fast and break things because we're talking about real people here and real lives.
Ann Mei Chang: I think that the culture derives from incentives, and incentives derive from goals. If you think about it, I believe that innovation, at its foundation, the birthplace of innovation is in an audacious goal. You imagine President Kennedy challenged us to send a man to the moon.
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When you have goals that are achievable with business as usual or with some minor improvements to business as usual, there's no reason to take risks or innovate. I think that often is true in the way non-profits are funded. They're funded to do something that we know how to do and that we can deliver relatively immediate results and do so with high confidence. But again, if we have problems that we're trying to solve, which that's not going to be sufficient in solving, I would argue that we need to set much more audacious goals.
The first place that I start with, with Lean Impact, is to say we need to think bigger. The core of Lean Impact is about thinking bigger and starting smaller. Instead, I think, when it comes to social good, we often think too small and start too big. How do we flip that around and set an audacious goal? When you have a goal that is ten times what you're doing today or 100 times what you're doing today, and you're not going to get there with your current path, then it forces you to take risks, and it forces you to test and iterate to find a better way.
When you start setting up the incentives that way, then I think the culture starts to shift around being more agile because you're trying to do something you can't do just by doing the same old thing.
Ann Mei Chang: Vanity metrics is a term that Eric Ries coined in The Lean Startup. It refers to absolute numbers, typically, that sound really good but don't indicate whether something is actually any good. Just as an example, in the social sector, if you look at your favorite non-profit's website, they'll usually tell you how many people that they've reached, touched, served, benefited in some way.
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If I say that I have touched a million people or helped a million people, what does that mean? I may have done something for them. I may have trained them. I may have given them a product or service, but did it make their lives better? It doesn't say that.
Even if we knew we made their lives better, could somebody else have made their lives better or done more with the same amount of money? Is it the most cost-effective solution, is another question. The third is that even if we made their lives better and we're more cost-effective than other solutions, and so we did the best we could with the money, do we have a path to scale, or are we only reaching a small tiny fraction of the people who could benefit?
These absolute numbers, such as how many people did we touch, tend to drive organizations to reach more people without sufficient regard to how well it's working or how they are going to scale.
In The Lean Startup and Lean Impact, we talk about actionable metrics or innovation metrics that are generally at the unit level. It's looking at, for example, for every 100 people we reach, what percentage excepts what we have to offer? What percentage are successful? What percentage changed their behavior, and at what cost? What's the unit cost for each person that we reach?
So, optimizefor unit metrics, for example, the percentage behavior change that has increased or the dollars that are required for the training decrease. Those things will be highly leveraged and increase, magnifying impact over time as you scale. Those are the metrics that, when you're focused on innovation, you want to track on a regular basis to understand, are we moving the needle on these metrics that matter versus the aggregate numbers, which is just a measure of activity, not of progress.
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