Using data to power meaningful impact at scale.

The ImpactableX methodology was developed by GoodCompany Ventures, an award-winning accelerator and innovation consortium. It has been used by leading social entrepreneurs, Impact Funds and Academics, including TSEF, Wharton, Stanford, USAID's Global Innovation Exchange, and Techstars, among several others.


Speaker: Well, thanks so much, Catherine, for joining me today, we were just talking about all the cool things going on with ImpactableX and excited to chat. But let's first start with sort of your journey and sort of impact venture and impact investing and impact entrepreneurship in general have just been in the space. 

Catherine: Thanks for having me on. I love this show.

I graduated college after having worked with the UN for some time in Geneva, where I saw firsthand the role of the global political base and some of its limitations. I came home really eager to figure out where I could bend my time and energy to really move the needle on some challenges that have really been plaguing the world for decades. You know, hunger, poverty, environmental degradation, despite trillions of dollars and decades of smart people's time and energy.  

So I started looking into what the private sector was doing at a time when, you know, Prius, and Facebook and Whole Foods were all just beginning to get a foothold in the market.  I was exploring, initially the role of corporate social responsibility, and then got recruited to join the management team of a few different startup companies that were really looking to leverage the power of the consumer markets, and consumer demand to drive impact in a number of different ways. Over the course of working with those different startup companies, we went through an accelerator program called "Good Company Ventures" designed for early stage social entrepreneurs to help them attract market rate venture capital, building business models that could scale not only, you know, revenue, but also impact. And while I didn't end up staying with the startup companies I joined, I became part of the "Good Company Ventures" team itself right when they had won a million dollar prize from Bloomberg Philanthropies competition with 360 other cities across the country to partner with the city of Philadelphia and work social impact initiative around addressing some of the city's really long standing and challenging and complex public safety issues.  With that prize money, we mounted this incredible consortium and sourced mobilize accelerated and ultimately launched 20 companies in the social early stage social impact space with a focus on public safety. So everything from criminal justice and recidivism reduction to providing access to benefits in a streamlined way to reforming the policing data infrastructure. We've now gone on to successfully close rounds with Andreessen and Kleiner Perkins and leading market rate VC firms, which was incredibly validating, you know, of our sort of underlying mission and scope. You know, from a career perspective, I got an opportunity to work firsthand with hundreds of early stage founders, well, time, they were really grappling with product market fit and proof of concept, figuring out how to get a foothold in a market, in the public safety space, which is notoriously difficult to penetrate. It was catalytic work. It was pivotal for my my career because, not only were we working with these entrepreneurs, but we were also working with an ecosystem of stakeholders, municipalities, academics, investors, corporates, thought leaders around the world to help them you know, get that  foothold, prove out their concept and then scale it up. So yeah, I mean, that was really the foundation for my career, and that experience ultimately led to my founding of ImpactableX.

Speaker: I want to ask a ton of questions about everything you had just mentioned. But let's first just get a broad overview of ImpactableX and sort of its mission and kind of what it brings to the impact business sector. As we stand here today.

Catherine: While you're running that accelerator, we just saw  how difficult it was for founders to quantify their impact, impact data to evaluate it, synthesize it, centralize it and leverage it to power, their growth. It was virtually absent in the space at the time. I mean, we looked around at some of the other approaches to quantifying impact, evaluating impact, and a lot of them were designed for later stage companies, or were really consultant driven. And the price points were just prohibitive for the companies we were working with. T he data and analytics themselves offered limited practical utility, either they were looking at dynamics of impact that really didn't apply to the kinds of companies we were working with, right, like operational footprint board composition, you know, headquarters location, you know, a lot of times we're working with companies that had a really small team, but the products and services they're selling had massive impact possibility and potential. So that was really what we wanted to be focusing on. We wanted to evaluate the relationship between revenue and impact, you know, the efficacy and efficiency of a business model as a lever for impact. When impact is created by commercial activity, it can't be evaluated in a silo to be meaningful. So we ultimately developed modeling methodology and deployed it internally, both with the Bloomberg cohorts and later with additional cohorts in partnership with the Obama administration's Climate Data Initiative. The companies that use this, were able to differentiate in front of investors at pitch competitions and other accelerator programs with their consumers and various partners, it was incredibly powerful stuff, so much so that the investors in our network provided some grant funding to spin this out, because they wanted to see this kind of analysis incorporated by every company that was pitching them. It provided just such valuable insight for them to evaluate, where they can place their capital for greatest impact leverage, right, a lot of companies sort of tell a compelling story that's sort of anecdotally driven or sentiment driven about their impact, but it's lacking grounding, and data and analytics, and research. So if we can incorporate those components into a story about impact, then it's incredibly powerful, and provides just so much more context and meaning. That's how ImpactableX was founded in 2019. Now, we're offering this methodology, publicly for companies around the world and impact funds around the world to help them define, quantify, model and forecast social and environmental impact as a derivative of sales so they can leverage their impact to more effectively execute on their mission and leverage their impact to drive sales and fundraising. So yeah, I mean, it's been incredible. The timing couldn't be better, earlier wave of interest around impact measurement and management right now, both at the global level and on the ground among founders. We are really helping, I think, to kind of bridge the gap between this very, very high level set of global standards and expectations, and the realities of founders on the ground who have limited time data and resources about really a tremendous amount of integrity and desire to deliver effectively on their mission. So we're really hoping to democratize access to high quality impact analytics.

Speaker: When we talk about analytics and sort of impact analytics, every company is probably going to need different metrics. There might be some foundational things, but every company is so different, right? They're going to look at impact metrics differently. Can you give us maybe an example or just like a case study of what this actually looks like? A company walks in, and you can use a fictitious company, or you could use a real case study that you've guys have done already, but just give us an idea of like, what actually is this and what you deliver at the end?

Catherine: I think that kind of like granularity can be super helpful. And you're right, every company is different, more or less. So let me give you an example of a company we just finished working with on the modeling side. They have these incredible storage bags essentially that they sell to smallholder farmers on every continent. And when they came to us, they were very proud of their latest Impact Report, which highlighted the various SDGs. Their work contributes to Zero Hunger, climate action, several others. And that was really where their knowledge and understanding of their impact stopped. So how their product drives hunger reduction, or, you know, reduced carbon footprint was really unclear or to what degree was really unclear. And so the way we started with them is the way we start with every company, which is we get on an intake call and we get a sense of the technology, the use case on the user side, and a company's business model. From there, we're able to work with them to define their key impact metrics. So in the case of the storage bags and cocoons, we looked at the following metrics: We defined metric number one to be reduced crop loss post harvest per hectare of land for various crops, categories, and two increased income for farmers resulting from reduced reduced crop loss. Yep, so already right there, we have much more clarity around the key levers that drive impact because of their product. And we also get a sense of their business model. So we begin our work by quantifying impact on a unit level, a unit could be a user or a product, or it could be a farm or a utility, or school or hospital or prison. In this case, we looked at a hectare of farmland, we also looked at each bag or cocoon, which is a much larger storage container. So we identified these two core units of growth. And then what we do is we begin a process of third party research and company data collection. So we quantify impact on a unit level compared to a baseline. So in Africa, looking at maize harvests, what is the average maize loss per hectare of farmland? We pull from third party research to define this turns out in Africa, there's about a range a 10%, to 40% range of crop loss post harvest, given the countries where this particular company was active, we decided to define a 25% baseline amazed loss post harvest due to pest and mold infestation, then we work with the company to aggregate company data to define the degree to which their product is able to reduce that 25% maize loss post harvest. Their research says that their technology can reduce crop loss by 100%. For the purpose of modeling we want with 75%. So let's take a very conservative assumption and quantify impact at that level. Because it's incredibly powerful to enroll various stakeholders, when you're able to say, you know, we have data that suggests we can reduce crop loss by 100%. But we're just going to model it out at 75%, then what we do is , we translate impact into economic value. So in this case, what that looks like is the market value of the maize that is saved post harvest, and the price point that a farmer can now sell that maize that because they have an effective storage container and can sell that may is at a higher dollar value for months post harvest. So we go through this process, a baseline definition company data collection, and valuation work. And from there, we do an initial analysis, we're able to determine the company's impact, which is the difference between the baseline and their company data, and then we assign an economic value to that. And then what we do is we model impact projections on top of financial projections. So if you know that one bag sold, or one farm can save, you know, 10 kilograms of maize, then you know that 10 bags or 10 farms can save 100 kilograms of maize. So we're able to extrapolate based off of our unit level calculations on top of accompany sales and revenue projections to forecast their social impact over a given term. And then from there, based off of that initial analysis, we generate summary analytics. So we look at the total social impact projection a company can create across all of their metrics, all of their products over a given term. So if we're looking at five years, typically, we'll create a five year social impact projection and then we can create multiples like an impact multiple of revenue, which says for every dollar of revenue we generate, we can create X dollars of impact and an impact multiple of capital. So a founder can go to investors and say, for every dollar you invest in my company, we can multiply that by 20x, or 200x, or 2,000x, and impact value creation. And so that's the modeling process. From there, we can create a number of tools, integrations, PDF data presentations that allow founders to really leverage this analysis to power their growth. So whether that's around internal impact management, key decision making around what data they need to be collecting, whether that's around articulation and communication to stakeholders. If this company is now able to go to farmers and say, we're going to save you 100 kilograms. That's incredibly powerful sales data, that is, in fact, their core value proposition. So  not being able to articulate leaves tremendous value on the table, and then if they can go to investors, and really be able to answer the inevitable question impact investors will have around how do you measure your impact, you know, they can really differentiate themselves and be prepared to deliver a rigorously developed, you know, answer. So I hope that's helpful.

Speaker: Yeah, it's great. I think that the key point I take out of it is that the social impact side, is also now turned into just an economic impact side, right? Because if you find ways to prevent waste, be more sustainable, usually, your economic outcomes are better. That's a really great selling point, whether you're pitching investors and you know, investors are gonna want to see the epic economic side of things is seems like what all of this comes down to across any level, right? It's like, again, you see more companies than I do when you're looking at metrics like this. But I would think more often than not, when you solve for the social impact metrics side of things, you also find that it actually might boost economic value, as well.

Catherine: So there are two dimensions to this one is risk reduction, which is really the basis for ESG investing, right? So if a company is dependent on, you know, infrastructure that could explode, like we saw in Texas, that creates market risk. And so sustainability from that standpoint, is really around limiting exposure to risks like that. Then there's the impact side, where we see impact creation, as value creation, typically, that value that a company creates an impact is not reflected in their revenue. That impact is borne by the comments or various third parties, but its value creation, nonetheless, and being able to capture and articulate that value allows companies to sell more effectively for sure, if they can articulate it to the right stakeholders, right. So if a company is reducing, you know, trash in a particular geography, that saves a municipality, certain waste management costs, if they can articulate to, you know, the, the buyer or the municipality, you know, how much they can save in waste management, that's incredibly compelling, and, you know, may provide the raw material for whatever, you know, products or services a company sells. Yeah, we think about our work, as you know, really helping a company to capture the full value of their innovation and leverage it to power growth, that growth component that you're talking about around economics is absolutely foundational. And in fact, 80% of the companies that have worked with us have gone on to raise 127 million in capital within one year of completing our work. So, both on the sales side, and on the fundraising side, it's incredibly powerful stuff.

Speaker: Does it matter what stage a founder or company is in? Because if they're early stage, very early stage, would they not have sort of the metrics, you need to give them a very sort of powerful identity that early on? Or would it matter?

Catherine: Yeah, it's a great question. So if a company is really, really early, you know, still at an idea stage, or MVP stage, we can absolutely do this work. Usually, we see that it's less of a priority for them. They're focusing on building out their product and testing and validating it, but what we're finding is that this work can be applied to any company at any stage. The question is, how strong the inputs to the model are. So if a company is pretty far along, and they've already collected lots of impact data, then we're able to build their impact model of a very strong foundation. The reality is, though, that companies at pretty much any stage haven't known what data to collect or how. They haven't been known, necessarily how to define what metrics to be tracking. So typically what happens with a company at any stage is that we begin to build their model off of initial impact assumptions, assumptions that, of course, are well grounded in research and columns and data. But usually assumptions. Then from there, a company knows what their metrics are, they know what data they have, what data they don't have, where what gaps they need to fill, and they can put a process in place to begin collecting that data. Then their model gets refined over time. So if a company is super, super early stage, still at an idea stage, it's likely that the metrics themselves are going to change and evolve, because their products are still going to change and evolve likely, once a company has really established product market fit, they can lock and load on the top impact metrics that are most core to their value proposition, begin to build a model and then have a core infrastructure, a place that centralizes and synthesizes all the data, they collect, and evaluates it in a way that tells a really compelling story. So typically, we're working with companies at the post seed, pre series, all the way through, you know, Series C rounds, and I'm finding that regardless of stage of development, impact data is often missing, which is absolutely okay. We like in impact modeling to financial modeling, you know, so if you're at an early stage, you need to build your model off of initial assumptions, and you need to be prepared to substantiate those assumptions with your investor. No investor is going to hold an early stage entrepreneur to their five year revenue projections, but no investor is going to take a meeting with someone who doesn't have them. It's become standard and expected among investors that founders, have a really well thought out, but assumption driven initial financial model that, of course, evolves as they start driving sales, and they get a better sense of their market. And so we think the same is true on the impact side, as long as a company then puts measures in place to collect data to refine and validate those assumptions.

Speaker: I want to go back to something you talked about a little earlier. And that was your time at the UN and then your time at "Good Company Ventures" when you worked a little bit with the city of Philadelphia on some aspects through the accelerator. As you're talking about this, this seems really a valuable asset, also for local cities, state governments, federal governments, uns, nonprofits. If we're talking about waste, there's a lot of waste in those entities. And I think if you look at, you know, a city program, like it did in Philadelphia, or a state program, federal program, a un program, programs can be looked at as companies. What's the waste on the government side as well? Can this be used to make government programs, aka, you know, there used to parallel for companies much more efficient, and less wasteful through something like this.

Catherine: Yeah. So we can absolutely apply this to various nonprofits, various government programs. What's interesting on that there is the dynamic between, money spent and funding received, and impact creation. So what's really unique about our model is we're, really integrating the financial side and the economics with impact. We've really seen impact evaluated in a silo. So, we can absolutely look at impact creation for a given brought program, but even more valuably, I think we can look at taxpayer spending, or various funding sources and the leverage they create for solving problems in an effective data driven way. So absolutely.

Speaker: I want to go back one more time to to the "Good Company Venture" accelerator. What has come come out of that? Do you still, look at those companies details, speak with them, like I guess what is the aftermath, of that program? How was the the maturity of that program?  How would you assess the companies that came out of that?

Catherine: Oh, my God, those companies are incredible. I'd have to go back and look at how many of them are still active. But what I know is that many of them are just crushing it. The learnings that many of your listeners might recognize in the criminal justice space in the agro tech space in the Ed Tech and healthcare, tech and gov tech spaces, their growth, their ability to engage market, right capital has really helped to demonstrate that you don't have to take a concession when investing in or otherwise supporting, impact driven companies. We think of entrepreneurs as problem solvers. And social and environmental challenges are massive problems. And by solving massive problems, you create massive value, just so happens that we tend to think of impact in sort of nonprofit or charitable terms, because that's sort of the last gen approach. But now we're starting to see that not only can you solve massive problems with technology, but you can also create tremendous returns. And I think that is really the takeaway of my work with "Good Company Ventures". So now ImpactableX is all about helping those companies get to that point by capturing their impact and the value that it creates, and leveraging it to differentiate themselves and power growth. So, the companies that we worked with, during Good Company Ventures, were absolutely still in touch with. I think of them fondly and often and promote their success as much as possible. And we have testimonials from them that say that the work that they did around impact measurement, and with ImpactableX was absolutely critical to breaking through, which is really why I do what I do. That's the whole game, as far as I'm concerned. We want to be able to offer that to as many companies and impact funds as we can around the world.

Speaker: Amazing stuff well, and on some congratulations. And then we'll we'll talk a little bit about the future, but Fast Company world changing ideas, awards for 2021. And the impact investing space factor will X was was was given that award. So congratulations on that. It's a pretty, pretty sweet thing to happen. Probably gives you a bit of motivation and optimism going forward. So let's end sort of a little bit on the future. And what are you optimistic about, let's say over the next, you know, 1, 2, 3 years, as, impact metrics are going to be a thing that I think every company will have to have in some way. Right? What are you optimistic about?

Catherine: I think you hit the nail on the head grant, like this is definitely a wave. And I think we're still at the early stages of it impact investors have really made it clear that impact data is critical for their work for a number of reasons. That reality is, really sort of setting in with founders and accelerators as the impact investing in the social impact space writ large, really evolves and grows in sophistication. We want to be sort of the go to resource not only for sort of static analytics, but you know, dynamic modeling, dynamic, automated track performance, tracking and reporting to really enhance the legitimacy of the space. Ultimately, we think, unlock capital that's on the sidelines, you know, from otherwise mainstream investors who are interested in impact, but are sort of questioning its legitimacy. W e can help enhance the sophistication we think we can help mobilize capital to. So I couldn't be more optimistic. I mean, every day, I'm learning of new companies that are solving new problems and new and fascinating ways. And we're seeing companies like you know, Adidas, and Burger King. I mean, really, mainstream brands begin to integrate new approaches, new technologies, new materials, into their products and services. It's incredible. It's like Christmas every day, really. I mean, we're we're just riding the wave and trying to maximize our value add to it again, it accelerate the evolution and enhance the sophistication and legitimacy of the space.

Speaker: Amazing. Well, thanks so much, Catherine. Best of luck to you and the team for the rest of this year and hopefully the decades to come.

Catherine: Thank you so much grant for having me on and if anybody wants to get in touch, visit us at

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