Impact data powers sustainability strategies for digital age

Transcript - Impact data powers sustainability strategies for digital age

Ana: This is Tech Beyond the Hype, a podcast about the future that looks at how today's business trends are impacting the way that we work. My name's Ana Salom and I'm on a mission to make sense of how advanced technologies like AI, blockchain and more are shaping the future of business. Today, we're talking all about ESG and impact intelligence.

In the past decade, as awareness about the urgency of the climate crisis has grown, ESG has been through a sort of 'glow up,' starting as an investment banking niche and becoming a hot topic and top priority for leaders in boardrooms across industries.

With more data at their fingertips than ever before, businesses have the opportunity to implement changes that drive long-term impact, leveraging AI and machine learning to get insights on their company's performance and how to improve. However, as with any AI-driven technology, the right data needs to be collected for those insights to be accurate and for the decisions that we make around them to be reliable.

My guest today is Fleur Heyns. Alongside her many accolades, which we'll hear more about later, she's CEO of Proof, an impact intelligence platform dedicated to driving positive impact across the global investment finance and business space. We sat down some weeks ago to talk about impact intelligence and explore the key challenges and opportunities that businesses face in the transition to a green economy.

Get ready for a comprehensive and open discussion about ESG and impact intel with lots of useful insights for anyone looking to leverage impact data, to drive long-term positive change in their business. I hope you enjoy the episode.

[00:01:49] Fleur: My name is Fleur Heyns. I am currently based in Cape Town, South Africa. I'm Dutch and I'm a bit of a global cosmopolitan in the sense that I feel at home everywhere. My real sweet spot is between the tripod of impact, impact data, impact intelligence, finance as an investment banker and technology.

I am currently building a couple of assets, but mainly focused on Proof, which is an ESG and impact data intelligence platform to start from the ground up because we unfortunately in this world have a very big problem with impact and ESG data, which could also be referred to as 'garbage in and garbage out.'

I won't go into too much detail just yet, but Proof is essentially a technology platform that leverages any form of technology advancement to start collecting data, information around where is real carbon emissions reduced? Where is water being saved? Where are we having inclusive financial products? And have that data evidence, of those companies, so that they can be more visible to investors, but also we think they can actually perform much better, even in their own environment. So, that's the objective of building the Proof platform and I'm sure we'll talk more about that.

[00:03:03] Ana: Yeah, sure. Thank you. And when it comes to the Proof platform, so thinking in terms of our audience, I'm conscious that there's a lot of people who won't have a finance background and potentially see ESG from a very business focus. Could you kind of bridge the gap between the two and explain how it works?

[00:03:20] Fleur: Absolutely. Absolutely. So, I think we need to first make a distinction between ESG in public markets. So, ESG is the term that's being used for environmental, social and governance predominant policies, that publicly listed companies have to disclose. They have to adhere to it because public shareholders are increasingly looking to make their investment decisions based on whether or not a company has these ESG policies in place. So, are they really telling us how they're managing the risks? That's the most important side for them, the risks in how they are engaging with the environment, society and governance. So, that's very much on the public market side.

And to be honest, that is a bit of a red herring -- as in, ESG in public markets has no real material value. It isn't something that you use to improve performance of your business. It's not something that you use to get higher returns. It's just a label on policies that public companies have to have so that the investor knows 'what risks could I be exposed to?' That's one part of the conversation, and to be honest, that is really much more addressed to the financial institutional market. It's not really addressing the entrepreneur or the businessman who is just trying to do the best that he can in his own business line.

On the other hand, which is a far greater market in the world, if you think about it, are private markets. These are businesses that also have a relationship with environment and society and that also have a responsibility to govern their businesses well.

The acronym E, S and G has no purposeful alignment. It's stupid that those three words got put into one acronym because they have very little to do with each other, other than what I mentioned earlier in the public markets, that it's more like a policy setting and you're setting policies on those three areas.

But when you're talking about real brass tacks, boots on the ground, what is it that you can do as a management team in a business, as a CEO of a business, as an entrepreneur of the business that relates to the environment, society and governance? Well, let's start with your business plan, right? What are you solving for as a company?

If you asked me this question 20 years ago, very few entrepreneurs would be solving what we would call an environmental or societal problem, because we didn't really know that we were creating such big problems, right? So, everybody was just building a product or a service that they knew there was a need for, and we didn't really take into account how much carbon would this be emitting if I build these cars or how much workers do I need to build a manufacturing site in China. It was like, go, go, go -- just produce, and no one was aware of the consequences of these productions.

That's now changed because we know that in order to produce fast fashion, there are factories out in Bangladesh, in India and God knows what, where yes, the fashion is produce fast, but people who are working to produce that fast fashion are not treated in a humane way, and that is now consequential to that company's perception with its target audience, which means it has now financial, business value whether or not you treat your people well.

So, this has changed the mindset and the opportunity set for entrepreneurs to not just focus on what product and services can I produce at whatever cost. It's become much more, 'how do I create businesses that produce a product or service that is firstly maybe addressing some of these unintended consequences that the previous generation of entrepreneurs produced,' which is, you know, having people that are not being treated well or having severe damage done to the environment. So, think about companies that are being set up to capture carbon, or companies that are being set up to provide inclusive services because there are excluded populations in the world. Those are all opportunities that are environmental and social driven, right? So, in the intent of setting up the business, you are thinking about your business as solving for a particular environmental social problem.

And that's more from a negative side. But then if you look at it from a positive side, there are also opportunities. The growth areas, if you think in the world of the problems to be solved, again, often relate to this transition to wanting to become more renewable. So, think about the battery business, the move to electric vehicles, the move to plant-based foods. These aren't necessarily businesses that only exist to damage control what was already done, these are businesses that exist because there's a genuine demand by consumers to have responsible coffee, to have a clean vehicle, to be able to go on an ecotourism holiday. So, these are actually growth opportunities that are now, again, driven by the desire of the consumer to make sure that whatever they transact with is responsibly produced.

In the second model, how you generate the return, what you do in order to create a responsible product or service is becoming far more important, and you need to have information to show how you created the product or the service and that comes back to Proof. So, the proof of how you produced the product that produced the return, that is what we're trying to capture in our intelligence platform for the users, for the companies.

Now in the Proof side, we have a positive side effect, where at the moment it's not just consumers who want to transact responsibly, it's investors who are saying, 'if I'm going to invest, I want to invest responsibly,' and in private markets, investors have historically been excluded from getting any information on how a company is producing its products, because the only thing they're really allowed to ask for is your cash flow, your revenue model, how many users -- but the data on what was your carbon footprint, what is the minimum wage that you're paying, wasn't necessarily part of the initial due diligence, and it wasn't something that you have to report on. So, again, giving investors insights even before they make an investment at the due diligence stage to show which companies are truly taking advantage of this opportunity to create products that are well-made and responsibly made.

That is, again, something that is now coming into the investment process. So, as an entrepreneur, you need to be aware that when you now go and raise capital for your fund or for your business, you're going to have to start answering some of these questions that allow the investor to assess, 'Are you as a portfolio company going to help me on my trajectory as a fund manager, institutional fund managers or the family offices that I am going to be a net zero investment fund by – I hope not 2050, because that will be way too late -- but say it's 2030?,' then at least these conversations are starting to happen.

And that's again, just purely from a risk mitigation perspective, but if you're smart and you can show, looking at unlocking the opportunity that by doing certain actions well -- by managing natural resources well, by managing your water, by managing your carbon, and you as investors, selecting portfolio companies that really manage carbon well, that really manage their water and also human resources well -- you're probably going to find that there's going to be correlations to financial performance.

And in fact, we have an example of that. We seed funded on the public market side an asset manager called Osmosis Investments, and I hate that they've been using this term, but they just got awarded the Best ESG Fund in the world because they look at resource efficiency. They should actually be called the best resource efficiency fund in the world or maybe just the best fund in the world because it's not necessarily anything to do directly with ESG policy. They actually look at the data of the publicly listed companies and they've been able to show that those management teams that manage natural resources well -- water waste, energy -- they get better financial returns. The market rewards ultimately because those are better companies.

So again, there's always the two sides of why you should look at environmental and social data, why you should optimize it. One is you want to reduce liabilities, you wanted to reduce disasters, reduce social lack of responsibility, you know, being caught out in the scandal, whether it's gender-related or race-related, etc. You want to avoid that and therefore you need to have those insights, because otherwise you just won't exist, but increasingly you want to optimize for driving performance to not just avoid risk, but to actually contribute.

Sorry, that was a very, very long-winded answer, but I think it just gives you a bit more context that this isn't just about writing a policy, calling it ESG, and then walking away and thinking job done.

[00:11:58] Ana: No, absolutely. And I think, well, thank you first of all, because I think that was a really holistic explanation that was very clear.

I've been following ESG for some years now from a financial perspective, but also seeing conversations about ESG in business and how people approach it. To me, it comes across that the paradigm that you're explaining of the risk side and then the opportunity side, for such a long time it's just been a focus on the risk and on ESG being a tick box exercise rather than something that could in itself be of value to the company and to bring new opportunities for a company.

When it comes to clients that come to you, what would you say is the percentage of people who understand from the get-go that there's a value add or are they coming to you mainly for the kind of CSR, tick-box type side of things?

[00:12:48] Fleur: So, our original version of our business was called Proof of Impact. So that kind of gives it away, right? Our DNA is very much more on optimizing for contribution that we're trying to measure.

What we've seen is the largest growth group for a product like ours, which is more sophisticated because we're looking at a spectrum of KPIs from that impact origin, but we've also added the ESG metrics.

ESG risk metrics per industry are largely within what's called the SASB framework, which is SASB, so that's an industry framework for both public and private companies where they look at, from a risk mitigation perspective, what could you measure that may have an impact on your financial return? And it's mainly around, could negatively influence your financial returns.

We've embedded those, this SASB, because at the end of the day, say that you are trying to move, you're building a fund, regenerative agriculture, right? And you're really focusing on environmental optimization of soil, of reducing carbon, of managing water, but you underpay your staff, you don't have a sexual harassment policy in case or whatever that means -- yes, at the face of it, the DNA of your business is doing good, is having impact, but you've got huge risk factors where you are not treating the human resources in your business appropriately, and that could still cause a massive blowup. So, that is something that you have to measure on both sides.

So, I would say the growth area is covering both the risk metrics and increasingly adding impact metrics to it. And that those businesses are our clients, and in our case, they are mainly the fund managers in the thematic areas of regenerative agriculture, education, financial inclusion and energy transition. Those are the four themes where you'll find investors who have to look at the entire spectrum of the equation.

When it comes to the ticking the box, I used to be very condescending about that because I'm like, how do you know if that data is correct? But increasingly I've realized that we all have to start somewhere. Asking companies to deeply integrate and give us, as a tech platform, APIs into their ERP, their payroll system, their CRM, do surveys with their employees, do surveys with their consumers, is very invasive, right? And that might not be something that they're entirely ready to do yet because they haven't even got the baseline. They don't even know from what point they're starting. I'm now coming to the conclusion, and I wouldn't call it a tick-box exercise, but maybe more of having a baseline survey where every company in the world, whether it's private or public, but the public already have to do that, but every private company goes through the exercise of just doing a simple baseline survey around the same 10 KPIs around the world.

And the example of that is now in Europe in the form of a regulatory compliance, module of requirements called the SFDR -- Sustainable Finance Disclosure Requirements. So, the same thought process has gone through all these experts in Europe and all these regulators who are trying to actually fight against greenwashing. That's what the exercise is for. They don't want to have funds who call themselves green or sustainable, who don't even have a clue what the baseline or any of the data their portfolio company is. So, they have researched what are the 14 mandatory -- it's called PAIs, Principle Adverse Impact. So, these are again, factors that could negatively impact the financial performance of your fund. So, it's very fund focused, but the fund manager has to get the data. The process, the checklist requirement, is that as a fund manager, you have to go and get data from your portfolio company on a quarterly basis. And it's not about are they moving in the right direction, are you reducing carbon? It's about, have you at least done the middle amount of efforts to start looking at this information?

The checkbox exercise has become more necessary because we need a baseline. We need to know around the world, everywhere for every industry, water, waste, energy, gender, wage equality, 10 KPIs and have them just in our toolkit, right? We need to create indices and benchmarks around that.

That has then given the opportunity for some regulators to say in markets where we want to ensure that the retail investor doesn't get burnt and thinks that they have invested in the pension fund or in an investment fund that is solving for the world's problems, or at least try not to do any harm, and it turns out they haven't even looked at the data, right? So that is the one of the use cases that is being now addressed in Europe and I think will be increasingly addressed in the U.S. and other markets as well, where there will have to just be that tick-box basic standard reporting requirement for anyone who is taking money from anyone else.

So, whether you're a company or whether you're an investment fund, if you're promising that you are having any form of 'no harm to the environment,' you have got to start showing the data. So, I've changed my tune. I'm not condescending about it anymore. I think it has a role to play and I think it's very, very important that at scale we get this adopted. And in order to get adopted, I mean, coming back to the theme of your podcast, I think it's very, very important that we have bottom-up technology solutions that can, in a smart, reliable, cost-effective way, start getting this information, from the survey to data integrations to then maybe AI-driven insights, to start really pulling this so that we truly have a clear picture of the environmental and social exposure of this company or fund, as we expect to have a clear picture on the financial exposure of these products.

[00:18:18] Ana: Yeah, that makes a lot of sense, and I understand what you're saying about the CSR not being a tick-box exercise, but rather having a baseline to run off of, makes a lot of sense. But on an international level, I guess one of the challenges that I see when it comes to having a set of standards that are expected across the board, like you said, is that we're talking about a really fragmented economy, where companies in some countries have access to tools and ways of working that can facilitate that or allow for them to be able to tick those boxes. What happens when you're talking about businesses in countries where that's not quite as, where maybe the development is, they're kind of earlier in their development phase. How does that work?

[00:19:03] Fleur: So, this is, it's a really interesting question and we get it all the time. So, we are pretty much geography agnostic. We started very much emerging market because of this whole sort of impact theme, which is often associated with development finance, and now we're global. We have, I think half of our clients are in [the] U.S. And I'll tell you something, we have greater problems and less visibility on extracting data digitally out of U.S. clients and portfolio companies than we do from emerging markets.

And why is that? Is -- and this has been the same for mobile telephony, digital banking -- typically when there's a really, really poor incumbent infrastructure, as you hint to, you know, they don't have the banks, they don't have the telephone companies, they don't have consultants they actually leapfrog.

They are not able to go to those more manual driven institutions -- they have got to solve for it with technology. So, you'll be surprised to hear that there's so much more readily available digital data that you can connect into in emerging market companies than there is in the Western Europes and the USes of this world.

So, I think that's a red herring. I honestly don't think that the access to data and the ability to capture data is geography specific. And if it is, I think it's almost the reverse from what you said -- we have greater digital, direct, real-time insights into most of the emerging market, highly tech-driven businesses than we do in a lot of the more developed market, more conventional incumbents. However, if you take the geography out of it, it is true that there will be gaps in the ability of a company to report on something.

There are definite gaps, but it's all about the diagnosis. It's better to know where you don't have data than not know at all. Even knowing that you don't have data in that particular KPI is knowing something and it means that you can then either provide a solution and say, okay, you may not have the data, but have you looked at maybe getting information in this particular way from your own operating environment? And if that didn't work, then there is -- again, I'm not a big fan of it, but there is a proxy default.

So, you could say, 'I don't have that data for my carbon footprint as a manufacturing shoe business in Denver, Colorado, but I see that most businesses in my size in Colorado roughly produce this amount of carbon emissions, so I'm just going to take that as a proxy for now until I figure it out.' So that would be the interim step, and that's also actually been accounted for in a lot of these compulsory compliance modules by regulators, is that you have an option that when you have a data gap, you share proxy data.

The requirement, however, is that you don't treat proxy and your own proprietary data the same. So, it will be visible what is proxy versus what is proprietary data.

So as an investor, I'm looking at investing in company A, all of their data's raw data. They're measuring everything. It's coming from the management team, even if it's self-reported, there is a measurement there. They sign off that they think that's true, and I have another asset B that I can invest in where I see 70% of the data, they have filled in with proxies. They have no clue. Well, that says a lot about that management team if it's in the same industry and one team is able to gather data and measure it and track it and monitor it, and the other one is filling in proxies because they have no clue. If I had to take a guess and I don't even need to look at the analytics, which company is better run, full-stop, I'd probably go for company A.

So, this is again, just giving investors another layer of not just what does the data say, but what data is that management team capable of collecting and gathering? And I think that's another really, really important factor in the future, which is what is the data quality? What is the data governance process, and how much confidence do we have that what a company reported is actually going to be accurate?

That is something that I think technology can help a lot with, in terms of doing a collection from different sources, doing validation on data, and then there'll come a time when it's just a norm that as a company in order to get access to capital markets or to satisfy your customer needs, you'll have to invest in data collection capability around these 10 core performance indicators that the world wants to see.

[00:23:11] Ana: That makes a lot of sense. I work a lot with companies looking at data governance from a totally different angle in terms of analytics to do with a whole series of different things but looking at business metrics.

[00:23:23] Fleur: Yeah.

[00:23:23] Ana: And in both circles, in terms of the impact intelligence and general business intelligence, there's the challenge of collecting and gathering the data and then putting that data to use -- in a future where this is more widespread and it's commonplace that people are verifying their data, and as you said, sharing those 10 KPIs, would the responsibility sit with the leadership team? There's obviously a challenge in self-reporting as you said that there may not be full transparency, or the data may not be accurate.

[00:23:55] Fleur: Yeah, no. So, I think, again, if you're asking about who does the responsibility sit with to monitor whether or not you are performing against -- call it your sustainability strategy or your future proof strategy, whatever it is -- that absolutely sits with the management team, just as making sure that you are measuring the revenues, the operating margins, the expenses of your P&L, to ensure that you're tracking toward your financial goal.

Again, I come back to the point where I said earlier, if you see in a business that the management team has not dedicated any time or resources toward building the infrastructure where this information is available, and even if it's a journey, you're not going to go from zero to a hundred percent in a month or even a year, but you're starting to at least look at your business from that angle, that's already pointing in the right direction.

So, in the public markets, I'll give you an example -- everyone thinks Tesla is such an amazing company because his brand is awesome. And from an impact perspective, they are solving for the move away from hydrocarbons -- like that is ultimately the goal, and that is inspirational and aspirational.

But if you look at the operating process of a Tesla factory versus the operating process of a BMW factory, and if you look at the fact that the BMW management team has reported on their sustainability goals for 30 years, you then have to ask yourself the question -- OK, yes, at the inspiration level, at the intent level, of course the business plan of a Tesla is incredibly impactful. However, how they're executing it is actually not very resource efficient, environmentally friendly, et cetera. Like we don't know where those batteries come from. They huge amounts of waste. They're not very efficient with water consumption versus a BMW where they measure per car produced, they only have 10 grams of waste. Everything else gets recycled.

So if I have to take a bet in 15 years' time as all of the automobile companies are transitioning to electrical vehicles and you have a BMW with a company culture where from 30 years ago, management team insists on whatever we produce, we're going to measure water waste and energy, I would take a bet that that company -- I mean public perception aside, because the markets are not always rational – will outperform the Tesla because they have ingrained it into their operating rocessses to be –sourceful, to be effective, and to be very responsible when it comes to human and natural resources.

So that just gives you an example where, yes, it has to come from the management team, it has to be implemented in the entire operating business. But I will make one caveat, which is we're talking about Tesla and BMW, which are multiple, almost trillion, billion-dollar businesses and they're very mature, et cetera, and they have a huge amount to optimize for and address, when you're talking about start-ups coming out of the ground, I think that there, you can only do so much, right? Like you're trying to fight so many fires from so many corners. However, again, I would say whatever is the most minimal viable effort you can do to start at least putting this into your dashboard -- again, those 10 key performance indicators -- even if you can only measure one of them, you know, how many employees we have and how many are maybe female, that's already something. So again, you can't be too aggressive in the assumptions that at every stage of a business, everybody's optimizing for everything -- like that is, that is just wishful thinking for now. But you should be on the journey to at least what you do know, you start measuring and you start performing yourself on.

[00:27:35] Ana: Thank you. that's really awesome, and so in practice, what does that look like when it comes to the technologies that you're putting into place? What do businesses need to start looking at from a tech perspective, to be able to gather and use that data?

[00:27:49] Fleur: Yeah, so again, there's a lot of hype and attention that has now gone to Generative AI, being able to - Chat GPT - ask the bot a question and then the truth comes out. And these are marvelous advancements, so that there's knowledge sharing at a degree that is unprecedented. The basic foundational problem that we have to solve for, and that we can use some technology for, is still 'garbage and garbage out.' No matter how well we advance with machine learning and AI, if you don't have the right inputs going into whatever is constructing the answers or is, you know, extrapolating, you're going to have the wrong outputs.

And this is not just inconvenient -- it could be quite dangerous. You could be investing in the wrong things. You could be optimizing for the wrong things. You could be transacting with the wrong type of companies. So, for the garbage in, garbage out problem, it's much more at the level of the data capture and the data storage that we need to be extremely diligent and where we need to have greater advancements.

So, let's take the examples of the carbon credit markets. You've probably heard of Gold Standard – Vera, Southco … These are all companies that on an annual basis, would supposedly certify that there are projects and businesses all over the world that have been able to reduce carbon emissions and captured carbon, and in exchange for having captured carbon, these businesses are issued a carbon credit. And the carbon credits is something that they can go and sell in the market. And then other businesses or governments that have produced too much carbon in the atmosphere can then offset their own carbon by buying these carbon credits.

Now, if you look a little bit more in detail in the processes -- and it really didn't take a genius to figure this out -- but if you look at how these carbon credit certifiers operated, they didn't operate any differently from the consultants we have in the NGO and donor space where they go into the field, they have a guy with a clipboard, the guy with a clipboard takes some photographs, makes some notes, takes about two years to process what he saw two years ago, and then he goes, oh, I think you're gold, silver, or bronze, as a standard or AAA, AA or A -- no data evidence, no real continuous real-time evaluation of what has happened since I was there two years ago. Yet that carbon credit certificate was issued and it's now in the market. And I think that the data collection side has caused a huge mistrust in anything that would be securitized that is of a natural societal impact.

So, carbon credits obviously are not real assets in the way that we normally describe it -- it's not a house, it's not a company, it doesn't produce anything. But we created an asset out of it because we thought that the validation systems were good enough and they're not good enough.

So, the first problem that we need to solve for, particularly in areas where there's a monetization or there is a securitization of an impact output, we need to make sure that there is a far higher burden of proof to make sure that that activity is justified, is validated, and that that gets captured.

So, one is having, as I said, multiple sources of data for a particular claim. So, we're talking about reduction of energy emissions. We could talk about satellite imagery live, of a particular forest area where we soil samples, maybe there are drones that fly over and go through the trees and see if everything's still there.

I mean, I'm just talking a little bit out of my head here, but there's numerous sources to collect data that then you could store, and I'll talk about that in a second, to really capture at that time and over a consecutive time, what is the footprint of this area and what are the calculations -- that also again needs to be scientifically based, to assume that a certain amount of carbon was reduced. So that's level one.

Then level two is at the storage level. So, once I have ascertained, with a high degree of confidence, because I've got multiple sources all saying the same thing, that at this point in time, in this area, we have legitimate carbon capture, then it would make sense to have all of that data evidence stored on some form of distributed ledger, so that it wouldn't be able to manipulate that data retrospectively. And also, you would have an audit log of capturing this data systematically and accurately, and if someone said, in five years' time, why did this forest in the Amazon get issued 5 million of carbon credits, well we go back to the audit log, and we don't have to send another consultant to do like historical studies on whether or not there were trees here five years ago.

So, I think that that's the data storage capacity that can improve. And then, I think we get into the area where the public markets have advanced quite a lot, which is, how do I interpret this information? So, I now know that this forest has captured carbon -- what does that mean? What is the financial value of that?

And in the forest example, you have every cubic ton of carbon has a certain market price. But say in my business, I have hired more women, right? And I'm doing that systematically, and I want the gender parity to exist across all my business areas. I have 3,000 employees, 1,500 women, 1,500 men. I also make sure that there's wage equity and that they're all given the same opportunities. I reliably obtain this information, that that is the case. I've got my payroll data, I've got the mobile money wallets, you know, emerging market advancements -- again, not bank accounts -- of these employees. I see that we've got track records of their performance reviews, what they've done, and they're all being paid and treated fairly. Then I can say, okay, I'm storing that but what does that data mean? So, I've done this as an act of wanting to be fair, but I also genuinely believe that diversity is super important for the productivity of the team. So, can I maybe map my progress toward this gender parity with maybe revenue growth or improvement in operating margins?

It doesn't even have to be as politicized as gender. It could even be treating all your employees well and them having less sick leave, looking after assets better. There's a really, really good book, Leaders Eat Last, [by] Simon Sinek, of course.

And he gives his example of live cases in manufacturing sites in the U.S., where a team of more innovative managers came in, into a labor force of a thousand people that had historically been treated a little bit like children. You know, you clock in, you clock out, this is your coffee break, this is your insurance product.

And they changed that model and just actually treated them like adults. And in the process of treating them like adults, they found that the care of the assets -- so looking after the equipment -- was so much better.

They found that people were willing to work longer. They found that people didn't take as much holiday. They found out that when they were at work, they produced more. So, it's a win-win situation. So again, these are all models that if we give the right inputs -- that is clean, right, because we've checked it -- into some of these AI algorithms and we start building scenarios where we have not just one example, but we have 10,000 examples where people have legitimately improved the wellbeing of their workforce, and they've been able to show that the result of that was improved revenues because people are producing more, but also improved operating margins because people are looking after the equipment better, there's not as much damage and wear and tear, and maybe there's even a level of perception in the market that this is a cooler company because everybody's happy and therefore, investors are like, wow, this seems to be growing faster than everybody else in this industry. So, we're going to give it a higher valuation. So, win-win-win on all fronts.

Then this kind of data would allow us to help all the other companies, the thousands that are at the beginning of their journey, they just said their baseline. They're like, 'we just got our 10 KPIs. Woo.' Now we're going to implement program A, which is 'we're going to advance the wellbeing of our employees.' Well, what would you advise, Proof API or Proof AI, in terms of the actions we should take as the management team to do better for our employees?

What are the things that we can do? Should we give them healthcare? Should we give them free working hours? Should we allow them to work from home? What are the interventions that can be done based on what we know historically has worked within certain categories, and then what would be the result of that? Like, what can I expect in terms of outcome?

So, I also know if I have to make an investment, like I might have to create a yoga room or whatever. If I put the $10,000 in, when will I get reasonably to expect that that amount of money come out. So, then the platform will then be able to process all this and take you on this journey and say, well, you're now here at step A, you've just set your baseline. You've got a wellbeing score of three or four, whatever it is, if you want to get to seven, then this is what you can expect will happen on the financial side. And then with that increased growth, you're going to be able to raise more money, which means you can hire more employees, which means you're going to be having more happy people.

And you create this golden circle of everything positively influencing each other. And at the core of all this is that data transparency. Without solving for the garbage in, garbage out problem, you cannot get there because your assumptions will be wrong, your outputs will be wrong, your AI algorithms will be wrong.

And that's just one of the risks that we have in our current market right now. If we do not really, really diligently assess what goes into the machine, and therefore we don't really know what comes out of the machine is reliable, we may have people take the wrong action or interpret the wrong action. That is, I think, one of the risks of the technology.

And then maybe one final point to come back to this blockchain innovation, it's got a bad rep at the moment, but ultimately, I truly believe, and this is why we actually started Proof of Impact, that we will transition to digital financial products. Like we're not going to have an investment bank issue, what we call paper, right? As a loan with a loan term, and then it's going to have like an impact report or an ESG report on the side. That's just not the future.

The future will be, I'll set my baseline, I optimize my operations, I see what the outputs are. I then optimize for my financial outcome and impact outcome by doing those outputs better and better. And then I'm going to have a bundle of results. I'm going to have my 10 KPIs that are trending in a certain way. I'm going to have my operating margins go up, costs come down, revenues go up, valuations go up, and that bundle right of that information, that is what I go to the market with.

And I then can sell it to an institutional pension fund and say, 'Hey, do you want to buy 10% of my cash flow or do you want to lend me?' But if I'm going to borrow money, I'm not going to borrow at a high cost because you see I'm doing all these great things. So, the risk of me as a business is decreased the more of these good things I do.

And then I think we can also have, on the buy side, we can have fractional ownership, so anybody in the world can own a piece of any company that they think is aligned with what they want to invest in and see happen in the world.

And that's another thing that we haven't been able to do yet because impact investing is typically only for very select few family offices. Whereas I would think every 20- to 40-year-old wants to put their money into something that they can see is doing good and well. So that would be the final cherry on top that because of all this advancement and all this transparency, we create an entire new digital financial market, that is fully inclusive in terms of what are the factors that we look at in order to price assets and invest in them.

[00:39:16] Ana: Mm-hmm, that's really, really cool. With the blockchain especially, it's so revolutionary, the idea that you would have that degree of transparency from any sort of organization. Do you find, because as you were saying earlier, obviously there's the difference between say a start-up or a company that's newly entered the market and then the larger corporations where you have more difficulty with the data governance and transparency.

Is another challenge that you're facing right now to do with encouraging businesses to see the value in the transparency? There's a lot of smoke and mirrors in business and they're kind of always has been to an extent, especially in some industries more than others, and specifically in industries that have, I guess, high impact, there's a lot of smoke and mirrors, for example, in the pharmaceutical industry or energy.

There's lots of very impactful industries where the culture is based on the opposite of transparency. How do you work against that?

[00:40:10] Fleur: You have got to be realistic about what you can tackle at what stage of your own business. So, we're obviously, a four-year-old startup tackling the pharmaceutical, publicly listed companies and their transparency issues is not on our radar screen for the next 24 months. Having said that, we do actually have one, I would say, healthcare, FMCG company on our client list, because it would make sense for a lot of those larger conglomerates to use Proof for their internal evaluations around what's happening.

So not necessarily the big ESG reports that go to the external investors and get dealt with by HQ, but if you are a GlaxoSmithKline and you've got 300 subsidiaries around the world, how do you really know, at the granular level that they are treating their employees well, that they're using sustainably sourced raw materials?

So, those are the things that you could measure, ethical considerations of their pricing methods and who gets access to the product, you could also measure, right? You could least benchmark, where are they at. And do people of lower income have access to these products and markets where it's most needed?

So you could do a bit of outcome searches on there, but if I have to be brutally honest, we're not at a size and the stage where that is the biggest problem to solve for, we'd rather move with what we call the SME, the Small to Medium Enterprise, private fund managers and market, because A, it's significant in size; B, they don't have anything, whereas the big conglomerates feel that they have already everything sorted out for them. And also, just purely from a data integration and plug-and-play system, if you're talking about these massive conglomerate enterprises, their operational infrastructure is extraordinarily complex. So, it's not even necessarily that they may not want to share some of it, it's like getting data out of it that is, you know, interpretable and meaningful is incredibly hard. So that's just not where we are at. And I'm sure at some stage we'll get there, or other people will solve for that problem, right at that really high complexity level, but I think in order to create a tipping point, it's a momentum, right?

It's a momentum of getting as many companies as possible to start disclosing. So, we've just launched an initiative, which we are basically, going to market within the next month, which is the objective to get 10,000 companies at that baseline that we talked about in the beginning onto our platform. Because if we have 10,000 companies on our platform with 10 KPIs, we are the world's largest private market index for the 10 KPIs that we're tracking. And that will hopefully give a lot of these other companies and fund managers a bit of impetus to say, oh, I can now compare myself to some of my peers, whereas before, it's like, there is no comparison or competition because you're comparing me to Coca-Cola and I'm only like a $10 million business. So, I think that will slowly start to create a bit of a shift in the market momentum. And then we'll go probably from the outside in, right? Then ultimately, we will be able to sufficiently service some of those die-hard conglomerates and corporates, who are able to get away with quite a lot of lack of disclosure. But my guess is that is not something that within the three-to-five-year time horizon is going to be a priority.

[00:43:26] Ana: Absolutely. Well, that's super exciting. I like the way that you explain it as a movement, a wave that businesses sign up to and when they see other people doing it too, it makes a lot of sense, and I think it'll be really valuable for a lot of people listening to the podcast who may look at the impact space and feel that there's a lot of chat and a lot of hope without much clarity on how it's going to get there, and it's really awesome to hear how you're looking at it from the data angle. It's really exciting.

I wanted to take a little step back to find out a little bit more about you and what brought you into this field. I mean, ESG is relatively new, impact is relatively new. Where did you start off and how did you get to where you are today?

[00:44:08] Fleur: So, one takeaway is that none of this was planned, right? I didn't wake up or I wasn't born a tree hugger or do-good or anything like that. I've just been somebody who at each point in time has made decisions to, I suppose, get the maximum experience out of what my capabilities were.

So, I was fortunate to be sporty. I was fortunate to be academic. I was fortunate to be brought up in an international environment. So, I've never been afraid of entering into new industries, new challenges, new countries, new continents. So as soon as I left university and I studied biochemistry at the university. I've shared this now several times, but my, entry essay, to university was, in 1992 was about vaccines for coronaviruses, and the coronavirus at the time was HIV. I was evaluating both the medical appropriateness, like innate immunity versus vaccine-driven immunity, because there was a bunch of studies that had been done around these Kenyan prostitutes who were naturally immune to HIV, whereas everybody else was pretty much dying.

So that would pretty much claim that innate immunity would be a way to go. And also, the -- I'm elaborating little bit here because it's really not that different from what we've experienced with Covid -- but the other problem obviously is, is that these coronaviruses adapt so quickly against these virus walls, or mutate is the better word, that you're just effectively spraying in vain. And now I think we're seeing that a lot of people are super, super sick and it's not COVID, but it's some other bug.

And the second thing was really the economic rationale for spending billions and billions of dollars on -- and this is where we talked a little bit earlier about the pharmaceutical and access -- they're spending billions and billions of dollars on people who may not be western or heterosexual, and therefore, don't really count, in some people's eyes. That was the gist of my essay.

And then I got picked up by the investment banking community. Did that for a couple of years, then went to Africa with the investment bank, which I loved, and then built my first business, which was an equities trading platform, which actually in its design and intent was really about bringing global financial markets to the man on the street and emerging markets.

I just have to admit that over the seven years that I ran and built that business, we couldn't really do that yet. Like we had to sort of focus on bigger clients, more of the small hedge funds, and not so much the man on the street, because we had to build our infrastructure, and in those days, it wasn't like venture capital was flying around.

It was like, 'Oh, just grow your business and don't worry about profits.' It's like you have got to be profitable in year two. But that business is now the largest retail equities platform in Africa -- it's got about two and a half, 3 million users. So, 20 years later it's doing what it's supposed to do, and that gives me a lot of satisfaction that even though we sold in 2007, it's now a super inspiring platform.

But that sell of the business in 2007 was the event which allowed me to go back to school. So, I went back to Oxford and then really learned about this opportunity, really not the risk mitigations, but the opportunity to create these sustainable growth companies. And certain names which were thrown around like social enterprise, which I think is a little bit degenerating, and there was like ESG impact -- impact investing I don't think even existed then. So, it's gone through various names and forms, but in 2008, I just really felt that that was where I should spend my time, my energy, and my skills, because I was really passionate about it. So, I immediately jumped onto mentoring and investing.

One of the entrepreneurs I met at that conference, and he built an accelerator for other grads from Oxford who were doing social enterprises, called Emerge. And then he decided that he wanted to just focus on one vertical, which is really smart, which is EdTech. And that was in 2009. So, we were probably the first in exclusive EdTech investments, and it's now the largest EdTech fund accelerator in Europe and incredibly successful at what they do.

And then Osmosis got started, and then we've been looking at helping various impact investment banks, intermediaries. And then by 2019, I just had a bit of an identity crisis, not about myself, but about this whole impact investing space, thinking it's just all nonsense. Like no one really cares. And we're not really able to mobilize capital because the way that we're allocating money and the way that reporting on what these businesses do just isn't adequate. It's not going to shift markets. So that's when I met the original co-founder of Proof. I was inspired by his approach toward getting data from the ground up rather than always coming top down. And the possibility that maybe this could be digitized, tokenized, and then sold to that new market of more progressive investors.

But that failed first round. There just wasn't that market, at least not in the donor, NGO space for various reasons, which I don't really want to go into now. So, we pivoted semi successfully. Like there was bite -- people were like, okay, this is cool. We want to, as an impact investor, see what we're doing, and we have some money to spend. But again, they were also quite stuck up in their own way. So, it wasn't what they were trying to measure that was really blocking them from going onto digital platform is they were just so used to speaking to a consultant and not creating a digital integration. And that's still a big, big problem in the investment space.

There's no CTO in investment funds, and when there's a COO, they're more on the legal side than they are about optimizing operations. So, we are now at a situation where we're kind of at the beginning of a massive growth curve because we have completely changed the way that we are approaching the ESG and impact measurement.

So rather than go into a client and say, 'Hey, what would you like, what are the 20,000 KPIs that you're looking at, and which 50 would you like to monitor?' We've actually now got enough intelligence ourselves and there's enough market standardization to say, you know what, these are the 10 KPIs, everybody should be tracking -- the baseline.

And then if you're a Regen-Ag at those 10 or 20, and if you're in education at those 10 or 20, and these are the data sources that we want to get the data from. And this is then the proof, like whether it's a Regen-Ag proof or an SFDR proof, you can go to the market with and you should be able to either raise money, renegotiate your loan terms, etc. And all of this will be on one platform. So, it's a very marginal Lego block platform, that over time will be augmented with, you know, as I gave the example of AI interpretations and applications as well as, you know, potential blockchain. But for now, the job to be done is just get as many companies on the platform with as much data points so we can make a little bit more sense out of who is trading where or who is performing where, and then for those who want to dive deeper, we've got that right? So, we've got that product already ready to go. And then the final thing for me is I wanted to have proof myself that this approach would legitimately mobilize more capital toward these assets and that this would also promote the performance of these assets.

So, it's not just, 'oh, we've raised the capital now, these assets, these companies don't work.' It's like a golden circle where the one positively reinforces the other, and which we've accomplished osmosis, that that is repeated in the private markets. That's really my goal for this industry.

And then I think over time I want to apply a similar type of methodology which is not looking at companies and investors, but looking more at the individuals, right? How do individuals make more intelligent decisions to drive their own wellbeing? And you could argue, maybe I should have done in reverse, because that's probably where it all starts, right? You solve for the individual and the rest will figure itself out.

I think I just learned that a little bit too late in life. So, that will be my grand finale, I think.

[00:51:45] Ana: That sounds really cool. Would that also include data? And if so, how would you be using that data to help people?

[00:51:53] Fleur: The good news is that we will need data, that's for sure. But we have a foundation, I don't know how many people know this, but there's one philosophy in the world -- it's called Vedanta. It comes originally from the Himalayas. It's been somewhat articulated in all religions. So, it's not a religion itself, but its core life principles are embedded in Judaism, Islam, but maybe more recognizable in Hinduism, Buddhism, etc. So, most of those Eastern cultures.

But the entire principle of Vedanta is improving yourself by a scientific analysis of yourself, a scientific introspection of yourself. So, as we all progress in the world, we all think that our happiness in the world depends on the world. You know, 'if I have a better home, if I have a better job, oh my God, if I just had a great husband or wife, then I would do this If I had kids, if I would live in an area that was greener,' blah, blah, blah.

So, everyone is always deducting their own state of fulfilment and wellbeing based on all of these external objects. And there's an element of that that obviously will influence how you feel, but there is an equal element that is you and that you have the ability to control and change. And this study, this Vedanta, for 10,000 years, has given the recipe on how you can change yourself to have the maximal interaction in the world to give you happiness.

That's the foundational work and that you can start pretty much from the age of eight or nine. You don't have to wait until you're retired and then read the Bhagavat Gita.

So that foundational work, we need to get into the education systems because it is more important than learning how to read or write -- that will all be done and solved for by all of these incredible applications. But your ability to think, your ability to know what you should be doing, what your purpose is, what you have as your inner nature that you can express and that you can improve on, your ability to become more and more aware of how you can contribute to others, including society, including the environment -- that's where all of impact starts. And the beauty is that you basically, by doing this, by practicing this, the outcome will be that you are a more happy, well-rounded person, which again, means that you can do more for other people and the planet. So that's the ultimate goal, and that's going to take another 20 years probably. So, uh, I'll be around for a while.

[00:54:25] Ana: That's so exciting. I love the way that it also circles back to the Ed-tech that you were talking about earlier, but I definitely agree with you in terms of self-awareness, and reflection being something that is missing from education generally.

Personally, I think it will make a massive impact on a whole load of challenges that we face if more people had a better sense of self-awareness. So that's, that's super awesome.

I'm conscious that we're running out of time, so I want to ask you the last question, which is one I'm asking everyone in the series, which is, 50 years from now, what's the ideal situation when it comes to impact data from a business perspective?

[00:55:04] Fleur: So, the ideal situation is, we don't call it impact data or ESG anymore. It will be part of the intelligence data set that any investor or company dashboard has embedded in it, in order to ensure that you're going to be thriving and surviving. The thriving meaning creating these opportunities and making the most out of them and, surviving because you'll be more resilient to crises, and crises will be stacking up on top of each other as we go through the next few decades.

Whether it's health crisis, environmental crisis, food crisis, the health, physical health foods, any crisis that really we're seeing a glimpse of right now is only going to be largely built up over the next few decades. So, I think that's the main takeaway is that it won't be a separate silo anymore. And likewise for the financial markets, I don't think you'll have a single financial product where this is not embedded. And I hope that those financial products will be in a digital format, because I don't see how else we're going to be able to execute on that.

[00:55:59] Ana: Awesome. Well, thank you so much for joining me today.

[00:56:01] Fleur: No thank you Ana. It was a pleasure.

[00:56:03] Ana: Is there anything that you'd like to share with the audience in terms of where they can find you or any links that you know, places that they can find out more about your work?

[00:56:12] Fleur: Yeah, no, for sure. Like if you are a company and you're like, okay, I've got the bug now, I think I need to get on this journey, then please do send us a note on the proof.io website and become part of the Proof index. I think that's really important because every company matters, and it also will give you some perspective on where you are.

And if you're investor and if you're in Europe particularly and you're like, oh my God, I am definitely behind on my compliance requirements, there's a whole section on our website on the SFDR, which I highly recommend they go to because it will be the easiest, most reliable and effective way to solve for that little kink in the chain that has been thrown your way.

[00:56:47] Ana: Brilliant. Well, you know where to go everyone. Thank you again, Fleur, and I'll speak to you soon.

So that's a wrap, everyone. As we transition toward a green and sustainable economy, we're going to see more intense scrutiny of businesses, with investors and customers alike demanding clear, reliable information that monitors progress and evidences sustainable transformation.

To anyone out there who has been struggling to understand the impetus for tracking impact, I hope that the episode has provided you with some food for thought. And that you come away with a clearer understanding of the opportunities that monitoring and improving impact can offer businesses on the road to net zero and beyond.

Thank you all for listening. If you enjoyed this episode, please make sure to like, and subscribe wherever you get your podcasts. Tech Beyond the Hype is a TechTarget original podcast.