If we really want to make climate data meaningful and we want to make it relevant for business intelligence, we have to meet the customer where they're at
Good morning, good afternoon, or good evening wherever you are in the world. This is the Climate 21 podcast, the number one podcast, showcasing best practices in climate emissions reductions, and I'm your host global vice president for SAP, Tom Raftery. Climate 21 is the name of an initiative by SAP to allow our customers calculate, report, and reduce their greenhouse gas emissions.
In this Climate 21 podcast, I will showcase best practices and thought leadership by SAP, by our customers, by our partners and, by our competitors, if they're game, in climate emissions reductions. Don't forget to subscribe to this podcast in your podcast app of choice, to be sure you don't miss any episodes. Hi everyone. Welcome to the climate 21 podcast. My name is Tom Raftery with SAP and with me on the show today, I have my special guest, Josh. Josh, welcome to the podcast.
Would you like to introduce yourself?
Yes. Thank you Tom is great to be here. My name is Josh Gilbert. I'm the co-founder and the CEO at Sust Global, which is the climate analytics company producing, not just by analytics and data, but also the APIs and integrations to make it useful.
Why, w what kind of analytics and why is that important?
Yes. Yes. So maybe I'll start with why it's important and then we can get into the what, um, but there's just been this, incredible engagement around climate, uh, in the corporate world, in the financial world. which is incredibly exciting. but also, you know, it's kind of, incredibly scary as well. You know, it's a real, over the last years, basically all of the existing climate models have been broken by the things that we're seeing.
and I think it was something that $145 billion in economic losses, just in the US last year from climate related events. And it's like 300 plus billion globally every year. So the world is changing very rapidly and we quite simply need better data on these changes. Not just better data, but also more actionable data. So that kind of comes into the what a little bit more.
There is a rich heritage and industry, not so much industry, maybe a rich heritage and a rich output from the academic community, providing climate data. These, these are called GCMS global circulation models where they can look across the globe, but multi-decade or horizons, uh, across different scenarios. And tell us these, you know, the, the things are getting worse. Unfortunately, they don't go very granular.
So. You will get things like wildfires are going to get worse in California, flooding is going to get worse in Florida and in parts of Europe, turning that data into something that's actionable and useful, uh, and is business intelligence is a non-trivial thing. So our aim at Sust Global is to transform the complexity of climate science into business intelligence.
So whether that is probabilistic risk of wildfire in the future, at a supply chain facility, or whether it's the risk of flooding a manufacturing site or a sea level rise next to a port or at a port, or even if it's the GHG emissions output from specific assets, Sust Global aims to provide satellite validated, granular data on all of these different types of climate risks and events, and provide that by flexible integrations to customers.
So whether that is a corporate who wants to understand their supply chain risks, whether it is an asset manager or an investor, wanting to understand the hidden risks that don't show up in a factor analysis in the day to day, or whether it's a company like SAP or another financial data provider or a data provider, or an integrator that recognizes that climate is now an endogenous rather than exogenous total business practices come in very early that with some complicated words, I don't
fully understand endogenous and exogenous outside, outside, in and inside out. Um, but the idea of being. We're entering into the climate economy at the top level, climate will touch everything. It will actually just become an integral part of all of our business processes. So we need to have good data and we need to have ways of integrating that into our workflows. So that's a slightly more unpacked version of what Sust Global does.
Good. Good. Thank you. Thank you. And where does the data that you're using come from?
Yes. So it comes from a number of places. Firstly, we do take the data from these global circulation models, which I described, which come from various academic institutions across the globe. And we integrate and interpolate a variety of geospatial data sources and satellite data sources.
So whether that's ground based sensors or whether that's satellite imagery from NASA or from the European space agency or from other commercial satellite data providers, we then effectively have developed, uh, deep learning techniques or AI machine learning techniques to interpolate all these different datasets and basically use these high refresh highly granular, highly accurate satellite and sensor data sets, and integrate them and bias correct these global climate models,
bringing them down to the asset level, making sure they are very granular and making sure that they're really trustable. So an example, right, is if you look at a site or property in Redding, California, where they have been awful wildfires, the current global circulation models will show Redding, California as a low risk site. Or an asset in Redding, falls into low risk because their models don't update very often.
They update every two or three years as tends to happen with academic and research and the data they have a year and then maybe another year. And then they have a third year where eventually they get to release the models by bringing in the satellite derived data. We can integrate data, every two weeks into the models, giving it higher refresh, making it more relevant for a business that maybe is less interested in. What's going to happen in the year 2100.
But he's more interested in what's going to happen over the next 5, 10, 15 years. Where should they be building their manufacturing, supply chains? Where should they be making changes? Where should they be building in, secondary points of failure in their supply chains, all of these different types of analysis, a) need to have better data and b) need to have ways of integrating it into company's actual workflows. Cause nobody wants another dashboard.
That's just going to slow down their workflows.
Fair enough. Fair enough. And are there particular industries that your are more, or less suitable for? I mean, I can imagine, for example, insurance industries would be salivating at the prospect of getting their hands on this kind of data. whereas, I mean, you mentioned supply chain, might they be more interested than, than insurance, less interested in insurance or, where, where does that whole spectrum workout?
Yeah. I mean, it's a, it's a fascinating question. And there isn't a straightforward answer to it in some ways I think,
The answer is it depends.
you know, uh, The answer is is that it depends. but the answer is also inherently placed in. The evolution of the needs for climate data. And so one of the things that's accelerated these changes is there's, there's a suite of regulatory requirements coming in, whether it's in the U S whether it's in the UK or in Europe or in Japan or Canada, governments have basically legislated to say, as of 2023 or 2024, you know, there, there are various dates of the regulation coming in.
Their mandating the disclosure of climate related risks for any large corporates. So, there is going to be this urgent need to, to find ways of disclosing this data. But interestingly regulation isn't the same as, risk, you know, and I think we are going to see this evolution towards more and more business intelligence, more and more. Integration of this data into risk functions, but we're at the start of this change in the, in the global economy.
So for example, some of our early customers have been large financial data providers, you know, who recognize these needs across multiple industries. And so we can get faster lean customer acquisition across the range of range of use cases. Um, places like real estate, where a real estate asset and you get a mortgage out. It's going to be 25, 30 years, and that's a real sweet spot in terms of understanding.
I need to know what's going to happen and how the climate is going to change over the time of holding this asset. And there are tangible consequences. Supply chains are another example where corporates, I think in 2011, um, flooding decimated like hardware supply chains, and it basically ground to a halt. We've seen kind of importance of supply chains in how COVID has been impacting on them. So climate risk, is another impacting, factor in a lot of these areas.
But we're starting with these early adopters is, is really the classic crossing, the chasm methodology. You know, we have the bell curve and you have the early adopters who, some of them are in insurance, some of these large financial data providers, they just want to get the data right now and play around with it and explore how it could be useful. And then you have the kind of early majority in the late majority, whether some of them are banks. For example, with credit and lending, they maybe
Of course.
integrating. Some of them are asset managers who maybe want to go beyond ESG because then that's social and governance. I know climate 21 is a climate pod so I'm guessing know what ESG stands for, but, but maybe they don't.
but in a lot of these industries, there is a lot of excitement around becoming more climate aware and a lot of net zero promises, but we haven't yet seen the full conversion of these promises into real action and real kind of digging down into the data to understand where and why and how these climate events actually manifest.
And you, you alluded to regulations. I saw, I think week before the US securities commission came out with new proposals around reporting for larger organizations, reporting climate risks, disclosing them by 2023. So next year out to scope two. And then by 2024 scope three, Europe is on a similar, but slightly later timeline of things. So this must be presenting a big burning platform for a lot of companies.
Yeah. it really is. And the SEC, documents, are, I want to say, I'm going to say fascinating. I'm not sure if we can ever say, regulatory disclosures are fascinating, maybe, maybe that's going to be a step too far, but we're very nerdy at Sust Global, but, um, one of, one of the really interesting things within the SEC documents is they talk about the need for auditing.
Yeah.
And that is a big step forward, you know, because to date, corporates give a good talk on climate and net zero transition pathways. Um, there's a lot of feet dragging in this often green washing, right? But the fact that this will now need to be audited is a real, huge step forward for the industry at large, in terms of making sure that we're held to account. But also for us at Sust Global, you know, where you need to then start to have more validated, more trustable data.
And one of the things that the satellite derived, uh, data sources provide you with is an objective source of truth.
You know, in the same way, in other geopolitical use cases, you know, if, uh, North Korea promises they're stopping launching missiles and then satellites detect the next day that there's one going off or, Iran's nuclear program and you see all the facilities are still switched on, like satellite data can really be this powerful objective source of truth in a lot of the time of a post truth world, you know, where we can spin things any which way, and whether it's social media or, you know,
just over promising and under-delivering on some of these climate goals. I'm really, really excited about these SEC, requirements. Presumably they get through in that current form because of that tiny little clause that just says, Hey, you guys, this needs to be audited.
Yeah, no, I saw that as well. Really, really interesting. But you, you mentioned satellite and the, the advances we're seeing there and we're seeing more advances than that. We're seeing now a satellite is capable of finding methane emissions and things like that. How have satellite technology advances led to improvements in climate analytics?
They have and they haven't in the way that the large European space agency missions and the NASA missions, the kind of the OGs, of the satellite data world are in many ways, still the channel, you know, the data quality, the way that the data can be processed, the consistency, the clarity. Many of you, these data sources have existed for, a very long time. That's also really important, Right.
Because you need to have a rich, historic set of data, to be able to, you know, use the long, the longer that that history goes back, the more valuable it is when you're integrating as a credible data source, um, And also we were originally funded by the European space agency, at Sust Global. We're supported by them. There's no such thing as a free lunch. You know, we had to fill in many, many miles of paperwork, and documentation to, to get through that process.
But you know, those types of data sources are incredibly useful um, if you know how to use them and if you know how to integrate them and turn them into, insights that an everyday user or an analyst in many of these end use cases, would understand. However, it is incredibly exciting. This explosion, this Cambrian explosion.
I think they call it in, um, in satellite, kind of design and launch where now we have new satellites to monitor things like methane CO2 is another one that that's going to be launching up, you know, thermal signatures, all of these new data sources and they have, additional granularity, bringing out all of these different ways to understand the world hyperspectral data is another one. A startup called pixel is launching some hyperspace hyperspectral satellites.
There's still gonna be a lag because you know, there's huge backlog of launches and they take a while to go up and then start sending down data but really, I think it's just an incredibly exciting time, not just in terms of the new data sources that are going to be coming online. But also the cost curve of
Um,
these data sources actually cost to integrate. You know, the more data there is, the more it becomes commoditized. The more the price point falls, the more that, data analytics firms and geospatial analytics firms can integrate this data, uh, where the unit economics stack up. And it becomes a viable proposition. Because ultimately however cool the technology. Isn't that me and my co-founder Gopal have written papers about this in the past and articles online.
And that they're on medium if anybody's interested in digging them out, but we, we talk about this kind of technology push versus market pull, and a lot of very smart NASA scientists have launched a lot of cool satellites, but we really need to make sure that the market wants these things that there is the traction.
So I think unit costs going down as well as this kind of breadth of new data sources means it's an incredibly, incredibly exciting time to be a geospatial analytics company or a company that's just using this type of data.
But ultimately the devil's in the details, the integrations matter, abstracting away the complexity of these beautiful images, which may be, would look nice on a wall but don't really effectively integrate into the workflows of the end users and ultimately that's what really matters.
And how do you go about doing that? I mean, as you say, beautiful pictures, look nice on a wall. How do you take that turn it into actual data that can be presented in the likes a dashboard.
Yeah. it's a non-trivial process. My co-founder was the head of analytics and insights at planet labs. One of these, um, the largest commercial satellite operator. Over 300 satellites kinda monitoring earth at all of the different points. Turning all of that data into insights is a non-trivial thing. There are several stages in kind of the processing chain, uh, that need to happen. I think also understanding what satellite data can do and what it can't do.
You know, satellite data is incredibly powerful, but it's not the only source of, useful data. A lot of the useful data is actually siloed in the existing ERP kind of setups of corporates where, you know, there are different datasets that can be complimented massively by satellite data. Um, but turning satellite data into whether it's an, a change detection algorithm.
a great article just came out, talking about, um, change detection, algorithms, and kind of how we need to go more focused on customer problems and satellite data. And it's @mouthofMorrison is the Twitter handle for Joe Morrison, who who's done some great writing in that area. But, um, turning this data, not just into usable data types, you know, like a time series or a CSV, but also integrating it with other different data sources to really bring it alive.
Because if you think about the risk of, I don't know, risk of flooding to a supply chain facility, right? Like you can use the global climate models, you can then bias, correct them with satellite drive, deep learning approaches that at Sust, you know, we've, we've spent a long time building. Even if you get to that, it is like what's this facility actually producing, how integral is this within the supply chain? Is this a single point of failure?
Is it, multiple points and to really understand that you've got to get a lot of the old, boring data, a lot of the unsexy data that's been there for ages, and you need to integrate that with all of these fancy cutting edge datasets. So I think it's the sensible application integration and transformation of this data into something that makes sense again, from the perspective of the end user, sometimes it's a lot of cool tech.
Sometimes it's finding a lot of these boring data sets and getting them to speak to each other.
Okay and who is your customer? And I don't mean, you know, which industry, I mean, within an organization you're not selling to the supply chain manager, I assume. Is that the chief risk officer? Is it the chief sustainability officer? Is it the CEO is it, again, it depends.
Mostly. Yes, but it depends most of, most of the personas that you just described. And I started that the CFO or the chief risk officer who needs to understand these things. Um, one of the really exciting things that we've been focused on though, and we talk about the last mile. Uh, and we talk about the penultimate mile, you know, in the last mile, in this case would be, you know, the risk officer or the supply chain person looking, looking at this data.
We as much as possible try and exist in the penultimate mile, you know, in the way that we think that there are incredibly smart people who can deliver that last mile insights that can marry this, this kind of satellite derived climate data with these kinds of, um, existing data sources and create something really powerful and specific to the end customer needs.
So what that means is often the CRO or the analyst, or, um, the end user isn't necessarily the buyer or the initial entry point for our data. Often it's the chief data officer or even the product manager, where they are responsible for this new product or this new insight. And they work with the internal data teams to create new insights off the top of our data. Because again, we can pipe the data straight through.
We can give a, a risk exposure score, uh, for any asset, anywhere on earth, in a very granular way to understand what the risk is. But often, you know, an example is one of our customers. Uh, one of our customer sets are asset managers in the residential mortgage backed securities space that RMBS. So that's looking at pools of mortgages and understanding the differences within them.
So these people understand the world of I dunno prepayment risk and probability of default and all of these different metrics. Our data, we work with a product manager at one of these large financial data providers, uh, and that, that data science team to integrate climate data into their models to then be served downstream to the asset managers and the end users.
So it's a really exciting and fascinating new area to apply this data where we understand that we are only a, we're an important cog, but a small cog in a big machine in one of these large corporates. So by integrating that with the data science teams, with the product managers, with the people who really speak data, they can then provide valuable insights to the CRO, or the financial analyst or any of these other personas.
Okay. And I mean, you, you're talking a lot about integrations versus dashboards What what's, what's the difference you see between providing integrations versus just dashboards?
I think there's two core, two core reasons why we, we believe integrations are more important than dashboards. I think number one, Dashboards can only provide a limited set of outputs. So there's a lack of customization. You know, there is a value at risk score. I don't know which is, which is the kind of value.
But then as I said, right, if you have a value of risk score that comes from the outside, how can you meaningfully integrate a lot of the ultimate data that may be the silo data that exists in a company, into understanding that score, or how can you have a dashboard that caters to not just real estate investors and supply chain managers in corporates, or the chief risk officers in corporates? There is this kind of multiplicity of end user cases, right?
So one single dashboard will struggle to have that breadth of applicability. The second thing is just friction. You know, there are so many dashboards that exist today, and most people don't want to use the existing dashboards that they have, because there's just so many of them, the last thing that anybody wants is another dashboard added to that list.
You know, what people really want is they need, they want the data, but they want to integrate it into the existing dashboards that they already use. Or even into the existing operational workflows that they have. So it's not that I'm like anti dashboards. I think dashboards can be great. I just think there's too many of them.
You know, I think the integrations enable the streamlining and if we really want to make climate data meaningful and we want to make it relevant for business intelligence, we have to meet the customer where they're at. You know, we've got to make sure that they can use it in their workplace. When we started Sust, I had like three, 400 conversations with different potential end users, whether they were asset managers or working in banks or working in supply chains, working in corporates.
One of the biggest things I heard was I'm just like, Yeah, the dates could be great, but if it doesn't fit into our existing workflow, if it increases the friction in the things we do, we ain't going to use it. And that was just this light bulb moment where I was like, nothing else really matters. Integrating this data into workflow.
It's just the only way that we're going to go from hollow climate promises, where we talk about net zero goals by 20 30, 51 or whatever the deadline is at the moment, into like real meaningful action, it's integrations.
Yeah, it makes sense. And you, you mentioned having hundreds of conversations. And you mentioned as well, that, you know, it's everyone from the CEO to the CFO, to the chief risk officer, to the supply chain manager, across lots of different industries. How are you getting the word to people, to potential customers that this is who you are, and this is what you do. How are you making that market? Because it's not like you're making Microsoft word where everyone knows of it or has a need for it.
This is a very specialized, so making that market and it is market making, making that market must be quite challenging.
Yeah. Yeah, it absolutely is. And it's, um, it's critical that it's such an important thing for us to work out. You know, there's a real drive when. When we're facing some of the issues we're facing, in terms of climate. and certainly that helps us in the conversations because it's very rare that you'll come across somebody that doesn't believe that this is important.
However it is market-making, and it is difficult to, especially when you want to be the integrations, because inherently an integration is, a connection between a and b.
Yeah.
That is what an integration is. So you've got to hope that there's going to be a lot of A's and a lot of B's, if you're just selling yourself as the integration. So that market making is absolutely critical. We've been very deliberate in looking at that, crossing the chasm methodology and thinking about where are these early adopters and these innovators who have to have this data and they have to have it at scale. And we went after them very early.
And through a mixture of skill and luck and right place and right time and right products, we've been able to really capture some powerful, um, kind of lighthouse customers in the financial data space in terms of, we're looking to announce three or four of these big partnerships over the next quarter or so, where, you know, it really provides that level of credibility. I think that's a big part of it. You know, no one gets fired for hiring SAP.
I believe that's a, uh, a, a refinement of the, of the existing existing one. Um, but you know, that that's a massive, massive task. And one of the big problems, if you go straight to the chief risk officer, if you go straight to the end-user is third party supplier risk, people don't necessarily want to rely on a startup to provide them with critical insights on critical parts of their business, you know, in the risk function, you don't want to mess it.
up. So we've been very deliberate in seeking the right partnerships, the right integrations, the right kind of, um, early relationships, so we can even go to market with some of, some of our customers are also partners, you know, because we want to make sure that people see that we working with the biggest and best in class. And then that does have that level of credibility that opens up many other doors. So it's a non-trivial thing.
And certainly momentum, you know, when it is there is a massive driver. But we tried to avoid a lot of the, the hype. We've tried to focus on building in private, really making sure that these integrations are enterprise ready, that the API is, do really work at massive scale. And now we're getting into these conversations with customers where they say, can you process four or 5 million assets? We say, Yeah, sure. You know, Hey, hit us with your best shot. So a lot of quiet building.
And then the truth will out in terms of finding those, right data partnerships.
Nice. Nice. And how do we avoid analysis paralysis with climate change? Both personally and in business.
Yeah. Yeah. It's a, well, there are two very different approaches, right. And maybe there are similarities but. On the personal beside the biggest thing I've learned, not just from, working in climate, but just working in startups full stop is like managing our sphere of influence. As in like, we can always increase the things that we can control, but also being hyper aware that there are some things that are beyond our control.
Um, I think analysis paralysis comes when we have that kind of awful. When you just wait, we spent none of that time looking at how bad the problem is. And how far away we are from finding the solution. In my personal life, I'd just try and focus on all the things that are in my control. It's cutting down on meat consumption, it's, you know, riding your bike or getting a train. and I know that these aren't addressing, they're not going to be enough on their own, um,
Yeah.
But they're really important to set that baseline and that momentum of, of being active in how, and in recognizing that we do have a voice and we do have things we can do. I just think on that point of having a voice, I'm lucky in some ways, because I work in climate, but having that voice, finding who our local in the UK local MP in, in Europe, it would be I dunno, that the equivalent of MPs and in the U S it would be um, your senator or whatever.
And the pen is mightier than the sword writing to them, letting them know kind of lobbying. because ultimately these people want to stay in power and they do that by listening to what people want. And if we tell them what they want and enough of us tell them, then they have to move climate up the list of priorities.
Um, I think in the business world, the analysis paralysis is absolutely the thing that that Sust are trying to solve by providing this climate analytics and integrations, turning all of this complexity into business intelligence, by making sure that it's methodologically, understandable that it's scientifically validated, and that it's kind of asset level and granular enough that we can, we can really use the data.
So I guess, I guess, they are different kind of on the personal side of the business
Um,
working out what's in our control, and, and trying to grow that sphere of influence.
The only other thing I'd add to that on the personal level is I. Use an RSS reader to get information, to get stories. But I focused on getting one, some sites that publish. Positive stories. And I try and make sure that I see at least as many positive stories as negative ones, cause there's a whole load of negative ones out there. you only consume that, then you, you know, you risk falling into despair and, and
Yeah.
throwing your hands up in the air. I, I
Yeah,
and look for and promote any positive stories I see out there just to try and bring a bit of optimism back to the fore.
Absolutely. There's a, uh, a Stanford study that I saw recently where, it was about stress specifically. Um, and I know there's a slight tangent, but I think it's a fascinating study. So they basically did this study on stress and how it affects people. It affects people's performance positively or negatively
Right.
and effectively what they found is if you had read a lot of research on stress, having a negative effect. You know, stress kind of choking you up and making you less optimal and performing, it had a negative impact. And if you believed in, if you, if you said, look, I rise to the, moment when I'm in stress mode, that's really what gets me into gear you then performed. So like what we consume and how we think about the world genuinely affects the world.
I think that point is so important in climate as well. Right? Where, and it's kind of why I think starting with these small things is really important because if we believe we can change the world, most of the time we can.
Yeah.
Whereas if you get overawed by all of the awful stuff that's happening and like I'm very impressed by this 50 50 ratio of good news and bad news. I think, think if you zoom out, there's a lot more like our brains are wired for bad news. Right. We love that stuff Yeah. Because before 24 hour news, we wanted to make sure we wouldn't get eaten by the wooly mammoth or, I mean vegetarians, but like, you know, there were so many, there were so many things that could kill us be.
That our brains are wired for that. But now in the 24 hour news cycle that dopamine hit. Like, we we freak out, it's it's like a sugar rush. Every time we see that bad news and we've got to fight against it because it does create this despair, this analysis paralysis, this kind of helplessness, and like we need to win the battle for our, our minds and our, and our kind of mental space just as much as you need to win the battle for, for climate, right? The kind of two go hand in hand.
Yeah, no. Agreed. Totally. Josh we're coming towards the end of the podcast now. Is there any question that I have not asked that you wish I had, or any aspect of this that we've not touched on, that you think it's important for people to think about?
The only thing that I would add is just on the personal side of climate, we're filming this episode. On Monday the 19th. Uh sorry Tuesday the 19th And Friday is Earth Day and we're spending some time off as a team to go out and get into nature on Friday and kind of see, and touch and feel and hug some trees and, and, get into nature. I just want to make sure that people do more of that. And I think that's, it's not something that you've asked.
It's maybe an ask of the audience of this podcast and maybe for you as well Tom like, I think that turning the climate crisis from an abstract thing to a very real thing is very important, so getting out, connecting with nature, can be a big part of avoiding that analysis paralysis and just helping refine and focus, like why we're doing what we're doing.
Lovely. Lovely. very nice. Josh has been really interesting. Thanks a million for coming on the podcast. If people want to know more about yourself, Josh Gilbert, or about Sust global or any of the things we discussed on the podcast today, where would you have me direct them?
Sustglobal.com is the website for the company. @sustglobal is on Twitter and all the other ones. I'm @JoshGilbertUK on Twitter. Do a follow, do a, like, do a comment would love to hear from people. Thanks so much for having me, Tom. It's been really great.
Josh that's been great. Thanks a million. Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about Climate 21, feel free to drop me an email to Tom dot Raftery @ sap.com or connect with me on LinkedIn or Twitter. If you liked the show, please don't forget to subscribe to it in your podcast application of choice to get new episodes as soon as they're published. Also, please don't forget to rate and review the podcast.
It really does help new people to find the show. Thanks catch you all next time.