Saif Hameed [00:00:00]:
PCfs are here to stay, but also are going to grow radically. We're super bullish on pcfs. I think that in general, this sort of metadata accompanying product transactions between companies is just going to gather steam and scale. And so I think wherever you are on this journey, it is helpful to start thinking about what value this could drive in your business, because you're probably going to get asked for it anyway by someone or the other. So you may as well start prepping for it.
Isobel Wild [00:00:34]:
I'm Isobel Wild. Welcome to the State of Sustainability podcast, a show for professionals transforming corporate sustainability strategies, brought to you by Altruistiqs. Hey everybody. Today we're going to talk about product carbon footprints. We're going to dig into what they are, when they're useful, how to build one, and what the outputs are. So a product carbon footprint is the total amount of CO2 associated with a product throughout its lifecycle. They provide a really good granular view of environmental impact and enable a kind of targeted action and transparent communication. Before we get into the weeds of it, though, Saif, how are you?
Saif Hameed [00:01:19]:
I'm good, I'm good. I'm really evented out this week, our customer advisory board, the day before the flagship event. So it's been a busy week. And then I had climate week not so long ago, I had a big supplier conference with one of our customers, not, you know, in the same week. So it's been a busy. It's been a busy four weeks on events.
Isobel Wild [00:01:39]:
You're a busy man, and maybe then what have you been seeing or what have you been hearing in terms of product carbon footprints in all these events in the discussions have therefore been any big trends that have emerged?
Saif Hameed [00:01:51]:
Yeah, I think I'm seeing three things come up. There's always three things. This is becoming a cliche, but there's always three things. The first is I'm seeing pcfs really pick up scale on all fronts, but I'm also seeing PCF generation pick up much faster than PCF exchange, kind of. So I was at the packed scope three summit in new York, and they shared an interesting stat, which was that around four and a half thousand packed conformant pcfs have been exchanged using the Pact API. That's a huge number, by the way, like four and a half thousand doesn't sound like a lot, but it's a huge number in context. If you just think of the growth rate or the acceleration from really the low hundreds, I would probably have guessed twelve months earlier to four and a half thousand. That's huge.
Isobel Wild [00:02:39]:
Pact is quick explainer on Pact.
Saif Hameed [00:02:42]:
So pact is the partnership for carbon transparency. I hope I get that right. And Pact is basically effectively a nonprofit effort set up by the WBCSD, the World Business Council for Sustainable Development, which is one of the group that brought you the greenhouse gas protocol. And they have, with Pact, worked on defining the data standard for how product carbon footprints should be generated. That's one thing. And how product carbon footprints should be shared across organizational boundaries. That's the other. So if you think of these things as Lego blocks, where, let's say the soft drink that I'm making is a stack of Lego blocks consisting of the can, the water, the mix, or whatever else goes into the soft drink.
Saif Hameed [00:03:26]:
Like all those are individual Lego blocks. I need to acquire those Lego blocks from my suppliers and I need to slot them together. So Pac defines how you make a Lego block, and it defines how the Lego blocks fit together in a stack. But to come back to my story, Izzy, second point. So I think that anecdotally, we've generated 400,000 packed conformant product carbon footprints. So using the Altruistiq software, 400,000 or thereabouts, pcfs have been generated. And if you think about only four and a half thousand being shared, that means that you have like 100 x delta in the rate at which these are an ATX delta and the rate at which these are being generated versus the rate at which they're being shared. And that would be if we were the only ones generating them, which is not going to be the case, unfortunately.
Saif Hameed [00:04:13]:
So I think there's just something around how this is picking up steam, but also actually, these are not really getting out into the public space. And I don't think there is any real expectation from me at least, that they will. So that's also kind of interesting. I think the other interesting aspect is that there is a little bit of a divergence between EU standards for this EU, PEFDEv and pcfs, as per pact, but also as per how companies want to use them. One of the main differences at least, is that if you look at the EU standards on this, there are certain emissions factor databases that are prescribed as allowable for your PEF conformant pcfs, let's say. And that limits how granular or how accurate you can get these to be. Actually, you might want to have a much more flexible range of databases. You might want to be able to put these together with a lot of custom databases that you might be using.
Saif Hameed [00:05:08]:
And so in the way that companies want to use them, there's an incentive to actually kind of break the mold that the UPAF standards sort of expect and go with a wider range of databases. So I think there's also maybe a bit of a divergence around having two standards, one for how companies use these internally and another for how companies might use them to share or to be regulated.
Isobel Wild [00:05:30]:
On the I think standardization is definitely a point I want to come back to. But to your second point, around the 100 x difference at a minimum of PCs being generated versus PCs being shared, why, that seems crazy. What's the reasoning behind that?
Saif Hameed [00:05:50]:
So I think if you take the world that hey, we're all in this together, we should do the right thing, Kumbaya, etcetera. Then of course you'd say why is everyone not sharing these? There should be a public ledger that has everyone's PCs for every product and I should easily be able to just use those and see those and compare and contrast. That is not the world we live in and it will not be anytime soon. If you think about how these are valuable in practice, I actually think that there are more or less two use cases where sharing a PCF is in the interest of the sharer and one of these is b two c, and one is b two b. I think that if you're a b two c company and you are a challenger brand, then it is in your interest to have a product carbon footprint that is visible. And I think you want this to be a cross category or a category leading kind of positioning. What I mean by that is let's say you're an oatly or you're a flora, for example, and you're competing with a whole different category. You're competing with milk and you're the challenger.
Saif Hameed [00:06:54]:
You're competing with butter and you're the challenger, then it is in your interest to have some sort of a comparative claim and say my product carbon footprint for this product is inherently better than the incumbent and so you should pick me off the shelf. And I think that only really works if you're a challenger brand. If you're an incumbent brand, the reverse is true. There's almost no upside as far as I can see it from sharing this, unless you're doing it at a sub brand level where you are the challenger. But then the whole, then you go back to the challenger positioning. So that's one use case. I think the other use case that I see on the b two B side is if you have a new innovation that you want to pitch to a customer, then having a pcf associated with it as a way to demonstrate its environmental credentials, I think is a really good way to go. It is in the confines of a b two B relationship, so it's not going out in the open.
Saif Hameed [00:07:46]:
And it just means that you're providing a rich set of metadata, of environmental metadata to go with this innovation that you're selling, which might help it command a higher price, a bigger margin.
Isobel Wild [00:07:57]:
Okay. And I actually think we jumped a few steps. I want to just take us back quickly to like why? Okay, so if people are generating all these PCs, why are they doing it? Why is it really important? When are the cases that you should be using it, and when are the cases where you shouldn't? So I guess you've just touched on some of the shouldn't cases and the sharing use cases. But yeah, I think there are a.
Saif Hameed [00:08:19]:
Couple of reasons why you might choose to generate pcfs. One is preparedness for regulation. And so most companies anticipate, expect that they will be required to share this data more publicly, which means that it's good to have it, because it takes time to work out all the kinks. So, for example, our customers generating pcfs with us often find that there are accuracy challenges in the pcfs because of the raw data that they're using, that you are often relying on data sets that have not really been used for this purpose and that may not be completely right or complete, for example. So it surfaces a lot of challenges in the underlying data, which means that it might take a year or two of teething. Another reason why you do this is to help with internal communication and focus. It is easier for a company to think about the product that it makes and what it takes to drive down the environmental impact of that product and communicate that holistically across the business, rather than to say, hey, we're trying to drive down the emissions of our energy transmission. If you're a beverage business, let's say it just doesn't make sense.
Saif Hameed [00:09:27]:
The third thing is that I think it really helps focus and provide clarity on what levers you need to turn. Because if you start looking at the constituent ingredients of a pcF, maybe it's the food, the packaging, the agricultural staff, the logistics, whatever it might be, you can really see it in a context that helps you understand where you might be able to drive change through material swaps, for example, and you know who to drive the conversation with from your supplier base as well. And that ability to have clarity of focus, I think, is something that's turning out to be super helpful, particularly for R and D teams and the new breed of team, which is the sustainable supply chain team.
Isobel Wild [00:10:08]:
Oh, can you give us some more details on the new breed sustainable supply chain team, which is a bit of a mouthful.
Saif Hameed [00:10:14]:
I actually made the mistake earlier of asking someone of speculating that someone was in procurement and they clarified and said, no, I was in supply chain. And I think that's a really important distinction. I'm seeing more and more sustainability teams set up within the procurement space as a team focused on facilitating supply chain collaboration. And this team is typically sustainability specialists. So the full time role is sustainability oriented, but they are sitting within the procurement function and they are there to enable a different type of dialogue with suppliers. And I think that's a really interesting trend. And innovation, I'm seeing it more and more in different shades. Diadrio has one, Kraft Heinz has one.
Saif Hameed [00:11:00]:
Im pretty sure Mars has one or similar. I think a lot of the large food and beverage companies have them and I see it taking off in other sectors as well, like personal care and so on.
Isobel Wild [00:11:12]:
Thats an interesting juicy insight into the workings of the big companies on what you were saying previously around the issue around accuracy. I think we heard about that quite a bit. In the event around state of sustainability, around having a lot of demand to share your PCF, but not having your data ready, or being in a place where you feel confident with your data to share it. How do you navigate that tension?
Saif Hameed [00:11:38]:
I think that there's a couple of hats that one can wear when answering this question. One is obviously the environmental hats. There's two hats in this case. There's the environmentalist hatred and there's the business hat. And the environmentalist hat is a bit like that meme of Simba and Mufasa, which says that's the bad hat. You must never wear that, basically. So I always avoid wearing the environmentalist hat. If I wear the business hat, I would say you should not share something that could get you in trouble.
Saif Hameed [00:12:07]:
To be honest, I think there's actually almost never any upside. I think that there are some exceptions to that general rule, and I think the exception is sometimes in the interest of building an amazing, enduring sustainability brand, it is worth the risk of putting numbers out there. That may not be right. And I think that my favorite data point for this is actually oatly, which I know I talk about a fair bit, but what I was reflecting on actually yesterday at our conference is oatly got the number on the pack wrong. I think there's probably different ways to look at this, but the actual number I don't remember this Izzy. But two years ago, I think it was where I read in the BBC that Oatly was in the soup because they had taken the on pack emissions number out of context across different packs. And then I think there was also this lawsuit from their shareholders for several million pounds for false claims. So they've gotten in the soup on the claim that they put out there.
Saif Hameed [00:13:11]:
So it was a risk that failed, basically. Right? Like they got burned at the same time. This might be a personal thing, but I don't think any of their customers actually think they're any less sustainable as a business or brand because the number was wrong. I think they get a lot of credit and leeway from their consumers for having been bold. And I think that's a tribute to the brand building that they've done, where overall, holistically, they have been so bold and so mission oriented in creating a great sustainability brand. Frankly, one of the best sustainability oriented brands of our time that I think everyone's like, yeah, they went for it. They were fearless, to sort of paraphrase. They were fearless and they took a risk and it didn't pay off.
Saif Hameed [00:13:54]:
And that's fine. And I think that's the exception rather than the rule. As a rule, I would not put anything out there that could cause massive brand hazard.
Isobel Wild [00:14:03]:
I think also to that point, I think Sean head of sustainability at Oatly was saying that they were, or if not, were, one of the first companies to put on PAC numbers. So they almost have that first mover respect, but also maybe a bit of leeway in order to make those mistakes. Because if they were putting on their pack labels in 2018, theyre the ogs, theyre the product carbon labeling dinosaurs. So I think that kind of first mover status gives them a bit of movement in the space.
Saif Hameed [00:14:36]:
I kind of agree and kind of disagree, Izzy, in that I think that it is more the fact the first mover status is about brand consistency. They did that to be consistent with their brand and to build their brand. But I think that if you didn't have brand consistency, then being a first mover wouldn't save you on this. Actually, I think, for example, if you look at h and m, right, h and m in terms of the H and M also got in trouble a couple of years ago over their numbers on their garments, which were based on the Higg index. I think. And I'm not sure if they were literally the first mover, but they've been pretty early. I think H and M deserves a lot of credit for a lot of the bold moves that they've taken on the sustainability front and I frankly don't think they get it. They get as much credit as they should have and that is about this brand.
Saif Hameed [00:15:22]:
They have just not been as successful in turning the stuff that they do into an enduring resident sustainability brand that might just be a function of scale. And as a result, I think they get less space to get things wrong.
Isobel Wild [00:15:37]:
Do you think that also comes down to the fact though that they aren't as like mission driven brand isn't in their DNA? It's like what you said in a couple of episodes back around Shell actually having quite a lot of great sustainability initiatives, but no one would instantly think of shell as a great green company to go and work for. So is there anything around that as well?
Saif Hameed [00:16:02]:
If Im being generous, Izzy, I would say that all these companies are mission driven in their own ways. I think it really does come down to consistency. I think that building a sustainability brand is not for everyone. And I dont mean that its, it's not for the faint hearted, I mean that it literally just isn't for everyone. Everyone will not benefit in the same way. It is easier to build consistency with upside more than downside as a challenger because you're targeting a smaller customer base, you're going niche. Oatly can win a market by being super focused on like London, New York, Paris based baristas for example. And people who are discerning and have the share of wallet to spend on buying a more premium product.
Saif Hameed [00:16:48]:
And they can therefore get all the upside of mission consistency with much less of the downside. So I think it's more about that. In the same way that shell could be a pure play sustainability business today. If they just sold all the oil and gas assets and were left with their renewable business, they could totally do that. But it means seizing to be a major, major energy company.
Isobel Wild [00:17:11]:
Yeah, I'm going to bring us back onto PCs because we've gone on a brand tangent onto the actual, the meat of the topic around calculating a pcf. What would you say are the three building blocks that you have to play with?
Saif Hameed [00:17:26]:
And Izzy, what do you mean by the three building blocks? What are you looking for?
Isobel Wild [00:17:30]:
I'm looking for the criteria that you need to consider when setting up your pcF. So the data that you need, the methodologies you need to consider the end goal that you have in sight, those kind of the strategy behind your pcF.
Saif Hameed [00:17:45]:
So I think maybe to start from the end almost, which is what are you looking to use these pcfs for? I think that if you assume that you're looking to use these pcfs really to understand that clarity and focus on where to drive change, it's unlikely you need pcfs for your full product portfolio. So if I'm a multi product company, I would actually probably choose to focus in tiers. I would say I'm going to cover certain products first, and then going to progress, and then going to progress. So maybe you say, actually, if I have 100 products, I'm going to start with five and then going to do another 15, I'm then going to do another 20 or 30, and then I'm going to scale up. And maybe in some cases you never do the full portfolio. I think the next thing is, from a methodology standpoint, how do you approach this? I think that I'm a little biased in that we are big supporters of the pact framework and approach for doing this. I think that to play back an earlier point in this episode, we are increasingly thinking of a dual methodology approach that is both pact conformant and PEF aligned as well. So that you can have the optionality and have the data ready for reporting, as well as have the data ready for analysis.
Saif Hameed [00:18:58]:
And that may mean that you have slightly different numbers. And then in terms of what data you need, it is typically similar data to what you would need for a corporate footprint. The main difference is probably the importance of bill of material data or some equivalent, so that you can actually know what are the inputs for that product. And so in like a food context, it would be bill of materials. In a food service, it might be the menu. In apparel, it might be something from the product lifecycle management system that you kind of export. I think it has its own eccentricities across different sectors, is something we've learned. And so this data typically sits in different places.
Saif Hameed [00:19:36]:
In apparel versus food, for example, is.
Isobel Wild [00:19:38]:
There a rule of thumb around the amount of primary data that you need to be confident in your PCF?
Saif Hameed [00:19:44]:
Yeah, good question. Actually, I think that. No, it is a good question. I think that there's a lot of value in iteration. Like I think you can actually do this thing fully secondary to start with, and then actually swap out certain ingredients. So if you think of, let's say, the PCF generation that you're doing on your side, so let's say you're a beverage company, you've made a fizzy drink, and that is fully using secondary emissions factors. So for example, the aluminum can, the aluminum can that you're using for the fizzy drink, you are using a generalized global average emissions factor for the can. Now actually, maybe you kind of want to swap that element of the PCF out and replace it with something more accurate.
Saif Hameed [00:20:30]:
You can still do that actually with secondary data. So maybe you actually learned that, hey, this particular input into my PCF is sourced from an american aluminum can sheet company. I'm actually buying this from ball, let's say. And Ball corporation has a facility in the US that they're using to supply this. And I do not yet want to engage with ball corporation, but I want to know what better secondary factor to use. Well, actually maybe a regional us specific emissions factor is going to be better because it's going to have a slightly lower weightage of virgin aluminum sourced from fossil fuel heavy manufacturing because there's more recycled canned sheet being used in the US versus the global average. Actually, that's already chipping away at the accuracy of the PCF. Now the next step is can I replace that with a ball corporation PCF for the aluminum cans that they've sold me and slot that into the PCF for my fizzy drink.
Saif Hameed [00:21:23]:
Now I'm actually progressively replacing secondary data with primary data so it can be very iterative.
Isobel Wild [00:21:29]:
That sounds like quite a big data headache in terms of tracking those changes, tagging them, keeping your data of state in quite good Nic, to be able to account for those. I think this also maybe I want to merge this with another question I have around aligning your corporate footprint with your product carbon footprint. What are the data hacks and the considerations that you need to take into account when you are making these changes or what you are channeling and managing a lot of data.
Saif Hameed [00:22:02]:
I think that you really need to scope well and set up well. And by scope well, I mean don't take off too much, don't aspire to do everything all in one go, either when it comes to all your products, for example, or using fully primary data, or as much primary data as you could get. Like just start out with a very small scope, start out with secondary data, start iterating and play from there. I think too many people jump into trying to do everything all at once. The next thing is that you're going to have a lot of iteration back and forth because as you do these, you're going to identify things that look funny or things that look weird in the output data. And when you start digging into it, you're going to find that the weirdness is in your actual source data and that might cause you to try and do either of a few things. Either go and clean the source data. So for example, can I add a code or add something else or clarify something on the source data that I'm pulling in to make it more usable for the output? Or you might say, can I change the source data in terms of what people are putting in? So actually there's data coming into this that's being entered wrongly or incompletely and someone needs to add something, or do I use a different source for the data altogether? Because actually there's a better source that the finance team is using, for example, and that's more accurate.
Saif Hameed [00:23:18]:
And so I think that you kind of are going to have this back and forth again and again, and that's okay. And you should expect that there's going to be a fair bit of that and you get it right before you start scaling it. So I think that's probably the main hack that I would apply.
Isobel Wild [00:23:33]:
And in terms of, we've spoken about when not to, you know, it's probably not the time to share your PCf if you're not confident around your data. And so for the internal use cases of data, of your PCF data, have you seen any cool ones? Have you seen any good use cases to actually apply this PCF lens where it's really valuable?
Saif Hameed [00:23:55]:
Actually, it was a great example that I think Jess from Huell cited in our book podcast episode some time ago, and she mentioned it again actually at our event, which is when she looked at two different products for Huel, she found that actually the PCF was quite different. And in one case, for example, packaging was super important. And in one case, actually, packaging was not a really relevant one. And that really helps in terms of deciding where to focus, because customer feedback often prioritizes packaging innovation or packaging recyclability. And that's obviously important. But actually, it might not be equally important for every product. There might be certain products where it is important, and certain products where actually they're completely different decisions that need to be taken. And so that helps you focus what you do, and it can also help you focus what you communicate, irrespective of whether you want to put a number on the pack, just the consumer behavior that you want to shape or the consumer narrative that you want to build.
Isobel Wild [00:24:53]:
Yeah, I think a main takeaway for me from that event was that pick and choose what you want to communicate. You don't need to fully blast everybody with every bit of sustainability progress that you're making. Like some bits of sustainability narratives will be great for consumers, other bits will be better for internal decision making. And I think having a bit more of a fragmented view of your sustainability progress. Estate is probably a better approach than just flooding the airwaves with everything you've got. Saif, are there any other thoughts or lasting comments that you have on PCs that you think would be valuable?
Saif Hameed [00:25:31]:
Yeah, I think pcfs are here to stay, but also are going to grow radically. We're super bullish on pcfs. I think that in general, this sort of metadata accompanying product transactions between companies is just going to gather steam and scale. And so I think wherever you are on this journey, it is helpful to start thinking about what value this could drive in your business because you're probably going to get asked for it anyway by someone or the other. So you may as well start prepping for it.
Isobel Wild [00:26:03]:
And is it something that you should prep with internal resourcing? Or is it something that actually is better to get externally or get external help on?
Saif Hameed [00:26:12]:
I think that is probably helpful for most companies to do this first with a consultant as corporate footprinting as well, for example. I think these things are best done first with a consultancy because a consultant brings you expertise, the advice, the ability to understand things before you automate and scale them. I think once you've done your first, let's say, LCA, or your first few lcas, even for a few different products, then you start to get a handle on what is it that you need from this and what value can you get if you automate and scale. And then I think it's the right time to go for a software solution. And I think you should look for a software solution that is demonstrably the right fit for your sector and needs because you'll just find more and more synergies from that over time.
Isobel Wild [00:26:56]:
Yeah, well that's great lasting piece of advice. Saif, thanks so much for your time. I hope you get some rest after your intense week of events or intense month of events. I'm sure they're probably going to continue that. Thanks everyone for listening. And please send through any suggestions you have on content, we love to hear it. Bye.
Saif Hameed [00:27:14]:
Thanks everyone. Bye.