Podcast #1: The Do’s and Don'ts: Setting up your Sustainability Data Transformation


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Transcript

Welcome to the first episode of State of Sustainability, where we discuss tips and tricks to help you with your sustainability transformation.

Today we're going to talk about sustainability, data management systems and processes. If you're listening in, what you can expect to get at the end of this session is an understanding of a few ideas and a few suggestions that might help you with setting up your sustainability data transformation. We're going to look at a few areas.

One is the big picture, where are you heading? What's the vision? Why are you doing this? And building a bit of that narrative around sustainability data. We're then going to look at the infrastructure side. How do you set up for success? What are the do's and don'ts? Where do you look to automate?

Where do you avoid automation? We're going to cover that. Then we're going to move on to engaging the internal stakeholders you have. How do we get people on board with this? How do we make it less of a chore? And more of an opportunity, more of a source of excitement. Finally we will move on to external stakeholders and how to overcome a lot of the hurdles that come with trying to engage your suppliers behind this topic. Again, we will turn that into an opportunity that you can lean into. We're going to go one by one and hopefully this is useful to you.

How to create a sustainability data transformation strategy that aligns with your vision

To start with, we need to understand what we're solving for. The way that I look at it is: there are dozens of different categories of sustainability priority that an organization could solve for, and whatever the framework is that you use, you'll find at least anywhere from 20, 30 or 40 different types of sustainability value drivers. When it comes to metrics, there's almost no limit to how many metrics an organization could be tracking if it was trying to solve for every single reporting framework out there.

The largest number I've personally come across is 218 metrics, which is what a mid-size packaging company has been tracking internally. That's literally because they've made lists of every single framework that they need to report against and are looking at each of those metrics separately.

Don't do that. Instead, identify where the battles are? Where do you as a business intend to win the game? What are the issues and the topics where you really want to stake your brand? Where you want to build brand equity. Where your customers and your consumers of your products are going to get really excited, and your suppliers are going to say, yes, that makes sense.

Figure out those areas. Those are where you want to win the game. Next, identify the areas where you just want to play the game. You don't want to do badly at these. You want to be above board. You want to be respectable and hold your head up high, but you don't necessarily need to excel. You don't need to go to that extra level of granularity, of detail, of perfection.

You don't need to be a leader. Usually, you'll find that there's a much smaller category of areas than where you really need to go deep and granular and get a really thorough understanding. What can inform this in your business is looking at your customers and your peers and what they're doing and what they're valuing.

So usually a really good thing to be doing in this stage, if you’re a B2B business, is to start speaking with your customers. Understand what they're prioritizing. If you're a B2C business, start engaging consumers. Understand what they're going to be looking for.

I worked once with a baby food company, which started surveying their customers and they found that the top issue for their customers or the consumers of their products wasn't actually emissions. It was biodiversity. That is a good suggestion that actually in the times to come, you might need to start working through that issue as well from a data and metrics perspective.

For B2B situations, you'll also find that some of your customers might have particular frameworks that they want you to match against. A customer of ours is a big supplier of Unilever, and in that situation, Unilever is moving its suppliers over to a packed-for-oriented framework where the supplier shares product-level data with the company. This allows them to also start building their own product-level data that they can pass on into a product label of some sort. In that case, the supplier already knows that they're going to be expected to conform to a certain framework, and that framework is going to require product level data not just scope one, two, and three, a standard greenhouse gas inventory.

What this already gets you thinking about is, okay, you're going to need to set up systems that can deal with this flexibility where they might need to have data that can be cut in different ways. So you're already likely thinking activity level data.

Starting to engage your stakeholders in this way can help you build a holistic picture of what's coming soon in your direction and what you're going to be expected to comply against when you take a value-driven view of this. From a regulatory perspective, the bar might actually be, in some cases a little lower, and the expectations of your customers might be in certain markets and certain sectors, comparably higher.

2. Building your data Infrastructure up for success

Let's now talk a little bit about how you bring these things together from an infrastructure perspective. If we reflect a little on the previous part, you've identified a smaller set of metrics and data where you really need to go deep. You should start thinking about where those data sources are likely to come from.

What types of data are you going to need to be pulling together? What types of business owners are you going to need? We're going to talk a little more about business owners shortly, but the first thing you need to start to accept, and understand, and communicate to others is that this will be a multi-year journey.

This is not going to be something that gets done in 3, 4 or 5 months. There are many companies that I speak with that are setting up sustainability data as a project, and they have a view that this is going to be a short-term fix in terms of finding a solution and getting it set up. Sometimes they're building something internally and they figure once this is set up, it'll run very smoothly.

This is never the case and it's seldom the case, frankly, in any other domain and in sustainability, it's really going to change. The reason for that is that sustainability standards and expectations are evolving fairly rapidly. The pace of evolution is actually also increasing, and that's already driving a change in how companies are expected to deal with data, work data, report data, and share data.

The other aspect deals with white spaces, and that can happen both in inside your business and outside. Within your business, there might be many areas where you're actually missing data, missing coverage, don't have the right assumptions, don't have data in the right structures, and in many cases this might be fine for you to get going with

In some instances, now looking outside the company, you'll be missing emissions factor coverage for the areas that you need to cover, and that might also be fine and you might also be able to use fillers or assumptions to block out the gaps within that. That said, this all points towards an iterative journey where you need to be able to evolve this and iterate this process and these systems to become better over time.

If now we think about who you need to be on this journey with, you need to identify the business, the owner, the data owners within the business, who own the activities that are involved, and also therefore, who own the data. This is likely going to be the same sets of people. In many cases, the people who are closest to a particular business activity are also the ones who have access to that data.

Facilities is a great example. If you think about utility data, and you have a range of warehouses in the business or you have a big retail presence, for example, the manager of each particular location may well be the person who has first access to a lot of the facility-specific invoices.

That person is a data owner and that person is likely the one that you'll be reaching out to  get data in the first place, but that person will also be important later on in the journey because they're going to be able to help you take action. We're going to come to that a bit further down the line. Understanding who those owners are is  another important part of setting up the right infrastructure to begin with.

The next thing that we think about is how you identify what you need to automate and what you don't need to automate. Let's first start with what's already automated. Nowadays, most vendors, most partners of yours in certain lines of business are likely to be pushing a particular platform or software.

You might have everything from legal tech, to energy tech, to procurement tech. For example, I spoke with an apparel company this morning and they have at least 18 different software providers disguised as utilities companies. They have an energy management platform coming from their energy supplier. They have a waste management platform coming from their waste management supplier. They have a water platform coming from their water supplier. So all of this data is already automated. The next question is, whatever it is that we're going to set up as new infrastructure, can it integrate or pull from these different sources of digitized information for instance?

That is good because that already saves you lots of time and potentially these are accessible via API. Even if they are not, they might still be able to export structured or tabular data that can easily be ingested by another system.

Next, let's look at what needs to be automated because you can't leverage existing platforms. In this area, you want to check, is there a category of data that is meaningful? It is going to be required frequently, and it's also not too fragmented, and it's not going to be too much effort to get it pulled together into some format where you can work with it in an automated way.

A good example of this is energy invoices. In most markets, you might have only a few big energy suppliers, and most energy invoices might look relatively similar, which means that it is comparably easier to automate the digitization of that sort of data. In that case, it is a relatively good candidate for automation. It is also a big driver of the emissions for certain parts of your emissions footprint, and a meaningful contributor overall. Therefore, makes sense for you to be able to automate that aspect.

Let us contrast this by adding another activity. Let’s look at waste, for example. In many types of organization, waste is going to be an extremely small contributor to your overall emissions. We are talking 1%-2% or less, very similar to the refrigerant. It might be a very small contributor. Think about a professional services firm, where you have lots of offices and there's really not that much in terms of wastage versus something like business travel.

The data is also very fragmented. It's probably very manual as it's in people's heads. It needs to be calculated somewhere. It's not in a structured format where you can easily digitize it. In that sort of case, it's neither meaningful enough, nor is it easy enough for it to be worth the effort for you to go and figure out how to automate that.

Figuring out or deciding which types of activities or which types of data sources are going to sit on one side of that fence, where automation makes sense, versus the other side is going to be an important distinction for you to make.

The other I thing I encourage you to think about is how do you already start to set up a data architecture for a system that can be, flexible, scalable, and secure?

If I think about flexibility, most systems right now when it comes to sustainability data are oriented to meet one, two, three or four different types of use cases. I was speaking with a head of sustainability at one of the world's top three or four food companies, and, they were showing me their sustainability data management system, which was built in house and it was a really impressive system. It was put together through a range of different component parts, so a consultancy had come in to define the original model. There was a power bi front end. They were using a different tool to gather farm level data for instance as well.

It was really cobbled together across a range of different component parts, and for the most part, it worked really well when it came to calculating and visualizing an overall emissions number for the organization and cutting it by geography, or by certain categories. What it was really bad at was cutting data by products.

This team had a number of chocolate brands in the portfolio and they couldn't go to one of those brands and say: here's where you are in terms of your emissions today, here's the target of where we need you to get to, and here's the delta, we need to work together on bridging the gap.

They were not able to communicate this message using the data because the system was not flexible enough to allow them to do so. It is not just in terms of the front end and how it's set up, but it is also the exports available. The way that they could get data out of that system as a user did not make sense. So especially for large organizations, it really makes sense for them to think early on about flexibility.

Moving on to scalability is quite interesting for me because I find that there is a really interesting difference between organizations that have been doing this for six or seven years versus those that are just getting started. Oddly enough, it works against the organizations that have been doing this for six or seven years, and you wouldn’t expect this. Let me give a couple of examples. I know two companies that are both incredibly mission-driven companies. They're really great consumer brands.

One is in apparel, one is in personal care and they both have really strong associations with sustainability at their core, and I am 100% sure that they're all doing the right things when it comes to actual sustainability action.

In terms of how they set up their data management system when it comes to emissions measurement, they both set up using a sort of Google Suite-based system. It’s like a Google sheet where they're trying to consolidate the information and they've tried to have data feeding in from different systems on their side. They have set up their own formulas and macros to process this. The problem is that as soon as they add on a business unit or a new product line, everything breaks down. The whole system stops working. It's just totally not scalable for them to actually expand it to accommodate the needs of a growing business. And so every couple of years they basically have to revisit it. They have to patch it up again. Someone has to come in. Very fortunately, in both organizations, the original architect who created these systems is still around. So they go to that person, and ask them what the original assumptions were so they can rebuild this.

If you think about the most forward-leaning sustainability brands, one of the best examples that I think about is Patagonia, where I was speaking with the chairman a few days ago. He told me that at Patagonia, they take emissions measurements super seriously.

As a result, they've actually appreciated that they need to rebuild their approach to measuring emissions multiple times. Now in fact, they’re on version three. When they did version one, they thought it was great, and for its time it probably was. A couple of years later they find actually, we need version two.

At that point, they also thought version two was fantastic, and now they're on version three. That is much more intuitive because if you think about the evolution and stages that you're going to go through in terms of data requirements, it makes sense that you'd need to refresh the view and refresh the picture.

The second thing that I'd really think about after thinking through flexibility is the scalability element. The third one is around security, and I don't think that most companies take this seriously enough yet when it comes to emissions data. The reason I say this, and the way that I know this, is that there are so many companies out there in my own network that are receiving email based requests for emissions oriented data, which means that there is someone on the other side sending out these emails and expecting to hear back in the form of Excel spreadsheets, PDFs, PowerPoints, Text and email.

Forget the, the challenge of just consolidating this, I mean, we've talked about that a little in terms of the automation element, and it's relevant for scalability as well, but it's also not the most secure way to share what is actually not just sensitive data today, but going to become increasingly sensitive data over time.

Ultimately, emissions data, if it starts to be even somewhat accurate, even 70% accurate, even 80% accurate, it's going to be business sensitive. It's going to represent a real cut of your business. You could reinvent the products of the business in question. You could reverse engineer their bill of materials. So this data is actually important, sensitive data that we should treat with the same level of data security, that we would apply to financial data, for example. So when you think about the infrastructure that you're setting up, I'd really look for that flexibility, scalability, and security aspect as well, and how you're going to solve for that.

Finally, most of the conversation so far has been around capturing activity level data. We've talked about energy invoices, waste data, and water data and so on. But equally, there is a big data category, which is the internal knowledge and expertise of the people involved, codified in the form of assumptions and those assumptions str ones that every sustainability analyst is probably incorporating into their calculations every day. You are asking someone, okay, this building where we've got this energy data from, is this three floors or two floors? What's the square meterage? You're getting a lot of different assumptions, from a lot of different people that represents a lot of embedded expertise and understanding. Many different categories of spend, for example, might have associated tariffs, discounts, credits, for instance. That is all retained wisdom in the minds of certain people who have provided that data to you and who have made them themselves available with their time to share those assumptions and insights with you.

If you don't also codify that Metadata in a way that it's linked to the activity data that you're going to be using, then you are running multiple risks. One is that you are going to have to go back and try and find that again later on from that person, and that person may have left. The second is that you run the risk of creating an inconsistency later on because maybe the assumption is different next year and you don't know why. That comparability element is really different.

Finally, and maybe most underrated challenge with not storing those assumptions and not storing that metadata, is that you inhibit the usability of the data for other purposes later on. Actually, those assumptions, that context that is associated with that data is what might make this data more useful later on also for operational improvements, for cost optimization, for example.

When we process data at altruistiq, we, we might associate a dozen different tags with an individual data item to really enhance the usability of that data going forward into the future.

3. Managing for organisational alignment

So that's a little bit around the infrastructure setup. Now what I want to move on to is how you really manage for alignment within the organization, just to ground ourselves and look at the world as it is today. In most organizations, sustainability data and sustainability, data gathering is a really transactional process.

It's something where I as, let's say the sustainability data coordinator or data manager, or whatever the role. I'm asking you to share some data with me. I'm saying, look, this is important. This comes from the ceo, pretty pleased. This is, this is going to save the world. But ultimately, I'm adding one more to do, one more task, onto the plate of someone who's probably already very busy. Think again about a facility manager, a logistics manager, or anyone else within the business, someone in procurement for example. This interaction leaves both people feeling somewhat drained, I would expect.

In the position of the sustainability analyst or manager, you're forced to chase up dozens of people again and again. If you're chasing them heatedly once a year that's inefficient in its own right, because they forget about you, you forget about them for several months and then, hey, I'm back.

In other cases, maybe you're going back to them every quarter, for instance, and that just gets to be a real pain. I think that there's a much better way to orient this where you already plan ahead, where you appreciate and understand that these people are going to be with you on a journey.

These people are your SWAT team. These people are your extended sustainability transition team, helping you drive change across the business over a multi-year program. A program that may well take, if we just have the narrow window of a 2030 target, several years. But really this is a decades long transformation, and the more that these individuals understand what they're doing, and understand what you need from them long term, the more they will be helpful to you because they're also excited and engaged and understand the big picture.

The best way I think of managing that is to approach them through two lenses. The first is that big picture vision aspect, which is explain what the journey is, what's going to be the future of our organization, of our company. Where are we heading? What are those areas where we want to win the game, and why? Why do we think this matters to us?

Why is this important to us as a business, to our consumers, to our stakeholders? What will this mean for the success of our core organization? Maybe it’s a leadership position, maybe we just want to be fast followers, but we feel like we're getting left behind. Explain the big picture, the vision, and the mission and why this is important.

At the same time, appreciate that not everyone responds well to just the big picture. So you also need to go into the details. You also need to share, here's the plan, and by the way, here's where you fit into it. It's not just that you fit into it as a bit player or a grunt contributing, a very tactical piece in the puzzle, you are an owner. You are an owner of one part of this mission that we are looking to complete, and what we're looking to for your help with and your support with today is the perhaps somewhat mundane task of providing the data, but we'd also like you to help us problem solve. How should we make this easier going forward?

Do we automate this? Is there some way for us to reduce the load? how do we capture any other knowledge that you have around this data? Are there assumptions that we might need to come back to you and get your wisdom and your thoughts and guidance on? Then also as you go through this journey on an ongoing basis, engage them always in the next step of the chain. So when you're talking about data, already start to preface that there will probably be assumptions here that you're going to need to clarify. When you go to the assumption clarification stage and you're asking them to give you more context on this data, then you might also want to start asking them, you know, I see this assumption actually driving our emissions number up, What do you think would take it down?

How could we actually introduce a new intervention, for example, that would reduce the volume of what we're doing here reduce the kilowatt hours that we're using when it comes to power? Reduce the amount of packaging that we're using for example. Is there something in the specifications of the package size that you've provided me that we could change and make a big saving.

Both in money terms and in emissions terms. If you're always engaging them in that next step, then where it actually comes to, for example, scripting a plan and ideating together, they've already had that seed planted by you a little earlier on, and they're already there with you. You don't have to come back and go through the context again.

One of the things that I think most people miss, or most organizations miss, when it comes to all of these unsung heroes, the people spending 10% of their time helping out with sustainability while really doing a full-time job on something else, is that a lot of the credit and the recognition doesn't cascade to these people, most of the credit for an effective sustainability transformation, and, you know, forget even an effective sustainability transformation. Most of the credit for even just a 2% shift in one year to the next will go to a CEO, a Chief Sustainability Officer, maybe a COO, maybe in some cases even a, a board chair, for example. Right? And, and these are the people who get a lot of the credit for these sorts of movements.

Whereas actually we need to be able to call up individuals around the organization who have been involved in driving change and who have been involved in the much less glamorous tasks of gathering data as well.

For example, one company that comes to my mind, which is a customer of ours, is a parts distributor. And in one of their teams there was this guy named Andy. And this is a this logistics team in a subsidiary of one part of the business. So we're talking really quite small. And Andy, relatively early in his career, probably mid late twenties, or early thirties at  most identified an intervention that would save the amount of packaging that the company needed to use for their parcels.

This was a relatively quick win intervention, but it was fully sourced and originated and implemented by Andy. The great thing was that this, again, it's the ideal sort of intervention. It saves money and it saves emissions, and fortunately, Andy's manager, was the sort of person who really appreciated his team taking ownership in this sort of way. And so his manager, you know, you would would talk about Andy and because he would talk about Andy eventually, Andy's name made it into the management committee as well. And someone started referencing how, you know, Andy and such and such a team had this great idea and implemented this initiative and we really need more of these sorts of moment to start to galvanize and energize people behind taking action. Because if you think about the a hundred percent of a greenhouse gas inventory, there are going to be parts of that that we can get without really the need for meaningful action at an individual level. There are going to be some centralized interventions that can get you 10%, 20%, maybe even 30% of your reductions can come from some big centralized levers. But for most of the balance, we're going to be eeking out percentage points, half percentage points and fractional percentage points with every little bit of help. That we can get from different people on the front lines of our businesses.

And I think it's super important to start to get them involved early, but also energize them and keep them going on the, on the long, long journey ahead. One of the best examples of this that I'm kind of seeing right now in practice is with, again, a large customer of ours and one of the first cohorts that they're onboarding onto their sustainability data management system is a set of around 200 facilities managers. And what they're hoping for and expecting with these facilities managers is that these managers are going to be onboarded onto the platform. They're going to see how data is represented. They're going to understand by playing around with it what's to come, and what's required of them.

And therefore, when they start uploading their data, they realize that they're actually on a journey. So, Because the experience  of interfacing directly with the platform themselves. As users individually in their own right is inherently different to interfacing with an intermediary by email who's asking you a specific question, one question at a time, or in a small survey of some sort.

And so from the get go, they feel like users, they feel like practitioners, they feel like people involved in the journey. And once they upload data, they'll see how the data is used and they'll understand the context. Which means that if there are data gaps or problems or challenges later on, they'll understand that because they have that context in which to put this data.

And then further along the line when they can see the targets being set and they can see how their data or the emissions attributed to the activity that their data represents, they can see what that contributes to the overall puzzle and they can see the delta that they need to help drive or fill within that target space. That's going to be super powerful and super impactful. And so for each of these 200 facilities managers, they're actually coming on a knowledge journey to upskill to understand more. And if you think about sustainability functions, most sustainability functions. Are in some stage of trying to devolve themselves into all of the mainstream functions of the business.

The more mature ones are figuring out how to really devolve into other functions of the business. And the best way to do that is to start upskilling those other functions and really growing the knowledge base and expertise.

4. Optimising for supplier alignment

So we've talked a bit about aligning stakeholders within the organization, I want to move on to aligning some of the most important stakeholders outside the organization. And the category that I really want to focus on for today is suppliers. And so I'm going to say a relatively uncomfortable truth for all of you who are asking your suppliers for data. And this is that with the very best of intentions, your suppliers would rather not share this with you.

And the reason for that is that they're not sure if the data is going to play in their favour, and they're not sure if the data is going to turn out to be sensitive, and they're not sure if the data is going to be used against them. And these are three very potent reasons, and it's not your fault and it's not the supplier's fault.

The reason is just that, procurement processes have evolved into a very sophisticated game between, buyers and sellers. In a B2B interaction, for instance, where every little bit of the interaction is optimized, and so if the sustainability data that is being shared is any good, it again represents a pretty thorough understanding of a business's processes and activities and builds of material, for example.

It is potentially possible at some stage, probably not now for most suppliers, but at some stage it would be possible potentially for you the customer to reverse engineer the cost base of the supplier selling into you. And that's a difficult place for a supplier to be  because they want to inherently be part of this big mission and this big story.

Inherently, they want to build a strategic relationship with you that moves beyond just the commercial aspects and moves on to something bigger, a bigger goal, a bigger vision, a bigger challenge. But at the same time, they don't want to handicap themselves where they're giving you sensitive data that could ultimately be used by your procurement teams, uh, to their disadvantage.

The other thing that they're afraid of, and I touched on this a bit in terms of the data not working in their favor, is that most suppliers don't yet know how you're going to use this data. What they expect is that you're going to use it in some sort of scorecard or grading system. Even if you say you're not, they will probably still think that's what you're going to do and that fear that you're going to compare them to another supplier and see whether your emission or their emissions are higher or lower.That's a game that they're very reluctant to play without knowing that they'll win.

There are multiple companies that I've spoken with that are being asked for this data by their large customers, and they're seriously considering to just go and find some small consulting shop that will give us whatever numbers we want as the output of an emissions measurement exercise purely so that we have the best numbers in our industry going forward.And that's obviously not a long-term strategy. It's not going to work  a year or two down the road. But there is enough flexibility where there is some room for them to actually go with that approach. And that's, that's not healthy for them long term.

And it's not healthy for you as the company asking your suppliers for data. And so, uh, if you want to start overcoming some of these reflexes, I would think about a few things. One is building trust, which helps explain to these suppliers how the data is going to be used. What are you going to do with it on your side? What are you not going to do with it? Think about those scorecards and comparative indices. Most companies are not thinking anything like that right now or just yet. Who's going to see this data? Are you going to be sharing it with the whole business? Or is it just within the sustainability team? It might make a meaningful difference if the sustainability team is going to see it, but maybe the procurement teamwon’t.

There’s a lever here around showing value, which is: why would this make sense for the business, for the supplier themselves to share this data with you. Is there any upside for them?Is this going to be a new cost to play where you're going to expect them to go through this effort? An additional ask, you know, one more ask in the same way that you expect them to onboard onto your procurement portal, or complete your compliance documents.This is something else.

Os there some positive value coming for them further down the line?For example, are you going to do a big PR campaign with a case study? Are some of your suppliers are going to be a central part of that case study? Will they be strongly and prominently positioned to all of your peers who might also want to also buy from them.That's a great positive value signal.

Are you at some point expecting to pay money in through the same system? Through which you're now getting data out. So are you going to say, “look, I'm buying, a hundred kilos of something from you now”. I'm a co-founder in a farming business, and our customers used to ask us, If we could give them emissions data related to our products so that they could then potentially compensate us more for emissions reductions linked to the product. Are you going to be going in that direction where you're actually going to be paying maybe not a dollar 50 per kilo, but a dollar 60 for something that has lower emissions? If that is on the table at any point, even if you don't have clarity on what those numbers are or what the magnitude is, it could still make sense to put that on the table.And to co-create the thinking with the supplier and to get a better understanding of what would work, what would make sense, what's possible in this space.

Fnally, I think it's important to be pragmatic with your suppliers. What is actually possible for them to do, given their size, their sophistication, their location, and what's within the realm of their capabilities.

I was at a CEO round table yesterday with 15 or more CEOs from the textile sector, combined with one of their largest customers. One of the top two or three apparel retail brands in the world. And what was exciting was that this global brand had brought just as many people to the table as we had CEOs in the room. They had the whole sustainability team, they had commercial people, they had procurement people as well. And they spent about three hours together on this round table. There was a very clear commitment from this big buyer, this big retailer. Not just to the industry and these 15 companies overall, but also just to understanding that this was a journey and that there would be missteps on this journey, everything wouldn't be perfect and that they were going to find a way forward regardless.

I think that the best companies understand that in addition to this sort of positive messaging, which is super important, you also need to provide some, maybe some coaching, some educational resources:, webinars, maybe even software tooling or support with building that capability because most suppliers, of a reasonable size company, are not going to be able to do this on their own, especially in the SME category.

Can you emphasize commonality, not just in the vision, but also in expectations and standards across your company as well as others in your space where this is not just going to be you, but this is potentially going to be other peers of yours as well who are looking for the same expectations and the same sorts of data.

So this is not going to be just a one person demand, forcing them to make a big shift. All these things are going to be super relevant in terms of how you engage with your suppliers.

Summary:

As we wind up, I  want to summarize a bit of what we've covered.

• How you set up the vision and the, the plan and almost build a narrative. What are you looking to achieve with your sustainability data? What are you prioritizing for? What's important, uh, what's coming next? Where do you win the game versus where do you play the game?
• How you set up infrastructure to support this. This vision and this plan and this narrative. And within that, we've looked at automation. Where do you look to automate? Where do you not look to automate? Data owners and how do you identify the right data owners for the right data categories. Setting up systems that are, are flexible or scalable or secure.
• Internal stakeholders: how do you bring internal stakeholders from whom you might only need data today, but whose support you'll need for implementation in the months to come. How do you take them with you on this journey over the course of your sustainability transformation? So they're with you hand in glove. Every step of the way.
• Suppliers - one of the most important constituents or stakeholders you have externally in this mission.

Given that, most emissions are still supply chain oriented emissions for most companies. And how do you really focus on disarming some of the inherent fears and concerns that those suppliers might have, and turn this into positively engaging them in a way that builds trust and credibility and excitement and motivation.

And so I, I hope with some of those lessons learned from me and for our organization. I hope that that's helpful for you as you think about how to craft your own sustainability transformation.Thank you so much for listening to today's episode of State of Sustainability. I hope you'll stay tuned for more episodes.

If you want to hear more from me or, or the things that I talk about, uh, please feel free to check out my LinkedIn anytime and best of luck.

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