Turn Your Sustainability Data into Action with Insights Hub video (57m)

Hello, and welcome to today's session on turning your sustainability data into action with Insights Hub. My name is Leah Jaggars, and I'm the senior education manager here at Worldly. And today, we're going to go over everything that you need to know about Insights Hub and how you can use it to actually take next steps and determine your strategy. here's a quick overview of the agenda for today. First, I just want to cover the goals for today's session. We'll get into navigation, then we'll start to break down each section of the insights hub so that you can better understand how to use it. And then finally, we'll get into a demonstration as well as have plenty of time for questions and answers. So like I said, let's discuss the learning goals for today's session. This session is designed for anyone who is new to Insights Hub. So by the end of this session, the goal is that you'll master the basics. So you'll understand, you know, where to find different information, KPIs, what that means, how to download your data. You'll also deepen your knowledge by applying filtering, different benchmark, and hotspot analysis, learn more about different initiatives as well as targeting your engagement. And then finally, you'll be ready to get started. So you'll understand use cases and examples and be able to get planning and working with your facilities or with your supply chain. So before we dive in, I'd like to get just a sense of who's in the room. This just helps me to orient a lot of the demonstration at the end of the presentation. So which of the following best describes your role? Brand or retailer, facility or manufacturer, manufacturing group who both owns facilities and collects data from their supply chain partners, a vendor or intermediary, or a verifier or auditor. So let me share those results. So it looks like the bulk of who we have in the room today are facilities and manufacturers. So that's super helpful. I'll definitely orient the demonstration accordingly. But don't worry if you don't fall into that category. The demonstration will cover all angles, but it's just a little helpful for me to know, you know, who's the bulk of who I'm talking to today. So thank you so much for participating. Alright. So with that, let's go ahead and review Insights Hub. So Insights Hub is designed to break you through that complexity to understand what's going on in your supply chain so that you can actually drive action. The goal is that it simplifies your con complex sustainability data so that Higg FEM data, Higg FSLM data, you know, both on the sustainability side and on the social and labor side, It allows you to benchmark against industry aligned metrics so that you can then build a resilient future proof supply chain. It's your central hub for Higg FEM and FSLM performance data. It's designed for both facilities and brands and retailers. So whether or not you fall into either of those categories, you should be able to get something out of today's session. It translates your raw data into clear, comparable performance scores. It also connects performance to benchmarks, trends, and improvement tools. So just instead of looking at just data, you actually get ideas of where you can go next with different initiatives and different things that you might want to dig into to improve your performance. And I'm sharing the getting getting started guide in the chat right now in case you haven't seen it yet. So here's an overview of the data driven cycle. Insights Hub takes you from data collection to driving results. Collect your supply supply chain data using other tools like we discussed in the Worldly platform, so Higg FEM, Higg FSLM, and Facility Data Manager. Then you use Insights Hub to understand your data and identify opportunities for improvement. Use these insights to target your engagement with your supply chain partners using the collaboration suite to drive results. Then continue the cycle with ongoing data collection and targeted goals. Please note that this time, Insights Hub has Higg FEM and Higg FSLM data, but facility data manager data is coming soon. So what can you really do with Insights Hub? First, you can report on progress against key performance indicators for all suppliers or a specific region, segment, or type of facility. You can identify specific regions or facilities with high or low performance and plan your engagement accordingly. You can analyze where making a change at a facility could lead to positive business and environmental impact and identify facilities that do not have plans to address risks. Or if you have segments within your, you know, performance where you don't have plans to address those risks. With that, let's get into how to navigate Insights Hub. So here's a short video showing how to access and navigate Insights Hub. But don't worry. We will go over all of this during the demonstration as well. But hopefully, this helps you orient in the platform if you would like to follow along. To to access insights hub, navigate to insights in the upper left hand corner and select insights insights hub. This will take you to the dashboard. On the left is a menu where you can select filters for your data. The middle contains key performance indicator cards and hotspots. On the right hand side are initiative cards. We will get into each section in much more detail during this session. If you don't see the insights section in your menu at the top of the page, please reach out to your account manager or support for assistance getting it added. But if you collect Higg FEM or FSLM data, whether you're collecting it for yourself or for your supply chain, you should have access to this. Alright. So I talked about filtering, so let's get more deeply into that. So currently, the data sources, like I discussed, are the FEM and the FSLM. Facilities also have access to Insights Hub, but you see your own data compared to the industry. I often get a question about what I mean by, quote, unquote, the industry or industry benchmarks. So what I mean by that is anybody who has submitted any of these assessments for that reporting year. So if you're looking at FEM data, that's going to be other people who have submitted FEM data for that reporting year. You can also use the filters like brands can to filter the dataset so that you're comparing your own data to, you know, different facilities that are in your country or different facilities that do the same type of performance or performance processes that you perform. So for example, you know, industry sector like it's showing here. So I'll get more into that, but just know that filters are helpful helpful for whether or not you're looking at just a single facility's performance or if you're looking at a group of facilities performance. Also, you can view data sources and outliers, have a section, and you can see more information about what is included in the insights hub. So outliers, there's a specific methodology that's applied. You can always access that information directly in the platform, but I'm also sharing the methodology for how we determine what's an outlier in the chat now. So feel free to check that out. You can view the affected data by clicking on the eye icon next to outliers. And if you'd like to just, you know, look at what that data is, you can download that to a CSV as well. If you would like to include your outliers, you can simply check that checkbox, and the dashboard will update. A newer feature in Insights Hub is the ability to allocate production so that you can see a proportional view of your performance. This can be toggled on and off depending on the analysis you wish to perform. Right now, this is done within the section the module section in the Higg FEM section. So this is done by a brand or different aggregator if you're collecting data from multiple facilities where you can say, you know, the amount of production that I get from this facility is about sixty percent. So that it shows you then a proportional value. You can toggle this on and off. I'll show you both how to apply that allocation as well as what that looks like when you turn that on and off during the demonstration. Here are all of the different filters currently available. We also have a short video showing you how to use filters, and that might also give you some ideas for different filters that you can apply. I'm sending a link in the chat to this video. One important thing that I like to highlight is that you can mix filters to narrow in on a specific dataset. So for example, if you want to look at only facilities that have verified data in China or you want to look at facilities where you have a high percentage of production allocated or a different type of facility, you can use that to narrow down your dataset. And for a facility, this is how you can also narrow down who you're benchmarking yourself against. So for example, you know, maybe your energy performance is highly dependent on what is actually available in your country. So you want to compare yourself against others within your specific region instead of everybody across the world. This is a way that you can do that by applying the filters. So I'll show you how you can do that during the demonstration as well. So some example use cases for filtering is, like I mentioned, regional analysis. So for example, you can filter by country or multiple countries to analyze performance of all suppliers in those areas. If you are a manufacturing group or if you are collecting your own facility data where you, you know, control that facility as well as facilities within your supply chain. There's also a filter there where you can filter by owned or, you know, shared with you data as well. Another example is sector bench benchmarking. So you can filter by industry sector to see how a group of suppliers compare to their peers. So, for example, comparing your textile mills against each other instead of, you know, your final process or or final assemblers because they have slightly different aspects. Maybe they're located in different areas, have different processes that you need to consider. And third is tier analysis. So you can filter by facility type to understand performance of different tiers and where to target your engagement. In all of these examples, you can also include other filters like tags or verified data to narrow your analysis further. So now, let's get into key performance indicators and benchmarking in Insights Hub. So a KPI or key performance indicator is an aggregate of the facility's FEM data compared to last year's performance and compared to industry performance. Like I mentioned before, industry performance in this context means different facilities that have submitted the FEM or FSLM depending on which dataset that you're looking at. So within insights hub, there are different areas that you can examine. That's going to first be your environmental baseline. So this is based on your Higg FEM data. This is the kind of high level overview is how I like to think of it. So it's different scores for the different sections, audit days, etcetera. Then there's decarbonization. These are going to be different key performance indicators around energy, emissions, target setting, and phase out plans for different decarbonization efforts. Then there's waste reduction and circularity. This is going to be around different waste reduction initiatives, recycling, circularity initiatives, etcetera. Then there's water use reduction. So these are initiatives around blue water, gray water, water reuse, etcetera. And finally, that your social baseline. So this is your Higg FSLM data, so the social and labor module, and it has different risk flags, section KPIs, etcetera. The central section of the dashboard displays all of those key performance indicators for each of those impact areas that I just talked about as cards. For each KPI, you can see the value as well as the percent change from last year and the percent difference from the from the benchmark. Again, your bench mark is comparing to peers. And if you have filters applied, that also narrows down your benchmark further. So, again, these cards will update as you filter. This allows you to benchmark different supplier population against their peers or your peers and compare performance year over year. To dig into a specific key performance indicator, you can click on the card to see the year over year comparison. The box plot, which is displayed here on the right hand side, shows you how either your group of facilities or your individual facility is comparing to industry benchmarks and where your performance is clustered. In either chart, you can hover your mouse over the chart to see specifics, or you can click the download icon to download the chart as an image or as a CSV of the data that comprises it. Now let's get into hot spots. So for each impact area that I discussed, you will have different hot spots available. So, again, those impact areas are decarbonization, circularity, water, etcetera. The first type of hot spots are distribution mixes such as energy sources or water sources. These charts show you the distribution of sources all suppliers or filtered to a specific group for decarbonization, waste reduction, and water use. The next type of hotspots are breakdowns by country, facility type, tags, cadences, or product category. These charts show you the intensity for these categories across all suppliers or filtered to a specific group. The last type of hotspots are tables where you can see all facility KPIs in a table format and download to a CSV for further analysis. And these are going to be specific KPIs that are relevant to the impact area that you're analyzing. However, there are also different areas where you can download all data if you would like to see that as well. And finally, let's review the initiative section. Initiatives are on the right side of the dashboard. There's a drop down menu at the top where you can select different categories, or you can click into an initiative card to learn more. There are a variety of sections that you can drill down into. These initiatives give you insight into different qualitative impacts at a facility that drive performance. Here are the different environmental initiatives available. First are top initiatives. That's that's going to be top initiatives for the impact area. For example, if you have it looking at decarbonization, that's going to be different initiatives that are proven to drive decarbonization efforts and improve performance. Next are strategy initiatives. These are things that are comprised of different policies or procedures or strategies that may be present or not present at a facility or group of facilities. Next is compliance. So these are going to be different compliance with either legal requirements, so base level requirements, as well as different industry participation. So if you want to see, you know, do they participate in an industry program when it comes to water? You can view this within the compliance section. Then there's engagement. These are going to be different initiatives around employee, subcontractor, supplier, and local community engagement. So is the facility or group of facilities engaging with these different groups to help better performance? Then there's tracking. So this is going be baseline tracking of different impacts such as energy use, water use, waste, etcetera. There's planned improvement and remediation and then recorded improvements and remediation. So planned is do they have different targets or phase out plans, you know, at the facility or at your specific facility? And then recorded would be, have they proven or have you proven that those improvements or remediations have had a positive effect? So to dig into the data, click on the initiative that you're interested in. This will open more information on the right side where you can see a table of the data. You have the option to download responses as well as capacity building resources to learn more. All right. So now that we have reviewed each section, let's bring it all together. Before I get into the demonstration, here are some different strategies for approaching Insights Hub. These are just some examples, though, so I do encourage you to discover the tool on your own as well. First, if you're just getting started in your sustainability journey, you will want to use hotspot analysis to choose key performance indicators that are meaningful to you. For example, if you're concerned about decarbonization, you might want to look at carbon intensity. If you look at your spots and you don't have a high carbon intensity in a particular facility type, you may want to focus more on regional group analysis. Then you can identify high and low performing groups or metrics. So this could be by country, region, type of facility, or suppliers that don't have specific plans in place or are not tracking key impact areas. If you are an individual facility, this may be specific KPIs that are underperforming compared to peers in your region. You can also compare to benchmarking. Compare KPIs to industry benchmarks to understand where to focus efforts. Next, you can go further into understanding your data and into analysis and planning. So learn more about the qualitative initiatives that drive your key performance indicators. So, for example, if we continue on our decarbonization example, if your KPI of choice is total emissions, you might want to take a look at the initiatives related to scope one and two greenhouse gas target setting and energy audits. Whereas if you're focusing on increasing renewable energy usage, you might focus on initiatives around phase out plans and purchasing EACs. So it really just depends on what you want to focus on, but you can use Insights Hub to narrow in on the different initiatives that can help you drive that performance. Then you can identify suppliers to engage. So if you're collecting data from multiple suppliers, you can identify who is either performing well or maybe not so well to identify different policies or procedures that you can implement with suppliers, programs that they can participate in, or technologies to adopt. Depending on your KPI, your strategy, and approach may be different here. And then lastly, engage with your suppliers. Develop implementation plans with them to drive these goals. If you're a supplier yourself, you can also track your monthly data with Facility Data Manager, also known as FDM, to keep track of data on a monthly basis for kind of keeping track of your targets over time. So that way, you can identify, you know, where do I have gaps in my performance with Insights Hub and then use facility data manager to keep track of your performance in real time so that you can identify things that you can change and see how that affects things instead of waiting for, you know, a year end reporting cycle. If you're a brand, you can also use collaboration suite or work work with your CSM to track all your suppliers and continue that data cycle. Also, if you are of individual facility or at a larger manufacturing group, you can also track your own supply chain with using Worldly tools to understand your scope three emissions as well. Alright. With that, let me get into the live demonstration. Alright. Hopefully, you can see my screen okay. I do have the q and a open on the other side. And I'm I do see a question, and I'll answer that once I'm in a place that I can kind of show that in just a moment. But just a few things. If you are relatively new to Worldly, in the upper right hand corner, this is where you can access different accounts that you have access to. So if you do have access to multiple accounts, this is where you can switch between them. I do want to note that I am in a staging environment. What that means is that this is not where you all do your work. So all of this data is just made up data. We did our best to make it look realistic, but in some cases, it's test data, and I'll be sure to point that out. What this also means is that there may be some features or functionality that is slightly different because this is where we are developing new features. If we do come across any of that, I'll be sure to point that out as well. In the upper right hand corner, you can also access your account profile information, access your user profile, purchase subscriptions, join more accounts, or add folks to your team. I do want to note that there is no user limit to Worldly. So if you do have in people within your company that might be interested in using some of these tools or seeing some of this data, you can always add additional users in the team section. In the upper right hand corner, you can access our help center where we have written data as well as short videos and step by step instructions. You can access our learning center where we have elearning courses. And I do want to mention that all of these elearning courses are free and available to all Worldly users. So regardless of your subscription level, all of this content is available to you. We have upwards of a hundred courses now, so definitely check it out. And I do want to kind of celebrate today that we have a bunch of new content available in our catalog. So just to kind of give you a sneak peek within the assessments category, we have a bunch of new content here that has been fully translated and gives you a lot more interactive abilities to explore the tools and test your knowledge. So definitely check these out. Any of the options that have, like, these eight courses, those are the fully translated options. We just announced it on LinkedIn. So if you saw that post, woohoo. We just want to kind of celebrate the work of the team today. But definitely check that out. A lot of that is on Higg FEM and FDM. So if you are interested in that, there's going to be a lot of good information for you there. And then lastly, you can also chat with our support team as well as submit a support request through the platform right there. Alright. So I've talked enough about that, so let us go ahead and get into Insights Hub. So to access Insights Hub, you go to insights, Insights Hub. Like I mentioned before, if you collect Higg FEM or FSLM data, whether you are an individual facility or aggregating data for a group of facilities, you will have access to Insights Hub. There is this banner at the top that says define your production allocation to get precise impact data. If you would like, you can click this. This will take you directly to the FEM modules section. So if you are aggregating data for a large group of facilities, this is where you can indicate, you know, how much of the production was actually kind of my responsibility. So here, it takes me to the module section. I have the option to either manually add different production values. So here, I can just do it one by one if I would like by clicking on that plus icon and then putting in one. You can see their total production volume that they indicated in their module. So in this case, I'm looking at FEM data. Again, this is example data, so that's why I warn you that this is staging. But here, you know, it's updated. And then now we can see, you know, I've got a hundred percent of that allocated to me. In this case, though, I can see that only half of this is allocated to me. If you have a large group of modules that have been shared with you, you can also do this in bulk. So if you would like to, you can click upload here, download this CSV template. That will give you a list of all the modules and then all of the kind of total allocation and a couple different data points. And then you can update your allocation in a column and then upload it here. And then once you upload, you go through just a couple just confirming that the matching makes sense, and then that will upload the modules accordingly. With the allocation applied, then within insights hub, you can then see that applied to your data. So here in my example case, I have allocated production for eighty two percent of my facilities. If I click on this little eye icon, so if you just happen to dismiss this before or anything, you can always access that again by clicking on the eye icon and then clicking define production allocation, and it will take you back to that spot as well. And it will just give you kind of a breakdown of how many facilities that have not yet defined allocation. You can also turn this off. So if you're like, I did define some allocation, but I want to see an overall review of all of my facility data without the production allocation taken into account, you can do so by checking that box. So just to kind of show you what that looks like, right now, I'm looking at my environmental baseline data. Here, let's actually go ahead and go to decarbonization because I think that'll be a little bit more of a meaningful change. So here, I can see okay. Eighty three percent defined. My let's go ahead and look at a total value because often the intensity values don't change quite as dramatically. So let's go ahead and look at our total emissions. So right now, this is for the facility set that I have said, you know, what my proportional values are for. So it's two point three billion kilograms CO two equivalent. If I then say, okay. Don't take that into account. I want to see overall not proportional. I can check that box. And just give it a moment. And now it's four point four billion. So whether you're looking at an overall review for a certain reporting standard or regulation or if you would like to look at a more proportional view, you can allocate that information and then affect the data accordingly. So just depending on what you want to see. You can also affect that outlier data. So if you would like to include the outliers for that holistic overview, you may. And this is also where you can download those outliers. And those are going to be things that are, you know, rather exceptional compared to your dataset, things like that. But, again, you can access the methodology here. The question that I saw that was related to allocation just since we were talking about that just now is, as a brand, what is the best and most accurate date parameter to use for defining production allocations to best match each FEM cadence? For example, I have a purchase order created date, purchase order ship date, or purchase order delivery date. That's a really great question. So I would say anything that the facility so the facility is reporting in the Higg FEM their total like like, production for the year. So it's not going to be a perfect science, right, necessarily. But if you're looking at what's their total production volume for the year, When you're looking at your purchase orders, I would say your created date is likely when it's submitted, and then the actual production occurs between the created date and the ship date. In my opinion, I would say the ship date is likely the most accurate because that is when the production has definitely been completed. And then you're not, you know, dependent on different delays that might occur for delivery. You can always, though, play around with that if you want to see how that affects things. But I would just say whichever option you choose, just be consistent in choosing that each time for your analysis so that you're not comparing, you know, one dataset to another that's not quite the same filter or quite the same lens. But I would say probably the ship date because created date, you know, you don't know necessarily when that actual production then occurred, but the ship date's likely the closest to when that was actually completed. So I would say that's probably your best bet. But, again, just be consistent with whichever you choose. Alright. So we've talked a little bit about production allocation. Just to give an overview of Insights Hub generally, I'm going to go ahead and close that because we've shown how you can access that again. So on the left hand side, this is where you can choose different sections of your data. So environmental baselines, decarbonization, waste reduction in circularity, and water use reduction is based on Higg FEM data. So whether or not you're aggregating data or an individual facility, this is all going to show different key performance indicators based on that data. Environmental baselines is going to be different data, and let me go back to twenty twenty four. Your data based on different section scores within the Higg FEM. So for example and I think it's just reloading. Sorry. There we go. So here, we have my total FEM scores. Within each card, you can download this. So if you would like to download this as an image to share within a presentation, for example, that is available. Within each of these cards, you can click on the metric to see performance over time. This, I have completely unfiltered, and I do have it based on production allocation. Or, actually, no. I just have it completely unfiltered. So here I can see year over year performance and how it's tracking against the benchmark. The dotted line is the benchmark. If you hover over each of these sections, it will give you the actual value. So this is how you can see how things change over time. Because this is a staging example, I'm seeing an account that actually has most of the data. So let me actually pop over to a different account because this will be actually a little bit more reasonable of an example. Alright. So here we can see how my dataset is performing in the red compared to the overall benchmark for this dataset. So in staging, that's going to be all of our fake facilities. But in real life, in the production environment, that's going to be everybody that's submitted these different assessments. I'll show you how this then looks once we apply filters as well. Then on the right hand side, this is where you can see how your facilities or your individual facility compares within the year against the benchmark as well. So these bench these box plots show you different quartiles. So the lines at the top and bottom are going to be the maximum and minimum. And then these kind of centralized sections are kind of where most of your facility data is clustered. When you're looking at an individual facility, this is going to just show a line. So this will just show you how you exactly fall within this benchmark. And I'll show you what that looks like in a moment as well. Again, you can download these charts, and you can also download the CSV data if you would like to download that raw data into, you know, Excel or anything like that so that you can manipulate it further as well. So for environmental baseline, again, that's going to be different section scores. For your initiatives, it's going to be kind of really high level information about the assessments. So for example, if you are collating data across multiple facilities, this is going to be different things like how many are verified, how many have achieved a certain level within a certain section or all sections, etcetera. To learn more about each initiative, you can click on that card to see a list. For my intents and purposes today, these are not very helpful. So, normally, what you would see is, like, a name of your facility, but, again, this is staging data. So for each section, the initiatives are going to be slightly different just depending on what category you're looking at. But for the environmental baseline, you know, it's looking at level achievement and things like that. As you scroll down, you can also download this table. So if you would like to download this to analyze further and see kind of the full dataset and how each individual facility answered, you can do so there. And then there's also capacity building resources below. So this is going to be more information about this particular question as well as a different guidance that you as a brand or as a facility can learn more to improve performance. So it's a really high level overview of kind of the different sections. So let's go ahead and dig into a more concrete example. So I'm going to go to decarbonization, and let me go ahead and dismiss that. And let's say that I am looking to set goals for either my individual facility or a group of facilities for decarbonizing my supply chain. So if I go to decarbonization, I'm looking at my twenty twenty four data. One facility is excluded, so I'm going to be you know, I'm okay with that. That's not a lot, so it doesn't make a massive difference. Maybe I want to look at that later to see, you know, what facility is kind of jumping out as an outlier. In this particular account, I don't have any of that volume allocated, so I'm happy to jump over to the other account to kind of show you the difference and how the allocation affects things. But just know that, you know, if you don't have it allocated, it's totally fine. You still get valuable data out of this view. So here on the left hand side, you can filter. So let's say that I would like to see what my data for decarbonization looks like in a specific country. So, for example, let's see. My carbon intensity overall right now is point one zero eight kilograms CO two equivalent per megajoule. Let's go ahead and filter to my facilities in China. So that's going to filter all of that data down to facilities in China, both for your facility dataset as well as the benchmark. So now my carbon intensity in my Chinese facilities is point one four four. So it's gone up a bit. So maybe this is where I would like to concentrate. I can click into this value to then see more information. Here, I can see that my performance was or my intensity was going up, and then I was starting to improve. And then I've sort of deviated from my benchmark. So I was kind of following along. So maybe this is where I would like to concentrate my efforts is reducing my overall carbon intensity in this subset of my facilities. I can see that most of these facilities are hanging out in this upper end of the intensity range. So that tells me, you know, this might be a good subset of facilities to concentrate my efforts on. Hopefully, is giving you some ideas of how you can use these filters as well. I'm going to go ahead and filter down to a specific facility so that you can get a better understanding of what it looks like when you're looking at an individual facility. So let's see. I actually should look at sorry. These are all named kind of silly, so I need to grab these. Okay. So let's look at a specific facility's data. And this is exactly what it will look like if you're an individual facility only looking at your own data as well. So I don't have it filtered by country anymore, but here I can see my carbon intensity is point one eight two. I can see that I'm improving from my own performance from last year, but I'm deviating from the benchmark quite a bit. So let's take a look at that. So I'm in the upper quartile almost, you know, towards the max end of carbon intensity. So, you know, that's a good place to start. Carbon intensity is going to be, you know, based on production volume, so it's a little bit easier to see changes instead of, like, an overall emissions because your overall emissions, you know, may still go up because you're increasing your business potentially. So maybe this is a metric that you would like to look at. If I take a step back, though, I can look at my overall performance. Each of these metrics is defined in the getting started guide and the different guidance. So I won't be able to get into every single metric, but I recommend starting with a few that are either underperforming or where you can easily see kind of where your next steps are. So if we continue in a decarbonization example, I might want to look at carbon intensity. Then we have a breakdown of different types of carbon intensity. So these are thermal sources and then electricity sources. So here, I can see that versus the benchmark, I'm a little bit more carbon intense from electricity sources there. So it's just something to think about. I can also see the thermal percentage or percentage of energy sources that are thermal sources. And then as it scrolls down, you can see more information kind of broken down in different ways. One thing I want to mention is if you ever see something like this where it just has a dash, that just means that this particular card or KPI is not applicable to either your specific facility or if you have filtered to the specific subset of facilities that you're looking at. So for example, in my case, my facility that I'm looking at measures production in kilograms, it's not going to have a per piece per pair production intensity value. You can also see total emissions. So that's also a good place to start if you would like to just reduce overall emissions generally. I can click in to see how this individual facility is comparing versus itself as well as overall data within this dataset. And this facility hasn't submitted data super far back, so it just starts with twenty twenty three. And here, I'm at the lower end, so I'm actually not doing too too poorly there when it comes to total emissions. Obviously, again, this is not real data, but hopefully, this gives you an idea of how you can look at these charts and interpret them to understand better. Now that I have filtered this to a specific facility, let me actually I don't know what country this is in. So this is a facility that's in India. And so I've applied the country filter, and here we can see how the benchmark has changed. So, again, right now, we're seeing that the percent versus the benchmark is plus sixty nine percent, which for carbon intensity, you know, the less intense, the better. So since it's a plus value, that's a bad thing. That's why it's kind of red coated. So if we remove that filter then, we can see how that then changes. And so now it's plus eighty nine percent point four. So you can kind of see how those things are different depending on what you're looking at. And, you know, if we go back and it might not have been yeah. So it's sixty nine percent. So when I compare my facility to other facilities in my specific country, my performance isn't quite as high or as poor as it is compared to overall facilities across the entire globe that has submitted the data. So here, we can see, you know, I'm still kind of in the upper end, but my trajectory is still going down. And in my region, it's kind of flattened out. So maybe I can make efforts to kind of meet where those benchmarks are and target this kind of median value. That also goes for different things like let's see. In this case, I'm not using any on-site renewables, but you can kind of see within your region what is possible. So in some cases, you know, it's gotten as high as, like, two point four percent. So it's not a a super high value, but that can give you an idea of, like, okay. So others have done it in my area, so it's at least possible. And so, hopefully, this is giving you an idea of how you can start to dig into this. Also, on the right hand side are your different initiatives. So, again, this initiative drop down is available, but it is based on which area you're concentrating on. So I'm still in decarbonization. I'm also still filtered to a specific facility. The initiatives don't really get filtered by the filter here because this is based on at least for an individual facility because it doesn't have the benchmarking that the KPIs do. But the initiatives here, again, top initiatives are things that drive performance in this specific category. For decarbonization, you know, industry program participation is something that is super helpful. If you're participating in a program, you're going to have targets. You're going to have different kind of community aspects as a part of that program, etcetera. And it shows that you're, you know, trying and you're implementing these things internally. Tracking your energy at a at a baseline is super helpful. If you're not tracking it, you don't, you know, know what your baseline is, and so therefore, you cannot set effective targets. Here, I can see that this particular facility is not currently purchasing any energy attributes certificates, also known as EACs or RECs, or any carbon offsets. So this might be an option if I would like to offset some of my emissions or energy use. So when you're looking at an individual facility, this is going to show you either one hundred percent. If you said yes to, you know, the question that's kind of displayed here, you are a part of an industry program that addresses emissions. Or if you said, nope. I don't currently do this. It will show zero percent. If I take a step back and unfilter to show an aggregate view, the way that this displays is it will show you all of your facilities and the percentage. So here, I can see when I take a step back and look at all the facilities that this particular account is tracking, I can see that sixty three percent of my facilities are a part of an industry program that addresses emissions. Maybe that's where I would like to close the gap and make this a hundred percent. Or maybe I scroll down and I see, okay. There's a huge gap in the amount of facilities that have had an energy audit within the last five years. Energy audits are super helpful to identify where there are opportunities for reduction. So that might be something to concentrate on because I can see ninety five percent of my facilities have not had that done. I can click into that initiative then to see my list of facilities. I can scroll and see in this case, it's just a couple questions, but I can see the intensity, and then I can see whether or not they've answered yes or no to having an energy audit. You can go through different pages or expand how many you're seeing here, or you can just download this data to a CSV so that you can then manipulate it further. There's also capacity building resources to learn more about energy audits and how they can be performed and how to address that. Alright. Hopefully, that's giving you an idea of how insights hub works. I'm not seeing new questions, but feel free to submit questions also. In addition to these KPIs sections, below that is the hotspot section. This is where you can see kind of a breakdown of different information. So for example, if you would like to concentrate on emissions, you know, reduce overall emissions in total, this is where you can see a breakdown of where your emissions are coming from. So for example, here, I can see because this is staging, it displays kind of weirdly, but this is my purchase of electricity information or data. So most of it is coming from a purchase electricity, but a good portion is coming from natural gas as well as purchase steam. If I then go into my larger account just to kind of give you more context, because it'll have a slightly different kind of view because it has more facilities taken into account. Here, I can see, you know, most of his purchased electricity. So ways that you can offset that is just reducing overall use and energy efficiency, increasing energy efficiency, also switching to, you know, on-site renewables, things like that. But I can kind of see, okay, there's purchased steamed, purchased natural gas. Maybe I want to look at my natural gas because that does have a higher emissions value generally than, you know, renewable energy sources. So you can start to break this down further, and then you can also use your filters to then look at how different regions or different types of facilities have these different hotspots and different mixes. There's different mixes like emissions, energy, renewable energy, so on and so forth. There's also different breakdowns if you are aggregating data based on which section you're looking at. So, again, I'm looking at decarbonization, so this will show me different hotspots for that purpose. Here, I can see that the bulk of my facilities in this dataset are in China, but I do have a good chunk in India as well as in Vietnam. And then I can see how the intensity in each region is kind of comparing against each other. So you can hover over each of these to see the different values. And then that way, you know, maybe you want to set different targets for different regions based on how many facilities you have in that region. There's also different ways that you can kind of slice and dice your data by these different facility types, different tags, industry sector, so on and so forth. And then there's also just kind of these tables. So if you do want to see a high level overview of just some different values related to the specific data that you're looking at, you can do so here, and then you can also download that to CSV. So if I go to water use reduction, this is going to give me key performance indicators around water. So for example, if you would like to look at your facilities that are specifically rated as high or very high for overall water risk, you can click into this. This will give you the data, and then you can download this data to a CSV. And then you can use that CSV to then use collaboration suite to engage with those folks. So for example, if you want to see the folks that have a high water risk, you can then filter that data to yes and then use that then to upload into collaboration suite to create a different segment that you can then have a different campaign with them. And, again, there's different capacity building resources below. And for individual facilities, this is also helpful, especially in a regional context. So for example, you know, maybe in your region, water is a little bit more of a big deal compared to other areas. And so, for example, maybe I want to look at things that are a little bit more relevant and, you know, what's the different benchmarks for a more water sensitive area. So here, I can see that only seventeen percent are not rated as high or very high for overall water risk. So that means the bulk of my Egyptian facilities are rated as high. So here we can see that they have a lot of recycled water use. You know, maybe we want to we want to reduce the overall withdrawal water percentage, so on and so forth. So this is also super helpful to look at things in a regional context in that way, especially when it comes to different things that are particularly sensitive to that region. It's not just limited to top initiatives, though. So for example, if you really want to focus on improvement planning and different things that can really drive kind of next steps and where a facility either individually or as a group can go. You can also go to, like, improvement or remediation planning. This will give you a breakdown of the different questions within the FEM around that type of topic. So for example, have they implemented a water balance analysis? Do they have baselines and targets? You know, are they setting different targets for these different types of water use, so on and so forth? So as you start to narrow in your scope and narrow in on what you want to focus on, then you can dig into these different initiative sections to learn more and to really guide that next step. Also, since we do have folks that might be both collecting their own aggregating data from other facilities. Within the section where it says data ownership, this is where you can filter to your modules so that have been submitted under this specific account versus modules that are shared with you. So if you are, you know, collating data on kind of both sides, this is super helpful so that you can look at your own performance. In this case, there's no specific modules on this account. But you can also then compare that, you know, look at your own performance to get, like, your scope one and scope two values, and then look at, you know, modules shared with you to get a sense of your scope three values. Also, with the addition of the allocation production addition, you can also filter by how much allocation you have at a specific group of facilities. So if you really, you know, know that you really only have leverage to make changes at facilities where you have more than seventy five percent allocation of their production, you can filter by that to then look at those values. And then that will also give you a sense of, like, okay. So these folks, I have a lot of production at. It's forty one facilities that can be my group of facilities that I want to concentrate on, and then you can see the values for them to then set appropriate guidelines and and targets. Alright. I talked a lot. I didn't see any new questions come through. Hopefully, this was helpful. But thank you again for your time and attention today. You'll see an email from me with the reporting as well as helpful, resources and links in a day or two. And with that, I hope you have a wonderful day, and I'll catch you on the next one. Alright. Thanks so much. Goodbye.