Purchases v2 (BETA)

Help guide: Purchased goods and services v2 (BETA)

Updated: June 2024

Table of Contents

Help guide: Purchased goods and services v2. 1

Purchased goods and services (PG&S). 1

PG&S Insights. 2

Supplier module. 3

Learn more: Actionable steps (PG&S Insights) 4

Section Overview: Engage for Reduction.. 4

Section Overview: Engage for Reduction.. 7

Methodology. 9

 

 

Purchased goods and services (PG&S)

• First, you can find our new feature under Measure > Purchases.
• Then, go to the bulk upload screen. You’ll need to prepare your purchases data – this may come from your accounting or ERP system, or you can use the sample file we provide. For the purposes of the beta, please use purchases data from your reporting year 2023.
  • You will need to provide the transaction date, vendor, internal accounting category, spend amount, and spend currency.
  • Optionally, you can add transaction-level emission overrides.
  • Review your upload and if everything looks good, proceed to complete.
  • At any point, you can go into your upload history and tag entry groups you’ve already created in the platform, like business units, to different files. This way, you’ll be able to segment by those groups in your emissions ledger.
• When your upload finishes, you’ll be brought over to the mapping screens.
  • First, assess if your transaction data has different names for the same supplier. On the identifiers tab, you can merge multiple identifiers to a single supplier.
  • Then, under the suppliers tab, you’ll see we have auto-generated suggested matches to our supplier database. Review and confirm where the suggestions are correct, and clear them where they are not. If they neither confirm nor clear, the mappings are not confirmed and will not be used.
  • You can also override any suggestion and select your own supplier match.
  • You do not need to map every supplier – only those that you confirm are a match for the ones in our database.
  • Lastly, under Commodities, you’ll map your internal accounting categories to our standard list of commodities. We’ll use these commodity mappings to calculate spend-based emissions estimates in the absence of supplier-specific data.
    • Again, you can confirm, clear, or choose your own match. At any point, if you want to revisit our suggestions, scroll to the top of the commodities dropdown.
    • If under goods, you will also need to select whether the type is general/unspecified (the default), capital goods, or production-related. This will affect the emission factor used and the allocation to GHGP category.
    • If you’ve selected a category that does not belong in Purchased goods and services, you will see a warning message and you can exclude that category by toggling the exclude flag on.
  • Once you’ve finished mapping, click SAVE. You will be prompted to select which reporting years you want to recalculate for, using these new mappings. 2023 is selected by default, but you can select additional if needed.
• If you already have supplier-specific data, go to Overrides, select the applicable date range, vendor, and category, and override the emissions value. Indicate whether the emissions were provided to you by revenue (spend over total revenue) or physical allocation (items bought over items produced by the supplier). Click Apply override.
  • If there are any conflicts with existing overrides, you will see an error message.
  • Otherwise, your override has been saved and applied automatically, and will be visible in the ledger in a few minutes.
  • You can also view your override history and delete any overrides that are no longer applicable.
  • The override amount will take replace any spend-based estimate that would have been calculated for this supplier/category combination.
• Under the Emissions ledger, you’ll see your high level spend, emissions, emissions intensity, and data source breakdown for the last two years. You’ll also be able to drilldown into specific suppliers and commodities.
  • Where you’ve added a supplier database match, we leverage publicly available sources of reported emissions data to automatically calculate emissions allocated to you, based on your spend with them, and their total revenue.
  • This gives you supplier-specific data without having to survey each and every one of them, increasing the accuracy of your inventory and reducing time spent.
• Click in to view more details on spend and emissions amounts, along with the emissions source.

PG&S Insights 

• Then, under Insights, identify top suppliers by total emissions, emissions intensity, and spend. Explore by supplier or commodity and get guidance on the next step to take with each.
• You can then begin a targeted process of engaging with them and requesting essential data on emissions, reduction targets, and ESG risk.

 

Introduction to Insights Bubble Chart 

This bubble chart is a visual representation of your supply chain data and emissions. This allows you to categorize suppliers and commodities and determine the best next steps for your sustainability program. This categorization is based on the availability of primary data and each commodities relative mitigation potential. This structured approach helps businesses focus their efforts more effectively on high-impact areas. 

 

Understanding the Categories 

1. Data Availability

Suppliers and commodities are first sorted into different sections depending on the amount and quality of primary data available. Primary data refers to direct data collected from activities within the company's control or supply chain, providing a granular insight into emission sources. This categorization allows companies to identify which areas have enough data coverage and which areas may need further data collection efforts. 

 

2. Mitigation Potential

Mitigation potential is evaluated based on the decarbonization opportunities within a particular industry or commodity. This was done by assessing how feasible it is to implement changes that reduce emissions. Industries with high mitigation potential are typically those that have existing technologies or practices that can be adopted to achieve emission reductions. 

 

Recommended Actions for Scope 3 Inventory Improvement 

For each section identified, our platform recommends specific actions that businesses can take to improve their Scope 3 PG&S inventory management. These actions are tailored based on the data availability and mitigation potential of each section. Users can then prioritize their supply chain efforts more effectively, focusing on areas where the impact of emission reductions and engaging with suppliers can be expanded. 

 

Interactive Features 

• Click on Section Labels: Users can click on the section labels to learn more about the specific characteristics of each category, including data availability and opportunities for improvement.
• Interactive Bubbles: Within each section, interactive bubbles provide a visual representation of individual suppliers or commodities. Clicking on these bubbles will offer detailed insights, including the current status of data collection, potential opportunities for improvement and next steps with suppliers or commodities. 

 

Supplier module

• With this new release, the supplier module is completely integrated with the Purchased goods and services category.
• Add the vendors from your purchases information as suppliers in your account.
• Then click into each supplier to add descriptions, add or change identifiers and supplier database matches, and add contact and entity information.
• Then, you’ll be able to send requests directly to suppliers. Whether or not they also use our platform, they’ll be able to create a free account and fulfill your data and later, ESG assessment, requests.
• Use our platform to keep track of which suppliers you’ve engaged with and the information you’ve collected back from them.
• When a supplier completes a data request, you’ll be able to approve it, and their reported emissions will now override any prior emissions calculation.

 

 

 

Learn more: Actionable steps (PG&S Insights)

Section Overview: Engage for Reduction 

High Data Availability and High Mitigation Potential 

This section highlights commodities and suppliers that have primary emissions data and also have high mitigation potential. This combination makes them good targets for impactful sustainability initiatives and emission reductions. 

 

Understanding High Data Availability 

High data availability means that there is a good amount of accurate and reliable primary emissions data. This data typically includes detailed information their scope 1 & 2 emissions and could come from publicly available data sources (e.g. CDP) or directly submitted data in the supplier module. This level of data enables precise measurement and management of emissions, allowing for emission reduction efforts to be seen in your inventory. This is why we recommend focusing on these suppliers and commodities for  effective decarbonization strategies. 

 

High Mitigation Potential Explained 

High mitigation potential indicates that there are significant opportunities for implementing decarbonization measures within these industries or commodities. This might involve adopting new technologies, changing operational practices, or utilizing cleaner energy sources. Industries and suppliers with high mitigation potential are capable of making reductions in their emissions. 

 

Strategic Importance of Targeting These Suppliers 

Direct Impact on Scope 3 Emissions 

Focusing on suppliers with both high data availability and high mitigation potential allows businesses to directly influence and reduce their Scope 3 emissions. By working with suppliers who can decarbonize their operations, a company can achieve considerable reductions in these indirect emissions and see progress since they are providing accurate data. 

 

Benefits of Targeting High-Potential Suppliers 

• Effective Resource Allocation: By prioritizing these suppliers, companies can allocate their resources more efficiently, focusing on partnerships that promise the highest returns in terms of emission reductions.
• Enhanced Sustainability Impact: Targeting high-potential suppliers maximizes the GHG impact of sustainability efforts, contributing to decarbonization goals.
• Improved Compliance and Market Position: Engaging with high-impact suppliers can also improve regulatory compliance and enhance a company's position in increasingly regulated

 

Actionable Steps 

Companies should engage with these high-potential suppliers to explore specific decarbonization projects, set ambitious yet achievable emission reduction targets, and collaborate on achieving these goals through improvements in practices and technologies. Supporting suppliers through knowledge sharing, and joint investments can further enhance the effectiveness of these initiatives. These suppliers are also suppliers that should be engaged for setting emission reduction targets, for example a formal science-based target (SBT) through the science-based target initiative (SBTi).  

 

Section Overview: Reduce Use 

 

In this section, we focus on commodities and suppliers characterized by high primary data coverage but low mitigation potential. These are often associated with industries that are difficult to reduce emissions from (e.g. Oil & Gas). 

 

High Primary Data Coverage Explained 

High primary data coverage means that detailed and reliable data on emissions and is readily available for these commodities and suppliers. This data provides a clear picture of current practices and their GHG footprints, making it easier to identify where changes and reductions can be most effectively made. 

 

Understanding Low Mitigation Potential 

Low mitigation potential indicates that there are limited opportunities for these suppliers or commodities to significantly reduce their emissions through conventional decarbonization strategies. This might be due to technological limitations, cost constraints, or the intrinsic nature of the materials and processes used. Despite the challenge in reducing emissions, the high environmental impact of these materials makes them critical targets for alternative strategies. 

 

Direct Impact on High-Impact Materials 

Since conventional strategies for emission reduction are less viable, focusing on reducing the use of these high-impact materials becomes the best option. This can mean decreasing the quantity used, finding alternative materials, or rethinking production methods. 

 

Actionable Steps for Buyers 

Buyers are encouraged to consider strategies such as: 

• Reducing the Amount Used: Evaluate and minimize the use of these commodities or suppliers if
• Switching Materials: Explore alternatives that have a lower emission impact but fulfill the same function.
• Revamping Production Methods: Invest in research and development to modify existing production methods or develop new ones that are less reliant on emission intensive

 

Section Overview: Engage for Reduction 

In the "Engage for Reduction" section, we address commodities and suppliers for which emissions have been calculated using standard commodity emissions factors or proxy data. This method is generally less precise compared to direct emissions data from suppliers. The section highlights the importance of engaging with suppliers to improve the accuracy of emissions data and the effectiveness of emissions reduction strategies. 

 

Standard Commodity Emissions Factors 

These are generalized emissions values assigned to commodities based on industry averages or typical production processes. While useful for initial estimates, they lack the specificity and detail provided by primary data, which can lead to inaccuracies in understanding the true emissions impact of specific commodities or suppliers. 

 

Proxy Data 

Proxy data is used as a substitute for actual emissions data when direct data is unavailable. It involves estimating emissions based on similar operations or industry norms. Like standard emissions factors, proxy data serves as a rough estimate and can significantly benefit from refinement and validation through primary data collection. 

 

The Need for Engaging with Suppliers 

Engaging with suppliers to obtain more accurate and detailed emissions data is important for: 

• Improving Data Accuracy: Enhanced data accuracy leads to better understanding and management of emissions, allowing for more targeted and effective reduction strategies.
• Strengthening Supplier Relationships: Active engagement with suppliers promotes collaboration and commitment towards shared sustainability goals.
• Enhancing Emissions Management: Accurate data allows companies to make informed decisions about where to focus their reduction efforts, potentially leading to emissions and regulatory benefits.

 

Actionable Steps for Engagement 

1. Mapping to Sustain.Life Emissions Database

• Automated Data Ingestion: By mapping suppliers that have reported emissions publicly to the Life Emissions Database, companies can automatically ingest primary data into the systems. This process enhances the precision of emissions calculations and facilitates more effective management and reporting.

2. Emissions Data Request

• Direct Engagement: Companies should proactively reach out to their suppliers with requests for detailed emissions data. This can be done through our supplier module with structured data requests that encourage suppliers to measure and report their emissions accurately.
• Support and Collaboration: Offering support in the form of tools, resources, or expertise to suppliers can improve their capability to provide accurate data, creating a cooperative approach to emissions reduction.

 

 

 

 

Methodology

 

We use several approaches to calculate purchased goods and services (PGS) and capital goods emissions. We also allow users to bring emissions calculated elsewhere into our system. We use a hierarchy based on the methodology used to calculate emissions to determine which emissions calculations ultimately go into your inventory. 

 

Emissions calculation hierarchy 

 

	Source	Methodology
1	Externally calculated	Product-specific life cycle assessment
2	Supplier reported	Physical allocation
3	Supplier reported	Revenue allocation
4	Sustain.Life supplier database	Revenue allocation
5	Sustain.Life supplier proxy	Revenue allocation
6	Externally calculated	Average-data method
7	Sustain.Life commodity database	Spend-based method
8	Sustain.Life commodity proxy	Spend-based method

 

Externally calculated – Product-specific life cycle assessment 

If you have externally calculated emissions associated with your purchase transactions, for example reflecting product-specific life cycle assessments, you can enter them into the application using the override column in the purchases upload. 

 

Supplier Reported – Physical Allocation 

When you request emissions from a supplier, we send them a notification of the request. If the supplier chooses to allocate by units produced, labor hours, or some other output unit, we ask for the following information: 

1. Total units produced by the supplier 
2. Units furnished to your company 
3. Scope 1, 2 and 3 emissions of the supplier 

 

We then allocate emissions to your company by dividing the units furnished into the total number of units produced. We multiply the resulting factor by the supplier’s relevant emissions (scope 1, scope 2, and scope 3 categories 1, 4, and 5) to get your scope 3 emissions from the supplier. 

 

Supplier Reported – Revenue Allocation 

When you request emissions from a supplier, we send them a notification of the request. If the supplier chooses to allocate by revenue, we request the following information: 

1. Total revenue of your supplier 
2. Revenue from your company 
3. Scope 1, 2 and 3 emissions of the supplier 

We then allocate emissions to your company by dividing the revenue from your company into the total revenue of the supplier. We multiply the resulting factor by the supplier’s relevant emissions (scope 1, scope 2, and scope 3 categories 1, 4, and 5) to get your scope 3 emissions from the supplier. 

 

Sustain.Life Supplier Database – Revenue Allocation 

If your supplier is found in our database of suppliers, we use our emission factor for that supplier and multiply it by your spending with that supplier. Our database is compiled from publicly reported emissions and revenue data. The emission factors in our database are composed of scope 1, scope 2, and scope 3 categories 1, 4, and 5. When selected emissions factors from the database, we select the most recently reported data relative to the year you are calculating emissions for. 

 

It is common for companies in our database to only report scope 1 and scope 2 emissions. When this occurs, we model their scope 3 emissions to create an emissions factor. 

 

Sustain.Life Supplier Database – Supplier Proxy 

If you have enough data reported from suppliers (either directly or from the Sustain.Life database) within a specific commodity, we use the reported data you have received to create a proxy emissions factor. We apply that proxy factor to the remaining spend in the commodity.  

 

This is because supplier-reported data is always more accurate then using environmental-extended input output (EEIO) data for calculating emissions. When you are working in Purchases, we check to see what percentage of spend in each commodity has supplier-reported data. When that percentage exceeds a set threshold, we create an emissions factor by dividing the total reported emissions by the total spend covered by reported data. We then multiply that by the remaining spend in the commodity that does not have reported data. 

 

Externally Calculated – Average-data Method 

We do not directly support calculating emissions via the average-data method in our app because this approach is time-consuming and does not yield high quality emissions data. We do, however, support our users in bringing in data that has been calculated externally into their inventory (e.g. via a consultant).  

 

Sustain.Life Commodity Database – Spend-based Method 

After mapping your internal spend categories to our commodities, we multiply the emissions factor for that commodity by your spend to calculate emissions. We select from one of two sets of emission factors, one set with markup and one set without markup. If you indicate the product was bought at the retail level we choose the emissions factor with markup, if you select wholesale we use the emissions factor without markup. 

 

Sustain.Life Commodity Proxy – Spend-based Method 

In lieu of any better data from the one of the above sources, we apply a commodity-based proxy emission factor to your unmapped data. We develop this factor by taking your total emissions from mapped commodities and dividing into the total spend for the same commodities. We then multiply this factor by any remaining spend. 

 

Inflation 

The above revenue allocation and spend-based methods are sensitive to changes in inflation. We use government-reported annual inflation rates to convert revenue/spend values into the same year of the emissions factor we use. 

 

Limitations 

 

While the spend-based approach is effective for providing an initial estimate for emissions from purchases, because it is based on general commodity emission factors, it cannot provide supplier-specific emissions estimates. For example, switching to a supplier with lower emissions will not be reflected in a spend-based analysis since the EEIO commodity factor would remain the same.  

 

Furthermore, this approach estimates emissions based on $ spent, so only reductions in spending will show reductions in emissions. In instances where environmentally preferable products and services are more expensive than their traditional counterparts (which is common), a spend-based approach will estimate higher emissions for the environmentally preferable alternative. Lastly, because the most reliable spend-based emission factors are based on an analysis of the U.S. economy, they may provide less accurate results for spending that occurs outside of the U.S.  

 

Despite these drawbacks, spend-based analyses still provide value in instructing organizations where to start when it comes to gathering more information or implementing policies. Results from this calculator should be used as a springboard for supplier-engagement surveys to collect specific supplier emissions data. By extrapolating mapped emissions onto unmapped categories (when the used does not map 100% of their spending), we assume that emissions of unmapped categories reflect emissions of the user’s mapped categories.  

 

For this reason, we require the user to map a minimum of 75% of their spending so that such extrapolation does not have a large impact on overall emissions. However, in cases where the user does not map particularly GHG-intensive categories, it could reduce the accuracy of our emissions calculation. To avoid this, users should map 100% of their spending.