Organizational carbon inventories and product carbon footprints both calculate greenhouse gas emissions, but answer different questions. The former cares about how much emissions a company produces within a certain period; the latter cares about how much emissions a product or service produces during its life cycle.
Main differences
| Comparison Orientation | Organizational Carbon Inventory | Product Carbon Footprint |
|---|---|---|
| Inquiry object | Company, group, factory or organization | Specific product or service |
| Common periods | A reporting year | The life cycle of a product |
| Boundaries | Organizational boundaries and direct, energy and other indirect emissions | Raw materials, manufacturing, transportation, use and end-of-life treatment |
| Common standards | ISO 14064-1, GHG Protocol | ISO 14067, Product Life Cycle Approach |
| Results usage | Reduction management, disclosure, regulations, verification | Customer requirements, product design, carbon label, material comparison |
What data do the two share?
Power, fuel, steam, refrigerant, output and waste may be used simultaneously in the plant. However, the organizational chart looks at overall emissions. The product carbon footprint must be further allocated to products, and raw materials, packaging, transportation, use and end-of-life treatment information must also be added.
Under what circumstances is it appropriate to conduct an organizational inventory first?
- The company has not yet established basic energy and emission data.
- Need to respond to regulations, sustainability reports or group audits.
- We hope to first identify the main emission points and sources.
- There are many types of products, and the priority products for inventory have not yet been decided.
Organizational inventory can first establish bases, energy sources, coefficients and audit processes to provide more stable process data for product carbon footprints.
Under what circumstances is it possible to create a product carbon footprint first?
- Customers specify a product to provide a carbon footprint.
- Products are about to apply for carbon labels or enter specific markets.
- The company’s products are simple and the inspection boundaries are easy to define.
- Evaluating differences in emissions from materials or design options.
Even if the product carbon footprint is determined first, it is necessary to confirm the energy distribution and organizational information of the factory at the same time, otherwise it is easy to use rough estimates during the manufacturing stage.
Most common mistakes
Dividing the organization’s total emissions directly by the number of products is generally not a substitute for the product carbon footprint. Different products use different materials, working hours, equipment and energy, and may also have different transportation and usage scenarios.
It is recommended to use one set of data and two outputs
Enterprises can share locations, equipment, energy, emission coefficients, suppliers and supporting information, and then aggregate them differently based on organizational and product boundaries. This can reduce repeated collection and also explain how product results are returned to the overall reduction of the enterprise.
The choice of which one to do first should be based on external deadlines, data maturity and management objectives; in the long term, the two should be linked to each other rather than divided into two sets of irreparable numbers.
Before comparing, first confirm what problem the company wants to solve.
Different systems may seem to use similar terms, but in fact they may serve regulatory compliance, information disclosure, verification, transactions or internal decision-making respectively. When choosing, you should not just ask which one is easier, but first confirm the external requirements, intended users, delivery period and whether verification is needed in the future.
It is recommended to use five judgment aspects
- Applicable objects: manage organizations, products, projects, supply chains or specific markets.
- Primary purpose: Quantification, disclosure, verification, regulatory compliance, or decision-making.
- Profile Boundary: Which companies, locations, life cycle or value chain activities are covered.
- Deliverables: Reports, statements, certificates, scores, declarations, or internal analyses.
- Ongoing Accountability: Whether annual updates, revalidations, tracking targets, or evidence preservation are required.
Do not create a separate set of profiles for each requirement
Enterprises should first establish a common organization, products, suppliers, activity data, attachments and audit basis, and then establish classification and output rules according to different systems. If each project collects data independently, multiple versions will easily appear during the same period, and the organizer will not be able to explain the differences.
Which situations require simultaneous use?
When regulatory, customer and disclosure requirements each specify different bases, companies may need to do so in parallel. At this time, a comparison table should be established to describe common data, unique requirements, boundary differences, and output formats, rather than requiring each department to fill it out repeatedly.
Common selection errors
- Thinking that the content can replace each other just because the names are similar.
- Compare only the number of clauses, ignoring customer or regulatory requirements.
- Choose tools first, then look back for management purposes.
- No assessment of data maturity and maintenance costs.
- Treat passing verification as the only indicator of system completion.
Self-check before making decisions
- Which one is a clear external requirement, and which one is an enterprise’s own choice?
- Is third-party verification, evaluation or reporting by the competent authority required?
- Can existing data support the required bounds and precision?
- Can the two systems share data and processes?
- Will there still be maintenance and update resources in the next three years?
There is not necessarily just one most suitable solution. If companies can establish a common underlying data, they can combine standards and tools for different purposes without having to start from scratch every time.
When companies choose a method, it is recommended to confirm four things in order
Start by identifying external requirements. Whether clients, authorities, parent companies, investors or verification agencies specify specific standards will directly affect the methods that can be used. If there is no mandatory designation, go back and evaluate the management problem that the company really wants to solve to avoid choosing the wrong tool because of similar names.
Next, confirm the management objects and boundaries. Some approaches focus on the entire organization, while others focus on products, value chains, projects, or specific disclosure situations. Depending on the boundaries, the required data, responsible units, and results usage will all change. When comparing, “what is counted, where it is calculated, and who uses the results” should be put on the same table, rather than just comparing the number of articles.
The third is to check the maturity of the data and resources. If an enterprise has not established basic inventory and data management and directly introduces more demanding methods, it may result in a lot of estimation and rework. You can complete the common foundation first, and then gradually increase the sophistication according to market demand. If multiple frameworks have common data, a design should be adopted to collect it once and output it in multiple ways.
Finally, consider verification and future expansion. A company may only need internal management now, but may face customer audits, public disclosures or third-party assurances in the future. Keeping records of sources, versions, assumptions, and approvals from the outset is much easier than reconstructing evidence afterward.
After comparing, how to make a choice that suits you?
Businesses don’t necessarily have to choose one or the other. If the two methods serve different purposes, a common data base can be established and corresponding results can be produced separately; if the two methods are highly overlapping, a set of main governance rules should be selected to avoid departments maintaining different versions. When making decisions, the five conditions of “necessity, data availability, implementation cost, external acceptance, and future scalability” can be used to evaluate, and the reasons for the choice should be recorded.
For companies that are in contact for the first time, the most important thing is not to adopt the most frameworks immediately, but to establish clear boundaries and traceable information first. When the common foundation is stable, adding new disclosure or verification requirements is usually just an adjustment to the output method; on the other hand, if the underlying data is confusing, even the most complete method will not be able to produce credible results.