Why measure one's carbon footprint?
Measuring the carbon footprint has many benefits for the company and is becoming essential for ensuring healthy and ambitious growth.
Regulatory compliance.
Without going into the details of all regulations by country, an increasing number of countries have put in place a number of regulations related to CO2 reporting. The specifics are generally related to the size of the company in terms of number of employees, its revenue, its type of activity, and whether or not it is present on financial markets. In France, private legal entities with more than 500 employees in metropolitan France and 250 employees in overseas regions and departments must carry out a greenhouse gas emissions inventory (called BEGES in French).
Environmental commitment.
At the customer or employer brand level, having an ambitious climate strategy helps to enhance the brand and align it with the expectations of customers and employees. These expectations are becoming increasingly important and complying with them is no longer an option today.
Cost reduction.
In general, reducing CO2 emissions has a positive impact on costs for the company because it allows for the use of several levers such as reducing intermediaries, reducing distances, operational efficiency, and energy efficiency."
How to calculate greenhouse gas emissions?
Calculation methodology and standards.
The CO2 emissions we emit are expressed, as previously explained, in CO2 equivalent. The formula for measuring emissions is as follows:
CO2eq = activity data x emission factor (EF).
As for activity data, it is expressed in units such as Kwh (e.g. energy consumption), distance (e.g. miles traveled), liters (e.g. water), weight (e.g. weight of a product), or units (e.g. 1 email).
Emission factors or EFs give the amount of CO2 emitted for each unit consumed. They are therefore the basis for calculating CO2eq to account for our consumed CO2 emissions.
We must now choose which CO2 emissions we want to account for.
Carbon impact measurement scopes.
To identify their impact on the climate, companies and organizations must quantify their greenhouse gas emissions (GHGs). While the accounting of direct emissions (scopes 1 and 2) is mandatory for some companies and organizations in France, the accounting of indirect emissions (scope 3) is simply recommended by law. "
Since July 2022, a new decree will require French companies that were previously subject to the completion of a BEGES scopes 1 and 2 to take into account scope 3 starting in 2023. This is a significant and necessary change when we consider that the majority of emissions often depend on scope 3.
Emissions are therefore categorized into three categories called scopes 1, 2, 3. Based on an international methodology defined by the GHG Protocol, this categorization allows for the separation of direct GHG emissions, indirect emissions related to energy, and other indirect emissions.
The formula is simple: Activity data x Emission factor = CO2eq
In practice, scope 3 is often rushed (monetary and accounting approach) because it is more complex to measure, or even forgotten because it is generally not taken into account by companies. However, it represents a large part of the company's activities and, on average, 75% of its emissions.
This part is therefore complex and may be time-consuming because it requires completeness:
Precise and reliable activity data such as miles traveled, energy consumption, volume of purchase transactions, etc.
A database of emission factors that will allow mapping with activity data. The emission factor reference must also be up to date with the latest modifications and standards.
Scope 3 is therefore the most complex exercise because it requires having all the necessary activity data, a complete base of emission factors, and data sharing with partners (suppliers, investments).
Limitations of current approaches to measuring carbon impact without automation.
The "one shot audit" approach.
Through this approach, reporting is generally annual. It is a good first exercise to implement a carbon impact measurement approach.
However, this approach has its limitations:
It does not allow for fine and continuous control of CO2 emissions
Quick evaluation of reduction actions
Less complete precision and data entry error
Partial analysis
The traditional platform (top-down) and carbon data platform (bottom-up) approaches.
The traditional platform approach involves organizing data collection to meet a specific case. It allows for continuous measurement of emissions but has certain limitations:
Calculations are carried out on aggregate or average data
Limited analytical depth and granularity as optimized for a single case
Long technical integration
Standard not in line with a modern stack data approach
This approach is similar to the ETL (Extract, Transform & Load) logic but applied to CO2.
The carbon data platform approach.
This approach allows for access to all data sources with the finest level of granularity, enriching them according to the activity of a business and using these data sources to address multiple use cases. There are many technical advantages:
This type of platform fits perfectly into a modern stack ecosystem
Complete depth and granularity of data
No limitation on use cases
Ability to activate data within third-party systems (integration into invoices or products in particular)
This approach is more in line with an ETL logic.
Therefore, the modern data stack appears as an essential lever in the management and automation of scope 3.
What is a Modern Data Stack?
A Modern Data Stack is a data architecture deployed in the cloud or through SaaS solutions composed of service blocks that respond to each step of data processing in a company. The data flows are fully automated and stored in a cloud-based data warehouse. Generally, the blocks are as follows:
Data ingestion for data import
Data storage for data storage
Data transformation for necessary modifications
Data visualization
Data activation
This infrastructure reflects advanced data maturity that enables value to be generated from data, particularly advanced analytics, the creation of AI/ML models, activation in services and monetization in order to maximize business development.
This approach is infinitely scalable and meets a number of business needs. For teams implementing this type of logic, it is possible to add or change services according to needs and the maturity of the organization.
The Modern Data Stack approach also allows for the industrial and organized standardization of all data processing steps. Data access is self-service and the data structure is covered by a semantic layer that allows for quick understanding of the data.
This technological approach eliminates silos and has an industrial organization of data in order to multiply the potential of "possible use cases" within an organization. This is how Modern Data Stack users operate. Analysis initiatives are centralized and rely on the same technologies, tools and data.
Benefits and functions of a "carbon data platform" within the modern data stack
Bringing together domain expertise to validate the mapping of data (factors and activity data).
In the context of deploying an impact measurement project, one of the main challenges is to centralize the structure of calculations, the domain expertise of data/indicator sources and their technical access (API, datalake, datawarehouse, etc...). These various challenges are often isolated, which adds a level of complexity in the deployment of an automation project.
The diagram above concretely summarizes the different links between the various domains at different stages of carbon impact measurement.
The climate expert can configure a CO2 impact and the complete details of its calculations through the platform, according to calculation standards and specificities.
The tech/data expert focuses solely on processing information and not on calculation, sending the necessary information for calculation and retrieving the result to meet a need (e.g. BI Dashboard).
The business user will use the result for their needs and advise the tech/data expert on the completeness, quality and compliance of the data.
A carbon data platform, such as Kabaun, therefore allows for the centralization of information, traceability and the implementation of a collaboration process so that each expertise can contribute.
Organizing metadata according to desired organization and analytical completeness.
Each organization has its specificities. A carbon data platform allows for enriching and allocating data by defining analytical perimeters and tags that are tailored to the organization, activity, business units, various sites, or even at the transaction level in order to have the desired level of analysis and adapt it to the organization.
Maintenance and management of the company's emission factor database.
The internal organization's emission factor database is the source of data for CO2 calculation. Having a carbon data platform has several advantages.
Semantic structuring of the factor database for quick access through tags and metadata to facilitate exploration and search for factors.
Traceability of factor calculation details to preserve the decomposition of calculations and facilitate their maintenance and updates.
Integration, standardization, and updates of standard databases used by the company such as Base Empreinte®, EPA, Defra, or ecoinvent.
Creation of specific factors from existing factors.
How to integrate automated carbon impact measurement using modern data stack and what are the prerequisites?Maintenance et gestion de la base des facteurs d’émission de l’entreprise
Modern data stack and carbon data platform architecture
Carbon data platform within a modern data stack.
An API first carbon data platform greatly facilitates the automation of analytical processes and particularly allows for integration within many modern data stack technologies.
Principle of connection within a carbon data platform.
From a functional point of view, the carbon data platform is complementary and allows for the integration of new business services dedicated to measuring greenhouse gas emissions
To go further: API-first carbon data platform
We previously mentioned setting up configurations within the platform to automate measurement. With the API-first model, it is also possible to automate:
the generation of calculation configurations;
the creation of the semantic layer, tags, and data structure;
the creation of various reports
Conclusion of the benefits of integrating a carbon data platform into the modern data stack
The modern data stack is an essential means of facilitating and simplifying carbon impact measurement from scope 3 within a company. The approach meets the needs of the various domains and facilitates integration for data teams.
This approach has the following benefits:
Continuous control
Precision and completeness of data
Traceability of calculations
Automation of data collection
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