Regulations like the EU’s Corporate Sustainability Reporting Directive (CSRD) and the International Sustainability Standards Board (ISSB) from the International Financial Reporting Standards (IFRS) Foundation will make sustainability reporting mandatory and increase the focus on companies’ carbon emission disclosures. Understanding, measuring, managing and reporting carbon emissions, especially those related to the supply chain (Scope 3), can significantly decrease a company’s risk and be a source of competitive advantage.
The previous articles highlighted the complexity of tracking, measuring, planning and reporting Scope 3 emissions, and the need for technology enablers. The market offers various technological solutions. Each of them comes with a different set of functionalities and limitations that are not always clear to the decision-makers in organisations. In general, technology enablers should meet customer and business requirements while being scalable and accomplishing the organisation’s vision. The previous article introduced technologies on the basis of three different categories:
In this article we are going to focus on Footprint Tech: owning quality input data, orchestrating different workflows and possessing a traceable ledger (output) and customer interface for ease of usability.
The Carbon or CO2 footprint is often understood as the amount of carbon (dioxide) generated throughout the supply chain. However, the visibility of raw materials’ journey is also an integral element in a firm’s footprint. To establish a comprehensive view across complex supply chains, Footprint Tech plays an essential role in the first step in evaluating the current sustainability position of an organisation: enabling data collection. Gaining access to sustainability-relevant datasets in the right formats and frequency paves the way for Model Tech solutions, like predictions and models, and Governance Tech solutions that influence an organisation’s core operating model as well as improving its reporting capabilities – details of which will be provided in following articles.
Footprint Tech solutions have gained popularity over time due to increasing regulatory requirements and end-consumer pressure. Organisations vary in their pace of adoption of this technology, depending on their supply chain maturity and priorities.
In general, organisations fall into three categories in this area:
In our review of potential solutions and software providers, we focus on technologies enabling “Seekers” and “Innovators”. These solutions are a few examples of the vast technology landscape and are neither exhaustive nor a recommendation from our side.
In this article we have touched upon footprint technologies. In summary, these technologies help customers isolate data to validate their supply chains and suppliers, enabling greater supply chain transparency, traceability, and visibility across their supplier networks.
Scope 3 emissions are often beyond organisations’ direct control. Footprint technologies can become key differentiators through collecting data, validating supply chain activity and strengthening supplier and partner relationships. Access to reliable data across the full supply chain, including Tier N suppliers, enables leaders to take action-based decisions.
Organizations often need advisory support to implement and interpret data analysis. Before deciding on a footprint technology solution, companies first need to align their strategy and requirements to outline what functionality they require to measure and assess their KPIs. Then one can assess the technology landscape to identify a solution that will live up to the company’s strategic and compliance requirements.
As already mentioned in this series, it is important to emphasise that footprint technology alone cannot produce optimal results for sustainable improvement. Further integration with two other important pillars – Model Tech and Governance Tech – is required. The next article will therefore focus on Model Tech solutions that manage both the infrastructure for ESG-related model-building and the data required to validate the output of these models.
This article has been authored by Hana Shiraz, Dennis Schulz, Meg Alderman and Marco Cioffi.