Client
Expertise
Assurance and labelling
Impact
Enabling robust and credible data sharing to decarbonise our food system
CHALLENGE
How can carbon footprinting software platforms unlock credible reporting in the food sector?
Our food system is responsible for a third of global GHG emissions.1 These in turn fuel climate extremes that disrupt supply chains, push up food prices and worsen hunger in many countries. To add complexity, the food sector is a highly fragmented ecosystem where most emissions sit at farm level and most capital with brands. These interconnected barriers impede decarbonisation progress at the pace and scale required.
Not only is collaboration critical, but stakeholders need a clear and accurate understanding of their emissions. However, calculating Product Carbon Footprints (PCF) is often a complex, lengthy and costly process. Methodologies and data inputs vary, and supplier-specific data is difficult to track down, resulting in inconsistent and generalised PCFs that hinder effective reporting and reduction of Scope 3 emissions.
HowGood set out to tackle this thorny challenge by automating PCF at scale with its proprietary software. With a client portfolio of influencing companies like Ahold Delhaize, Nestlé and Danone, working across millions of products, HowGood’s ambition was to become the leading carbon platform for food and drink, ramping up the sector’s decarbonisation efforts.
To achieve this, the company had to ensure that its customers could trust the quality of the PCFs it generated. As a result, HowGood turned to the Carbon Trust to independently assure its footprinting model.
SOLUTION
Strengthening credibility through model assurance
As an expert in carbon accounting methodology, the Carbon Trust was well placed to provide the assurance HowGood needed. Our track record includes co authoring and contributing to the development of international standards like PAS 2050, ISO 14067 and the GHG Protocol Scope 3 guidance.
The Carbon Trust model assurance is uniquely ambitious, as it not only guarantees alignment with these standards but looks at extra criteria from model governance to data quality.
To assure HowGood’s footprinting model, we:
Verified that the software’s underlying methodology, data inputs and calculation logic were robust, transparent and aligned with internationally recognised standards, including the GHG Protocol, PAS 2050 and ISO 14067.
To do this, we conducted extensive model testing to ensure that the estimation and outputs are behaving in the intended way. That included the allocation of land use change, recycled materials and co-products.
Evaluated the model governance, looking at how the software is managed in practice and how often it is reviewed.
These criteria are not included in the main standards but are critical to ensure the PCFs generated by the software are fully consistent.
We also assessed the training provided by HowGood, enabling users to correctly enter data into the model and interpret its outputs.
Issued assurance documents, including a Customer Certificate, that HowGood can send to its customers to prove that their PCFs have been calculated within an assured model.
IMPACT
PCFs rooted in transparency, consistency and trust
This assurance provided HowGood’s customers with credible third-party validation, building an extra layer of confidence in its model and enabling the company to achieve its potential to streamline carbon footprinting and scale up collaboration across the food sector.
Thanks to this extra trust, HowGood’s customers can:
Share PCFs with value chain partners more reliably, laying the foundations for better informed conversations and decisions.
Get the opportunity to assure and label their PCFs faster and more cost efficiently, should they wish to obtain that additional stamp of approval.
Make more credible sustainability claims, mitigating the risks of greenwashing.
Collaborating with the Carbon Trust to assure our footprinting model added a crucial layer of trust for our customers. We can now demonstrate that their product carbon footprints are calculated in line with best practice, ensuring accuracy and transparency.
