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What is Automated Modeling?
Automated Modeling is CarbonCloud’s climate footprint calculation engine for large food portfolios. Automated Modeling automatically maps out the supply chain and calculates the climate footprint of thousands of products in days, with minimal input from you.
Is the Automated Modeling engine credible?
CarbonCloud is a combination of a climate calculator (LCA tool), a supply chain management system, and a database. Every product assessed and published on the platform is available on the platform as an ingredient for other production processes. Everything with market-leading consistency and detail.
At the foundation is the agricultural engine (based on 2019 IPCC guidelines) that calculates the climate performance for agricultural products at farm gate. It comes pre-populated with production system data for close to every commercially grown crop from every country in the world where it is grown. They are all consistently calculated based on the best available data for yields, fertilization, soil types, climate zones, etc.
On top of this, there are thousands of modules for refinement processes and semi-refined products, fuel types, country-specific electricity, and a vast dataset of benchmark products at store shelf.
The data counts in the tens of thousands and is rapidly growing, as CarbonCloud continuously develop the dataset and increase its resolution, and via increasing numbers of farmers, B2B producers and B2c producers joining the platform. All this data is available for users of the platform and a large share of the data is openly available at ClimateHub.
Each footprint is based on input data from high-quality sources. The data available on the CarbonCloud platform mainly derives from three origins:
- Statistics and data from national and international agencies for example the Food and Agriculture Organization of United Nations or the National Inventory of Submissions of the UNFCCC.
- Relevant scientific literature: if the process ingredients are modeled, we utilize extensive scientific literature which our in-house science team reviews and adapts accordingly.
- User input: the platform learns as users feed production system data into it.
Our calculations and methodology are compatible with ISO 14067 and GHG protocol Product Life Cycle Accounting and Reporting Standard, which are the current standards for LCA studies.
What data do you require to get started with Automated Modeling?
As a starting point to do the initial mapping of your product portfolio, we would ask for the following information on your products:
– Product name
– Bill of Material
– Production location, at least country
– Market where the products are sold
– Packaging material(s)
There is a long list of information that will increase resolution and accuracy, but a relatively short list will do most of the work.
CarbonCloud never asks for GHG emissions for any process. For consistency, all emissions are calculated by the platform. All questions relate to production processes with a focus on readily available information to the producers and suppliers. You don’t need to dive deep into the science or methodology to get the climate footprints of your portfolio. You instantly get the richness of immediate insights while feeding in the data and working on the platform. Everyone quickly becomes a climate expert on their part of the business.
What happens after my company provides the data?
CarbonCloud runs your data through a machine learning algorithm, together with the platform’s library of ingredients, production processes, transport modules, etc., to map out representative supply chains for every ingredient and product. At this stage, your company gets complete and consistent scope 1+2+3 mapping for your portfolio, accompanied by a breakdown per product and per stage in the value chain.
Granularity and precision depend on the amount of information available at the time of the mapping. The insights from Automated mapping will guide the users of the platform as to how best to proceed: Which additional data to collect to increase resolution where it matters the most, which products to focus efforts on, and which suppliers to engage for the highest ROI relating to actionable insights and data.
How is Automated Modeling different?
Automated Modeling is unique in its value in 3 different domains:
• Food & beverage industry
Users of Automated Modeling can get their hands on the most accurate and actionable emissions baseline digital technology can provide in a matter of days. The results of Automated Modeling enable food industry players to solve their most pressing emissions problem: Map out emissions throughout the supply chain, orchestrate supplier engagement, and automate Scope 3 primary data input. Users can unlock the automatically modeled digital twin of every product and jump straight into enhancing the climate footprint fidelity. Automated Mapping is the fastest way to start with meaningful reductions in the food supply chain.
• Life cycle assessment
To this day, LCA studies require a hefty penny, a time-consuming hunt for activity data, and way too many methodological decisions to be made. All that to produce climate footprint results that are valid for a year maximum and cannot be compared to the results of a LCA with different methodological decisions. Automated Modeling redefines how LCAs are done with dynamic, always up-to-date climate footprints and inaugurates a new era where what matters is not having a result but what you can do to improve this result.
The technological components in Automated Modeling are the flagship of CarbonCloud’s innovative spirit and pragmaticism. It combines a cutting-edge product classifier and modeling engine and applies this rapid identifying and modeling technology to CarbonCloud’s accumulated knowledge: Our climate footprint library of thousands of data points.
Automated Mapping is the fastest way to start with meaningful reductions in the food supply chain.
What problems does Automated Modeling solve?
Well begun is half done. But in the challenge of data-driven emissions in the food supply chain, the food industry cannot even begin solving it without the map of supply chain emissions. Automated Modeling provides precisely that digital map that propelled the food industry to half-done. Users can locate their emissions with precision, find focus in reaching their climate targets, prioritize suppliers and get to the deep end of the supply chain in a systematic and automated way.
Automated Modeling solves another, more understated issue around food emissions: It moves the needle from “How do we measure the emissions of this product?” to “How do we reduce the emissions of our product portfolio?“. Automated Modeling does that by providing holistic, actionable, comparable climate information fast, regardless of portfolio sizes.
The engine visualizes and maps out information to scale – add primary data, engage suppliers, and pinpoint reduction opportunities with increasingly high definition. Automated Mapping is the data-driven launchpad of a sophisticated climate strategy that moves your organization from discussing reduction opportunities to leveraging them.
GETTING THE MOST OUT OF AUTOMATED MODELING
Menigo, Sysco's Nordic wholesaler subsidiary calculated its baseline, mapped out supply chain emissions for 23,000 products in two weeks, and is on-track to automate Scope 3 engagement throughout its network of suppliers.
The data from CarbonCloud allows us to focus on the things that truly matter. Now we want to collaborate with our suppliers and customers to reduce our climate impact together.
What else makes CarbonCloud special?
This shan't take long...
Ready to meet your portfolio emissions? Let us automate it
Getting started is hard – Simplify it with Automated Modeling and jump straight to the action. Reach out to our climate performance experts and see how you can jumpstart your climate strategy.