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Looking Ahead: Using AI to Build Dynamic Cost Models

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Results Product Carbon Footprint Calculator

With that input our model identified these three NAICS classifications as the most likely to use for the emissions factors:

Table

Ranked Recommendations

NAICS Code

Description

Emission Factor (kgCO2e/USD)

Total Emission (kgCO2e)

1

337211

Wood Office Furniture Manufacturing

0.24

0.72

2

337214

Office Furniture (except Wood) Manufacturing

0.24

0.72

3

337122

Nonupholstered Wood Household Furniture Manufacturing

0.178

0.72

Muir leverages novel technology capabilities, including AI, to generate actionable insights on products and supply chains. Here is how it works:

Muir requires simple procurement data (product name, supplier, destination) in order to generate advanced insights. Combined with product mass or quantity, the Muir AI engine can begin processing results.
Muir creates a synthetic Bill of Materials (BOM) for every product, providing insight into the components and materials that make up a product.
Muir provides insights into the likely sourcing locations for every material in the product, enhancing understanding of a product's global supply chain. Muir also analyzes the carbon emissions associated with every product.
And for every product analyzed, Muir automatically generates recommendations to reduce carbon emissions, evaluating interventions based on total reduction of emissions, change in cost, and the difficulty to implement.