If your organization uses the spend-based calculation method for Scope 3 emissions, you know that spend information is often disparate and poorly classified. And the more countries involved in your value chain, the more complex it gets. Manually categorizing this data to apply the correct emission factors for emissions calculations can be a struggle.

There's a better way.

IBM Envizi's AI-powered ESG software can efficiently categorize spend data, match it to emissions factors drawn from embedded emissions factor libraries, and produce Scope 3 emissions insights.

How? IBM Envizi leverages large language models to bring uniformity and speed to spend-based Scope 3 GHG emissions calculations. A capability powered an emissions factor library of over 100,000 emissions factors spanning 8 years, 188 countries, and the US EPA's 66 EEIO summary spend categories.¹

The outcome: IBM Envizi automates spend data capture, categorizes spend information, creates a unified set of classifications, and helps map these back to the relevant spend-based emission factors. So, you can focus on bigger Scope 3 challenges.