Simplifying Scope 3 Accounting for Manufacturing: How AI is Transforming Emissions Management!
Sustainability and emissions reduction are essential. Manufacturers can no longer afford to delay tackling Scope 3 emissions. With growing regulatory pressure, investor scrutiny, and customer expectations, manufacturers must take control of their entire carbon footprint, including Scope 3 emissions. This is challenging as these often represent the largest share of a manufacturer’s total carbon footprint and remain the most difficult to track, measure, and reduce. The complexity stems from the vast network of suppliers, transportation partners, and product lifecycles contributing to a company’s overall emissions.
Fortunately, AI and automation are transforming Scope 3 emissions accounting, helping manufacturers streamline supplier data collection. AI-infused platforms like IBM Envizi ESG Suite are simplifying Scope 3 accounting by automating supplier data collection, managing emission factors at scale, and enhancing decarbonisation planning.
Automating Supplier Data Collection
Manufacturers rely on extensive supplier networks, making it difficult to gather accurate emissions data. AI-driven ESG solutions can:
- Engage suppliers at scale for the collection of emissions data.
- Automate the capture of transactional data from ERP and financial accounting systems.
- Categorise supplier spend data for accurate Scope 3 Category 1 emissions calculations.
IBM Envizi uses Natural Language Processing (NLP) to classify the Scope 3 Category 1 spend data, based on user-provided spend transaction descriptions.
Managing Emission Factors at Scale
Keeping emission factors up to date manually poses a challenge – there can be thousands if not tens of thousands of global emission factors that need to be aligned with manufacturing calculations. AI-driven systems like IBM Envizi automatically:
- Apply the latest emission factors from the embedded emissions factor libraries.
- Provide an overview of the accuracy and health of your Scope 3 data.
- Provide transparency and auditability of emission and energy factors.
By removing human error and ensuring emissions are calculated with the most accurate factors available, AI and Automation help to produce audit-ready Scope 3 data.
Enhancing Decarbonisation Planning
AI enables manufacturers to forecast future emissions and model reduction strategies. Through ESG solutions, manufacturers can simulate different sustainability strategies (e.g., switching to low-carbon materials, optimising logistics, or adopting circular economy principles); predict the impact of supplier changes on overall carbon footprint, and set science-based emissions targets and track progress in real-time.
IBM Envizi allows users to run scenario analyses to determine how shifting to local suppliers or using alternative raw materials would impact emissions, empowering manufacturers to make informed decisions accordingly. Time-series AI algorithms help you analyse and model forecasting data over time, detect seasonality and trends, and enhance forecasts with automatic outlier detection and correction.
Scope 3 data needs to be accurate, transparent, and auditable, especially with stricter requirements such as the EU’s Corporate Sustainability Reporting Directive (CSRD), and the UK’s ongoing assessment of the International Sustainability Standards Board (ISSB) regulations. Using ESG reporting software enables manufacturers to streamline supplier data collection, meet investor expectations for climate risk transparency, and create supply chain efficiencies that reduce costs and emissions.
Want to future-proof your ESG strategy? Get in touch with us to discuss how AI and automation can transform your emissions management.