Scalability and Speed
Reduced LCA processing from months to seconds per product, enabling analysis across more than 5,600 components within minutes.
Western Digital
Western Digital turned a months-long manual LCA workflow into real-time carbon analysis across 5,600+ components with full coverage and improved accuracy.
100x Faster
Modeling individual BOMs compared with manual approaches.
100% Coverage
Across 5,600 assessed components.
+30% Improved Accuracy
Compared with expert manual LCA results.
The Challenge
Western Digital’s process-based LCAs were run manually and depended on slow supplier data collection. A single product assessment could take as long as six months, and after two years of effort only 20% of required supplier data had been collected. Manual workflows also demanded significant time for BOM scrubbing, data collection, and site-level modeling, which limited scalability and delayed sustainability decisions.
The Solution
With Sluicebox’s Generative LCAs, Western Digital transformed a months-long process into real-time analysis for thousands of components. The platform also enabled what-if scenario modeling so teams could quickly test design, logistics, and manufacturing changes to identify lower-emissions options before making strategic decisions.
Key Results
Reduced LCA processing from months to seconds per product, enabling analysis across more than 5,600 components within minutes.
Achieved 100% data coverage on assessed components, including roughly 70% exact matches and 30% improved matches.
Third-party audits confirmed a 30% improvement in matching accuracy, and 52% of the data was from 2024 or later.
With Sluicebox, we've evolved from manual, months-long LCAs to real-time carbon intelligence. Now, we have the potential to scale auditable emissions across thousands of products, proactively identify sustainability opportunities, and make strategic decisions faster than ever before.
Suprit Pradhan
LCA and Product Stewardship, Western Digital
Key Takeaway
Sluicebox helped Western Digital turn LCAs from a slow, specialized workflow into a real-time decision-making capability. The result was broader coverage, faster insight, and a practical way to use carbon data in product and supply chain strategy.