How AI-led SKU categorization strengthened ERP migration for a global hospitality group

As part of a major ERP transformation, a global hospitality company was faced with the challenge of migrating a highly complex SKU catalog. A manual approach risked creating a major resource drain, slowing down the program, and introducing errors. While AI offered a way to address the scale of the challenge, success depended on accurately interpreting the organization’s business-specific taxonomy and category rules. To achieve a high-quality migration, the organization partnered with Efficio to combine its procurement and AI expertise. 

The challenge 

The organization was migrating its entire SKU catalog into Dynamics 365, requiring each item to be categorized through a five-level taxonomy. With the catalog spanning millions of SKUs, manual classification was not a feasible solution. To further complicate the task, the categories were based on a taxonomy that demanded detailed interpretation of business documentation, accounting dictionaries, and product attributes.  

Efficio’s approach 

Efficio developed a custom AI-enabled SKU categorization solution based on a five-layer large language model (LLM) architecture. Efficio utilized their deep procurement category knowledge to refine the client’s taxonomy to enable the LLM to accurately interpret it.  

Bringing together procurement category knowledge, a strong understanding of the client’s business context, and technology expertise, the Efficio team was able to ensure accurate interpretation of the client’s taxonomy from the outset. This meant the solution was built in weeks rather than months, with the number of feedback loops with the client kept to a minimum.  

The solution translated SKUs to English where necessary and categorized items for all levels, enabling a structured final review. The result was a scalable, automated categorization tool that enabled the team to categorize each hotel’s historic catalog items in under three hours with strong accuracy: 5–10 times faster than traditional, non-AI approaches.