Max HenryFounder & Executive Director, Global Supply Chain Council (GSCC) · Founder & Executive Director at Global Supply Chain Council (GSCC)

Oracle Data Migration: AI Solves Supplier Data Gaps #shorts

15 Oct 2026 · 1 min

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1:09

In this short, the speaker explains a recent migration from PeopleSoft to Oracle, highlighting that the two systems have fundamentally different supplier modules with distinct mandatory requirements. After extracting supplier data from PeopleSoft, the team compared it against Oracle's templates to identify missing fields and additional requirements. They discovered common data quality problems such as duplicate supplier records, spelling variations, and inconsistent name formats (e.g., "Ajay Kapoor" vs. "Ajay Kumar Kapoor"). The speaker emphasizes that AI was used to automatically detect these gaps before implementation, enabling the team to engage the appropriate stakeholders—partners, IT, and other functional groups—to clean and standardize the data, thereby establishing a strong foundation for the new Oracle system.

Chapters

see, I'm just taking one example. Uh, recently we have just moved from PeopleSoft to Oracle, where if you see the system both together is different in nature. The supplier modules are different, lot of requirement, mandatory requirements in the supplier modules. And we have just pulled the data from the previous system, and then we have seen the templates of the new Oracle system And then we just try to match what are the fields where some gap is there, what are the additional. Sometimes we have seen multiple partners or multiple suppliers are registered with the same name, or maybe some spelling error, or maybe Ajay Kapoor, Ajay Kumar Kapoor, Ajay Kumar Ajay. So that I think with the help of AI, again, before implement, with the help of AI, people are able to Understand the gap so that accordingly we have connected with the different stakeholders, whether it is a partner, whether it is an IT function, or maybe the other function. So that first we need to create the strong foundation, cleaning of data. So that is the first step we will have taken.