SDS 487: Fixing Dirty Data — with Susan Walsh

Data Normalization

Normalizing supplier data is crucial for enhancing procurement accuracy. Susan Walsh shares her experience in reducing the number of suppliers from 43,000 to 34,000, highlighting the importance of accurate supplier data 1. This process not only streamlines operations but also ensures consistency in supplier classification, which can lead to better business decisions 2.

Normalizing suppliers can significantly reduce the number of entries, making it easier to manage and classify.

--- Susan Walsh

Jon Krohn notes that many companies struggle with supplier data due to missed names and inconsistencies, which normalization can effectively address 2.

   

Cost Savings

Clean procurement data not only enhances accuracy but also uncovers significant cost-saving opportunities. Susan Walsh explains how misclassified data can lead to substantial financial discrepancies, citing a case where $31.7 million was misallocated 3. By addressing these issues, companies can negotiate better deals and optimize their supplier relationships 4.

Investing in high-quality data can literally save you huge amounts of money.

--- Jon Krohn

Walsh emphasizes the need for businesses to engage in data quality improvements to realize these savings, despite initial resistance from some managers 3.