How To Build A High-Trust Procurement Data Organization
Your procurement team can’t automate what it can’t trust. When supplier names duplicate, dashboards sit unopened, and every “simple” request turns into an Excel fire drill, AI doesn’t fix the problem, it exposes it. We sit down with Laura Beth ("LB") Hirt-Sharpe, Data Offerings Leader for IBM Procurement and an IBM Outstanding Technical Achievement Award recipient, to get specific about what a strong procurement data organization looks like in the real world. We dig into why many teams hit the end of their “AI runway” after a few proofs of concept, how the rapidly changing procurement technology landscape can scatter priorities, and why rebuilding focus is now part of the job for modern procurement leaders. Along the way, we talk about the trust gap created when data access is controlled by a few gatekeepers, and how to map your data flow so requests stop bouncing around the org. We also get into the surprising upside of data analytics maturity: keeping great people. When teams have democratized spend analytics, usable supplier master data, and faster self-service reporting, they make better sourcing decisions and they stay. LB shares practical ways to gauge progress, including the CEO data test and the idea that timeliness is a measure of trust. If you’re looking for a grounded approach to procurement data governance, data cleansing, and AI in procurement that actually sticks, this conversation is for you. Subscribe for more, share this with a teammate who lives in spreadsheets, and leave a review with the one data problem you want fixed first.







