Don’t Confuse Data Quality Dashboards With Data Quality

Does your software treat data quality as a core competency? Or is it just surfacing issues in “data quality dashboards”?

Supply chain data costs are often measured in AWS, SAP, and integration spend. But the more significant cost is the gap between what your data could enable and what it actually does.

Data quality is the elephant in the room.

The value of supply chain data comes down to one question: is it fit for purpose? Teams can only answer that with confidence when the data is trustworthy and accessible when it matters. Without trust in the data, teams delay decisions and operate in the dark.

Imagine a physical product built with no standards and no understanding of how parts fit together downstream. One wrong or missing part and the product fails.

You'd never ship that. But bad data ships every day.

Supply chain data problems have a blast radius. When a vendor reduces the quantity of 25-cent screws on an order and the update doesn't make it into the system, it looks trivial in isolation. But tied to a $300 bill of materials for a new product launch, that one missed change can create excess inventory, halt production, and kill revenue.

Don’t settle for a dashboard. Ask whether the software can handle a PO line with a missing unit of measure or one attached to the wrong shipment. If it only surfaces the issue and leaves the rest to your team, that’s not a solution. That’s a handoff.