“I don’t trust the data” – these four words can stop a data project dead in its tracks. Data validation challenges typically fall into two categories: genuine data inconsistencies and misaligned expectations. Whether it’s discrepancies in your Warehouse Management System (WMS) or unexpected variations in your Order Management System (OMS), getting to the root cause can become a resource-intensive process that pulls in more stakeholders than necessary. That’s why it’s important to have a predesignated validator who can help you resolve any data believability issues. They’re typically team members who work closely with the business, and have time to track data issues. You create a clear path for data verification and troubleshooting by identifying these validators before your project begins. Instead of scattered, ad-hoc validation attempts that can derail project timelines, you have a dedicated expert(s) who can efficiently assess data quality and help resolve discrepancies. All the Best, Tucker |