Dirty Data: How it Affects Last-Mile Logistics

Data is the foundation for improving fleet efficiency.

At Wise Systems, our AI-driven dispatch and routing platform is designed to unlock your perfect delivery experience. But AI and machine learning require good data to build reliable training data sets, and to deliver on their promise. That’s why it’s essential to recognize dirty data, eradicate the problems, and leverage clean, robust high-quality inputs to maximize your results. Here’s how we can work together to do that.

What, Exactly, Is Dirty Data?

For most last-mile operations, dirty data refers to missing or inaccurate data, as wellas to changes to rules about how data in a given field is used in a system of record. Cleaning up data sets is often required before embarking on a routing and dispatching transformation, so it’s the perfect time to look at the bigger questions around data and stewardship, as well as to take care of the more basic requirements.

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