In today’s supply chains, there’s no shortage of data. Every process, every movement, every interaction, it’s all being tracked. From shipment tracking to delivery confirmation, route history to vendor updates, compliance checks to fuel logs the numbers are there. The systems are active. The dashboards are full.
But here’s the question that keeps coming up: Is all this data actually helping us make better decisions?
More often than not, the answer is no.
Fragmentation is a major challenge.
Many supply chain teams rely on different tools for different functions, one for planning, another for tracking, something else for invoicing or compliance. The problem is, these systems rarely talk to each other. Information stays siloed, and it’s up to the teams to manually connect the dots. That slows down decisions and creates room for misalignment, especially in fast-moving operations.
Manual data handling is still far too common.
Even when data is available, it often needs to be cleaned, matched, or verified before anyone can act on it. Whether it’s checking a document, correcting a delay status, or matching shipment IDs across systems the amount of manual effort involved makes “real-time decisions” nearly impossible. By the time the data is ready, the moment has already passed.
And then there’s the issue of volume.
With so many tools and trackers in place, supply chains now receive a flood of data every hour. But more doesn’t always mean better. Not all of that information is relevant, and teams often spend valuable time sorting through what matters and what doesn’t. In the end, too much unfiltered data becomes just another distraction adding noise instead of clarity.
Making Supply Chain Data Work.
The solution isn’t collecting more data, it’s making existing data easier to use. That starts with connecting systems, so planning, tracking, and documentation don’t live in silos. The second step is reducing manual effort by automating routine updates and document flows, so decisions aren’t delayed by cleanup work. Finally, it’s about filtering out the noise focusing on the right data at the right time, instead of overwhelming teams with unnecessary reports.
