We'd love to know of any problems with incoming supplies in time to either fix them, or make them irrelevant to our needs today. But most of us live in the world of surprises and reactions.

Think of the airport control tower. They can't afford to have a plane show up with no notice, nor for one to decide to land the other direction. A storm miles away may impact both the inbound and outbound flight potential.

Now apply that concept to your supply chain. With the right data at the right time your supply chain team could see exceptions before they become a problem. They can prioritize, make adjustments, and made decisions to minimize any negative impact.

That takes data.

Think through the kinds of data you would need, and how you would get it.

We only want to know about exceptions, which means we need a standard -- or an expected time and location for everything. Then we need the current reality. Data analytics can identify normal acceptable variation and highlight to the supply chain control tower personnel exceptions that require attention.

GPS information, updates from your 3PL, weather forecasts, data from your own operations -- those are all part of the equation.

As you consider your approach to digital transformation for your manufacturing business, end-to-end supply chain visibility has a place.

This term currently refers only to tier one and "should be happening right now" supply chain issues. That's an important start, but next we want will to proactively see supply chain problems and opportunities and more integral information from suppliers' suppliers to customers' customers.

We'll address the potential for that in next week's podcast on traceability, smart contracts, and blockchain.