Data doesn’t always equal intelligence

Data drives many modern supply chain processes. Measurement of the time, equipment and costs involved in these processes allows for optimization and improvement. What can be measured can be improved.

It is easy to collect lots of data. What is hard is to know what data is valid, and how to interpret it so that it can be used to improve the processes. More data doesn’t always equal a better process. In fact, there is a point where collecting more data actually increases the noise in the data and makes it harder to interpret.

Data properly validated and interpreted equals intelligence. And intelligence must be action-able. It must tell us what we need to do differently.

For example, collecting lots of data on vendor lead time variability might seem like a good idea. But by itself this data won’t tell us the whole story. We need to know about all the factors that could impact this data, and decide which factors are significant and manageable, and which factors are outside our control. Penalizing a vendor for poor lead time performance based solely on data measurements may hide the fact that our own processes are keeping the supplier from improving. I know of a case where the vendor’s lead time increased dramatically because the company that was ordering product from them was also arranging the freight pickups from the vendor, and was not scheduling these correctly. Not the vendor’s fault here.

So remember that data by itself frequently won’t tell you how to improve your business. Only the intelligent interpretation of the data will allow you to see where you can take action to improve your processes.

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