The past is prologue to today’s supply chain challenges

Instead of consistently investing in incremental improvements, we keep postponing the investments until we have no choice.

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It’s great to see the increased investment in technology in supply chains since the COVID pandemic began—surveys indicate 50-60% of companies across a wide range of industries have plans to invest in technology and automation, and it is one of the top trends in many industries, even above labor concerns. Certainly, the companies with more up-to-date technology have often enjoyed an advantage during the crisis and technology also provides a competitive advantage at any time, when done rightly.

The latest supply chain technology darling seems to be artificial intelligence (AI). The rise of “no-code” AI means that the acute labor shortage for coders and data scientists is less of an issue for implementing this valuable technology.

Why is AI so valuable? We produce far more data than can humanly be processed. One recent study of data found that the average industrial bakery produces upwards of five petabytes of data per day.

Except there’s one important fact often overlooked: the recent supply chain crises have resulted from long pre-existing conditions. Supply chains’ greatest issue results from a fragmented data environment—just about every company has its own data system and they do not easily communicate with other data systems. The result is lack of transparency, an especially tremendous issue for efficient on-time delivery and procurement operations.

One of the most impactful steps to improve transparency would be to standardize data and provide much more comprehensive access to it. Supply chain providers can only optimize their processes when they have the complete picture and all of the pertinent data, yet that has long been a challenge. Companies focus on the data most useful for their internal operations, and, furthermore, they tend to silo the information both with regard to the IT infrastructure and who has access.

How can AI optimize a process when it cannot even see what’s going on? It’s like asking the doctor for a diagnosis without access to a single lab test.

Yet even with perfect information, our long-standing policies of not investing enough in infrastructure will continue to severely limit the throughput of our supply chains. We need modernized infrastructure.

Certain stakeholders do not want to see increased automation because it will mean that some jobs disappear. They are right to be concerned for their economic well-being. We live in a world with more wealth than has ever existed before; however, we must find some way to create economic prosperity for everyone while increasing automation and efficiencies. This will be our greatest challenge.

The past is prologue, as true now as when Shakespeare inked the words with his quill. Our past? Instead of consistently investing in incremental improvements, we keep postponing the investments until we have no choice. No wonder COVID hit so hard, we were hobbled with geriatric supply chain technology. There’s a much higher risk of failure when trying to make a 20-year leap in technology as opposed to a five-year leap, not to mention the years of reduced competitive advantage and lost market opportunities.

Let’s up that with new initiatives like the White House’s Freight Logistics Optimization Works (FLOW) and the wave of corporate technology investments creates a better prologue for the sake of our future selves.

Michael J. Gravier is Professor of Marketing and Global Supply Chain Management at Bryant University. He received his PhD from University of North Texas, MS from the Air Force Institute of Technology, and BA from Washington University in St. Louis. His research focuses on supply chain connections including procurement, industrial marketing, transportation, and the impact of technology on supply chains. He can be contacted at [email protected].

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