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Home » Watch: Digital Data Drives Supply Chain Design
VIDEO

Watch: Digital Data Drives Supply Chain Design

May 17, 2022
Russell W. Goodman, SupplyChainBrain

Digitizing data is of immense help in mitigating supply chain risks, says Bernard Tremblay, chief executive officer of the U.S. and Canada for Miebach Consulting.

From an operational perspective, the last few years have been difficult for many traditional companies, as they’ve had to adjust to doing more business directly with consumers, Tremblay says. At the same time that e-commerce has seen explosive growth, labor management issues have increased. Consequently, automation has become more important, especially for companies in North America. Europe largely made the transition to automation 15 to 20 years ago, he says.

Digitized solutions are precisely what companies need to get proper labor management, in Tremblay’s view. “Dimensioning” solutions correctly is what’s required. He doesn’t completely agree with those who say automation is highly rigid. “If you size it the right way, you can anticipate through data-driven analysis what you're going to need for the next day, weeks, month in terms of labor.”

He notes a growing trend to have flexible automation. You purchase a certain design first, then rent additional capability. As always, success turns on having good data. “So all of this information goes back to doing deep analytics on the past, but also looking at what's coming and how you can forecast based on different aspects of the data you can bring in, not just from your ops, but extended data.”

Companies have struggled to bring data together to make better decisions, but risk management and resiliency turn on utilizing data properly. Pulling data to understand how one’s supply chain behaved in certain situations is key. “If you can extrapolate and see where you were stronger, where you were weaker, really do a data-driven, deep dive into these things, you can put actual figures behind your risk analysis. This is where you're really going to get value out of the data.”
 
 

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