Predicting Supply Chains' Disruptions

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Omar Choudhry, Supply Chain Insights' principal group product manager, poses for a photograph.
Omar Choudhry, Supply Chain Insights' principal group product manager, helped develop a system that predicts supply chains' disruptions.

Microsoft is giving ERP Partners the tools they need to navigate enfeebled supply chains.

Using Dynamics 365 Supply Chain Insights, Partners can build a digital twin of their supply network, predicting disruptions to their supply chains and increasing their network's resiliency.

Supply Chain Insights works horizontally, reaching across Partners' systems to analyze supply chain vulnerabilities from supplier to customer.  Omar Choudhry, Supply Chain Insights' principal group product manager, helped develop the program.

"We have awesome process applications, ERP Cloud applications, but they weren't helping us be predictive or helping us manage these (COVID-19-fueled) supply chain disruptions," Omar said.

In early 2020, a convergence of unexpected, pandemic-related crises placed unprecedented pressure on global supply chains, which had already been working at capacity.  As shipping and manufacturing networks buckled under the weight of unpredictable economic, labour and infrastructural disruptions, industry leaders played increasingly reactive roles.

"And so, we want to build an application that can (...) get predictive about port disruptions, natural disasters, all of these types of things," says Omar.  "And then what you're to do and who you're to collaborate with afterwards."

Supply Chain Insight's predictions will be built from data.  Information from organizations' internal systems, collected data from Partners and data companies, and information from customers will coalesce into a duplicate of users' supply chains.  Users will be able to ask it questions, create simulations and get out ahead of possible problems.

Obviously, the simulation is only as good as the data, so, as always, good, clean data is important.

We spoke with Heidi Tucker of InsideView to learn about dirty data, its financial and functional costs, and what we can do to address the problem.  You can read that article HERE, and you can check out what else we've been up to on our website.

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