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Using Predictive Analytics For Better Supply Chain Resilience

Blue Grace Logistics

Improving predictability in outcomes is valuable, but ensuring your supply chain is nimble enough to act on the data is even more so. We explore how predictive analytics and big data with human sentiments can add value and amplify their supply chain strategies. The presence of data throughout the supply chain is vital to its evolution.

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Internet of Things (IOT), Cost-to-Serve, Segmentation and Supply Chain CoEs are unable to deliver promised business value without Prescriptive Analytics

AIMMS

The big theme of course, is the digitization of the supply chain and the implications it will have on business performance. In other words, for digital transformation to succeed, organizations need to be able to “take action” based on their data. Data availability and technology wasn’t what it is today. Cost-to Serve.

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The One Key Shift in Your Supply Chain and Procurement Strategies that can Drive Better Business Continuity and Resilience

Logistics Viewpoints

The urgency of response to a disruption of a Category 1 supplier is of course much higher than that of a Category 4 supplier. Leverage AI to benefit from supplier community data: Building trusted relationships with suppliers is an imperative for success. Nari Viswanathan is a six times SDCExec Supply Chain Pro to Know award winner.

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Modeling brewing capacity to drive cost savings at HEINEKEN

AIMMS

But it had its limitations, of course. It was taxing to report above the country level with this tool. For instance, if I wanted to know what the HEINEKEN canning capacity was in Asia, I would have to sum up 20+ Excel files to sum up the data for all the breweries. There was no global master data in place either.

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Autoliv’s Supply Chain Risk Management Journey

Logistics Viewpoints

Implementing the solution involved cleaning up master data and mapping their complete global supply chain. Risk management solutions scrape data from hundreds of thousands of online & social-media sites, but Autoliv also has access to sources of information that they pay for. The implementation was not trivial.

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Modeling brewing capacity to drive cost savings at HEINEKEN

AIMMS

But it had its limitations, of course. It was taxing to report above the country level with this tool. For instance, if I wanted to know what the HEINEKEN canning capacity was in Asia, I would have to sum up 20+ Excel files to sum up the data for all the breweries. There was no global master data in place either.

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Use Prescriptive Analytics to see value from Internet of Things and other digital initiatives

AIMMS

The big theme of course, is the digitization of the supply chain and the implications it will have on business performance. In other words, for digital transformation to succeed, organizations need to be able to “take action” based on their data. Data availability and technology wasn’t what it is today. Cost-to Serve.