Here’s Why Today’s Supply Chain Optimization Strategies Need to Change

Supply Chain Optimization Strategies

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In my work as CTO for the manufacturing industry at Microsoft, I get to work with the leading global firms on helping them define strategies to transform operations. In my conversations, the topic of creating more intelligent supply chain optimization strategies is often top of mind. For most, this means finding ways to better track raw materials, products, and finished goods as they travel through the supply chain. What many manufacturers have yet to come to grips with, however, is the role smart factories, production data, and IoT analytics have in enabling true end-to-end supply chain visibility.

Manufacturers have historically focused supply chain efficiency efforts on increasing visibility of output, with an emphasis on better monitoring logistics. In a steady-state environment, this strategy can be effective. But what happens when there is a disruption in the value chain, for example when demand fluctuates? How do you deal with it if supplies aren’t there?

Supply chain leaders are only now beginning to understand the important role visibility into production and quality can have on optimizing the supply chain. By leveraging IoT and AI in supply chain, enterprises can build algorithmic decision-making and automated execution to deliver disruptive capabilities and new business models.

With the adoption of Industry 4.0, we are now seeing manufacturers integrating the broader value chain across physical, information, and financial flows. With new kinds of data being generated, it is possible to drive better outcomes in planning or in inventory optimization.

Supply Chain Optimization Strategies

Building a foundation for the intelligent supply chain

The foundation for building an intelligent supply chain is a digital platform with capabilities like IoT, AI, cognitive and blockchain, that can enable different aspects of a manufacturing process and also enable companies to build new disruptive capability. For example, sensor-based replenishment allows manufacturers not only to understand customer use of the product but also to drive capacity planning. In a physical supply chain, IoT sensors can provide near-real-time visibility to the movement of materials indoor or outdoor. Such tracking combined with AI enables manufacturers to better predict inventory stock addressing material availability on the factory floor.

IoT sensors are also capturing additional data including temperature, humidity, and vibration that can impact manufacturing processes and the quality of the final products. We are also seeing the application of blockchain smart contracts providing another level of traceability, authentication, and reducing counterfeit materials in the supply chain.

Industry 4.0 has enabled manufacturers to develop a foundation for smart manufacturing. That has enabled monitoring uptime of the manufacturing equipment and the quality of the production, so manufacturers can now predict supply chain issues proactively. With emerging IoT technologies, manufacturers can look into multiple factories making the same product to spot performance problems as well as track a product when the output from one factory goes into another factory.

A good example would be a sub-assembly from one factory being shipped to an OEM factory. Beyond understanding factory performance, manufacturers are also gaining insight into capacity and material availability and any associated issues with shipping and handling.

One of the major focus areas for manufacturers is the ability to enable track and trace of output, to meet supply chain, compliance, and quality objectives. Complex products like automobiles today are built by combining assemblies, which in turn often contain sub-assemblies, each built by different suppliers. Identifying how problems within these complex systems will impact supply chain inventory levels has typically not been feasible. Leaders need to leverage technology that accounts for the complex interactions among components to enable proactive inventory management.

Microsoft is working with a growing number of manufacturing clients. The key opportunity is to implement a software platform that enables companies to look at not just a single factory but across multiple factories, and up and down the supply chain.

True end-to-end visibility isn’t possible without deep insight into supply chain optimization strategies.

To see case studies where Sight Machine and Microsoft are partnering to deliver new levels of production visibility, visit the Sight Machine Use Case Page.


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Picture of Indranil Sircar

Indranil Sircar

Indranil is the CTO and Director of Technical Strategy for the Manufacturing Industry at Microsoft.

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