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Cognitive supply chain and the game-changing role of digital twin technology

Implementing a cognitive supply chain technology foundation may be complex, but benefits include enhanced operational performance and strategic ability.
 
5 minutes read
Lisa Clontz

Author

Lisa Clontz
Director, Strategic Alliances, Industry NeXT and IoT, HCLTech
Arindam Sen

Co-author

Arindam Sen
Senior Sales Director – Industry NeXT and IoT, HCLTech
5 minutes read
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Cognitive supply chain and the game-changing role of digital twin technology

In recent years, we have experienced both rapid technological advancements and increasing global complexities for supply chains, and the concept of the cognitive supply chain has emerged as a transformative lever in global supply chain management. At the center of this transformation is , a powerful tool that is redefining possibilities within the supply chain ecosystem. By integrating cognitive computing with DTs, businesses are unlocking unprecedented levels of efficiency, agility and resilience. This powerful combination not only enhances operational efficiency and resilience but fosters innovation and strategic decision-making.

This blog describes the synergistic relationship between cognitive supply chains and DT technology and highlights vital industry use cases demonstrating these benefits.

Cognitive supply chain: An overview

Cognitive supply chain leverages AI, ML and advanced analytics to create a self-learning network that can predict changes, adapt to dynamic environments and proactively manage risks. This goes beyond traditional automation and embeds intelligence into every part of the supply chain, from procurement to client delivery. This intelligent supply chain is not only reactive but more predictive and prescriptive. It is also capable of anticipating disruptions and optimizing operations in real time.

Role of DT technology in cognitive supply chain

DT technology is a cornerstone in the cognitive supply chain, providing a virtual representation of the physical supply chain. It captures real-time data from various sources, including IoT devices, to create a dynamic digital mirror of the entire supply chain network. This enables not only visualization and monitoring but also simulation and analysis, allowing for data-driven decisions and scenario planning. DTs serve as the neural network of the cognitive supply chain, processing vast amounts of data to generate insights, predict outcomes and recommend actions.

Top 5 critical industry use cases for DTs in cognitive supply chain

  1. Enhanced demand forecasting and inventory management

    DTs transform demand forecasting by integrating market data, consumer behavior and real-time supply chain dynamics. This complete view enables more accurate predictions, allowing companies to optimize inventory levels and reduce costs associated with overstocking or stockouts. DTs can simulate consumer responses to promotions or changes in product mix, enabling more strategic inventory planning.

  2. Dynamic decision-making in supply chain planning

    DTs enable dynamic decision-making in supply chain planning by simulating various scenarios and optimizing them for the most effective outcomes. This is done by leveraging predictive and prescriptive analytics. As the supply chain DT can assess historical and real-time data across the supply chain network, it can offer actionable insights across multiple touchpoints for optimized strategic and operational decisions. This not only enhances the decision-making process but creates an adaptive, self-optimizing capability within the supply chain, as well, ensuring resilience and efficiency.

  3. Resilient supply chain design

    DTs enable businesses of all sizes to simulate different supply chain configurations and the level of resilience in relation to various risk scenarios, such as natural disasters, trade disputes and supplier failures. This simulation capability is invaluable for industries like manufacturing and pharmaceuticals, where supply chain disruptions can significantly affect global operations. Companies can design more resilient supply chains by utilizing simulation to identify vulnerabilities and test contingency plans early on.

  4. Smart manufacturing and production optimization

    DTs create a virtual replica of the production process in manufacturing, from an individual machine to an entire factory. This virtual replica allows for real-time monitoring for predictive maintenance to be applied, reducing downtime and extending equipment lifespans. Cognitive supply chain capabilities also enable production optimization for scheduling and resource allocation. This ensures efficiency and flexibility in response to changing demand.

  5. Sustainable supply chain practices

    Sustainability is an important topic at the forefront of supply chain management globally. DTs can support making supply chains more sustainable by optimizing routes and loads for transportation. DTs also impact sustainability goals by reducing energy consumption in warehouses and factories, as well as by minimizing waste with improved inventory management. Supply chain DTs help organizations achieve environmental targets, operational cost reductions and regulatory compliance requirements.

Conclusion

The future of supply chain management is cognitive, with DT technology playing a pivotal role. Implementing a cognitive supply chain technology foundation may be complex, but the key benefits — enhanced operational performance, reduced supply chain risk and enhanced strategic agility — make the journey worthwhile.

It is clear that as businesses continue to navigate supply chain complexities across global markets, cognitive supply chains powered by DTs will be a critical differentiator. The future of supply chain management is cognitive. The time to act is now.

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