In an era where operational speed, agility, and risk mitigation define competitive advantage, digital twin technology is transforming supply chain management. A digital twin — a dynamic virtual replica of physical operations — enables organizations to visualize, simulate, and optimize complex supply chain systems in real-time.

​

This presentation examines how combining digital twins with predictive analytics unlocks unprecedented capabilities, ranging from proactive bottleneck detection and labor optimization to asset maintenance and response to disruptions. Through real-world case studies in warehousing and transportation, attendees will see how early adopters use digital twins to make informed decisions, improve service levels, and future-proof their operations.

​

Attendees will leave with a practical framework for implementing digital twin ecosystems, understanding data and modeling requirements, and maximizing ROI. They will also learn how to shift from reactive firefighting to proactive orchestration in today’s digital supply chain landscape.

The WMS and warehouse implementation is a journey an organization undertakes to fulfill operational needs and strategic goals.

It involves defining scope, selecting a WMS and warehouse automation partner, and all essential elements of the implementation foundation, such as design, configuration, integration with ERP/TMS, testing, training rollout, and daily operations before going live with the software.

However, before making an investment, it is crucial to analyze and consider the balance needed between Return On Investment (ROI) and employee retention, especially in warehouse automation projects.

Despite years of voluntary programs and certifications, systemic labor injustices and environmental issues persist in supply chains.

​

Discover, through case studies, how AI can revolutionize Responsible Sourcing and Human Rights Due Diligence (HRDD) with scalable, intelligent solutions that automate tasks—such as audit review, CAP (Corrective Action Plan) creation, questionnaires, and risk analysis—saving hundreds of hours on report reviews. 

In the AI age, supply chains must balance sustainability, traceability, and profitability. This session highlights an information framework that facilitates clear communication and data consistency between suppliers and customers.

By standardizing information requests, this framework ensures that data interpretation is clear and unambiguous for all parties, thereby enabling the accurate use of IoT and AI technologies.

Participants will learn how this approach helps align strategies and inform AI data requirements, leading to more efficient and transparent supply chains that support timely strategic decision-making.