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What if you had an assistant who continuously provided recommendations for optimizing your supply chain operations, then immediately implemented them upon your authorization? Would that assistant be even more valuable if they knew when they didn’t need to ask, but instead took immediate actions without your intervention?
Of course, no such person exists, but artificial intelligence-enabled digital twin (DT) technology has advanced to the point where this “super assistant” scenario no longer has to be just a dream.
Today, AI-enabled DTs are uniquely positioned to transform supply operations by connecting and synthesizing siloed operations to improve visibility and decision-making across the end-to-end supply chain ecosystem in which thousands of people are making decisions. This becomes possible when data is standardized and cleaned, integrated with disparate systems, and understood in the context of a specific business.
There are many implications for how this can impact a supply chain, so here are five significant ways that AI-enabled digital twins might shape an organization’s future.
1 End-to-End Real Time Visibility
Previous efforts to eliminate silo barriers have been less than successful because existing enterprise resource planning and other management systems, disconnected data sources, delays in communications and data transmission, and occasional missed communications between subject matter experts prevented true end-to-end supply chain visibility.
Digital twins can close many of these gaps by synchronizing in real time across an entire supply chain to successfully implement business plan objectives. Still, real world conditions can change beyond business plan assumptions, from sudden new market demands to local highway traffic jams. Now AI can quickly develop insights and recommendations based on continuously evolving insights, in part because AI can work with natural language, rather than requiring conversion by a Large Language Model, which also can become outdated.
AI-enabled DTs, combined with a strong data fabric, provide an interconnected view of inventory and supplier activity in real time, transforming fragmented operations into a cohesive system.
As an example, a leading global OEM transformed its order-to-promise performance and customer satisfaction by deploying an AI-enabled digital twin of its supply chain. This advanced solution integrates data across suppliers, logistics and production, delivering real-time visibility into potential disruptions. By proactively anticipating delays and dynamically adjusting production schedules, the OEM increased factory throughput by 33%, reduced inventory by 20%, and improved on-time promise (OTP) by 40%.
2 AI-Driven Actionable Insights
AI-enabled DTs transform how companies interpret data, enabling actionable insights that drive smarter decision-making.
AI connects and synthesizes all relevant data into a single DT platform. With this unified system, both predictive and prescriptive analytics are performed simultaneously, and this can be done without the costly and time-consuming training of generic large language models (LLMs). Instead, semantic (no code) models can efficiently create a foundation for AI by enriching data with meaning, enabling organizations to develop “teaching muscles” that train their unique data.
By integrating live data streams into a dynamic data fabric, these systems create a foundation for anticipating challenges and proactively addressing them.
In one case, a global manufacturer used an AI DT to gain real-time insights into upstream supplier problems and transportation delays along with their impact on production and financial performance. The system flagged potential delays, and options for recovery. As a result, the company reduced revenue loss ahead of their industry peers, improved on-time delivery by 40%, and reduced inventory by 32%, demonstrating the power of AI-driven actionable insights.
3 Multi-Enterprise Collaboration
The imperative for developing multi-enterprise collaborations has never been greater. As the web of supply chain connections becomes ever more complex, forming strong, transparent and dynamic partnerships with suppliers, logistics partners, customers, and others opens new opportunities to achieve operational excellence.
AI-enabled DTs can now support the transformation of multi-enterprise collaboration. With real-time insights, predictive analytics, collaborative workflows and more agile response mechanisms, partners can work together seamlessly to prevent supply chain disruptions and create a transparent and resilient network.
Benefits include data-driven insights that facilitate optimized operations and supplier interactions, as well as a new level of trust between multiple partners. As a result, all parties can achieve elevated performance metrics through accurate, real-time data analysis. End-to-end supply chain security can also be optimized.
4 Business Modeling and Scenario Planning
Central to the application of AI-enabled DTs is their ability to bring business modeling and scenario planning into the real world, as opposed to a series of theoretical “what-ifs.”
Creating the business model comes first, which requires the integration of goals, processes, policies and structures. The model will be a real-time, fully connected behavioral replica of the entire supply chain ecosystem of the business.
With a realistic business plan, DTs excel at scenario planning, enabling businesses to simulate disruptions and craft tailored solutions “on-the-fly” for mitigating risks. To be successful the DT must be capable of working with real-time information. This embeds resilience as an integral part of the supply chain.
A manufacturer, for example, can use its DT to simulate the impact of various disruption scenarios to include sourcing materials from alternative suppliers and maintaining production continuity, ultimately reducing downtime and protecting customer commitments.
5 Supply Chain Co-Pilot
Culminating with the successful development of an AI-enabled digital twin is the emergence of virtual agents that automate many tasks within the existing business rules. These agents, or supply chain co-pilots, work alongside managers to solve complex problems quickly and effectively. Humans interact with the co-pilots using natural language that the semantic network translates. This capability removes the barriers that have previously made it difficult for DTs to adopt to the multitude of unique business practices and languages.
Each co-pilot draws on the experience and knowledge of each subject matter expert with all the history, data, real-time events and evolving customers’ needs that are occurring across the supply chain in real time. Simultaneously, network co-pilots are collaborating to continuously optimize operations.
Supply chain co-pilots now provide insights and recommendations that have not been available to supply chain managers previously. Difficult tasks that are simplified include the execution of inventory actions (expedite, de-expedite, or stop production), recognition of potential obsolescence risk, triggering a stop order or an open purchase order, or initiating an inventory write-off action.
Unleash the Magic of Your Supply Chain
TADA is leading the development of AI-enabled digital twins for supply chains across a wide range of users. Its supply chain platform enables businesses to navigate the complexities of their operations and deliver real improvement to cost, cash, carbon and revenue.
Its proprietary, AI-enabled digital twin platform offers the best time-to-value in the industry, providing real-time visibility, multi-enterprise collaboration and orchestration, and actionable insights. Businesses are empowered to act with clarity and to optimize operations.
TADA works collaboratively with manufacturing, CPG, and healthcare users to achieve optimized supply chain performance in many ways including:
• Asset management,
• Dynamic production scheduling,
• Supplier collaboration,
• Network inventory management,
• Demand forecasting, and
• Risk and resiliency.
TADA is ready today to support your enterprise in the development and adoption of AI-enabled digital twins that will exceed your expectations and lead to market share growth, while better serving the world’s needs.
Resource Link: www.tadanow.com/
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