Supply Chain Data Predictions for 2024

With this approach, organizations can use the digital supply chain to make the right decision and then use the physical supply chain to act.

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Traditional approaches attempted to address supply chain issues by deploying a variety of specialized standalone systems, indicated by three-letter acronyms, like PLM (product lifecycle management), WMS (warehouse management system), TMS (transportation management system), OMS (order management system). These traditional standalone systems are no longer sufficient. These systems were effective in resolving specific supply chain problems, but could not provide an integrated, end-to-end solution or effectively adapt to major challenges caused by climate change, geo-political dynamics, macroeconomic issues, and changing customer behaviors. This has driven two significant supply chain management trends over the last five years.

Firstly, organizations are transitioning to a data-first strategy that addresses cross-functional and systemic issues. This approach focuses on enhancing inventory visibility, reducing inventory discrepancies across the supply chain, and fostering consumer trust, all while being adaptable to supply chain disruptions. Secondly, organizations are increasingly seeking simplicity with their supply chain management approach, replacing traditionally manual data integration methods with machine learning (ML) based data association. This second trend represents a significant shift from isolated problem-solving to a unified, technologically advanced approach, meeting the complexities of today’s global supply chain challenges.

Both of these trends will continue to influence supply chain management and drive predictions for 2024.

1. Generative AI Removes Undifferentiated Heavy Lifting in Making Better and Faster Decisions

There is a lot of excitement around generative AI but also a lot of confusion regarding effective deployment/usage/security/ethics—especially for supply chain management. In 2024, we will learn with greater detail how generative AI empowers supply chain leaders with better insights and helps them discover outcomes of complex scenarios and tradeoffs between different supply chain decisions. Supply chain management has slowly adopted technologies like ML to assist with computations and trend analysis, but we will see a concerted requirement for smarter, more efficient and customer-centric solutions.

Digging through layers of data to automate labor-intensive tasks that accelerate decision-making is an ideal use case for generative AI. Supply chain leaders will be able to conversationally ask what, why and what-if questions to address complex scenarios, trade-offs and potential outcomes. Generative AI will also simplify business functions like supplier auditing, evaluation, selection, and substitution by automating the analysis of operational performance, sustainability metrics and financial health.

2. Data Will Finally be Associated and Unlock Innovative Supply Chain Management Capabilities

Valuable supply chain data still remains scattered in data silos, making it difficult to use effectively. Previously, technology for creating true supply chain visibility was cost-prohibitive to implement, but large language model-powered data ingestion and transformation are lowering this barrier to entry. In 2024, organizations will be motivated and more easily be able to transform scattered data across multiple systems into a unified model. They will finally have a practical, scalable, and cost-effective approach to unify supply chain data to improve supply chain decision-making. With more data, organizations will have better intelligence and visibility.

With data in one place, organizations can finally deploy an effective generative AI strategy and enable optimal performance from generative AI models.

3. Digital Supply Chains Will Increase Agility in the Face of an Uncertain World

Digital supply chains with generative AI will enable the simulation of supply chain scenarios that illustrate the impact of different supply chain decisions. As shown with recent environmental, economic and geopolitical issues, instability can happen at any time and anywhere. Organizations that utilize a digital supply chain are more likely to increase their resiliency against these disruptions - regardless of when they occur.

Digital supply chains will help organizations boost the agility and flexibility of their physical supply chains. Generative AI will run hundreds of thousands of scenarios with different variables to predict outcomes that provides more accurate guidance. Organizations can then act to maximize efficiency, effectiveness and responsiveness across the supply chain. With this approach, organizations can use the digital supply chain to make the right decision and then use the physical supply chain to act on that knowledge with speed and certainty.