Before the COVID-19 pandemic, the “Just in Time” (JIT) inventory strategy was widely regarded as the gold standard in supply chain management. This approach, which minimizes inventory by timing deliveries of supplies just before they are needed, helps companies reduce storage costs and streamline operations.
The JIT approach model gained notoriety after Toyota’s success linking all its plants and their production processes in a continuous flow―by making only what is needed, when it is needed, and in the amount needed. Other auto manufacturers followed Toyota’s lead, with some maintaining just half a day of inventory of some parts supplied domestically.
Then came the pandemic.
The Downside of Just in Time
COVID-19 highlighted the fragility of global supply chains, particularly those reliant on the JIT model. Supply chain disruptions during the pandemic, which was annotated by factory shutdowns, transportation delays, and sudden spikes in demand, underscored the risks of maintaining minimal inventory levels.
The pandemic was not the first time these risks were exposed—previous events like the flu pandemic and natural disasters such as Hurricane Katrina had already triggered discussions around the need for stockpiling essential supplies. In response, regulatory bodies like the FDA introduced requirements for health systems to maintain a certain level of supplies, recognizing the dangers of depending solely on JIT.
But the pandemic accelerated the move away from JIT as companies realized that supply chain management model is no longer sustainable in today’s complex and disrupted world. The disruptions caused by the pandemic, among other challenges, exposed the vulnerabilities of the JIT model, prompting a significant shift in supply chain strategies across industries.
Whatever benefits businesses realized from the JIT model, they were outweighed by the cost of not having sufficient stock on hand. Even minor disruptions had significant consequences, including financial losses, operational delays, and damage to brand reputation.
The shift has not been easy, as moving away from JIT involves significant costs and risks. However, the need for a more resilient supply chain that can withstand disruptions is now the priority.
Embracing New Supply Chain Models
Many companies have begun re-evaluating their strategies to better manage stock levels and mitigate risks – including a look at hybrid models or entirely new approaches to inventory management. A hybrid model combines elements of JIT with strategic stockpiling. This approach, which is gaining traction, allows companies to balance the need for cost efficiency with the desire for resilience.
For example, large distribution centers such as Cardinal and Owens have been re-evaluating their strategies to better manage stock levels and mitigate risks. This shift involves not only increasing inventory levels but also leveraging advanced technologies like artificial intelligence (AI) to forecast demand and manage disruptions more effectively.
These use cases also demonstrate how business can deploy AI to navigate this transition.
For instance, smart forecasting applications that use AI to predict disruptions can help customers manage their inventory more proactively in the event of a new crisis.
Organizations can also conduct “what-if” analyses, anticipate potential supply chain disruptions, and adjust their strategies in real-time. By integrating AI with supply chain management, an organization gains better visibility into their suppliers’ inventory levels and makes quicker decisions to address sudden changes in demand.
The Role of AI in Supply Chain Management
Companies in industry after industry are applying AI to their respective use cases, such as machine learning for forecasting and conversational user experiences (UX) to streamline interactions with supply chain management systems. These advancements are part of a broader trend toward creating cognitive systems that leverage AI to improve efficiency and decision-making in supply chain operations. It’s also why the supply chain industry is also figuring out how to deploy this technology to reduce its reliance on JIT.
Consider the example of predictive analytics in better demand forecasting where companies can use AI-powered predictive analytics to their benefit. By analyzing vast amounts of data, including historical sales, market trends, and external factors like weather or economic indicators, AI models can predict demand more accurately. That allows businesses like Amazon to adjust inventory levels proactively, ensuring that they maintain adequate stock levels without relying solely on JIT. Bottom line: it reduces the risk of stockouts or overstock situations.
AI-driven inventory optimization is also helping companies perform better inventory management by predicting the optimal stock levels for each of its stores. For example, Walmart is making good use of this to analyze data such as sales patterns, local demand, and supply chain lead times. The AI systems can recommend when and how much to reorder, reducing the need for JIT deliveries. This approach helps Walmart maintain a more resilient supply chain, capable of absorbing disruptions without running out of critical items.
All of these smart forecasting tools help alert customers to sudden changes in demand, such as a surge in interest for a particular product and allow them to source additional supplies from multiple suppliers in real-time. This is just the start of a larger change where proactive companies will be able to mitigate the risks associated with supply chain disruptions, ultimately leading to more resilient and adaptable operations.
Looking Ahead
As the pandemic further recedes from view, more lessons will be learned, and supply chain management will continue to evolve. What’s clear is that companies are increasingly focused on diversifying their supply chains, reducing risk, and adopting new technologies to enhance resilience against the many disruptions the industry is currently navigating. While the JIT model may still have a place in certain industries, the trend is moving toward more robust and flexible supply chain strategies that can withstand the complexities of a globalized economy.
This much is clear: in the face of unforeseen disruptions, companies need to position themselves to meet sudden vagaries in customer demands. And that means learning how to leverage AI and other advanced tools if they’re going to navigate successfully in an always-uncertain modern world.
JIT was great for its time, but experience has underscored the need to adopt more resilient strategies. Only by embracing these changes will businesses be in a better position to weather future challenges and ensure the continuity of their operations.