Just-In-Time (JIT) manufacturing –also referred to as lean manufacturing– was popularized in the US after its success in Japan’s Toyota manufacturing plants, which developed the strategy to revitalize the automotive industry after World War II. The system optimizes efficiency by aligning supply with production, so manufacturers receive raw materials and parts only when they are needed to fulfill orders. The benefits of this system come in the form of cost savings from low inventory storage, reduced waste, and minimizing the risks of canceled orders.
While efficient and cost-effective, JIT relies heavily on predictable demand and reliable supply. Without storing significant quantities of inventory, changes in demand like a drastic increase in orders may mean the manufacturer is unable to procure enough supply for production, or may not have the capacity to produce at the rate required to fulfill the surplus of orders in the expected timeframe. Likewise, parts and raw materials must reach the manufacturer quickly in order to produce and ship the product to consumers in a timely manner. If supply chain problems occur, delays in supply have a ripple effect on the entire manufacturing process, the effects of which are felt by the end consumer.
When the Just-In-Time Model Fails
In the early days of the pandemic and the years that have followed, the risks of the JIT system have been illuminated as demand for goods became increasingly unpredictable, and shipping became volatile with manufacturing plant closures, route disruptions, and shipping containers became scarce. The two criteria upon which the efficiency of JIT are predicated –predictable demand and reliable supply chains– suddenly evaporated, making manufacturers that leveraged JIT methods vulnerable.
Some companies have since shifted to nearshoring or localizing their supply, reducing the distance parts and materials must travel to circumvent the vulnerability of supply chain disruptions, while others have begun increasing their stores of inventory to insulate themselves from the rapid changes in demand. In sectors where these options are viable due to the availability of localized suppliers and capacity for inventory storage, the additional costs associated with increased inventory are worth it to reduce the vulnerabilities of JIT and prevent their consumers from feeling the precarity of unreliable supply.
In other sectors however, like agrifood, localizing and increasing inventory are not always viable options.
Agrifood Sector Challenges
Agriculture and food sectors have always had to leverage some form of the JIT system due to the perishable nature of much of the goods being procured, processed, and shipped in the industry. Food items and other raw materials that have a short shelf life cannot be stored in large quantities over long periods of time, and increasing inventory of those items that can be stored has a ripple effect on warehousing logistics and insurance premiums. They must therefore be shipped in alignment with demand. In addition, localizing supply is only possible where there is a pre-existing capacity and environment for producing food materials. In order to localize, manufacturers are limited by the availability of local growers and of the local climate, which may not be suitable for producing all the necessary crops. As a result, organizations in the Agrifood sector are still at the mercy of the global supply chain.
The rapid changes in demand and reduced reliability of our global supply chain have not spared the industry, begging questions like ‘who is liable for recouping the costs of products that have spoiled in containers during shipping delays?’
There is no single answer to this question, as contractual agreements and insurance policies dictate liability on a case-by-case basis. For example, companies who have begun chartering their own air, rail, or ocean freight for the delivery of goods, as Walmart has, are more likely to be liable for the costs of wasted or damaged shipments than they were when outsourcing shipping.3 The same is true for growers who take on the management of their own shipping.
De-Risking Just-In-Time Shipping
Given the precarity of demand, delivery routes, container availability, and so on, the best way for parties at any stage in the agrifood sector to protect themselves against the volatility of supply chains, is to leverage the predictive capabilities of advanced analytics and machine learning.
Tools like FullConfidence by Stratizant are able to use advanced analytics to rate and predict the reliability of suppliers in order to minimize the vulnerability caused by precarious supply chains and changing demand. While these tools are useful for manufacturers in any sector, they are especially important for organizations that don’t have the options of managing risk by moving away from JIT systems with increases in inventory and localized supply.
For the agrifood sector, where climate and environmental considerations necessitate global sourcing of certain goods, and where food perishability limits inventory storage, JIT shipping and manufacturing is not going anywhere. Risk management requires better predicting and adapting to supply chain disruptions and changes in demand. That level of predictability is possible only with the best in machine learning technology.
Resources
Banton, Caroline. 2022. Just-In-Time (JIT): Definition, Example, and Pros & Cons. Investopedia. https://www.investopedia.com/terms/j/jit.asp
Vilsack, Tom. 2021. USDA Amplifies Farmers Voices and Concerns over Transportation and Shipping. USDA. https://www.usda.gov/media/blog/2021/04/19/usda-amplifies-farmers-voices-and-concerns-over-transportation-and-shipping
The Hartford Staff. 2022. Changes in Shipping Logistics Due to Supply Chain Disruptions. The Hartford. https://www.thehartford.com/insights/home-workplace-safety/supply-chain-shipping-logistics