Just-in-time (JIT) manufacturing began in Japan in the 1970s and has remained an often-chosen model around the world since then. It revolves around only producing goods on an as-needed basis instead of too far in advance. This model eliminates stock excesses and often makes companies more agile, but it’s also becoming increasingly challenging.
Factors such as the COVID-19 pandemic, economic uncertainty, and long-term supply chain shortages have made it difficult and sometimes impossible for companies to keep succeeding with the JIT model. However, there’s a better option made possible with cloud-based modeling.
Cloud Models Enable Demand Planning
When manufacturers use cloud-based platforms, all authorized users can access the relevant data from any compatible, internet-enabled device. That easy accessibility allows producers to get the data they need to match manufacturing output to customers’ demands. The resulting data-driven forecasts minimize stockouts and excess while keeping customers happy.
Given how demand planning works, it’s easy to see how it complements JIT manufacturing. Cloud models help decision-makers reach the necessary conclusions so they can keep the stock that’s most likely to sell on hand.
People build effective models by studying various consumer trends, seasonal fluctuations, and other factors that influence how well things sell. Cloud platforms support that kind of intensive data analysis because they keep the information readily available.
It’s also usually relatively easy to make the data more digestible to people who may not work with it frequently, such as C-suite executives. Complementing business intelligence (BI) tools allow people to create charts and graphs or add annotations to clarify critical information and promote better understanding.
Data From the Cloud Supports a Shift Away From the Pure JIT Model
Manufacturers hoping to successfully use the JIT model must navigate a couple of challenges first. One of them relates to supply chain shocks. However, savvy producers can often mitigate those by partnering with reliable suppliers. Otherwise, severe shortages could halt production and cut into profits.
Additionally, today’s producers must figure out how to cope with surges in customer demand. These are the two main reasons why sticking to a purely JIT model is increasingly unrealistic.
However, some experts advocate for moving away from traditional just-in-time approaches to something called just-in-case (JIC). It centers on planning for various scenarios. The goal is to figure out what a company must do to come out on top if the worst occurs.
Some manufacturing leaders may already do some of the things often recommended within the JIC model. Making supply chains more sustainable requires identifying all wasteful aspects. A manufacturer using the JIC model may do that by sourcing supplies closer to where production occurs. Then, there’s less transportation-related waste.
When people can refer to cloud-stored data, they can also make better predictions about how to stay resilient despite future challenges. In one example of what’s possible, researchers at the University of Delaware examined how climate-related shocks could affect the global food supply. They evaluated factors such as algal blooms, floods, droughts, extreme heat, and coral bleaching to see whether those issues cause ripple effects in the supply chain.
The End of JIT as We Know It?
Just-in-time manufacturing has been a staple in the industry for decades. Therefore, it’s likely premature to say it’s wholly a thing of the past. Instead, people should look forward to its evolution. The JIT approach is like most other aspects of manufacturing in that it must change with the times to remain relevant and valuable.
Some manufacturers may find the JIT model still suits them, despite all the fluctuating circumstances that can often wreak havoc. However, if they keep using it, they’ll almost certainly find that access to cloud platforms and data makes things more manageable.
Besides making the information more accessible, many cloud tools have built-in data analysis and visualization features. Such resources aid decision-making and help people feel more confident in what they opt to do. For these reasons and others, people should expect a prominent shift towards cloud modeling from parties that previously used JIT manufacturing without cloud computing.
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