Just in time (JIT) is an inventory system designed to efficiently match raw-material orders with production schedules, in manufacturing and/ or shipping a given product. The idea is to move the precise amount of material into the production process, warehouse or to the customer, ‘just in time” to be used.
Receiving goods only as they are needed reduces the cost of storing excess inventory, and requires producers to forecast demand accurately. This compares to “just in case”, an earlier method of inventory control whereby producers always kept enough inventory to meet periods of high demand.
JIT has become ubiquitous in today’s consumer economy. Examples include car-parts assembly plants; food distribution networks where fresh produce must be grown, stored, refrigerated and transported to maintain peak freshness; container shipping where goods are transported in multiple modes – ocean carrier, train and/or truck – then arrive at a port to be loaded onto a vessel with minimal delay; and Amazon, which revolutionized online commerce through a highly efficient and robotized system of packaged good delivery. Imagine the coordination that goes into an Amazon Prime customer receiving a package ordered the same day.
For most companies, most of the time, JIT works very well, as long as there are minimal disruptions to the chain of supply, all the way from the material in its rawest form, down to the finished product that is delivered to the end user. It is for the most part an efficient, cost-effective, common-sense way to run a business.
Enter a disruption, however, and the average JIT system falls apart quickly, and spectacularly. A good analogy might be a chain-reaction crash on a highway during a snow storm. The damage from one car sliding into a ditch is minimal and easily contained. Add 20 cars all traveling in the same direction not far behind one another, and an accident involving the lead car turns into a multi-vehicle pileup with many people injured and several cars damaged or written off.
When JIT fails, the negative effects on production lines, delivery schedules and especially on a company’s reliability, can have a severe impact on operations and involve a number of unexpected and hidden costs or fees.
Investopedia gives a good example of Toyota’s JIT system coming to a screeching halt in 1997 due to a fire at an auto-parts supplier. The fire decimated Aisin’s ability to produce P-valves. The weeks-long shutdown at Aisin caused Toyota to halt production for several days. However the worst part was the ripple effect. Because Toyota relied on P-valves at a certain point in the assembly process, all the other Toyota parts suppliers also had to shut down because the automaker couldn’t use their parts during that same period. The fire consequently cost Toyota 160 billion yen ($) in revenue.
Covid-19 and JIT
Over the past couple of months we have been reading regular news reports about how the new coronavirus, Covid-19, has impacted supply chains. No surprise, considering that China, the epicenter of the outbreak, accounts for 35% of global manufacturing output, has been the world’s largest goods exporter since 2009, and in 2013 became the world’s biggest trading nation. Arguably, considering China’s heft in the world economy, the coronavirus outbreak couldn’t have happened in a worse country.
Economic fallout from Covid-19 continues to worsen. On Monday Oxford Economics downgraded China’s annual growth projections this year to 4.8% – the worst in decades. The OECD issued a report saying that the outbreak could ding global economic growth by half a percentage point, putting it at 2.4%, in a best-case scenario. (global growth last year was 2.3%, the worst in a decade)
by Richard Mills for Ahead of the Herd