Just in Case 2020

A hundred-year storm is defined as a weather event with just a 1% chance of happening in a given year. These days, the term is fairly devoid of meaning, with once in a hundred year floods ravaging cities every few years or even multiple times per year. These increasingly unpredictable weather patterns have forced us to move away from probability based weather predictions towards hyper-local real-time weather forecasting.



The year 2020 is seemingly on track for a new once in a hundred year disaster happening each month. And the agriculture industry is almost always impacted in some way. In Beirut, where ammonium nitrate recently caused a tragic explosion, 120,000 tons of grain silo capacity were lost and 15,000 tons of grains were evaporated. Lebanese companies must look for creative ways to source grain to maintain their business. 3,000 KM from Beirut, a feed mill in Belarus needs to reassure its suppliers that the volatile political situation will not affect their ability to pay.



What happens if your company is one or more steps removed from the crisis? If ammonium nitrate, a very potent fertilizer, is being used by any of your suppliers, their costs may increase due to increased delivery insurance. If your feed additives customers have a significant market share in Belarus, their exposure to risk may have just increased. If you rely on a single supplier from Wuhan, you’ve likely experienced this already.



As I’ve written previously, one way to manage our supply chains in these times is to increase the amount of inventory that can be quickly accessed. Just-in-case solutions can be very costly however, not only for the basic cost of the inventory, but for management costs including touch labor, accountability, auditability, and shelf life concerns. Of course the most costly scenario we face is the complete interruption of supply during a global crisis.

With the cost of doing business going up in an increasingly unpredictable world, we need access to better data for decision making. Like with weather forecasting, it is no longer enough to make predictions based on past patterns. Our industry needs access to data that is hyper-local and real-time, because the next once in a hundred year event could be as soon as tomorrow.