Humans are not very good at doing this. As the last two years have proved, lots of people have hoped for the best and then planned for that best case. This has not turned out to be a very good approach.
In the good times, planning on everything turning out reasonably well and running lean with just in time deliveries can result in good return on investment and higher profits. Typically there are enough buffers in the system that small interruptions can be dealt with, so a week or two delay in shipping due to storms do not cause the system to break down.
Bigger interruptions however can cause major problems, but ideally the effect should be localized. Earthquakes obviously have a major local impact, but unless it hits a monopoly provider location, the impact should not be global. Obviously in an era of offshoring to cheaper locations, there has been a lot of concentration of industry, so the vulnerability to regional disruption is worse.
The downside to the optimization however is the lack of slack in the system. This is when planning for the best case causes problems. Hoping that a pandemic is going to fade away quickly is OK, but making plans on that assumption is not sensible based on the history to date. By now policy makers should be thinking and talking about how many more waves could occur, rather than scrambling to contain the current wave. How do we get the number of active cases in the population low enough that we can control the spread in the long term?
One effect that is starting to be seen is the effect on staffing. How organizations cope when 5% of the staff are off at any one time is a relatively solved problem, but when 25% to 35% are off there are no ready made answers.