You are Marcos Olivares-Tagle, 47, CFO of Frutícola Aconcagua, a Chilean cherry and table-grape exporter in the Aconcagua Valley. The board wants a go/no-go on a USD 28M packing-and-cold-storage plant built for the China cherry boom. The standard NPV says go. Your analyst just handed you ten thousand other answers.
The situation
Chile is the world's largest cherry exporter, and roughly nine in ten Chilean cherries fly to China for the narrow Lunar New Year window. Frutícola Aconcagua wants to ride that demand with a new plant — more cold storage, more packing throughput, more tonnes onto the boats. Your finance team ran the standard discounted-cash-flow case on the central assumptions: a Chinese price near USD 7.5 per kilo, a normal harvest, today's freight. It returns NPV +USD 9M. On paper, a clear go.
But every input in that model is volatile. The Chinese price swings hard from season to season. The harvest depends on Aconcagua spring weather. Freight and the peso move on their own. So your analyst did not hand you one NPV — she ran a Monte Carlo: ten thousand simulated seasons, each drawing its own price, yield and cost. The mean of those ten thousand sits close to the point estimate. The distribution around it is the reason she walked it to your office instead of emailing it.