When forecasting went wrong.

In our class discussion, we talked about how businesses rely on forecasting to formulate their strategies. We all know that forecasts are not perfect, they just give us an idea what the sales might be in the future. In most cases, companies would try to take all the outside factors into accounts while forecasting; however, what happens when you totally underestimated the impact of certain events?

It’s been more than three weeks since the Umbrella Revolution started in Hong Kong. The protesters occupied the financial district and some of the main shopping area in this small city. Countless retailers and restaurants have stood up and complained that how much loss they have during the protest.

This protest started just two days before the “Golden Week”, a week long holiday for mainland China to celebrate the National Day. The time when companies stock up and getting ready for the countless mainland shoppers. For small to midsize businesses, the owners complained that they are about to go out of businesses if the protest continues. These small/midsize rely largely on mainlanders and they are holding their inventories longer than they would like and since the Golden Week is now over, they are not optimistic about the inventories will be gone anytime soon.

This movement has been planing for more than one year and everyone in Hong Kong knows exactly when it was going to start. But it turns out most businesses have underestimated the impact of it. My questions are, how should a business forecast its sales under such events? What would you do about the forecasting for NEXT year?



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3 thoughts on “When forecasting went wrong.

  1. This is a really interesting post about forecasting in extraordinary events such as protests. The “Golden Week” is an event that goes on every year where the business sales increase. Knowing this the forecasting for products to be sold is going to be high. On the other side, the protest started only two days before the holiday. The protest would be an extraordinary event which I think none of the businesses has count an event like these while they were forecasting the sales for this year. The companies have already stocked up on products and now it is to late to change the numbers for the forecasting. But what happened this year, is probably going to change the forecasting for the next year. One question the businesses are going to take in consideration next year while forecasting for this holiday week is going to be: ” What if another protest happens next year too?”

  2. Wow. Great questions. I am not really sure what I would do in that situation. I guess for forecasting next year’s sales, I would have to skip that year and maybe pencil in that that year was a fluke? Like you mentioned earlier, how are businesses supposed to forecast such an event? I guess they could have gauged how the general attitude of the people who frequented their shops were, and then maybe make provisions on that…? This is really a quandary.

  3. Interesting forecasting questions. This may be oversimplifying, but I think a company needs to weigh how likely a situation like this is to happen again, and then they must respond accordingly. Treating unlike any other factor that impacts forecast would be a poor decision because it does impact forecasts the same way. We are not taught in school how to foresee movements like this but they clearly need to be recognized and responded to when possible.

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