Growth, and more generally trends, needs to be taken into account in order to deliver accurate demand forecasts. However, growth; as a statistical pattern, proves to be more difficult and more elusive to capture than other well-known patterns such as seasonality.
Forecasting demand for existing products is difficult enough. But forecasting for radically well performing products is a happy dilemma that can derail even the most experienced supply chain practitioner. Why? Because there are no past trends to reassuringly extrapolate into the future and there are many factors that can affect whether the growth will in fact be sustainable or not.
In this episode, we discuss just why forecasting for growth is so difficult and what can actually be done in order to have some degree of confidence in purchase decisions. There are many different ways that a company can grow and quite often a business doesn’t exactly know when it will grow, increasing the complexity of forecasting.
Sometimes, as is human nature, managers tend to be too optimistic when predicting their future growth. As a consequence, a major problem with forecasting for too much growth is the valuable revenue that is wasted on stock that cannot be shifted. This can happen to even the largest and most successful companies such as H&M who reported $4.3 billion dollars of unsold stock in March 2018. How can this be avoided?
This week on LokadTV, we try to understand what growth patterns look like, so that a company can better anticipate its stock needs. We also discuss in more detail why statistical patterns work best with uncertainty.
To wrap things up, we explore what clues a company should be looking out for so that they may understand whether the product they are forecasting for is going to present a hit or a miss scenario for them and how they should therefore respond to such a scenario.
00:27 What problems do companies face when forecasting for high-growth scenarios?
01:15 What different kinds of ways can companies grow?
04:05 How should you respond to a hit or miss scenario with a product?
05:43 What other problems can occur when trying to forecast growth?
07:59 A company might know it’s going to grow, but not exactly when. What can be done to counter that?
09:21 There’s no guarantee that your product will succeed, how do you forecast such a scenario?
14:12 What kind of clues can a company look out for to know that they’ll enter into a growth period?
15:14 Could website visits and statistics be included in forecasts?
16:22 What can a company do to be best prepared if they’re growing exponentially?
18:12 What happens in the real world? Do people often over-forecast their growth?
21:09 What’s the core message for businesses to take away from this?