Simplified Forecasting and Active Response

After reading these materials, I think the following two arguments about forecast in supply chain management are worth discussing. 

The first thing I want to mention is aggregate forecasts. To reduce the uncertainty of forecasts, it is essential to do aggregate forecasts. Apple makes a great performance in this respect. Choosing an Apple product is very simple for consumers because the core technology in almost every Apple product is the same. You can just think about color, size and memory then there comes with the product. By doing so, it is also easier for Apple itself to make predictions on its products. For example, most parts of the iPad are the same regardless of its differences in color, size and memory. Moreover, all of the products in Apple share some components with each other. Therefore, it is more efficient for Apple to do aggregate forecasts. However, in other companies, one of their strategies in marketing and supply chain is product variety. In order to meet with different customers, some companies are dedicated in offering multiple products. They may have sufficient and even complicated choices for different consumer groups. They also use differed technology on different products. For instance, many companies in China, especially for some creative start-ups, have complicated product line which requires correspondingly complicated forecasting methods. Nevertheless, most of them lack of matched supply chain management and get into trouble in this competitive market. So how could those start-ups make specific and effective forecasting on various products of technological innovation? 

Another thing I would like to discuss is about the goal of forecasts. Although we have a variety of forecasting methodologies applied to different companies. I think the goal of forecast is the same and is to determine how to adjust the strategy on products and management to the ever-changing market. This is extraordinarily important in any fast-moving sector where the demand of consumers and the supply of product mix changes. If a company made a prediction suggesting a disadvantaged position in future market, then it is time for the company to make a change. 

A good forecast should be timely and a good responding to the forecast need to be immediate. However, some companies in the world refuse to make any transformation or upgrading about their product though they have predicted and even witnessed a new trend of consumer’s behavior. Nokia serves as a typical example. As touchscreen devices has covered most of the mobile phone market, Nokia remains overconfident in its bar phone and is still unwilling to take measures to alter the core design of its product. In result, Nokia is fading away. The same story happened in Kodak. Under the approach of digital time, Kodak still stuck on traditional film market. Failing to take an action in transitions, this iconic industry leader in film market eventually went bankrupt. From my point of view, people seem to prefer positive anticipations and are inclined to take late corresponding measures under negative forecasts. And I think greed is part of their motivation because they are unwilling to give up previously dominant status in traditional market. Under an extremely negative situation of a forecast, how to avoid late and inappropriate respond might be a determinant for surviving and developing in the future.