Demand Forecasting and Its Benefits for Business

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Demand Forecasting and Its Benefits for Business

If a breakfast cereal company wants to introduce a new product in the market, it is reasonable to invest in forecasting demand. Here, the company should choose between quantitative and qualitative techniques. I would recommend using a simple moving average and market research approaches because they are suitable to present short-term demand. In addition to that, the methods can generate significant benefits when they are used together.

Jacobs and Chase (2014) state that the simple moving average is a time series forecasting model. This quantitative model focuses on the previous demand for related products. For example, the company under consideration can analyze week-by-week sales of another breakfast cereal to predict the future sales of the new product (Mitra & Majumder, 2019). The idea is to use an average value for the next forecast. However, this approach can present inadequate information because a new product is under consideration. That is why it is rational to support it with a market research technique that is a type of qualitative forecasting. This model implies identifying customers preferences and habits through surveys and interviews to estimate the market sentiment (Brillio, 2018, para. 6). Thus, the combination of the two methods is suitable to forecast demand because it draws attention to the previous data and tries to predict future changes in them. Furthermore, the two work well together because they are designed for short-term forecasting.

In conclusion, demand forecasting is a significant step for every business that is going to introduce a new product. As for the breakfast cereal company, it can utilize simple moving average and market research techniques. It is so because the combination of these approaches allows the firm to analyze the previous demand data with the help of quantitative forecasting and adjust them to the market through the qualitative one.

References

Brillio. (2018). Choosing the right forecasting technique. Web.

Jacobs, F. R., & Chase, R. (2014). Operations and supply chain management (14^th ed.). McGraw-Hill Education.

Mitra, S., & Majumder, A. (2019). Quantitative and qualitative forecasting techniques in logistics management. Project Guru.

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