How do you ensure that you are using the appropriate forecasting methods for your business?
Selecting the right forecasting methods can be highly critical in how accurate your forecasts are. Unfortunately, there isn’t a golden ticket to forecasting which can essentially ensure accuracy. While the best-fit forecasting method is dependent on a business’ specific situation, understanding the types of forecasting methods can aid in your decision-making.
Types of Forecasting in Supply Chain Management
There are many types of Forecasting methods and techniques in Supply Chain Management; however, all these types can be broadly grouped into three major categories as outlined below:
Also known as the Judgmental type of Forecasting, this method relies on the opinion of experts in predicting the future. Some of the examples of Qualitative Forecasting are Delphi technique, Salesforce opinion, and Market research.
Extrapolative Forecasting is a type of Quantitative Forecasting technique, which uses time series methods to project demand based on the past sales of a specific product category under normal conditions. Some of the examples of Extrapolative Forecasting are Moving average method, Weighted moving average, and Exponential Smoothing.
Some of the examples of Causal Forecasting are Barometric technique, Regression analysis, and Econometric technique.
Components of Forecasting in Supply Chain
For each of the forecasting categories listed above, the factors that influence the future demand include:
- Historical sales data.
- Various lead times like purchasing, manufacturing & shipping lead times.
- Planned advertising and marketing efforts.
- Planned pricing discounts and rebates.
- Operating business scenario.
- Market intelligence and competitor moves.
Additionally, in selecting a forecasting method, here are some general forecasting characteristics to keep in mind.
Characteristics of Forecasting in Supply Chain:
- All forecasts have inherent errors due to assumptions and hence are always inaccurate. Forecasts thus need to include the expected value of forecast, range specifying the minimum and maximum forecast and a measure of forecast errors.
- Short-term forecasts are generally more accurate than long-term forecasts. Forecasting process includes consideration of factors which can influence future demand. Hence, the short-term factors are more predictable than long-term.
- Aggregate forecasts are generally more accurate than individual stand-alone forecasts due to a lower standard of deviation. Disaggregated forecasts have limited biased perspective.
- In general, farther up the Supply Chain, a company is, the greater is the distortion of information it receives. Hence, for such companies, agile systems can respond better to forecast inaccuracies.