In this lesson, you’re expected to:
– understand how demand forecasting is used in operations
– learn about commonly used forecasting methods
– explore the demand forecasting process
Demand forecasting is the basis for operations planning decisions
Forecasting is a process to predict future events that forms the basis for several operations planning decisions, such as those related to production, inventory, human resources, and capacity. Its use is applicable to every type of business, such as retail, manufacturing, services etc.
Some examples of the use of demand forecasting:
– Governments need to forecast the number of children in a region order to build or expand schools.
– A book retailer needs to forecast the number of books sold so that they can plan their inventory levels.
– A management consulting firm has to forecast the number of projects in order to allocate or hire staff.
Some decisions only need short-term forecasts, such as deciding how many newspapers should be ordered the next day or next week. On the other hand, capacity planning, such as building a new plant, should consider long-term forecasts.
Mature products, such as salt or milk, are usually more predictable and easier to forecast; however, some products, such as fashion goods, are unpredictable and difficult to forecast.
The essence of demand forecasting is analyzing its driving factors in the context of a specific product and market
For example, to forecast the number of children joining school within five years, one can think about the current birth rate, assuming 5 years old as the school-entering age, as shown in Figure A.
Forecasts are always wrong and the uncertainty level varies according to the level of aggregation and time frame
1) The time frame of the forecast
Long-term forecasts are usually less accurate than short-term forecasts, i.e. it is easier to predict how many units are likely to be sold within the next hour than within the next decade.
Aggregated forecasts are usually more accurate than disaggregated forecasts. This is because, in aggregated forecasts, the errors are sometimes canceled out.
A combination of qualitative and quantitative forecast methods can be used by bringing together expert judgement and predictive models. There are two main approaches to forecasting:
– Qualitative methods: based on opinions, past experience, and even best guesses.
– Quantitative methods: based on data.
It is important to note that no method will result in an accurate forecast.
2) Delphi Method
3) Scenario Planning
2) Causal methods
Source: Slack et al. (2010)
Enlarged version: http://bit.ly/2pWCzg6