Are Historical Patterns of Demand a Good Indicator of Future Demand?

Historical demand patterns can indicate future demand where the demand for the organisation's products or services has been stable. In time series analysis, the fundamental assumption is that future forecasts are based on past demand patterns. This works well in mature markets where products or services have been available for a period that has allowed historical demand data to build.

However, the only thing that can be said for forecasts is that they are incorrect. It is rare for a forecast to be 100% correct. However, forecasting is fundamental to the organisation's manufacturing demand and inventory planning management procedures and processes.
 
Organisations and their suppliers work together by eradicating, where possible, the commercial risks of long-term inventory and manufacturing demand planning by identifying and eradicating issues such as products or services with long lead times or where the price of products or services only becomes viable where long production runs reduce prices down to a sustainable level through economies of scale.
 
This is an issue where MRP principles are used to place requirements for materials in advance, which takes lead times into account. Lead times for two sequential MRP items with lead times of 12 weeks each means that inventory planning horizons could stretch beyond 24 weeks if the second item can only be produced when the first item has been manufactured.
 
Long lead times can mean that purchase orders need to be placed so far in advance for these products or services that demand becomes impossible to forecast with a high degree of accuracy, the result of which is that high levels of inventory are built up, which increases the capital tied up in stock and the commercial risks of obsolescence.
 
The longer the forecasting period, the greater the commercial risks become, with most organisations carrying out forecasting at Stock Keeping Unit (SKU) level for no longer than a month in advance or the length of their longest lead-time item.
 
Organisations plan at an aggregate level for periods longer than this to measure the demand for the whole organisation's products or services. Organisations use this data to plan their productive capacity and to secure production time with their suppliers of manufactured parts and sub-assemblies. Actual demand is confirmed near the required delivery date by placing purchase orders detailing the product, price and delivery date needed.
 
The manufacturing industrial sectors have developed tools such as Just In Time (JIT), materials planning requirements (MRP i & ii), kanban and Vendor-Managed Inventory (VMI) as ways of managing the demand for raw materials, parts, and sub-assemblies.

In some cases, the commercial risks of inventory demand planning have been pushed back onto the supply base, where suppliers are made responsible for planning the requirement for the products or services that they supply in exchange for a commitment with the parent organisation of a long-term supply partnership where mutual trust and product development initiatives are shared. This is a typical example used by the car industry.
 
Organisations that use just historical demand as the primary input into their manufacturing and inventory demand planning processes are placing themselves at a greater commercial risk than those that use a mix of planning methods, three other examples of which are:

• Qualitative: using intuition or opinions as an input to planning processes.

• Casual: using assumptions that demand is strongly related to certain factors.

• Simulations: that combine casual and time series methods.

Historical demand data is a powerful source of information when planning manufacturing and inventory resources and works well where the demand for an organisation's products or services has been stable for many years and where the accuracy of historical demand data can be relied on but to use just one planning method alone places a greater commercial risk on an organisation, most organisations use two or more methods of planning which decreases the commercial risks on relying on just one method.

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