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.
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