Matching the supply and
demand in the supply chain is a critical challenge. Planning and managing
inventories in a supply chain provide the solution to reduce cost and provide
the required services level. It is of a paramount importance to take on board
the inventory holding and set up costs, lead time, and lead time variability as
well as to forecast demand.
Forecast for demand in
supply chain was part of issues we discussed in the last week class. We
discussed various issues concerning product design for operational
effectiveness and the supply and demand in the supply chain. The last issues in
the class discussion were the three rules of inventory management, the first
rule is forecasts are always wrong and forecasts can’t match the exact demand.
The second rule of
inventory management is that the longer the forecast horizon, the worse is the
forecast. The implication of the second rule is the accuracy of weekly forecast
decreases as the forecast horizon increases. The third rule of inventory
management is that the aggregate demand information is always more accurate
than disaggregate data. It is obvious that the third rule address that the
aggregate demand data have much smaller variability which is the basis for risk
pooling concept to enable lower the level of inventory without affecting
service level.
In inventory management relies
much on accurate forecast of demand. Therefore forecast plays a key role in
planning and management of inventories in supply chain as a result the
researchers have come out with various tools and methods to ensure that
forecast provides more accurate data on demand through the use of forecast
analytic models. The main objectives of forecast analytics are:
•Improve
the understanding of product characteristics based on historical analysis
•
Provide sustainable forecasting processes and models
•
Provide a process for forecast algorithm selection
•
Provide initial set of optimized forecast model parameters
•
Provide a process of promotional impact analysis
•
Provide replenishment strategies for slow moving products
The diagram below show the
high level analytics roadmap
Forecasting to Planning and Managing Inventories in
Supply Chain
The logic connection
between issues concerning forecast and this week readings on planning and
managing inventories in supply chain made me to retrieve the rules underpinning
the forecast and its relationship with planning and managing inventories. The diagram
underneath (Frazelle, 2002) incorporates measure and improves forecast accuracy
as the foundation of the return on inventory. He pointed out that throughout
his experience and all the researches he did on this field he has come out with
five initiatives that lead to an increase in return on inventory as well as
increase in inventory availability concurrently which are:
1.
Improved forecast accuracy;
2.
Reduced cycle times;
3.
Lower purchase order/setup costs;
4.
Improved inventory visibility; and
5.
Lower inventory carrying costs.
These initiatives are
depicted on the diagram below.
Source: Supply Chain
Strategy – Edward H. Frazelle, Phd
These
five initiatives make the foundation of a lasting progress in management of
inventory in supply chain management. Most inventory managers are facing with
the challenges of ensuring that efficient inventory levels are in place in each
of the following inventory categories. The major issue here is to ensure that
inventory levels are minimized and at the same time satisfying customer service
requirements.
Conclusion
The
planning and management of inventories in supply chain is the backbone of the
company’s performance therefore for the process on managing inventories to work
there should be a good forecasting methods that enable the company to make a
proper plan and hence management of inventories to ensure that the company
obtains return on inventories.
REFERENCES
2. Frazelle,
H. E. Supply Chain Strategy. New York: McGraw Hill, 2002.
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