Tuesday, February 11, 2014


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.

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.

2.     Frazelle, H. E. Supply Chain Strategy. New York: McGraw Hill, 2002.

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