High Demand Variability

For products with fluctuating demand, postponement is an effechve long term strategy. Tactical strategies include improving forecast accuracy, increasing raw material and product visibility and document automation. 

A winning procurement strategy for products with high demand variability is to buy globally from fhe lowesf cosf counfry and handle demand variability through spot purchases from local sources. This is similar to FlP s portfolio strategy to handle supply risk we discussed in Section 7.7.2. 

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With low forecast accuracy and/or high demand variability, companies usually have to increase safety stock levels or transship products from one warehouse to another, on an expedite basis, when a warehouse is short of inventory, otherwise they will lose profit margin and become less competitive. However, these operational initiatives despite allowing companies to achieve the required service level, hurt operational efficiency and increase supply chain costs. 

Low forecast accuracy (e.g., less than 50% FA at SKU level) with high demand variability. 

Several companies have been implementing forecasting tools and processes to improve demand planning performance, but these initiatives were not enough to eliminate OOS problems, and improve supply chain efficiency, due to a mismatch between supply and demand, low forecast accuracy for medium and low volume products, high demand variability and/or high number of new product introductions. 

The effects of information sharing are particularly remarkable if demand is high, demand variability is high and if lead times are long (Lee et al. 2000). 

For example, the higher the demand variability and imcertainty, the greater the need for buffers. Buffers can be in the form of spare capacity, inventory and order lead times. If we want to shorten the time the customer has to wait, then it is necessary to make speculatively - perhaps finishing off (customising) the product once the final order details are known. Finally, planning and controlling the flow of materials across the supply chain needs to be carried out centrally when in high demand variability and uncertainty conditions in order to coordinate the response of supply partners. In more stable demand conditions, it is possible to relax controls and allow more local flexibility. 

The fact that certain human adults or infants develop types of anemia which respond to small doses of folic acid can be interpreted to mean that, for reasons which doubtless have some genetic basis, these individuals have unusually high demands for this vitamin. Presumably they develop the disease when consuming diets that do not induce the disease in others. Folic acid needs are (for one reason or another) highly variable from individual to individual among patients as is shown by the fact that many patients will respond to as little as 0.5 mg. folic acid per day, whereas others will not respond at all... 

Power rate structures vary from area to area. A common rate structure is a variable one with high power costs during high-demand periods and lower costs during the lower-demand periods. In these circumstances, it may be appropriate to shut noncritical equipment down or turn down equipment and supplement from backup liquid. The power rate contract should be understood and the equipment optimized with this in mind. 

Peak Power - Power generated by a utiiity unit that operates at a very low capacity factor generaiiy used to meet short-iived and variable high demand periods. 

Tests performed on the raw data show that the one-one method greatly amplifies demand variability of end consumer throughout the supply chain, especially when the demands have a high degree of randomness. In this context, the application of multiagent model, with other forecasting methods, markedly reduces the Bullwhip Effect generated. 

The efficient supply chain. This supply chain is focused on the lowest cost/case. There are five characteristics. Demand and supply variability is predictable, volumes are high, supply chain reliability is high, demand-shaping activities are low, and the raw material costs are stable. 

The responsive supply chain. The responsive supply rhain is designed for short cycles. This supply chain has high volumes, but also high demand and supply variability due to factors like seasonality, weather, short life cycles, and high levels of demand shaping in the channel. 

Based on demand variability and sales volume, planners understand SKU profile and apply appropriate forecast methods (same as in level 2) for SKUs with low variability, and make to order strategy (pull system) for SKUs and customers with high variability (less than 50% of sales volume). 

Management has a clear focus and goal to reduce demand variability due to end of the month loading process, price discount to high volume customers or special consumer promotions (actual performance shows less than 40% variation between high and low peak weeks during the month). 

For Statistical Forecast, it is important to define a process to formally analyze and cluster the SKUs sold in different customers and channels based on sales volume and demand variability, in order to apply an approach that combines statistical forecast for SKUs with low variability and actual POS demand information for SKUs with high variability. It is also suggested to implement a root cause analysis to map and understand the reasons of low forecast accuracy by SKU, and then, implement an effective action plan to fix the problems. 

Product with high demand uncertainty or forecast errors During the growth phase of a new product, the demand variability is very high. Since risk pooling reduces the variance of the demand, it can reduce the safety stock for the same level of service or increase the service level for the same amount of safety stock. 

When the demand frequency is more than twice the periodic proof-test frequency, the application should be considered a high-demand mode application. Therefore the equations and techniques that use test interval as a key variable are not valid. In effect, one cannot take credit for periodic inspection unless it is done very frequently. Credit may be taken for diagnostics that cause the device to fail to the safe state (i.e. automatic process shutdown on any detected dangerous failure) in the high-demand case, as long as the diagnostic time period plus the time necessary to safely return the process to a safe state is less than the available process safety time (the time period between initiation of a demand and the hazard). 

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