Motivational obstacles, Information processing problems...

Motivational obstacles

They refer to a situation where motives offered to different supply chain counterparts lead to actions that increase variability and reduce overall supply chain profits.

Obstacles, which focus only on local effects, result in decisions that do not maximize the total supply of the supply chain. For example, if the motivation of the transportation manager is related to the average cost per unit of transportation, it is likely to act so as to reduce the cost of transport, even if the storage costs are increased or the level of customer service is reduced. Naturally, any participant in the supply chain acts in such a way as to optimize the performance indicators for which it is valued.

Also, the improperly structured sales promotion system is a significant obstacle to coordination in the supply chain. In many companies, sales promotion is based on sales for a given period (month or quarter). Sales, as a rule, measured by the manufacturer, represent the quantity of products sold to distributors or retailers (resale), but not the quantity of goods sold to end-users (external sales). Performance indicators based on resale are often justified by the fact that efforts in sales of the manufacturer do not regulate external sales. Stimulating the sales department based on domestic sales, therefore, results in a variability of the order significantly greater than the variability of the consumer demand in retail.

Information processing and whip effect

Information processing problems refer to situations in which the required information is distorted as it moves between the various links in the supply chain, leading to an increase in variability in orders (stocks) within the supply chain.

When forecasts are based on orders received, any change in customer demand will be increased as orders move up the supply chain to producers and suppliers. This is the manifestation of the so-called whip effect in supply chains [19, 89, 122, 129-131]. Each link considers its main role in the supply chain as fulfilling orders from partners downstream. Thus, each link judges their needs for the flow of orders received and generates a forecast based on this information.

In this scenario, a small change in customer demand becomes exaggerated when moving up the supply chain in the form of customer orders. Consider the impact of a random increase in customer demand from the retailer. The retailer can interpret part of this random increase as a trend of growth in demand. Such an interpretation will result in the retailer ordering much more than the observed increase in demand, as it expects that growth will continue in the future and, thus, orders will cover the demand expected in the future. The increase in the order placed by the wholesale company is also greater than the observed increase in the retailer's need. Part of the increase is a one-time increase. The wholesale seller, however, does not have the ability to correctly interpret the increase in the order. He simply watches the jump in the amount of the order and makes a conclusion about the growing trend. The growing trend implied by the wholesale company will be greater than the trend implied by the retailer (recall that the retailer increased the order volume to match future growth). The wholesale seller, therefore, will place even an even larger order to the manufacturer. As we move up the supply chain, the order size will increase more and more.

Now suppose that the period of random growth in demand will be followed by a period of accidental fall. Using the prediction logic just described, the retailer will predict a falling trend and reduce the size of the order. This decrease will also become increasingly significant when moving up the supply chain.

The fact that each link in the supply chain predicts demand based on the flow of orders received from downstream links results in increased variances in demand as we move from retail to the manufacturer.

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