Supply chain aggregators

The aggregated effects of the Old supply chain exceed those of the Next Generation supply chain, because the former aggregates more (positive) individual effects. For example, the Current simulation model has 14 dummy factors (which have zero effects), so the first sequential bifurcation step gives a smaller main (group) effect for the Current model this effect is 7,101,983, whereas it is 15,016,102 for the Old model. 

For solid dosage forms, scale-up is a major challenge and includes ensuring the bioequivalency of the clinical product to the commercial product. For proteins, shear-induced aggregation can be an issue, as well as establishment of a commercial supply chain that is robust, reliable, and able to deal with large amounts of temperature-controlled materials. 

Singhvi A. and Shenoy U.V. 2002. Aggregate planning in supply chains by pinch analysis, Trans. IChemE, part A, September. 

However, if we prioritize access to capacity for product 1 (which has a higher variability), then the new lead times, using the formulas provided earlier, would be Z, = 1.12 and L2 = 4.03 days. With these lead times, notice that the corresponding safety stock for the first product would be 272.55 units (which decreases from the earlier case), while the safety stock for the second product would be 103.15 units (which increases from the earlier case). Note that the total inventory across both products is now 375.72 units. This decrease in inventory reflects the benefit of tailoring access to the supply chain based on product demand characteristics. Notice that giving priority to the more variable product permits its lead time to decrease, thus decreasing the safety stock for that product. But clearly this comes at a cost to the less variable product, whose lead time increases but at a slower rate. Thus, we have traded off lead time customization for an aggregate decrease in the overall inventory. 

As products flow along the supply chain, the prices for one entity become the costs for the next. Thus, for the commercialization of new technology, the word cost has different meanings for producers and users. For users, the price and cost of a product or service are the same. For producers, however, cost is the expense incurred to produee a product or supply a service. To earn a profit and a return on investment, the producer s aggregate costs over time must be lower than the aggregate revenue. Time becomes the key element in the equation. In the short run, costs are often higher than prices but there must be an expectation that, in the long run, prices will exceed costs. 

In phone interviews, as the leaders think through their answer, they will often cite Apple s dominance in high-tech innovation, DelTs leadership in defining new business models, and Toyota s definition of lean processes. However, when the pioneers are pressed to name a single leader, one name is usually mentioned followed by silence P G is seen as the year-over-year leader by the pioneers. Apple is the second most often mentioned and Dell is third. The aggregate response of the supply chain pioneers is shown in Figure 1.9. 

Pull based supply chain strategy, usually suggested for products with high demand uncertainty and with low importance of economies of scales, which means, aggregation does not reduce cost, and hence, the firm would be willing to manage the supply chain based on realized demand. 

When there are a large number of client requests, a supply chain monitor can aggregate some requests to potentially improve overall system performance while increasing the latency of individual client requests. Further benefits can be obtained by processing these results as they arrive since a server may provide replies to some clients earlier than if it delayed providing a response until after the entire answer was obtained. 

As stated at the beginning of the chapter, the success of a manufacturing supply chain depends on its ability to accurately forecast customer demands and plan the production process to meet those demands in time. So far in this chapter, we discussed the forecasting principles and several qualitative and quantitative methods for demand forecasting. Based on the demand forecasts, aggregate production planning is done to plan the production. 

The aggregate planning problem is basically a medium range tactical supply chain problem. There are primarily three aggregate planning strategies a company can follow. 

As we discussed earlier, aggregate production planning is a tactical decision in supply chain management. Production scheduling is an operational decision. It is important to understand the key differences between the two, with respect to the time horizon and the level of detail in the production plan. 

Bullwhip effect results in poor aggregate production plans that lead to increased safety stocks, reduced customer service due to shortages, increased transportation cost, and inefficient allocation of resources (labor and equipment). By increasing the communication of actual downstream demand and collaboration between trading partners, the bullwhip effect can be minimized. One such collaborative process is known as collaborative planning, forecasting and replenishment (CPFR). Refer to the appendix in Chapter 3 of this book for a detailed description of the bullwhip effect in supply chains. 

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