Supply chain features

Our goal in this chapter is to understand commonly observed supply chain structures and discuss their potential impact on performance. Key supply chain features include the number of links in the chain, the locations where capacity is shared, the level of flexibility of the entities and their impact, the impact of chain structure and capacity, the impact of uncertainty on performance of the network and finally, how country boundaries interact with flows across the chain. 

The consequence is the loss of a customer segment. This is because the focused competitor does his homework not only on the supply chain features needed, but also on the economics of delivering those features. Very often, this segment is the most profitable otherwise, it would not have attracted the competitor. This process can occur over a long period as a slow-moving erosion of market share. Often, however, the market takeover can be dramatic — executed by an upstart company already in the industry or a start-up outside the industry. 

Growth As the market expands, winners have been sorted out on base product features and less so on supply chain features. Profit margins are high. The principal supply chain mission is availability. 

The model has been around for a long time, and many readers will be familiar with it. The model helps us understand the relative importance of supply chain features, as distinct from product features, to product success. 

At the center of the QFD approach is the house of quality shown in Figure 6.3. The house encapsulates what is known about customer requirements, their importance, and the supply chain features needed to meet those requirements. 

The how is a list of supply chain features. If QFD is to measure the current supply chain, then these could represent the existing (as-is) supply chain. In the design process, the hows can be the features in the to-be supply chain. This will help assure that the new supply chain has all the features needed to satisfy the customer. A how in the coffee business might include product variety and the interior design of the stores. Another result should define needed flexibility as described in Section 3.5.2. 

The correlation matrix indieates reinforeing or eonflieting supply chain features. An example might be the eonfliet between eostly inventories to provide short turnarounds in a responsive supply ehain and the need for cost reduction in an efficient supply ehain. 

In the last chapter, we examined three frameworks, or models, that offer different ways to think about supply chain strategy. The model described in this chapter uses the "product life cycle" to define the product s position in its competitive market. The model helps us imderstand the relative importance of supply chain features, as distinct from product features, to long-term product success. It also brings into play the notion of time-criticality in supply chain innovation. As George Stalk noted in his article, time can be the dominant element in a strategy. 

The supply chain features, as we noted in Chapters 1 and 2, are part of what we have called the "extended" product. Competitor imitation or lapses of patents eventually enable competitors to imitate the physical features of the product itself. Extended product and supply chain features, in turn, often become the principal basis for competing. 

The market expands. The winners have been sorted out based primarily on product and, to a lesser extent, on supply chain features. 

An example used in some training sessions is a cup of coffee. The "whats" for a cup of coffee can include both product and "supply chain" features. Product features include the size of cup, the temperature of the coffee, the insulating wrap aroimd the cup, and the type of beans used to make it. The supply chain features include options on serving size, promptness of service, and ambiance of the location. Starbucks is an often-cited example of using ambiance to turn a very fimctional product into an innovative one. 

In the case of coffee, market research might find the customer weighs both product and supply chain features. For example, type of coffee might be the most important quality earning, for example, a 40% weighf, and ambiance second wifh 20%. Complexity is added when considering the requirements of differenf customer segments. 

A distinctive feature of these metrics is that they can be stacked along the whole product supply chain. In this way, ecological bottlenecks can be identified readily. For example, a chemical product that might appear as benign for the environment, could involve, in reality, highly toxic materials in some intermediate steps of manufacturing. 

What the project must achieve is total security of production, public education (particularly health professionals), security of supply chain, effective monitoring and keeping features updated. 

In the previous chapters isolated planning problems in chemical industry are described, reviewed and modelled. These approaches allow analysts to model typical chemical production processes and logistical planning problems in chemical production networks. Chemical production networks consist of many chemical plants clustered at chemical production sites. Such networks can be seen as an important part of chemical supply chains (SC). In the scientific literature, there is no unique and concise definition what a SC is, but some common features are prevalent in most definitions ... 

The models and arguments in this section are mostly based on Watson et al. (2013) s book [4]. Location problem are very diverse. American Mathematical Society (AMS) has specific codes for location problems (90B80 for discrete location and assignment, and 90B85 for continuous location) [2]. General location problems include customers and facilities to satisfy customer demands. Facility locations problems are classified as discrete and continuous ones. Here, we are interested in discrete facility location problems. Also problem distinction is based on being capacitated or not. Melo et al. [2] identify four core features to be included in a facility location model to use in supply chain decisions ... 

This model reflects a physics perspective, however this model might not fit a regular supply chain design since objective function employs a second degree penalty for unit distance travelled. However, gravity location model can give insight for potential location areas. Every model is an abstraction of reality that comes with assumptions. This model is no exception. This model does not take into account the physical features of location areas, i.e. mountainous or not, proximity to labor force or required infrastructure etc. 

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