Efficiency Ratios and Evlauating Supply Chain Processes Research Paper

Pages: 3 (1277 words)  ·  Bibliography Sources: 3  ·  Level: Master's  ·  Topic: Business


[. . .] Sharma and Bhagwat (2007b) regard the first model to be ideal for the prioritization and selection of the ideal metric and measure to support everyday organizational operations. But others contend that it is theoretically unstable, thereby potentially resulting in modifications in the preferences of the decision-maker, as pairwise comparison metrics cannot thoroughly fulfill the consistency AHP demands (Cao et al., 2008). Additionally, Sharma and Bhagwat (2007b) extended the last of the three aforementioned models and incorporated AHP in the determination of measures to be included and the corporate level (i.e., operational, strategic, or tactical) at which to integrate them. The BSC model is criticized for its exclusion of individuals, industrial social and environmental elements, and competitive scenarios (Barber, 2008).

Gomes and colleagues’ 2004 review led to the conclusion that the BSC frame is more of a strategic instrument instead of an authentic and comprehensive system for measuring performance. The SCC- (Supply Chain Council) formulated SCOR describes the supply chain process as being an integrated process entailing planning, sourcing, making, delivery and return. The following analysis levels are incorporated, namely, (1) type of process; (2) process groups; (3) components of the process; (4) execution; and (5) metrics for performance assessment. But measurement models to assess the performance of supply chains have certain drawbacks as well, including the use of a large number of independent supply chain measures. For instance,

Gunter and Shepherd’s (2006) work encapsulates single indicators of supply chain performance associated with time, expense, reliability/quality, inventiveness and ?exibility. While the above measures provide vital information facilitating the decision-making process, it is hard for diverse supply chain members to choose and trade off such a large number of measures for obtaining effectual, key improvement strategies. Additionally, such models prove unsuccessful in establishing explicit cause–effect linkages between multiple, hierarchical, independent major performance signs (Cai et al., 2009). Araldi and Persoon (2009) maintain that SCOR is utilized, essentially, for static, not dynamic, supply chain operations. The latter include inferior quality raw materials, manufacturing rate modifications, and other supply chain bullwhip-linked impacts (Mishra and Sharma, 2014).


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