Informes de Proceso Electoral: a. Informes de precampaña

Performance Metrics can be employed within every division of an organization. Our use of PMs has specifically focused on supply chain management (SCM). The logistics involved in the production of a product can be measured throughout the product lifecycle process, from obtaining raw materials to final delivery (Agarwal et al., 2006). Researchers such as Beamon (1999), Gunasekaran et al. (2001,2004), Hervani et al. (2005), Kleijnen and Smits (2003), Lai et al. (2002), and Melnyk et al. (2004), have studied the use of performance metrics within the supply chain. Most of their models support the use of both quantitative and qualitative measures as well as financial and non-financial measures.

2.1.1

Brewer and Speh (2000) pointed out that some of the challenges that are unique to the supply chain include the trade-off between product standardization or customization, and product cycle time. While Hervani et al. (2005) maintain the multiple levels or tiers in a supply chain are the main obstacles of

establishing a universal PM, Kleijnen and Smits (2003) and Shepherd and Gunter (2006) believe that the difficulties lie in the competition between external and internal motivators. According to Brewer and Speh (2000) and Gunasekaran et al. (2004), organizational managers have expressed that they are not concerned with the generalizability of a particular model but with what works within a given company, and that the model must be balanced with a controllable number of metrics. To focus on the managerial concerns, Gunasekaran et al. (2001) have divided the organization into different hierarchical levels including strategic, tactical, and operational focuses. Other common methods of addressing managerial concerns include: SMART, which was first used in the 1980s and incorporated non-financial measures (Cross & Lynch, 1998) and the Balanced Scorecard (BSC). The BSC is a strategic planning and management system that is widely applied in profit and nonprofit organizations to align business activities to the vision and strategy, so as to improve internal and external communications and monitor organization performance against strategic goals (Kaplan & Norton, 1992). The BSC makes use of multiple approaches to balance competing objectives. Brewer and Speh (2000) show that the BSC encourages coordination and focused efforts that can provide real benefits when both long-term and short- term motives are rewarded.

2.1.2

Organizations are increasingly driven to focus on core competencies (Brewer & Speh, 2000). It can be challenging to identify and prioritize core competencies when the development of PMs does not allow for the unique weighting of specific performance metrics. A drawback of extant performance measurement systems is that many PMs are strictly driven by predetermined requirements for International Organization for Standardization (ISO) ratings (Hervani et al., 2005). A PM model should be flexible, balanced, able to incorporate additional “interactions” among the PMs, and able to specifically “weight” PMs (Beamon, 1998; Bhagwat & Sharma, 2007; Gunasekaran et al., 2001; Jharkharia & Shankar, 2007; Marasco, 2008).

Bhagwat and Sharma (2007) began with the traditional BSC approach; however in order to deal with the issues of balance, interactions, and weighting, they settled with the Analytic Hierarchy Process (AHP) to weigh and to prioritize the different performance metrics. AHP uses a system of pairwise comparisons to measure the importance of the components of the structure, and to prioritize the alternatives in the decision. AHP has been used to weight PMs in other models, as seen in (Agarwal et al., 2006; Sarkis, 2003; Yurdakul, 2003). More recently, Hervani et al. (2005) and Vachon and Klassen (2006) took interest in Green Supply Chain Management, and suggest a multi-criteria hierarchical PMs could be applied to build an evaluation model for their systems.

2.1.3

Organizations may choose to outsource their distribution function in order to focus on their core competencies, take advantage of cost reductions, outsource international logistics providers, increase the availability of capital, and/or develop the potential for long-term relationships (Fantasia, 1993; Hertz & Alfredsson, 2003; Marasco, 2008; Rao et al., 1993). Third Party Logistics (3PL) is a multi-billion dollar business that has become increasingly competitive on the margins (Hertz & Alfredsson, 2003). Vaidyanathan (2005) found that the use of a 3PL provider can improve customer service. Teaming with a 3PL can pose various challenges including information sharing (Jung et al., 2008), trust and reciprocity (Knemeyer & Murphy, 2005), and opportunism (Marasco, 2008). Several approaches have been used to evaluate 3PL selection. They include DEA (Zhou et al., 2008), ANP (Jharkharia & Shankar, 2007), a marketing perspective (Knemeyer & Murphy, 2004), and an IT-based framework (Vaidyanathan, 2005). In section 3 we discuss how ANP can be used to organize the 3PL selection decision according to the temporal flow of the product.

2.1.4

The Analytic Network Process (ANP) is a more general form of the AHP used in multi-criteria decision analysis to analyze complex decisions (Saaty, 2005). The ANP structures a decision problem into a network with decision criteria organized into relevant clusters which are weighted and compared against alternatives to decide which alternatives should be selected. The ANP is a flexible but rigorous method designed to model and prioritize decisions. The added value of using a network over a hierarchy comes from the ability to allow for and incorporate the interactions and dependencies among the criteria throughout all levels of the model which are assumed to be independent in a hierarchical model. Saaty (2005) refers to the interactions between the criteria of the network as influences. The influences among criteria are identified and then compared using the 1 to 9 scale (Saaty, 2005).

An ANP model also facilitates the incorporation of quantitative performance metrics and cost data along with qualitative information by using the 1 to 9 scale. A common example that has been used to support the use of the 1-9 scale over exact measurement is in comparing the sizes of objects (Saaty, 2005). The inconsistency index also adds to the flexibility of ANP by accounting for how decision makers make decisions and allowing for some inconsistency within the pairwise comparisons. The ANP lends itself to decisions made both by a single individual and in a group. Further discussion regarding combining group judgments including the geometric mean has been addressed by Saaty and Vargas (2007). After a network has been synthesized, the decision makers can perform sensitivity analysis to determine the robustness of a proposed decision. Potential trade-offs can be addressed through the sensitivity analysis.