Espectrometría de masas de alta resolución (EMAR).

An issue of significant importance to supply chain practitioners and researchers is how and what to measure relative to the outputs of the supply chain (Stock, 2009). Many companies have not succeeded in maximising their supply chain’s potential because they have often failed to develop the performance measures and metrics needed to fully integrate their supply chain to maximise effectiveness and

efficiency (Gunasekaran, et al., 2004).

Without clear performance measures, an organisation cannot establish its current state and develop a strategy to fit where it wants to develop (Hammer & Stanton, 1995). The availability of past experiences in the form of objective critical

measures, linked to clear expectations, provides a picture of the past and leads to motivated desirable present and future behaviour. Performance measurement is vital in strategy formulation and communication and in forming diagnostic control mechanisms by measuring actual results (Wouters 2009). Christopher (1994) believes that benchmarking of the supply chain should occur not just within the organisation but relative to the competition.

Performance evaluation is defined by Juiping et al. (2009, p. 628) as the “process of quantifying action, or more specifically the process of quantifying and analysing effectiveness and efficiency.” On this basis, supply chain efficiency is defined as a measure of how well the firm’s resources in a whole supply chain field are utilised to achieve its specific goals (Jiuping, Bin Li & Wu, 2009). Supply chain

performance evaluation problems cover a wide range, from evaluating the

performance of independent organisations among supply chains to evaluating the performance of a whole supply chain system (Jiuping et al., 2009)

Research scientists have shown an increasing interest in improving the

measurement systems design during the last few years (Keebler, Manrodt, Durtshe & Ledyard, 1999; Vitale & Mavrinac, 1995; Caplice & Sheffi, 1995; Kaplan &

Norton, 1992; Eccles, 1991). They have questioned traditional performance measurement and looked at alternates (Holmberg, 2005).

Holmberg (2000) states that many companies still rely too heavily on financial figures as their key performance indicators. Financial metrics are primarily

designed to meet external evaluators’ needs, to compare firms and to evaluate a firm’s behaviour over time. Atkinson, Waterhouse and Wells (1997) agrees by saying that financial information is not required for decision making for many people inside organisations, and the information is often presented too late to make meaningful decisions on actions such as demands and production. Vitale and Mavrinac (1995) argue that success in business today is not solely determined by a strong cash flow or meeting a financial budget. Instead, developing

competency, capabilities and skills in areas such as team-based problem solving and innovation are much more important, yet not easily measured in financial terms (Holmberg, 2005). Johnson (1990) claims that financial measures are insufficient for the complex and dynamic characteristics of a supply chain. However, Johnson (1990) does not argue for completely removing financial

measures as accounting-based information does play an important role in strategic planning and for monitoring financial results. It is just it must be used in conjunction with other measures more suitable for controlling and improving activities. Maskell (1991) expands on the situations where the measures are used by suggesting that companies should use financial performance measurements for strategic decisions and external reporting, while day to day control of manufacturing and distribution operations should be handled by non-financial measures.

The metrics that are used in performance measurement and improvement should be those that truly capture the essence of organisational performance. A

measurement system should facilitate the assignment of metrics to where they would be most appropriate. For effective performance measurement and

improvement, measurement goals must represent organisational goals and metrics selected should reflect a balance between financial and non-financial measures that can be related to strategic, tactical and operational levels of decision making

and control (Gunasekaran et al., 2004). Gunasekaran and Kobu (2007) propose the following as the purposes of a performance measurement system:

. Identifying success.

. Identifying if customer needs are met. . Better understanding of processes.

. Identifying bottlenecks, waste, problems and improvement opportunities. . Providing factual decisions.

. Enabling progress. . Tracking progress.

. Facilitating a more open and transparent communication and co-operation. Balanced scorecard methodology developed by Kaplan and Norton (1993, 1996), is an important tool for performance management. The idea of a hierarchical, balanced set of performance metrics compatible with the top management strategy is repeatedly emphasised in current literature as an essential element of

performance measurement (Bhagwat & Sharma 2007). The balanced scorecard method was used by Barber (2008) to measure the performance of the supply chain as a whole. In the measurement Barber included both tangible and intangible elements that impact supply chain success, including participant satisfaction, financial management, strategic management, change management, relationship management, and quality, innovation and knowledge management. Kaplan and Norton (2004) also emphasise the importance of measurements related with

intangible assets (human, information and organisational capital) which are evident in the balanced scorecard perspective.

Another popular model for supply chain performance measurement is the Supply Chain Operations Reference (SCOR) model created by the Supply Chain Council (SCC). This model provided guidance on the types of indicators decision-makers can use to develop a balanced approach towards measuring the performance of an overall supply chain (Supply Chain Council, 2004). The SCOR Model advocates a set of supply chain performance indicators as a combination of:

- reliability measures (e.g. fill rate, perfect order fulfilment); - cost measures (e.g. cost of goods sold);

- responsiveness measures (e.g. order fulfilment lead-time); and - asset measures (e.g. inventories) (Supply Chain Council, 2004).

Authors such as Lockamy and McCormack (2004), Hwang, Yin and Lyu (2008) and McCormack, Ladeira & Oliviera (2008) all strongly support the use of the model. Hwang et al. (2008) supports the SCOR model as it enables companies to analyse their supply chain performance in a systematic way, to enhance

communication among the stakeholders in the supply chain, and to design a better supply chain network.

Akyuz and Erkan (2010) promote the model because it provides the following benefits:

- Providing a standardised way of viewing the supply chain (cross-industry standard).

- Offering a consistent ‘scorecard’ framework for development of performance.

- Emphasising process orientation and deemphasising functional orientation.

- Enabling cross-industry benchmarks.

Time-based methodologies are another method of performance measurement. They have been developed to provide a process-based approach to supply chain analysis. They have a proven ability to determine the major areas of waste within processes and consequently the opportunity for cost reduction (Stalk & Hout, 1990; Blackburn, 1991). Waste is defined as any activity that does not add value to the product (Stalk & Hout, 1990). One of the key aspects of time-based methodologies is the ability to account for both value adding time and non-value adding time in processes (Gregory & Rawling, 1997). Time based process mapping (TBPM) identifies value adding and non-value adding activities within the supply chain. Value is seen as a part of a product or service that the customer cares about and

would be willing to pay for. Value is said to be added to products or services only when the following three criteria are met: firstly the customer cares about the change, secondly the item is physically changed and thirdly the change is done right the first time. Non-value adding activities are everything that does not fit within these three criteria (Blackburn, 1991; Gregory & Rawling, 1997)

3.2.8 Military Logistics and Supply Chains