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Quantifying the effectiveness of SCOR measures in make-to-forecast supply chains

Conference Paper


Abstract


  • Effective management of an internal supply chain is a complex process whereby

    individuals make a conscious choice about how best to align business operations

    to customer demand. Reference models such as the supply-chain operations

    reference (SCOR) model have become popular within industry because they

    propose various pre- and post – performance metrics to support more effective

    supply chain decision making. Despite the merits and popularity of the SCOR

    model, further research is required to empirically verify the performance

    metrics that best align to specific customer demand patterns. Using theoretically

    derived customer demand patterns that provide the stimuli for a lean, agile or

    mass production supply chain strategy, this study evaluates the effectiveness of

    common SCOR performance metrics. The metrics characterise each of the four

    primary building blocks in the SCOR reference model ─ plan, make, source and

    deliver. Empirical evidence is based on a simulation model that mimics the

    BlueScope Steel supply chain; a large make-to-forecast process industry in the

    Asia Pacific region. The simulation model provides a test bed where the most

    optimal combinations of supply chain strategy and performance metrics can be

    experimentally derived. Results indicate that a performance metric’s ability to

    capture the alignment between business operations and customer demand can

    be augmented by aggregation with additional performance measures. The study

    concludes with a discussion on the methodological difficulties that researchers

    face when attempting to empirically examine multidimensional reference

    models such as SCOR.

Publication Date


  • 2012

Citation


  • Munoz Aneiros, A. (2012). Quantifying the effectiveness of SCOR measures in make-to-forecast supply chains. Proceedings of the 10th ANZAM Operations, Supply Chain and Service Management Symposium Melbourne, Australia: ANZAM.

Ro Metadata Url


  • http://ro.uow.edu.au/buspapers/153

Abstract


  • Effective management of an internal supply chain is a complex process whereby

    individuals make a conscious choice about how best to align business operations

    to customer demand. Reference models such as the supply-chain operations

    reference (SCOR) model have become popular within industry because they

    propose various pre- and post – performance metrics to support more effective

    supply chain decision making. Despite the merits and popularity of the SCOR

    model, further research is required to empirically verify the performance

    metrics that best align to specific customer demand patterns. Using theoretically

    derived customer demand patterns that provide the stimuli for a lean, agile or

    mass production supply chain strategy, this study evaluates the effectiveness of

    common SCOR performance metrics. The metrics characterise each of the four

    primary building blocks in the SCOR reference model ─ plan, make, source and

    deliver. Empirical evidence is based on a simulation model that mimics the

    BlueScope Steel supply chain; a large make-to-forecast process industry in the

    Asia Pacific region. The simulation model provides a test bed where the most

    optimal combinations of supply chain strategy and performance metrics can be

    experimentally derived. Results indicate that a performance metric’s ability to

    capture the alignment between business operations and customer demand can

    be augmented by aggregation with additional performance measures. The study

    concludes with a discussion on the methodological difficulties that researchers

    face when attempting to empirically examine multidimensional reference

    models such as SCOR.

Publication Date


  • 2012

Citation


  • Munoz Aneiros, A. (2012). Quantifying the effectiveness of SCOR measures in make-to-forecast supply chains. Proceedings of the 10th ANZAM Operations, Supply Chain and Service Management Symposium Melbourne, Australia: ANZAM.

Ro Metadata Url


  • http://ro.uow.edu.au/buspapers/153