Supply chain performance measurement and improvement system: a MCDA-DMAIC methodology

Syed Tahaur Rehman, Sharfuddin Ahmed Khan, Simonov Kusi-Sarpong, Syed Mehmood Hassan

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Abstract

Purpose - The purpose of this study is to adopt a supply chain performance measurement (SCPM) framework as proposed by (Dweiri and Khan 2012) to model a novel SCPM index (SCPMI) system to measure and improve supply chain performance (SCP).

Design/methodology/approach - The adopted SCPM framework developed by Dweiri and Khan (2012) is used to model a generic SCPMI framework aided by analytic hierarchy process (AHP) method and inputs from industrial experts. To exemplify the applicability and efficiency of the generic SCPMI system, an automobile assembling company from an emerging economy was used. This SCMPI system is used to measure, improve and measure post-improvement SCP guided by DMAIC (define, measure, analyze, improve and control) methodology.

Findings
- The study’s initial measurement results showed an average SCP of the case company over a four-month period as 82 per cent. DMAIC methodology was used to identify inherent problems and proposed improvements. The post-improvement SCP measurement saw an improvement from an average of 82 to 83.82 per cent over the four-month period.

Practical implications
- The proposed generic SCPMI framework aided by AHP-DMAIC has been successfully implemented in a case company. After implementation, managers and decision-makers saw an improvement in their SCP. The proposed SCPMI system and results can be useful for benchmarking by manufacturing organizations for continuous SCP improvement.

Originality/value
- An original SCPMI framework proposed is general in nature and can be applied in any organization.
Original languageEnglish
Pages (from-to)522-549
JournalJournal of Modelling in Management
Volume13
Issue number3
Early online date14 Sep 2018
DOIs
Publication statusPublished - Oct 2018

Keywords

  • Performance management
  • Decision-making
  • Supply chain management
  • Decision support systems
  • Decision analysis

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