Engineering patterns of supply chain optimization to manage oscillation effect

  • Received November 29, 2016;
    Accepted January 12, 2017;
    Published June 8, 2017
  • Author(s)
    Thokozani Patmond Mbhele
  • DOI
    http://dx.doi.org/10.21511/ppm.15(2).2017.12
  • Article Info
    Volume 15 2017, Issue #2, pp. 124-139
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  • 666 Downloads

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The cascading order variability from downstream trumping up the upstream site of the supply chain network indicates the deleterious effect to the performance of the fast moving consumer goods industry. The fundamental likelihood to optimization in this industry requires dexterous flows of quasi-real-time information, as well as reliable product availability. In this context, this study analyzes the challenges of bullwhip effect on the perspective of ingenious optimization strategies, and further contemplates to establish the engineering patterns of interrelationships on the magnitude of pooling the resources to advance supply chain capabilities. The suppression of bullwhip effect on underlying optimization strategies is sought to elevate accelerated responsiveness, improve network demand visibility and reduce volatility in frequencies to inventory replenishment. A rigorous and disciplined quantitative approach afforded the tentatively development of pattern of interrelated supply chain dimensions. The factor analysis method was used on 448 responses and insightful findings were produced from the compelling purposive sampling technique. The findings indicate that the magnitude of better ameliorating bullwhip effect, the value of competitive economic information and strength of selected optimization strategies depend on the model of unified engineering patterns. This paper provides insights to FMCG industry on using innovative strategies and modern technology to enhance supply chain visibility through integrated systems networks.

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    • Figure 1. Global optimization strategies on bullwhip effect – part one
    • Figure 2. Global Optimization strategies on bullwhip effect – part two
    • Figure 3. Engineering circular patterns of supply chain optimization strategies and leagility system
    • Table 1. Descriptive and factor analysis on KMO and Bartlett’s test rotated components
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