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Towards an Analysis Methodology for Identifying Root Causes of Poor Delivery Performance

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Listed:
  • Nielsen Peter
  • Do Ngoc Anh Dung
  • Nielsen Izabela

    (Aalborg University, Department of Mechanical and Manufacturing Engineering, Denmark)

  • Eriksen Thomas

    (CS BtB Operations Center, Telenor ASA Group, Denmark)

Abstract

This paper presents an analysis methodology for establishing the demand stability of the planning environment faced by a company and the impact on the stability from changes to sales order. The methodology focuses on three critical planning parameters derived from customer orders: product mix, volume, and order sizes. Furthermore, the methodology links the delivery performance of a company to the changes made to sales orders. Based on a test case application of the methodology, it is concluded that by accepting changes, the demand faced by the case company has become more unstable on product mix, volume, and the number of order lines per period, while some added stability has been achieved with regards to the order size distributions. Ultimately, by applying the methodology to the case company, it is found that by changing the sales orders, the company does not improve the delivery performance.

Suggested Citation

  • Nielsen Peter & Do Ngoc Anh Dung & Nielsen Izabela & Eriksen Thomas, 2014. "Towards an Analysis Methodology for Identifying Root Causes of Poor Delivery Performance," Foundations of Management, Sciendo, vol. 6(2), pages 31-42, December.
  • Handle: RePEc:vrs:founma:v:6:y:2014:i:2:p:31-42:n:3
    DOI: 10.1515/fman-2015-0009
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    References listed on IDEAS

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    1. Hax, Arnoldo C. & Meal, Harlan C., 1973. "Hierarchical integration of production planning and scheduling," Working papers 656-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Elbashir, Mohamed Z. & Collier, Philip A. & Davern, Michael J., 2008. "Measuring the effects of business intelligence systems: The relationship between business process and organizational performance," International Journal of Accounting Information Systems, Elsevier, vol. 9(3), pages 135-153.
    3. Gong, Zhejun & Hu, Sun, 2008. "An economic evaluation model of product mix flexibility," Omega, Elsevier, vol. 36(5), pages 852-864, October.
    4. Tsubone, Hitoshi & Furuta, Hirohisa, 1996. "Replanning timing in hierarchical production planning," International Journal of Production Economics, Elsevier, vol. 44(1-2), pages 53-61, June.
    5. Feelders, A. J. & Daniels, H. A. M., 2001. "A general model for automated business diagnosis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 623-637, May.
    6. de Groote, Xavier, 1994. "Flexibility and product variety in lot-sizing models," European Journal of Operational Research, Elsevier, vol. 75(2), pages 264-274, June.
    7. Akkerman, Renzo & van Donk, Dirk Pieter, 2009. "Product mix variability with correlated demand in two-stage food manufacturing with intermediate storage," International Journal of Production Economics, Elsevier, vol. 121(2), pages 313-322, October.
    8. Wijngaard, J., 1982. "On aggregation in production planning," Engineering Costs and Production Economics, Elsevier, vol. 6(1), pages 259-265, April.
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