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Impact of inventory inaccuracy on service-level quality: A simulation analysis

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  • Daniel Thiel
  • Vincent Hovelaque
  • Thi Le Hoa Vo

Abstract

This article discusses the impact of inventory inaccuracy on service-level quality in (Q,R) continuous review, lost-sales inventory models. A simulation model is built to study the behaviour of this kind of model exposed to an inaccuracy in inventory records as well as demand variability. We have observed an unusual result which goes against certain empirical practices in the SMEs that consist in hiking the inventory level proportionally to the data inaccuracy rate. A nonmonotone function shows that at the outset, the service-level quality is lowered as the inaccuracy rate increases but when the inaccuracy rate becomes much higher this quality is conversely enhanced. This relation can equally be observed given that stocktaking commences as soon as the threshold of decline in the service-level rate has been reached and when demand consequently dwindles. Finally, another noteworthy result also shows the same phenomenon between the function involving a level of safety stock defined by the simulation and the function between the service-level quality and the inventory inaccuracy. These different observed results are discussed in terms of both contribution to the (Q,R) inventory management policies in SMEs and of the limitations to this study.

Suggested Citation

  • Daniel Thiel & Vincent Hovelaque & Thi Le Hoa Vo, 2009. "Impact of inventory inaccuracy on service-level quality: A simulation analysis," Working Papers SMART 09-01, INRAE UMR SMART.
    • Handle: RePEc:rae:wpaper:200901
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    File URL: http://www6.rennes.inra.fr/smart/Media/Working-papers/WP09-01
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    References listed on IDEAS

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    More about this item

    Keywords

    Continuous review inventory system; inventory inaccuracy; continuous model; discrete-time simulation;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

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