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MRP/DRP

Based on NetSuite, the new MRP/DRP calculations for make-to-order manufacturing companies.

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  • Product Overview

  • Key Strengths

  • Key Features

  • Related Cases

Product Overview

Hitpoint combines business experience in the manufacturing industry and NetSuite technology experience to introduce parameters such as minimum order quantity, substitution material, factory (multiple locations), parallel calculation, multiple calculation methods, calculation result traceability, requisition downward push traceability, and variance analysis, to form a product package that meets the typical MRP needs of Chinese enterprises.

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Key Strengths
  • Designed for single-order production enterprises

    The new design is suitable for MRP calculations of single-order production enterprises.

  • Comprehensive functions to serve multiple departments

    The functions cover procurement planning, supply variance analysis of demand, procurement orders, etc., providing comprehensive services for the Planning Department and Purchasing Department.

  • Clear results and integration of functions

    MRP calculation results are clear and concise, and the original documents can be traced back to understand the reasons for the demand and the differences, so as to match the demand with the supply, and the function perfectly integrates the functions of purchasing privileges and purchasing ladder price.

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Key Features
  • Adopting external recording method, non-invasive design, without affecting the functions already existing in the environment;

  • Introducing common and important calculation parameters in MRP such as substitution material and minimum order quantity;

  • Establishment of factory and goods by factory parameter settings, simple configuration modification settings;

  • Create MRP record sheets, calculate each data source into detail lines, and consider the parameters affecting demand;

  • Separate execution of daily MRP and MRP variance analysis, without affecting each other's operations but the results can be compared and analyzed;

  • Use Map/Reduce to break through the bottleneck of large data volume processing to ensure successful execution without interruption;

Related Cases