Advantage of master data tool at supply chain

Master data is one of the most important data for companies to work with in Supply Chain Planning (such as product, Bill of Material, customer etc.). Master data problems are the weak spot of all SNP optimizer projects. That can cause unfeasibility or unexpected erroneous solutions. There are two main complications with master data management;

  1. Volume of the data: The complexities of master data at companies are directly affected by different types of products and several levels of production. Planning relevant data can be different for each product and production level. To maintain a large volume of master data is very difficult for companies with concern to big supply planning network, different products and production levels.    
  2. Getting data from different departments: Master data is needed by the SNP optimizer from many departments of the company based on the planning model of the company, such as Purchasing, Logistics or Sales and Distribution. Using the data without error from different departments is not a walk in the park for planners. Data belongs to different responsible persons from different departments, but the accuracy of the data effects SNP planners. Planners should check the accuracy of master data before planning a run to enable persons responsible for master data to fix it.           

Planners need a master data management tool to handle these two points.   

How the master data management tool helps customers;

  • Errors and warnings are categorized in different codes
  • Easy navigation of error or warning codes
  • Filtering master data based on error or warning codes
  • Transfers filtered master data to SNP optimizer through master data management tool.

What is the advantage of this tool? 

  • Planners can easily manage master data to fix or escalate problems to the other departments   
  • Run SNP optimizer based on correct master data. Wrong data will not affect the quality of the SNP result.
  • Analyzing and reporting production chain. Relations between production levels and transportation lanes are shown 

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