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7 Best Practices for a Parts Classification Project

Posted by Convergence Data Team on Nov 19, 2020 11:35:07 AM

When we talk to companies who are just starting their classification journey, we provide them with the best practice framework focused on obtaining the most value from their classification project. All too often this work is done in only one division or it becomes an “engineering searchability” project which limits the value of the project.

When making an investment in classification, the budget for this program should come from these sources:

  • Person responsible for direct material spend – VP of Operations, CFO, or CPO
  • ERP or PLM Deployment budget

7 Best Practices for a Parts Classification Project

    1. Target high value parts for classification – high spend, proliferation, too many vendors, shared across programs, etc. Start with the 10 top categories using this criterion.
    2. Pull all the parts from each organization for each category – this is the biggest bang for the buck approach.
    3. Assign one (1) Engineering SME and one (1) Purchasing Category owner for each commodity – they will approve structure and data. You don’t want too many cooks in the kitchen.
    4. For each part – provide part number, part description,
      MFG Part Number and MFG Name, drawing or specification.
    5. Obtain the commercial data for each part – provide pricing,
      supplier names, buying org and volumes.
    6. Clustering – once each category is complete, look for clustering opportunities – this will expose cost savings for procurement spend rationalization. Clustering will expose parts with higher prices compared to other similar parts with lower pricing. 
    7. Load classification data to PLM - make sure to validate the data against the PLM systems rules. This saves time dealing with load issues.
The advantage of taking this approach is that you only go into each category once. You don’t want to have to go into each category multiple times. This will allow you to have a much better chance of finding cost savings. Lastly you will be in a better position to prepare the data for your global PLM system. You don’t want to have to keep updating your PLM system with changes. The video below describes the process to prepare your classification data for cost savings and sourcing cost savings.

Here are some useful links and videos:

     • 15 min PLM Classification Process video:

     • 5 min Clustering video
     • 1 min Explainer video

     • DVA Case Studies
     • CDS Brochure

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Topics: Classification, Product Analytics, PLM, Part cost, convergence data, Part Preparation, DFR, Cost Reduction, Spend Analysis, Loading Data, Cost Savings, Part Standardization, Duplicate Analysis, data normalization, categories, classification structure, reclassify, smartclass

New Multi-Select Structure Editing

Posted by Convergence Data Team on Oct 23, 2020 12:34:41 PM

We are excited to announce our 10.1 release and promote our new data classification multi-select editing capabilities.  Now DFR users can select multiple categories at once and perform different types of edits – copy/paste or prune/graft.  What this means is users can make significant data model changes when building and iterating your classification structure; that much easier to do.  Along with the categories – all the associated attributes get moved in one single operation.

If you have parts assigned to categories that you want to move – don’t worry – our multi-select prune and graft allows DFR users to select multiple categories and move them along with the attributes and the parts – all in one single operation.  These changes will save our users lots of time and hopefully give them the structure they desire with less effort.

For more details check out the short video or contact us today for a demonstration –

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Topics: Classification, Data Cleansing, convergence data, DFRv10, DFR, categories, classification structure, Category Editing, prune

Demonstrating the Magic Clusters

Posted by Richard Turner on Apr 30, 2020 11:45:05 AM

How to Save Money by Clustering your Parts

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Topics: Classification, convergence data, DFR, DFR University, Cost Reduction, Spend Rationalization, Value Engineering, Cost Savings, Direct Materials, Part Standardization

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