• +1 407-906-9790
  • info@convergencedata.com
convergence-data-logo
  • Our Solutions
    • Data Services
    • Competitive Intelligence / Smart Teardown
    • Design for Retrieval
    • PLM
    • Image Services
  • Who We Serve
    • Industries
    • Marketing
    • Engineering
    • Ecommerce
  • About
    • Partners
  • Resources
    • Blog
    • Resource Center
    • Classification Community
    • DFR University
    Contact Us
    Contact Us
    con_logo

    What can we help you with?

    Follow Us

    7 Best Practices for a Parts Classification Project

    Convergence Data Team
    Nov 19, 2020
    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

    7 Best Practices for a Parts Classification Project

    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

      Posts by Tag

      • Classification (48)
      • Convergence Data (26)
      • Cleansing Data (24)
      • Governance (17)
      • PLM (16)
      • Data Cleansing (15)
      • Duplicate Parts (14)
      • Ecommerce (12)
      • PIM (12)
      • Teamcenter (12)
      • Cost Savings (11)
      • Part Cleansing (11)
      • Product Analytics (10)
      • Cost Reduction (8)
      • DFR (8)
      • Part cost (8)
      • Duplicate Analysis (7)
      • Part Standardization (7)
      • Benchmarking (6)
      • Data Classification (6)
      • Manufacturer Parts (6)
      • Parts Classification (6)
      • Taxonomy (6)
      • classification structure (6)
      • Part Rationalization (5)
      • Spend Rationalization (5)
      • categories (5)
      • Part Preparation (4)
      • Searching (4)
      • Spend Analysis (4)
      • Workflows (4)
      • Analytics (3)
      • B2B (3)
      • Clusters (3)
      • Customer Experience (3)
      • DFRv10 (3)
      • Direct Materials (3)
      • Engineering (3)
      • Integration (3)
      • Loading Data (3)
      • PTC (3)
      • Product Data (3)
      • Value Engineering (3)
      • data normalization (3)
      • 2019 Blogs (2)
      • Aftermarket Parts (2)
      • B2C (2)
      • Enrichment Lifecycles (2)
      • Findability (2)
      • Kalypso (2)
      • PLM World (2)
      • PTC LiveWorx (2)
      • PTC Windchill (2)
      • Product Structures (2)
      • Relationship data (2)
      • Repair Parts (2)
      • Standard Parts (2)
      • Supplier Management (2)
      • Supplier Rationalization (2)
      • reclassify (2)
      • smartclass (2)
      • supplier pricing (2)
      • 2016 Top Blogs (1)
      • 2021 blogs (1)
      • Business Integration (1)
      • Category Editing (1)
      • DFR PLM Integration (1)
      • DFR University (1)
      • Data Factory (1)
      • Data Management (1)
      • Data Mapping (1)
      • Data Policies (1)
      • Digital Commerce (1)
      • Electrical Parts (1)
      • Electronic Parts (1)
      • HVAC (1)
      • Hybris (1)
      • IoT (Internet of Things) (1)
      • M&A (1)
      • Mechanical Parts (1)
      • Mergers & Acquisitions (1)
      • NPI (1)
      • National Oilwell Varco (1)
      • New Part Introduction (1)
      • Part Reclassification (1)
      • Pricing Data (1)
      • Procurement (1)
      • Product Information Management (1)
      • SAP Hybris (1)
      • Sales Conversions (1)
      • Siemens (1)
      • Sourcing (1)
      • WBR Research (1)
      • Windchill (1)
      • allowed values list (1)
      • cx (1)
      • outsourcing (1)
      • prune (1)
      • units of measure (1)
      See all

      Recent Posts

      Stay in the know!

      con_logo
      Convergence Data's proprietary software and time-tested processes eliminate the clutter in your data—so you can use it to make sound business decisions.
      Our Solutions
      • Data Services
      • Competitive Intelligence
      • DFR
      • Image Services
      Who We Serve
      • Industries
      • Marketing
      • Engineering
      about
      • About Us
      • Partners
      Resources
      • Blog
      • Resource Center
      • Classification Community

      © 2023 , Convergence Data All Rights Reserved.