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    The Five M's to Onboarding An Acquisition's Product Data

    Convergence Data Team
    Apr 17, 2023
    Product Data, Data Management, Mergers & Acquisitions, Data Mapping, Product Information Management, Data Migration, Data Onboarding, Match and Merge

    The Five M's to Onboarding An Acquisition's Product Data

    💡 Why operate like separate companies when you don't have to? If you acquired another company, chances are, they are still operating independently (and their data is, too). Imagine the possibilities through integrating an acquisition's product data and yours into one centralized source!

     

    To help expedite the integration of recent acquisitions, it's critical to analyze the data on the parts and products for each acquisition prior to onboarding them to your ERP, PLM and PIM systems. To achieve the economies of scale you get integrating operations and to operate like one company, you'll need to include parts and product data model reconciliation, as well as duplicate identification and management as part of the data migration process. 

     

    ⛔ If you fail to do this, then you will likely add needless complexity or confusion to your data models, creating governance headaches down the road. You may also be migrating duplicate parts into your ERP system(s), which will increase your inventory and material handling costs.

     

    Getting this process started can be tricky, so we've broken it down into five steps you can take to migrate acquisitions successfully, while mitigating the introduction of duplicate parts. At CDS, we call this "The 5 M's" -- Match, Merge, Migrate, Mitigate, and Manage. 👈

     

    1. Match the data models: Review the acquired business' taxonomy and compare it to your own.
      • First, identify categories that have a 1:1 match.
      • Then locate near matches, such as categories with slightly different labels but contain similar parts or products.
      • Finally, determine the net-new categories of the acquired business that map to nothing in your current data model.

      With category mapping established, you'll next need to compare attributes using a similar process: attributes that map 1:1, near matches, and net-new attributes. Now, you have a complete picture of how the data models map to each other, allowing you to migrate data from the acquired business to your corporate data model! 🖼️

    2. Merge the data: SKUs or parts can now be migrated to the existing corporate data model. However, the work doesn't end there. 🚧 At this point, you will know which categories you can classify the acquired products and parts. You will still need to migrate the attribute values (specifications) for each item. At this stage, the goal is to ensure parts and products are classified to the right place. 

    3. Migrate and normalize the attribute values: Once you've classified your parts and products to their new homes in the corporate data model, you will migrate over the attribute values and then go through a normalization process to cleanse the specification data. Here, you need to align the specs with your data quality standards and corporate style guidelines. ⚠️ This can be an intensive process if you don't have tools to support and control it, but without clean, comprehensive, and uniform data, you'll only be adding to governance challenges and findability issues which can have drastic results in the long term. 

    4. Mitigate duplicates: Conduct a thorough inventory analysis of all the new acquisitions items to identify any duplicates. This analysis should include comparing item IDs (SKU or part numbers), descriptions, and specifications.  This can easily be done in a classification database like DFR that has duplicate analysis and reporting capabilities.

      Determine the importance of duplicates: Once duplicates have been identified, determine the importance of each one. ⚙️⛓️ Some duplicates may be essential for critical systems, while others may be unnecessary and can be removed.  The ones that are essential can be mapped to a corporate unique ID to mitigate duplicate purchasing and inventories.  The acquired business can still use the same part numbers, but only the corporate ID will be used for ordering from preferred suppliers.

       

    5. Manage and monitor via your data governance process: Ensure your data governance program has repeatable processes in place to build out new data model categories, add attributes, enhance your style guidelines and data quality rules, and implement governance decisions into your data. ⛓️ With tools like DFR, you can also leverage accelerators such as description auto-generators as you align the SKUs according to corporate marketing description standards. Now you're ready to bring the acquired products to market/eCommerce, and publish your acquired parts to your PLM, and handle new acquisitions with (relative) ease going forward! 👏 

    By taking these steps, you can effectively manage new parts and products from a new acquisition and ensure that critical systems have the necessary governance process in place to normalize data and mitigate duplicate items.  The benefits of this valued-added migration process are vast and leveraging economies of scale across the corporation will deliver big cost savings longer term!

     

    Looking for help with onboarding acquisition data? Interested in accelerating the process? ⏩ Contact us for more information!

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