7 Best Practices for a Successful Data Migration to SAP S/4HANA

Posted by Utopia Marketing on July 15, 2019

There can be a lot of risk when migrating to a new platform like SAP S/4HANA. How do you ensure you're creating a smarter approach to managing the data up front?

  1. Ensure data is part of the timeline:

    Whatever the defined timeline is, data quality could be one of the things that throws it off the rails. Having a well-defined process and dedicated organizational team to manage process and data components drives the speed and success with which system migration can happen.

  2. Get executive buy-in early:

    Without early and active participation in the strategy phase of a large-scale move, technology business unit leaders may get involved too late, putting the entire program at risk if there lacks agreement later on.
  3. Agree on one set of business rules, processes and goals, aligned to master data:

    Having a uniform way to designate data rules and taxonomies to reference throughout the process – this will create only one structure going forward and help align to overall corporate goals.
  4. Have a “champion” in each department or unit who will enforce decisions:

    Find a subject-matter expert in each unit or department who is respected. Once a decision is made around a new process or business rule, they can communicate it teams within the unit or department and explain the method behind the madness. This will increase speed of adoption and boost the likelihood rules are followed.

  5. Leverage the tools available:

    If the organization has a governance program or SAP data service already in place, use it as a bridge in the process to accelerate the movement of master data from the old system into the new operating environment.
  6. Seek out low-hanging fruit:

    Go through the inventory of data assets, where they exist, what systems they’re in, and how they’re relevant to the new model. Profile that data to identify any early opportunities or benefits relevant to business drivers. For example, if one of the drivers is to increase customers by 50 percent, use any clean data to shore up existing relationships to ensure the customer experience doesn’t suffer.
  7. Have a plan for post-migration:

    While it’s important to define what “good” looks like now, if an organization doesn’t govern good data, it will be right back where it started in 18 or 24 months. The ideal scenario is a combination of data transformation and data governance, so have a plan in place for how to keep the data sparkling clean once the golden record is created.  

 

Topics: data migration

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