Introduction. Seeing the Elephant. PLM Data Migration happens rarely at a company, but is very difficult to plan and design.

Transcription

1 Introduction Seeing the Elephant PLM Data Migration happens rarely at a company, but is very difficult to plan and design. 1 14

2 Approach The Iterative Nature of the Process The design of the new PLM implementation (processes, data structures etc.) can t be isolated from the planning and execution of the data migration process. There are many, many permutations of product data almost infinite. Each test cycle introduces small nuances that need to be dealt with. The only way to ensure success is to enable many test cycles. High performance Data migration tools/process are a requirement The only way to enable many test cycles is to design a set of tools and migration process that can be executed in hours rather than days. Test for Success- Fail Fast - Allow time for correction 2 14

3 Factor 1: What Is In Scope? What is the overall business/division organization? What part of the business is in scope for PLM implementation? What is the high level deployment phasing for the program? Often the initial data scope is incomplete and a different scope is needed for consistency Some program aspects will influence you to make your project smaller Training and deployment Resource availability Amount of data Some aspects will influence you to expand it Data relationships Cost efficiencies 3 14

4 Factor 2: What Needs to be Moved? What are the source product data systems and data types (and quantity) that are in scope for the Data Migration program? Examples: Part #, BoM, Change Management, PDM/CAD, etc. Are these systems segregated similar to the organizations that are in/out of scope? Be sure to include files on disk and local tools. 4 14

5 Factor 3: How Much Do You Need? What level of historical data needs to be migrated? Latest revisions only may be the best approach. Archiving systems can provide access to old data while freeing you from the need to maintain legacy systems. 5 14

6 Factor 4: Where Are You Going? What is the application scope of the target PLM implementation? Examples: Doc management, Change Management The application scope and the legacy systems should align. Be careful about migrating partial data from a legacy system. 6 14

7 Factor 5: How Does My Old Data Constrain My Destination? What constraints will the migrated legacy data have on the business processes and applications in the new PLM implementation? Can t define new PLM in a vacuum Don t try to make PLM work like the legacy system Are you making assumptions about a new process that is data driven? Are you making assumptions about consistencies in your source environments? CAD conversion can be done as part of a PLM migration, but adds challenges. 7 14

8 Factor 6: How Will My Destination Constrain My Data? What constraints do the target PLM system schema, processes and applications have on being able to input the legacy data? Example: CAD and EBoM misalignment, informal CAD names vs. Part Numbers The more sophisticated the to-be PLM deployment is, the less likely it is that the legacy data will be sufficient. You may need to think of legacy data and new data as two separate things. 8 14

9 Factor 7: What is the Big Picture? Quantify and assess the constraints in #5 and #6. Holistic Assessment of all related legacy data in scope for migration Duplicate scenarios must be holistically assessed and a strategy developed prior to any data being loaded. This often overlaps with partitioning and sequencing. 9 14

10 Factor 8: What will the Business Impact Be? How much down-time can the business tolerate in order to execute the migration? Timing drives the amount of data Performance is critical Busy-work (fixing old data) should be minimized. Your primary efforts should revolve around added value, not support for intermediate processes

11 Factor 9: Where Do We Start? What is the ideal system/data segmentation to map into data migration projects? Big Bang/System/Program/Product Line/Manual Incremental Partitioning and sequencing of loads can be difficult if they don t align to natural boundaries. If your migration involves keeping legacy systems, recognize the impact of having two systems coexisting with shared data. The Manual Incremental approach tends to have the highest risk, and be the least effective/most costly. Big Bang risk is training and testing, but these are manageable processes

12 Factor 10: Who is Going to Do All This? Select the right Data Migration vendor/partner Use a vendor for areas that are not core competencies of the company Data migration requires specialized tools and expertise Defining use cases and test/validation should be your requirement Vendor criteria Experience at both source and target systems History of successful and referencable data migration projects 12 14

13 Seeing The Elephant 10 Success Factors 1 What Is In Scope? 2 What Needs to be Moved? 3 How Much Do You Need? 4 Where Are You Going? 5 How Does My Old Data Constrain My Destination? 6 How Will My Destination Constrain My Data? 7 What is the Big Picture? 8 What will the Business Impact Be? 9 Where Do We Start? 10 Who is Going to Do All This? 13 14

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