The success of the migration
project depends on proper planning, strategy, approach and testing techniques.
The following steps for successful
implementation of the migration program.
§ Analyze the business requirements
§ Prepare the migration test plan/strategy
§ Prepare environment equal to production.
§ Identify success and failure conditions and also the
application interface requirements
§ End-to-end migration plan for data verification and
validation
§ Compliance with Data acceptance criteria
§ Post-production
support to eliminate any issues that may occur during system go live
Pre-requisite Before
migration
§ The organisation must look for the expertise in the
migration area so that he can provide better guidance for the migration
process. The data migration project involves specialized skills, tools and
resources. But sometimes the resources identified for the migration project may
not have the essential knowledge to carry out the migration program.
§ All stakeholders must be informed in advance of the
migration project so that they are well known about the time period of the
migration process, the duration the old system will not be in use, and benefits
accrued through migration of the legacy system into the new application.
§ Ratify the working condition of old systems and
address the issues found during migration.
§ Ensure
that the backup of the old environment or system is taken so that if the
migration fails, the data can be reloaded or migrated again.
During migration
§ Always be interactive to all the end users and stakeholders
when the migration process is in progress.
§ No change in environments during migration trial runs.
Backup environment should be available.
§ Risks
should be documents with mitigation actions.
§ Compliance
to the agreed entry – exit criteria.
After migration
§ All failed items should be reviewed, migrated and RCA to
ensure why they failed to migrate.
§ All stakeholders should be informed about the expected
time when the new system will come into existence.
| Slno | Category | Parameter |
| 1 | Technical | Lack of agreement on system of record, data definitions, standards, transformations, conversion methods, etc. |
| 2 | Technical | Data migration tool(s) not well defined or settled |
| 3 | Technical | Hardware sizing and data volume are inconsistent |
| 4 | Technical | Requiring historical data conversion (rather than using legacy systems for historical purposes) |
| 5 | Technical | Multiple legacy sources of data for single master record loads. |
| 6 | Technical | Data gaps – no corresponding data record for conversion |
| 7 | Technical | Different data structures between legacy systems. For example may have structured hierarchies and the source data may not. |
| 8 | Technical | Poor data quality – errors, duplicates, inconsistent use of fields |
| 9 | Management | Improper estimates of data migration effort and activities |
| 10 | Management | Client side skills gaps on data migration |
| 11 | Management | Deferring data corrections until after go-live |
| 12 | Management | Knowledge of and access to data sources |
| 13 | Management | Insufficient or incorrect change control processes |
| 14 | Management | Insufficient participation from key functional project team members (client and consulting) |
| 15 | Management | Improper management of dependencies between functional areas or modules. |
| 16 | Business | Identifying legacy and other data sources |
| 17 | Business | Cleaning or scrubbing the data |
| 18 | Business | Ensuring the converted data meets business processing requirements |
| 19 | Business | Defining sufficient test plans to validate data is properly converted |
| 20 | Business | Provide sufficiently skilled employees to work the data |
| 21 | Business | Make as many data corrections as possible in legacy systems before conversion |
| 22 | Business | Ensure there are sufficient hardware resources available for meaningful data conversion tests |
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