Implementing a Successful Data Migration Strategy
Nov 12, 2022
Upgrading a legacy system, mergers & acquisitions, the ending of a life cycle of an IT system, or outsourcing a business function – carriers will inevitably need insurance data migration from one platform to another. Whatever the reason for data migration, data must be correctly and quickly migrated into the new application.
Successfully migrating data quickly and smoothly means that the return on technology investment, and other benefits, can be realized sooner. Smooth data migration is reproducible, trackable, and of prime quality.
Challenges to Data Migration in the Insurance Industry
Data models within the old and new applications are often different in structure, syntax, and semantics. Source and target systems handle data differently, making such projects highly risky because they affect many systems. For example: within the source system, only individual documents are kept, but, interim balances at the end of the year are required from the target system.
Moreover, old data may be distributed amongst many applications, and their use is rarely documented, which leads to inconsistencies or inaccuracies in data.
The data conversion usually runs parallel to implementing the new application, which implies that the available resources are often insufficient. Insurance Data Migration procedures need to be reusable to migrate data from other legacy systems into the new application. When many applications are to be migrated, such as business associates, collection/disbursement, commission, inventory, etc., a sequence that considers the technical dependencies must first be developed to migrate the data to create cost benefits. The expertise required to evaluate a legacy system is not always found within a business and needs external intervention.
Key Elements for Successful Data Migration
- Data Quality is Paramount. The success of the migration depends on the quality of the data. Regular testing is carried out to ensure the quality of the data.
- Speed is Essential. Faster data migration by making the process more efficient, and flexible, and minimizing the required effort; the sooner the cost benefits can be realized.
- Reuse is Encouraged. The framework for successful insurance data migration can be applied to other applications, reducing the project’s cost.
- Testing is Critical. Data testing and dry runs are critical to the viability of the particular production data. These testing routines must be run numerous times and on an everyday basis to spot exceptions, confirm data relationships and detect early warnings of any data quality issues.
- Automated Tools – Leveraging tools that help automate the process brings a significant advantage to insurers by reducing their conversion time frames.
| Key Element | Description |
|---|---|
| Clear Objectives | Define the goals of the data migration |
| Data Profiling | Analyze the quality and complexity of data |
| Mapping and Design | Map data fields and design migration process |
| Data Cleansing | Clean and standardize data |
| Data Validation | Validate data accuracy and completeness |
| Testing and QA | Test the migration process and validate data |
| Training and Support | Train users and provide ongoing support |
| Risk Management | Identify and mitigate potential risks |
| Project Management | Plan, execute, and monitor the migration project |
| Communication | Communicate progress and changes to stakeholders |
At KMG, we use established migration processes, sound technical advice, and end-to-end data migration solutions that will put your organization on the road to unlocking the hidden value in your enterprise legacy systems.
