Question: How do you plan for and implement a successful data conversion process?

The importance of careful planning and good execution when it is time to convert your data from one system to another cannot be emphasized enough. In fact, data conversion is one of the most important aspects to a successful policy administration system replacement or implementation. With the right approach and execution plan in place, your data can become a strategic asset that preserves historical experience and leverages customer histories for future competitive advantage.

First, it is important to clearly articulate the business rationale for converting data from the current system. Conversion strategies run the gamut from manually entering policy information at the point of renewal to fully-automated conversion of all historical data. And, these options vary greatly in terms of both cost and complexity.

Further, it is critical to involve not just IT, but also business analysts and stakeholders in the planning phases as well as in the QA and data validation phases. In fact, you will want to involve a user from each department that will ultimately need to access and utilize the data.

When executing a data conversion project, insurers should keep the following guidelines in mind:

Treat the data conversion effort as its own project, complete with its own stakeholders, project management and governance.
Analyze and identify the critical and value-add data to be migrated, and map to target.
Consider how much history is required, both for regulatory and future decision-making or servicing purposes.
Get early access in the project to the actual source data for analysis, as there is often the opportunity for discovery of potential data quality issues or other unrealized data sources.
Merging data from multiple sources requires insurers to pay close attention to any structural, semantic and syntactical differences among the data sets.
Be alert to the possibility of unique application design requirements for converted data such as validation or underwriting referral rules that will not be applied to converted policies or grandfathering.
Evaluate the requirements of the target policy administration system, as well as downstream systems such as billing, claims, data warehouse and statistical reporting in the design.
Define performance requirements up front and allow time in the schedule for performance tuning of the conversion process.
Conduct multiple dry-runs with large data sets to flush out inconsistent source data, resource leaks or logic bugs.
Devote separate hardware resources and QA environments to data conversion, as long-running conversion test cycles may consume resources that interfere with other development teams.
Ensure that the design contains a strong audit component to make certain the process and its outcome can be monitored.

It is no secret that accessing the right data for cross-selling and up-selling in real-time can prove to be a competitive differentiator and turn your data into a powerful business advantage. The challenge is how to get the data working for you when obstacles such as legacy systems and incompatible data formats stand in your way.

Working with a provider that has experience with the complexities of managing data migration of customer, insurance transactions and product data can help you achieve the best business outcome while eliminating unnecessary costs and reducing the risk of common pitfalls so you can keep that historical data working for you and your business. Without this, your business challenges will persist and all you will have achieved is adding one more system to manage.

Steve Forte is the director of global product management and alliances for OneShield. He can be reached for further comment via email at sforte@oneshield.com.

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Virtual Viewpoint: Planning for a Successful Data Conversion

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