Data validation is an important part of the data conversion process when transitioning to new financial management software. Whether your firm is transitioning to new software now or intends to in the future, how you approach this process can have a significant impact on the success of the project. Data validation provides key feedback during data conversion and helps identify issues with data mapping or improper extraction/loading into your target system. To streamline this effort, validation should be a multi-step process, as follows:
1. Perform report-level comparisons
The most common form of validation occurs at the report level. This step involves a comparison between reports from the source system and those of your target system. Before any data conversion, begin by checking to see if your new system enables report-level comparison. Assess if the new system can run the reports that you need, including all of the same fields. Understanding any limitations early in the conversion process helps data validation go as smoothly as possible. Comparing two completely different reports prevents proper data validation and can cause a panicked response, potentially causing unnecessary software customization’s and a delay in the overall project schedule.
2. Be specific in your parameters
When performing report-level validation, many firms will use arbitrary reporting parameters. For example, they’ll compare data at the firm-wide level instead of comparing a specific matter, department, timekeeper, etc. When the report-level validation becomes more specific, it enables valuable discovery of any existing conversion issues. Its clearer if there is a data mapping issue or a loading issue, saving your conversion team time.
3. Get organized
Breaking down all reporting metrics by record type is an excellent way to organize your validations. It enables you to determine if all records are converted properly under the same record type. Additionally, most firms have complex calculated metrics with variables that are filtered on certain records types. Make sure that your firm has an accurate understanding of these metrics, that they’re mapped correctly, and that you have access to reports showing these metrics. Otherwise, it can be difficult to reconcile without pre-existing knowledge of how these calculations were built in your source system.
4. Set up a validation schedule
Some firms perform validations far too often in hopes that metrics showing variance between systems metrics will have changed overnight. Data validation is just one step in the conversion process. It doesn’t have to be done daily.
Firms should plan to complete a data validation after each conversion on a scheduled basis. While you are waiting between conversions for additional changes, you can set up an automated look-up comparison. This feature enables you to compare extracted data between systems to save you a considerable amount of time over the life of the implementation process.
To learn more about data conversions, including planning, extraction, programming, and validation, please contact the Wilson Allen team of legal technology experts.