Background 

As part of their on-going digital transformation, a client from the charity sector initiated the migration of several critical applications to an Oracle platform, encompassing systems for Finance, HR, Payroll, and Volunteer Data.

Their previous volunteer management system stored data for approximately 1000 volunteers, making it essential to migrate this information accurately and efficiently.

Challenges

The previous volunteer management system contained vital details about the roles of individual volunteers, and the challenge was to migrate this data into the new system.

• To migrate this data into the new system, the data first needed to be extracted by manually producing an estimated 170 exports one by one.

• The data then needed to be manipulated to include all the information required.

• Finally, all the exports needed to be combined into one report that could be imported into their new system.

The expectation was that this report would have to be produced on four separate occasions. The primary challenges revolved around the need to produce these exports quickly and ensure their accuracy. Any manual approach in comparison would have been slow and costly, and potentially prone to errors.

Solution

Two automated scripts were created to streamline the data migration process. The first script automated the extraction of the required data from previous volunteer management solution, whilst also enhancing it by adding essential information such as project names and volunteer role types. The second script then seamlessly combined all the exports into a single CSV file, ready for import into the new system. 

The key tool used for this automation project was Selenium WebDriver, which is typically employed for automating functional tests on web-based applications, however in this case, it proved to be highly adaptable to the task of data extraction. Thanks to these scripts, the time required to generate the necessary report was significantly reduced.

Outcome

The implementation of the automated scripts brought about several positive outcomes for the successful data migration.

ACCURACY

The risk of human error was eliminated by automating the data extraction and manipulation process.

SPEED

The task now takes just about an hour to complete.

REDUCED COSTS

The Return on Investment (ROI) increases each time the scripts are run. Initially, it was anticipated that the exports would need to be run only four times. However, the automated scripts have already been run five times, with at least one more run scheduled before the migration project’s completion. This demonstrates a tangible cost-saving and efficiency gain.

Conclusion

As the automated migration solution has been repeatedly used, it continues to save both time and money. In comparison to the initial estimation of 10 hours for manual report production, followed by manual data manipulation and amalgamation, the automation process significantly reduces the effort required.

This case study exemplifies how embracing automation in data migration can lead to enhanced accuracy, efficiency, and cost-effectiveness, ultimately benefitting clients in migrating data from system to system.

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