5 tips for ERP test data management

In today’s IT industry, companies look for ways and means to reduce costs. They do this in various ways, for example reducing infrastructure costs, shortening test cycles to reduce testing costs, introducing automation, etc. One of the key factors in improving quality and reduce costs in providing the right set of data at the right time to the right environment.

Testing ERP applications is a critical and challenging task. This is due to the mission-critical business operations and frequent changes to the application with upgrades, patches, and others. Incomplete, missing or corrupt data will impact the quality of testing and is therefore more likely to increase the risks of business blocking defects. This leads to real-world effects when it comes to ERP.

 

ERP test data challenges

ERP testing poses challenges due to business-critical operations and frequent changes in the application with upgrades and patches. The implementation of proper test data management is essential for ERP landscapes. But it differs from the traditional implementation for SaaS, Cloud, on-premises, or other legacy applications.

There are challenges in preparing and managing test data. For example, data integration, data availability, data compliance, data generation and automation, downtime and storage costs. They affect the quality of testing and increase the risk of business-blocking defects.

 

Best practices for ERP test data management

1. Matching ERP data volume to demand. LEAN copy versus EXACT copy

When providing data for testing ERP systems, it is important to consider the types of testing that take place. If data are established for unit testing during development, the volume may be small and isolated to the process being tested. It makes no sense to put large amounts of data into a development branch that is not intended or suitable for performance testing.

 

2. Ensure that production data to be copied does not impact other scenarios

Many of our clients, particularly those in consumer electronics and retail, come to us when they need to update test data. Without damaging other already present data or scenarios.

For example

Some parts of a material master have been updated on the test environment, such as expanding the material to a new plant. This cannot be overwritten, but testing cannot continue without the latest pricing conditions, new suppliers or customers recently created in production. This requires laser-like precision in identifying data and the filter options chosen. Production-driven data virtualization can be a solution to this problem, as it is easy to create and restore snapshots before (or after) test execution.

 

3. Sensitive data should be masked without reducing its testing value

By intelligently masking labels and identifiers, you can use real data for testing without losing its value. When that capability is lost, companies fall back on asking the tester to create the data. The danger here is that the person testing brings their biases with them. While intelligently masked data often surprises us the most by revealing otherwise hard-to-discover flaws.

 

4. Good testing processes are repeatable and where possible automated

Manual testing is costly, prone to error, and simply too time consuming. To enable business agility, testing must become faster and easier to schedule and execute. With 35% of large enterprises’ IT budgets going to software testing, there are clear benefits to be gained through automation.

 

5. Create simple, change-focused test scripts

Make the data and exact testing process identifiable and recordable. This ads consistency and repeatability to your test scenarios. Once your organization has a collection of repeatable test scripts, the reliability of development goes up. Besides that, automation becomes much simpler, cheaper, and it allows manual testing (often performed by Business Key Users) to focus on the new and/or complex and critical cases.

 

Conclusion

Managing test data is crucial and important for ERP success. Test data management is the driving factor for today’s continuous delivery model. Tools only aid you in moving data from one place to another, but test data management solutions around process, architecture, virtualization and automation will drive the success of your ERP implementation.