The Challenge:

Throughout the E-Business Suite and Fusion Cloud application lifecycles, existing data must be analysed. For example:

• Business-as-usual support to investigate and resolve issues
• Current setups when designing changes or enhancements
• Customisations to understand the impact of upgrades and patches
• The effect of upgrades and patching on existing setups
• The effect of upgrades and patching on application components to determine where testing should be focussed
• Changes to seeded data during upgrades and patching and the effect on business processes and security
• Change over time to support audit and control requirements

Traditional manual methods provide no easy mechanism for a user to analyse existing data. Documentation is difficult to interpret and may not be a true reflection of the current set up. Standard application reports for setup areas are generally poor and inflexible. Users usually revert to manually reviewing data within the system itself, running standard reports and then manually manipulating the output, writing ad-hoc queries or a combination of these approaches. None of these methods are effective.

The need for analysis is perhaps most acutely felt during patching and upgrade cycles, where potentially thousands of changes occur and organisations have no simple way to identify the impacted items and their effects. The burden of finding the impact and any resulting issues is generally left to the testing cycle. However, as impacts have not been systematically identified it can never be known whether the test cycle has successfully identified them all or not, increasing the risk that some impact is missed. Further, as impacts cannot be easily isolated, testing scope is often broadened to compensate for the lack of clarity; this means, inevitably, areas are tested that were not actually affected adding to the cost of managing the change.