Data Consistency Management in Solution Manager comprises the tools and procedures required to prevent, detect, investigate and correct inconsistencies in your solution landscape. This helps to ensure the successful execution of your core business processes and prevents costly business process downtimes.
Today's business processes evolve in complex structures involving several systems of the overall landscape. As shown in the picture below it is important to ensure the data consistency between all involved systems.
Apart from user level errors like an incorrect manual entry in the system, there are possibilities of inconsistencies as well on application and technology level. The figure below presents potential causes of data inconsistency.
User Level: Data inconsistencies due to
Application Level: Data inconsistencies within one system or between two systems due to
Technology Level: Data inconsistencies due to
- Database Crash at a customer and last backup ~12 months old. Which business documents/areas are affected?
- Inconsistencies between MM and FI during goods movements with unknown Root Cause. What is the root cause?
- A custom made report has accidentally deleted parts of business objects. Which objects are affected?
- Some data has been replicated multiple times between two systems
- Inconsistent data storage in multiple systems using sRFC/HTTP within one business step. What data arrived where?
- Many IDoc errors between ECC and WM. Is there an interface error that affects my most important business partner?
- What is the financial impact of erroneous FI-IDocs on my PEC?
- Global transparency across organizational units & process variants through increase visibility of current data quality and consistency state.
- Reduced operating costs through automating data consistency management and reduce manual process inefficiencies and human errors. Avoid systematic process exceptions.
- Higher customer satisfaction & faster revenue stream by avoiding delayed business documents and financial losses by quick reaction to interface errors affecting data of core business processes.
- More accurate business reporting by avoiding inaccurate reporting data by ensuring consistency between systems and quicker clean up due to earlier detection
- Higher reliability of financial reporting & possible detection of fraud by avoiding avoid inconsistencies in FI-AP and FI-AR before PEC. Review consistency between MM & FI and between systems.
The process of Data Consistency Management consists of 4 steps: Prevention, Detection, Correction and Investigation. In the picture below, these steps are displayed in a cycle expressing the continuity of the process.
Solution Manager includes several tools to cover the Data Consistency Management cycle and different technologies. The following figure presents those tools. Details for these tools are provided in the tool-specific section.