Corporate Performance Management - CPM - Solutions for Data Quality - Uniserv

By: A W Tunbridge Land Surveying  09-12-2011

Incorrect, out-of-date or duplicate data falsifies important key figures

CPM is focused on the key figures (Key Performance Indicators/KPI) of the company. They represent the quantitative performance of a department or the entire company and form the basis for the permanent monitoring, analysis and optimization of the business processes. In contrast to Business Intelligence, other dimensions such as customer satisfaction, the value of trademarks and patents or the motivation of employees play a role in CPM and not just financial indicators and throughput times. Since countless IT systems from different departments have to supply data here, incorrect, out-of-date or duplicate data can have a devastating effect on the precision and reliability of the evaluations.

Inaccurate performance indicators lead to incorrect decisions

If your performance indicators are based on poor data quality in the Data Warehouse, incorrect results may be obtained when your planning targets are matched against the current company performance. This may mean that you incorrectly assess the performance of individual departments, business processes or the entire company and carry out the requisite optimization of operative or strategic activities too late or not at all. In this case, your forecasts may be wrong and you quickly fall behind the competition. Risk management is also affected if you incorrectly assess current weak points, which can also cause difficulties in adhering to compliance regulations.

No confidence in CPM –  less efficiency in corporate planning

If the CPM system does not meet the expectations of the decision-makers as a result of poor data quality and imprecise evaluations, the excellent opportunities offered by CPM may no longer be used consistently. Bad planning and bad forecasts are the inevitable result here, since decisions are not made on the basis of key indicator analyses, but on the basis of inadequate information or even a gut feeling.

Manual data cleansing delays decisions and increases costs

If the data required for the analysis is incomplete, incorrect and inconsistent in the Data Warehouse, it has to be manually compiled, evaluated and prepared in reports. This prevents it from being matched quickly against planning targets and delays urgent adjustments of critical business processes. And you spend a great deal of money on IT resources which you could use e.g. for business-critical IT projects.

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