Many organizations collect metrics without carefully analyzing the purpose behind them. If the metrics don’t meet their needs, they tend to ignore them, and where metrics are not carefully defined or analyzed, doubt may arise regarding the validity of the data.
In this case study of Washington Mutual, more than 1800 metrics were being collected and disseminated, sizable errors were being made, and confidence in the available data was low.
They developed a process to review, create, analyze, and manage all metrics. A lifecycle management practice was enacted to ensure that regular reviews could be scheduled and executed to maintain relevancy and accuracy.
A complete analysis reduced the metrics to 250, confidence and usability of data increased and the infrastructure teams were able to leverage the data to make decisions that significantly affected projects and budgets, producing savings of $2.7 million.