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The pace of change is constantly increasing, and companies have to keep up with the latest trends, consumer needs to stay relevant in a highly competitive environment.
To serve customers better, many companies today rely on a vast amount of data. Monitoring solutions are collecting and sharing log data, metrics, status reports, alerts, and more, so that service providers can react to errors, reduce downtimes, and improve service quality in general.
Nevertheless, not all organizations are prepared equally to utilize data efficiently, therefore more data is not always the answer in itself. Without proper monitoring maturity and preparedness, organizations are missing out on important insights that real-time data can provide, and cannot differentiate the origin of an IT issue.
This is where the Business Process Maturity Model (BPMM) published by the Information and Communications University of Seoul, South Korea can serve as a useful tool, to identify the current level of preparedness of a given organization to monitor IT performance.
According to the Business Process Maturity Model (BPMM), there are 5 distinct levels of IT performance monitoring maturity:
Level 1 - Ad-Hoc: No awareness of user experience
At the first level, monitoring of the components is ad-hoc and chaotic. Many of the errors and issues are undocumented, unidentified. Due to this fact, several issues can stay unresolved causing an ongoing decline in user experience and service quality. Because of the unpredictability of additional errors showing up, most of the burden is on the IT helpdesks to receive, identify, and solve the IT-related issues, which can result in long mean-time-to-recovery (MTTR) rates.
Level 2 - Reactive: Basic awareness with component monitoring
The second level can provide information about the status of the different components separately, and the operation is mostly limited to reactive solutions. While it has more data available, operations are still mostly about “putting out fires”, rather than proactive error-mitigation. Organizations at this maturity level often have to work through a large quantity of event noise and find the root cause of errors demands significant efforts to be done manually.
Level 3 - Advanced-reactive: More in-depth monitoring
The organization is able to monitor the IT performance from different viewpoints, and optimize the functioning of specific tools. Moreover, it is starting to move towards the use of service impact analysis, to understand the effect of certain events on the IT service levels, and user experience. However, it is still lacking the aggregation of machine data, and it requires manual effort to consolidate all the available data into a common service impact analysis report.
Level 4 - Managed: A deeper level of understanding and integrated overview
Organizations with level 4 maturity focus on the interactions between applications, infrastructure, and workload. Service Level Agreements (SLA) can be guaranteed to clients with high reliability. Centralized data consolidation and normalization are supported. The effective predictability of future failures is still lacking at this maturity level.
Level 5 - Optimal: Real-time visibility and automated operations
Level 5 organizations have optimal IT performance monitoring processes and assets in place. Machine learning algorithms help businesses conduct predictive analyses, to address issues that might be lurking in the background but just not manifest yet. Scaling up or rerouting services can be done before systems are overloaded, and faster mean-to-to-recovery (MTTR) rates can be achieved, along with a high level of user experience and flawless service levels.
Visit the MCG website to learn more about how to improve your IT performance monitoring, and what solutions are available.
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