Earlier portions of this series introduced the Five Phases of Maturity and the first five areas of the Six Assessment and Planning topics.
In this final part, we wrap up the series with a discussion on Data Analytics and Business Outcomes.
Getting started with monitoring and observability isn’t difficult, though it can sometimes be overwhelming—particularly in an era where organizations have hundreds, sometimes thousands of applications supported by what seems to be ever-shrinking IT operations teams.
If you’ve made it this far in the series, you should be on the right track in terms of leveraging your IT tools to fully monitor your entire IT estate, minimize downtime, optimize application performance, and streamline troubleshooting through powerful, tool-driven, cross-domain intelligence.
Tools deployed and working together allow our IT teams or ‘silos’ to be the best versions of themselves, experts in their realm, and with fully meshed data sharing and correlation between teams.
And that sets the foundation for our final topic, Data Analytics and Business Outcomes. The data from our optimally deployed tools can be leveraged to go beyond just health and performance, and we can begin to analyze our tools data in valuable ways that better support the organizational goals and outcomes. This includes;
- Performance trend analysis to better understand workloads and balance costs for improving workload performance
- Advanced aggregation of monitored entities and time series data using organizational-specific data dimensions
- Federated sources blending different organizational data with IT tools data
- Custom visualizations not available in native monitoring dashboards
- Capacity analysis and planning closely related to performance trends
- Analysis of user engagement and user behaviours of applications for improved user experience
- Analysis of shared infrastructure for planning hardware refresh, cloud/application/data migrations, hardware retirement, etc..
- Analysis of applications for possible re-architecture, cloud hosting, or containerization
- Analysis of organizational performance with clear relationships between the scale of the IT operations environment and the headcount responsible for the environment
- Analysis of tool effectiveness, feature completeness, and potential licensing level increases or decreases
- Providing IT leadership with clear visibility of tool investment vs return on licensing, staffing and training
Achieving these advanced analytics is normally beyond the native dashboard and reporting capabilities of the tools themselves. As such, we frequently leverage industry business intelligence tools. Microsoft PowerBI, Tableau, and Qlick are all examples we routinely encounter with our clients.
As outlined in the Observability Data and Metrics assessment area, the data being collected and retained is fundamentally important to the quality and integrity of the analytics performed using that data. Establishing data lakes dedicated to analyzing tools data over more extended time frames is also common. Most tools platforms suffer some performance penalty if too much history or detail is retained in the primary tools repository.
Virtually limitless possibilities exist once these types of tools are brought to bear against monitoring tools data while frequently still remaining closely tied to the tools platforms via integrated dashboards.
Alignment to strategic organizational goals becomes easier while still supporting data-driven methodologies. Frequently, the faith in tools increases as the data analytics grant the insights necessary for improved decision making, forecasting and/or validating strategic ideas.
Finally, driving organizational outcomes through IT tools analytics isn’t a destination, like so many aspects of business operations, it is a continuous journey that must adapt to changing technology and business practices over time. Adopting L1M3 can help start your organization on that journey. Safe travels!
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