Vladimirs Romanovskis
Incident Management Teamlead

In our final chapter, following the establishment and streamlining of Incident Management (IM) at Dyninno Group covered in the previous articles, we now turn our focus to the future. Here, we will delve into the strategic use of metrics and the integration of advanced technologies like AI, which represents not just a change in operations, but a leap towards a more proactive, efficient, and future-proof organization.

Strategic Use of Metrics

We have established key metrics for incident management. Firstly, we began tracking the monthly incident count to identify gaps in our awareness. Secondly, we measured the proportion of incidents detected by monitoring tools versus other sources, like end-user reports.

We also started evaluating incident resolution times and the implementation of preventive actions, with the latter ensuring that issues would not recur.

This move aimed to transition from quick fixes to a more robust, future-proof system.

To measure the process’s efficiency, we’ve established SLA metrics, focusing on response times to monitoring alerts and end-user reports. This helps ensure immediate action on incidents rather than delaying until the next business day.

We also track handover times, detailing the timeframe from incident acknowledgment to escalation. Data on ‘time decomposition’ illustrates how time is spent during an incident’s lifecycle, emphasizing the importance of swift detection, reporting, reaction, handover, and resolution.

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