AI-assisted Postmortem Analysis
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Last updated
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In incident management, the post-mortem process is crucial for teams to learn from past events and reduce future risks. Traditionally, creating these post-mortem reports has been a detailed and time-consuming task, requiring a lot of effort to create a clear story from different sources of data. However, the introduction of AI and Large Language Models (LLMs) brings a new approach to incident analysis, making it easier and more efficient to develop post-mortem documents.
AI-assisted post-mortems make analyzing incidents straightforward and powerful. They leverage chat conversations, alerts, and reports, turning them into a detailed event narrative. This data, showing every decision, observation, and action, becomes easy to navigate with AI, making what used to be a complex task simple and automatic.
AI systems can quickly read and understand large amounts of text from conversations and logs. They focus on finding the main events, choices made, and actions agreed upon. Using advanced language models, AI can pinpoint important details like how the incident affects the business, what caused it, and the steps taken to fix it.
LLMs excel in gathering and arranging information into a well-structured, brief report. This report efficiently covers the entire event, including what led to it, the sequence of events, and the efforts made to manage it. The AI provides a straightforward and clear narrative that lays a solid groundwork for further examination and conversation.
Moreover, AI-assisted post-mortems can highlight potential areas for improvement. By analyzing the incident in the context of past events and known issues, AI can identify patterns and suggest actionable insights. These might include recommendations for process adjustments, training needs, or system enhancements to prevent future occurrences.
The advantages of integrating AI into the post-mortem process extend beyond saving time. By ensuring a high level of accuracy and comprehensiveness, AI-generated reports offer several benefits:
Consistency:
AI ensures that every post-mortem report adheres to a consistent format and level of detail, facilitating easier comparison and trend analysis across incidents.
Objectivity:
By relying on data and analytics, AI minimizes the potential for bias or oversight, offering an objective account of events.
Depth of Insight:
With the ability to process vast datasets, AI can uncover insights that might be overlooked in manual analysis, providing deeper understanding of underlying issues.
Actionable Recommendations:
AI models can correlate incident data with historical trends to offer pragmatic suggestions for preventing future incidents.
Below is a sample post mortem report that was generated entirely by ilert AI.