Top 10 Post-Incident Review Best Practices

Want to handle IT incidents better and prevent them from happening again? Post-incident reviews are your solution. They help teams learn from failures, reduce downtime, and improve system reliability. Here’s a quick summary of the top practices to get it right:

1. Create a No-Blame Culture: Focus on processes, not people, to encourage honest discussions.
2. Act Quickly: Start reviews within 24-48 hours while details are fresh.
3. Build a Clear Timeline: Break down the incident into phases like detection, response, and recovery.
4. Perform Root Cause Analysis: Use methods like 5 Whys or Fishbone diagrams to uncover underlying issues.
5. Involve All Teams: Gather insights from technical, customer service, and operations teams.
6. Centralize Data: Use one platform for logs, metrics, and communication.
7. Define Actionable Steps: Turn insights into specific, measurable tasks.
8. Document Findings: Write clear reports with timelines, root causes, and action items.
9. Leverage Automation: Use tools to collect data, detect anomalies, and generate reports.
10. Commit to Improvement: Continuously refine processes and track progress.

Quick Tip: Tools like eyer.ai can streamline data collection and analysis, helping you act faster and smarter. Start implementing these steps today to turn incidents into opportunities for growth.

A Post Incident Review Review

1. Build a No-Blame Environment

Turning post-incident reviews into productive discussions starts with creating an environment where team members feel safe sharing what went wrong. A no-blame culture shifts the focus from individual errors to understanding and fixing systemic issues.

Here’s how to make it happen:

• Focus on processes, not people: Use neutral, fact-based language when discussing incidents. For example, say, "The deployment process skipped testing," instead of pointing fingers.
• Highlight areas for improvement: Treat every incident as an opportunity to refine systems and processes.

"A blameless culture is essential for effective reviews, enabling teams to focus on learning, not blame." - Atlassian ^[1]

Google has mastered this approach in its incident management, balancing accountability with a focus on systemic fixes. This mindset helps improve response times and overall reliability.

Leadership plays a huge role in setting the tone. When managers and executives show through their actions and words that blame isn’t the focus, teams are more likely to follow suit. To measure progress, keep an eye on metrics like the quality of incident reports, team engagement, and how well action items are being implemented.

2. Start Reviews Without Delay

Kick off post-incident reviews within 24-48 hours to ensure details are still fresh. As Jira Service Management Cloud highlights, postponing reviews can lead to missed insights and less effective outcomes ^[1].

Gather logs, communication records, and performance metrics immediately. Assign a team member with relevant expertise to lead the review, ensuring clear accountability and timely progress. Tools like eyer.ai can simplify this process by automatically capturing performance data and identifying anomalies, making it easier to perform an initial analysis.

Using standardized templates helps maintain consistency, avoid missing key details, and speed up the review process. Focus on these critical areas:

• Initial Response: Record the immediate actions taken and their results.
• Impact Assessment: Note which systems and users were affected.
• Resolution Steps: Outline the steps taken to resolve the issue.
• Team Involvement: Identify all teams and individuals who played a role.

Act quickly to maintain accuracy while covering all necessary details. Aim to collect data and assemble the team within 24 hours, draft documentation within 48 hours, and complete the review within five business days.

"A prompt review revealed a critical gap in communication that led to an extended downtime. By identifying this gap quickly, the team was able to implement changes that significantly reduced MTTR in subsequent incidents" ^[1].

Once the review process is underway, the next step is to create a clear incident timeline for a deeper analysis.

3. Map Out a Clear Incident Timeline

After gathering the initial data, the next step is to organize it into a detailed timeline. This timeline helps pinpoint critical decisions, identify communication gaps, and highlight areas where response times can improve.

Break down the incident into key phases, noting exact timestamps for both automated and manual actions:

• Detection: When the issue was first identified and alerts were triggered.
• Response: Steps taken to troubleshoot and notify the team.
• Communication: Updates shared with stakeholders and coordination efforts.
• Resolution: The technical fixes implemented to address the issue.
• Recovery: Verifying service restoration and ensuring everything is back to normal.

Keep records in real-time to ensure accuracy. Tools like eyer.ai can automatically link related events across logs, alerts, and team communications, making it easier to build a cohesive timeline.

"A timeline is a very helpful aid in incident documentation. Often it's the first place your readers' eyes jump to when trying to quickly size up what happened." - Jira Service Management Cloud Documentation ^[1]

Using standardized templates ensures consistency and clarity. This structured approach lays the groundwork for root cause analysis, which we’ll dive into next.

4. Perform Root Cause Analysis

Once you’ve mapped out the incident timeline, it’s time to dig deeper into the reasons behind the issue. Root Cause Analysis (RCA) is all about methodically identifying what went wrong and why.

Start by collecting detailed data from monitoring tools and team inputs. Tools like eyer.ai can simplify this process by linking anomalies to performance data, helping you pinpoint problems more quickly.

When analyzing, focus on these key areas:

• Technical Factors: Look into system setups, recent code updates, and infrastructure.
• Process Gaps: Pinpoint where workflows or documentation fell short.
• External and Human Factors: Assess environmental conditions, decision-making, and communication.

To make your RCA effective, track metrics like incident severity, downtime, and Mean Time to Resolution (MTTR).

Tackle challenges by:

• Leveraging automated tools for better data collection.
• Encouraging open and blame-free discussions.
• Sticking to structured analysis methods.
• Fixing system issues rather than pointing fingers.

Once you’ve identified the root causes, your team can concentrate on making specific changes to avoid similar problems in the future.

5. Include Input from All Relevant Teams

To create a thorough post-incident review, you need input from a variety of teams. Each group brings a unique perspective, helping to paint a complete picture of what happened and how it was handled.

To make the most of these insights, assign a facilitator to lead discussions and ensure all viewpoints are captured. Automated tools can also help by providing objective data to keep discussions focused and productive.

Challenges like scheduling conflicts or differing opinions can make this process tricky. Tackle these issues with structured review sessions, clear agendas, and options for asynchronous feedback. Track team participation and the diversity of insights to gauge involvement.

When gathering input, focus on how teams detected and responded to the incident, shared information, allocated resources, and evaluated the impact. Encourage them to suggest ways to improve processes. This collaborative effort ensures a well-rounded understanding of the incident and paves the way for better handling in the future.

Once all inputs are gathered, the next step is to centralize the information for deeper analysis and clear communication.

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6. Centralize Data and Communication

After gathering input from all teams, it’s important to bring everything together in one place. This ensures everyone works with the same information, avoiding confusion and breaking down silos.

To centralize effectively, focus on these three components:

When building your centralized system, assign specific team members to manage and organize the data. This prevents disorganization and ensures the information stays accurate and easy to access.

For technical monitoring, tools like Eyer.ai can help by automatically gathering and connecting performance metrics. This makes it simpler for teams to analyze and act on incident data.

Here’s how you can strengthen your centralized system:

• Use standardized templates for consistent incident documentation.
• Set access permissions to safeguard sensitive data.
• Enable version control to track changes and updates.
• Define data retention policies to keep historical records for analysis.

Challenges like resistance to new tools or poor documentation can be tackled with proper training and clear guidelines. Regularly review and adjust the system based on team feedback to keep it effective.

With everything in one place, teams can shift their focus to creating actionable steps for preventing future issues and refining processes.

7. Focus on Actionable Next Steps

Once your data is centralized, the goal is to turn insights into practical actions. Clear, measurable steps are key to making progress.

Use the SMART framework to ensure each action is specific, measurable, achievable, relevant, and time-bound. This approach helps convert insights into real-world improvements.

Here’s a simple structure for creating effective action steps:

When documenting these actions, make sure to assign clear ownership and set deadlines. Tools like Eyer.ai can help teams track progress and evaluate how effective these changes are.

To make sure your action items are executed smoothly:

• Track Progress: Use a shared dashboard to keep an eye on implementation.
• Regular Reviews: Hold bi-weekly check-ins to tackle any roadblocks.
• Measure Impact: Define metrics to gauge the results of your efforts.

Start with quick wins - those high-impact, low-effort changes that can build momentum. For bigger tasks, break them into smaller, manageable steps to keep things moving forward.

"Avoid language that singles out individuals as personally responsible for the incident. Instead, focus on actions, results, and impact." - Jira Service Management Cloud ^[1]

Once your next steps are outlined, the next move is to document and share these lessons to encourage growth and improvement across the organization.

8. Document and Share Key Findings

Keeping track of what happened during an incident is crucial for learning and improving. Writing down key details within 24-48 hours helps ensure the information is accurate and useful, turning incidents into a resource for the entire organization.

Using a structured template can help keep your documentation clear and complete. Here's what you should include:

When sharing this information, aim to make it easy to understand and actionable. Tools like eyer.ai can enhance your analysis by identifying patterns or anomalies in performance data that might go unnoticed during manual reviews.

To make your documentation truly effective:

• Keep it simple and centralized: Focus on the main takeaways and next steps.
• Update it regularly: Adjust and improve the documentation as new insights emerge.
• Measure its impact: Use metrics like response times and the frequency of recurring issues to see if your process is working.

Good documentation doesn’t just describe what happened - it explains the context, decisions made, and lessons learned. This way, it becomes a powerful tool to help avoid similar incidents in the future. Once your findings are recorded, you can move on to using automation to make processes smoother and prevent future problems.

9. Use Automation to Improve Processes

Automation can cut down manual work, boost accuracy, and ensure consistency in post-incident reviews. According to Gartner, it can even reduce Mean Time to Recovery (MTTR) by up to 50%. Studies highlight that organizations using automation see noticeable improvements in handling incidents.

Here's how automation can reshape your post-incident review process:

AI observability tools make anomaly detection faster and connect performance issues to incidents. For instance, eyer.ai helps teams identify problems early, preventing them from escalating into major incidents.

To get the most out of automation:

• Start with repetitive, time-consuming tasks to see immediate results.
• Maintain human oversight: Let automation handle data and analysis, but keep humans in charge of critical decisions.
• Integrate with existing systems: Choose tools that align with your current setup, supporting open-source solutions and protocols like Prometheus and OpenTelemetry.

Automation isn't just about saving time - it allows teams to focus on strategic goals, encouraging continuous improvement and a forward-thinking approach to incident management.

10. Commit to Ongoing Improvements

Turning lessons from post-incident reviews into actionable strategies is key to building long-term resilience. Experts in incident management note that organizations with structured improvement processes often experience fewer recurring incidents over time.

Here’s a breakdown of how organizations typically approach continuous improvement:

To create a solid framework for continuous improvement, prioritize these key elements:

Metrics-Driven Decision Making

Use data to assess the impact of your changes over time. Tools like eyer.ai can provide real-time performance insights, simplifying the process of tracking and refining your strategies.

Knowledge Integration

Update runbooks, documentation, and training materials with lessons learned. This ensures your organization retains and applies its knowledge effectively.

"A blameless culture is key to making sure your teams openly share information and get to the root cause of an incident." - Atlassian Support, Jira Service Management Cloud ^[1]

Cross-Team Collaboration

Keep communication channels open so all teams can contribute to and benefit from improvement efforts. Collaboration ensures a unified approach.

Resource Allocation

Allocate resources thoughtfully to balance improvement initiatives with day-to-day operations. This helps maintain steady progress without overburdening your team.

Improvement is an ongoing process. Start with small, achievable changes, and build from there. Automation tools can handle repetitive tasks like data collection and analysis, freeing your team to focus on strategic advancements.

Conclusion

Post-incident reviews play a key role in creating stronger systems and teams. By applying these ten practices, organizations can improve how they manage and learn from incidents, resulting in better system reliability and team effectiveness.

Organizations that adopt these practices often see improvements in two main areas:

Modern tools and automation make the review process even more effective. They offer detailed performance data and help teams spot and address risks before they escalate. When combined with these practices, such tools enable a proactive approach to incident management.

The strength of post-incident reviews lies in their structured approach. Each practice - whether it’s timely reviews, in-depth root cause analysis, or fostering teamwork - builds a framework that turns incidents into learning opportunities. Together, these steps enhance an organization’s ability to handle challenges.

Improving incident management is an ongoing process. Start with the basics, then introduce more advanced techniques as your team grows. Treat post-incident reviews as moments to learn and improve, not just as routine tasks.

FAQs

How to conduct a post-incident review?

A post-incident review works best when approached methodically. Here's an outline of the key steps:

Aim to conduct the review within 48 hours of resolving the incident to capture accurate details. Use standardized templates, set clear review criteria, and monitor metrics such as downtime and MTTR for consistency and measurable outcomes.

When documenting, focus on these key details:

• Teams and individuals involved
• System states and changes during the incident
• Communication methods and tools used

Tools like eyer.ai can simplify this process. They automate data collection and analysis, speeding up root cause identification. Plus, their anomaly detection features offer insights into system behavior before the incident occurred.

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