Correction of Errors (Aka CoE): A Practical Playbook for Fixing Glitches

Learn how to systematically identify, analyze, and fix errors using the Correction of Errors (COE) framework as popularized by Amazon. At #Amazon, CoE is not just a concept; it is how teams continuously learn, improve, and prevent future mistakes through rigorous root cause analysis and structured solutions. Discover actionable insights and a step-by-step playbook for driving operational excellence and fostering a culture of accountability and innovation.

Disclaimer: The example in this blog is entirely fictional. Any resemblance to real-world incidents, companies, or individuals—living, dead, or in the tech industry—is purely coincidental. No subtitles were harmed in the writing of this blog.

Introduction

In the fast-paced world of tech, even the smallest glitch can snowball into a massive outage. Whether it’s a server crash, a missing feature, or a failed update, errors are inevitable—but how you handle them defines your success. Enter Correction of Errors (COE), a systematic approach to turning mistakes into opportunities for improvement.

In this blog, we’ll break down the COE process using a fictional example inspired by real-world incidents. More importantly, we’ll provide a practical playbook for error detection, correction, and prevention. Let’s dive in!

What Is Correction of Errors (COE)?

Correction of Errors is a structured method for identifying, analyzing, and resolving mistakes in processes. It’s not just about fixing the problem—it’s about understanding why it happened and ensuring it doesn’t happen again.

Key Components of COE:

1. Error Identification: Spotting the issue.

2. Root Cause Analysis: Digging deep to understand the “why.” Read more on 5Whys

3. Corrective Actions: Fixing the problem.

4. Preventive Measures: Stopping it from recurring. [That's SUPER important]

The Problem - Silent Screens: The Great Subtitle Outage

Let’s imagine a global streaming platform (let’s call it Streamify) faced a major outage where subtitles disappeared from all shows and movies. Here’s how they applied COE to resolve the issue:

Step 1: Error Identification

What Happened: Subtitles vanished globally across Streamify’s platform. Users were left frustrated, and social media exploded with complaints.

How It Was Detected:

• Customer Complaints: Users flooded Twitter and Reddit with reports.
• Internal Alerts: None. Streamify’s monitoring systems failed to flag the issue, leaving the outage entirely dependent on external factors for recognition.

Impact:

• Users Affected: 10 million+ (global outage).
• Financial Loss: Estimated $2 million in lost revenue due to canceled subscriptions and ad revenue drops.
• PR Damage: Unaccountable and escalating. Trending on Twitter with hashtags like #StreamifyFail, #WhereAreTheSubtitles, and #CancelStreamify, sparking widespread backlash.
• Press Release Required: Yes

Key Takeaway: Early detection is critical. Relying on external factors for error identification is a recipe for disaster—but it happens far more often than anyone would like to admit! A culture centered around patchwork solutions and quick bug fixes leaves organizations vulnerable, creating a metaphorical 'house on fire' waiting to collapse. Building a proactive approach to error detection and prevention is the key to long-term stability and success.

Step 2: Root Cause Analysis

Investigation: Engineers (Inhouse Sherlock Holmes) traced the issue to a recent software update. The update introduced a bug that disrupted subtitle rendering across all regions.

The 5 Whys:

1. Why did subtitles disappear? Because the subtitle rendering service failed.
2. Why did the service fail? Because the latest update introduced a bug.
3. Why was the bug introduced? Because the update wasn’t tested in all regions.
4. Why wasn’t it tested in all regions? Because the testing process didn’t account for regional differences in subtitle formats.
5. Why didn’t the testing process account for regional differences? Because the testing framework was outdated and lacked comprehensive coverage.
6. Why was the testing framework outdated? Because maintenance and internal upgrades fell below the line for priority.
7. Why did maintenance and upgrades fall below the line? Because resources were allocated to high-priority projects, such as front-end features and competitor-driven initiatives.
8. Why was the update rolled out without A/B testing or a controlled launch? Because it was believed to be a “small change” with minimal risk—a no-harm release.
9. Why was the release classified as no-harm? Because the parameters used to determine “no-harm” were incomplete and subjective. The release was classified as “no-harm” based on perceived Impact (The update was seen as a minor change to the subtitle rendering logic), past success (Similar updates had been rolled out without issues in the past), and limited testing (basic unit tests passed, and no critical failures were detected in staging). We missed accounting for regional complexity (The update wasn’t tested across all regions, ignoring differences in subtitle formats and encoding.), End-to-End Testing (The impact on the entire subtitle rendering pipeline wasn’t fully assessed) and Risk of Cascading Failures (The potential for the bug to disrupt other services wasn’t considered.)
10. Why did approvers of release not Notice the Gaps? Because releases classified as “no-harm” bypassed the standard approval process, as they are deemed low-risk.

Root Cause: The testing framework fell below the line due to resource allocation skewed toward high-priority projects, leaving maintenance and upgrades neglected. The lack of A/B testing and a controlled launch further exacerbated the issue, as the team underestimated the risk of the update. Misclassification of the release as “no-harm” allowed it to bypass critical checks, amplifying the likelihood of failure.

Note: while we are using 'we 'here. Actual CoE will state exact team's name.

Time Taken:

• Error Detection: 10 hours (via customer complaints) before it was escalated.
• Root Cause Analysis: 48 hours (due to lack of internal monitoring and no way to directly link issue to cause).

Key Takeaway: The 5 Whys technique helps uncover the root cause, not just the symptoms. Remember to resist the urge to jump to solutions too quickly. Focus on thoroughly breaking down the root cause until it cannot be analyzed further. It's a process that requires patience and persistence, so take the time needed to ensure a comprehensive understanding!

Step 3: Action Plan

Once the root cause was identified, Streamify implemented the following corrective actions, and preventive measures:

Corrective Actions

1. Immediate Fix

• Engineers rolled back the faulty update and restored subtitles on MM-DD-YY [Tks hours after identification]
• A hotfix was deployed to address the bug without disrupting other services on MM-DD-YY [Tks hours after identification]

2. Customer Communication

• Streamify PR/Communications Team issued a press release acknowledge the issue, assured users the issue was resolved. They provided regular updates on social media to keep users informed.

Preventive Measures

• Modernize Testing Framework: Allocate resources to upgrade the testing framework with comprehensive coverage. ETA: MM-DD-YY | Owner: TKS
• Deprecation Alerts: Establish a mechanism to determine service depreciation timelines and severity, ensuring timely upgrades can be made without critical tools or frameworks falling below the priority line. ETA: MM-DD-YY | Owner: TKS
• Monitoring Enhancements:

1.Add real-time alerts for subtitle rendering errors. ETA: MM-DD-YY | Owner: TKS

2.Implement a dashboard to track subtitle performance metrics. ETA: MM-DD-YY | Owner: TKS

• Automate Rollbacks: Implement automated rollback mechanisms for critical systems to mitigate potential failures quickly and efficiently. ETA: MM-DD-YY | Owner: DevOps Team
• Daily Traffic Testing: Run daily automated tests to simulate user traffic and identify issues early in the workflow. ETA: MM-DD-YY | Owner: TKS

Release Classification and Approval Improvements

1.Define Clear Parameters for “No-Harm” Releases:

• Establish objective criteria for classifying a release as “no-harm,” such as: No changes to critical systems, Full test coverage across all regions and use cases and/or No dependencies on other services. ETA: MM-DD-YY |Owner: Engineering Leadership

2. Mandate Approval for All Releases:

• Remove the “no approval required” loophole for “no-harm” releases.
• Require sign-off from at least two senior engineers or managers for every release.
• ETA: MM-DD-YY |Owner: Release Management Team

3.Implement a Risk Assessment Framework:

• Develop a checklist to assess the potential impact of every release, including: Regional compatibility, End-to-end pipeline testing and Risk of cascading failures. ETA: MM-DD-YY |Owner: QA Team

4.Conduct Post-Mortems for Misclassified Releases:

• Review every misclassified release to identify gaps in the classification process.
• Update the risk assessment framework based on lessons learned.
• ETA: Ongoing |Owner: Engineering Leadership

Key Takeaways from Actions

1. Quick Fixes Aren’t Enough: Preventing recurrence requires systemic changes, not just immediate solutions.
2. Objective Criteria Are Essential: Clear guidelines for release classification and approval reduce the risk of misclassification.
3. Accountability Matters: Mandating approval for all releases ensures accountability and reduces the likelihood of catastrophic failures.

Not All Errors Are Created Equal: a Severity Index

Not all errors or lapses are of the same degree. Some are minor annoyances, while others are full-blown crises. To prioritize effectively, create a severity index that helps your team understand the urgency and impact of each issue.

Factors to Consider for Severity Index:

1. Blast Radius: How many users or systems are affected?
2. PR Impact: Will this issue make headlines or damage your brand’s reputation?
3. Downtime: How long will the issue take to resolve, and how critical is the affected service?
4. Financial Impact: What’s the potential revenue loss or cost of fixing the issue?

Severity Index Table:

Examples:

• Low: A typo in a non-critical feature.
• Medium: A regional outage affecting a specific feature.
• High: A global outage affecting core functionality.
• Fire in the Palace: A security breach or complete system failure.

Action Plan:

1. Define Severity Criteria: Create clear guidelines for each severity level.
2. Train Teams: Educate teams on how to assess and escalate issues based on severity.
3. Automate Alerts: Use monitoring tools to automatically classify and escalate issues based on severity.

Key Takeaway:

A severity index ensures your team knows when to treat an issue as a low-priority task vs. a fire in the palace.

The Role of Leadership in COE

COE isn’t just a technical process—it’s a cross-departmental commitment. For high-severity issues (High and Fire in the Palace), the Head of Department must review and sign off on the corrective and preventive actions. This ensures accountability and alignment across teams.

Why It Matters:

• Accountability: Leadership oversight ensures that corrective actions are thorough and effective.
• Alignment: A signed MoU (Memorandum of Understanding) between departments ensures everyone is on the same page.
• Stickiness: Leadership involvement reinforces the importance of COE, making it a lasting part of the organizational culture.

Lessons from Real-World Outages

While Streamify is fictional, its story mirrors real-world incidents like the AWS outage and the CrowdStrike update. For example:

• During the AWS outage, a single misconfigured update caused widespread disruptions. Companies learned the importance of redundancy and failover mechanisms.
• The CrowdStrike update affected millions of devices, highlighting the need for rigorous testing and rollback plans.

Key Takeaway:

Every outage is a learning opportunity. By applying COE, businesses can turn failures into stepping stones for improvement.

How You Can Implement COE in Your Business

Ready to bring COE to your organization? Here’s how to get started:

1. Create a COE Framework: Define clear steps for identifying, analyzing, and fixing errors.
2. Leverage Technology: Use tools like AI and machine learning to detect errors in real-time.
3. Train Your Team: Empower employees to take ownership of error correction.
4. Measure Success: Track key metrics like error rates and resolution times.

Pro Tip: Start small. Focus on one process, implement COE, and scale as you see results.

The Future of COE

As businesses become more complex, the importance of COE will only grow. By embracing this practice, you’re not just fixing errors—you’re building a culture of excellence and innovation.

What’s your take on Correction of Errors? Have you faced a similar outage or glitch? Share your thoughts below—let’s geek out over operational excellence!

Disclaimer: The example in this blog is entirely fictional. Any resemblance to real-world incidents, companies, or individuals—living, dead, or in the tech industry—is purely coincidental. No subtitles were harmed in the making of this blog.