Understanding the New AWS Cost Efficiency Metric

As cloud usage grows, organisations are finding it increasingly difficult to understand whether their cloud spending is actually efficient. At OpsLyft, we work closely with engineering, finance, and FinOps teams, and we see the same challenge everywhere: scaling infrastructure is easy, but measuring cost efficiency is not.

AWS recently introduced a new Cost Efficiency metric within Cost Optimization Hub, and it aims to simplify this problem. In this blog, we break down what the metric means, how it works, and how teams can use it effectively. Our goal is to help organisations use metrics like this to improve cloud governance and cost visibility.

Why measuring cloud cost efficiency has been so difficult

Teams often invest heavily in cost optimisation but still struggle to answer basic questions such as “How efficient is our cloud spend?” or “Which business unit is using resources wisely?”

Based on our experience, these challenges appear consistently:

• Lack of agreement among stakeholders

Different teams prefer different metrics:

• Engineering teams look at utilisation.
• Finance teams track ROI.
• Product teams focus on unit costs.
• Leadership wants simple business metrics.

Without a unified definition, building consensus takes months.

• Misaligned optimisation goals

Teams track different metrics:

• One measures CPU utilisation,
• Another tracks commitment coverage,
• Another focuses on idle resources.

This results in:

• No standard benchmark of “good performance”
• No consistent view for comparison
• No ability to drive behavioural change

• Difficulty combining optimisation components

Optimising only one metric can harm the others. For example:

• High commitment coverage discourages idle cleanup.
• Focusing only on CPU ignores memory or network constraints.
• Teams spend excessive time reconciling datasets.

These issues highlight why a standardised and automated metric is important.

Why a unified cloud cost efficiency metric matters

A single efficiency metric simplifies communication and ensures that optimisation efforts are aligned across teams.

The new AWS Cost Efficiency metric addresses common pain points by offering a unified score.

It provides:

• A combined view of rightsizing, idle cleanup, and commitment savings
• A shared language for comparing business units fairly
• Automated calculations instead of manual reconciliation
• A balance of clarity and detail for both practitioners and leadership
• A clear link to action, since the score directly reflects optimisation changes

This makes cost efficiency easier to measure and explain across the organisation.

Understanding how the AWS Cost Efficiency metric works

Before using the metric, teams must enable:

• AWS Compute Optimiser
• Cost Optimisation Hub
• Cost Explorer (recommended)

Once enabled, the metric becomes visible within 36 hours.

Formula used by AWS

The Cost Efficiency score is based on the last 30 days of optimisable spend and today’s savings opportunities.

Cost Efficiency = [1 − (Potential Savings / Total Optimisable Spend)] × 100%

To understand this score, we break down its components.

What “Potential Savings” includes

AWS calculates potential savings by identifying cost-saving opportunities across multiple areas:

• Rightsizing recommendations

• EC2 instance downsizing
• RDS instance optimisation
• Autoscaling group adjustments

• Idle resource cleanup

• Unattached EBS volumes
• Idle RDS instances
• Unused load balancers

• Commitment-based savings

• Reserved Instances
• Savings Plans
• ElastiCache commitments

• Migration optimisations

• Moving to Graviton-based instances

• Storage optimisation

• Right-sizing EBS volumes
• Managing RDS storage efficiently

All calculations consider existing discounts for realistic savings estimates.

What “Total Optimisable Spend” means

This represents:

• Net amortised cost of supported AWS services
• Spend where AWS provides optimisation recommendations
• Cost after removing credits and refunds

The goal is to balance simplicity and accuracy so that leadership can clearly understand the result.

Tracking efficiency over time

Once enabled, you can view 90 days of historical data with:

• Daily trends
• Monthly insights
• Custom ranges for quarters or fiscal periods

This helps organisations understand both short-term reactions and long-term patterns.

Supported dimensions for analysis

Teams can break down efficiency by:

• AWS account
• AWS region

CLI and SDK support allows deeper automation and reporting.

Usage patterns and best practices

1. Benchmarking across teams

• Cost efficiency allows us to compare different business units fairly.
• For example:

Team / Account

Efficiency Score

Marketing

78%

Engineering

65%

Data Science

82%

Benefits:

• Helps identify best-performing teams
• Encourages positive competition
• Guides focus areas for optimization

2. Tracking improvements over time

• We can see the impact of optimization actions within 24–48 hours.
• Any decline in score acts as an early warning, prompting investigation.

3. Demonstrating ROI to leadership

A clear before-and-after comparison highlights the business value:

• Baseline efficiency: 60%
• After 6 months: 82%
• Realized savings: $386K/month
• Annualized impact: $4.6M

This encourages ongoing investment in FinOps practices.

Integrating with existing FinOps practices

• The metric complements traditional KPIs like commitment coverage, budget variance, and cost per transaction.
• Using the ListEfficiencyMetrics API, we can pull this data into dashboards on QuickSight, Tableau, PowerBI, or internal FinOps portals.
• Deep links to Cost Explorer enable users to seamlessly drill into spend insights.

How Opslyft enhances this ecosystem

• At Opslyft, we extend these capabilities with a comprehensive FinOps platform designed to help teams operationalise cloud cost efficiency more effectively.
• Our product includes:
  • Advanced anomaly detection, enabling teams to create custom anomaly definitions unique to their organisation
  • AI-powered recommendations tailored to actual usage, cost patterns, and business context
  • Multiple integrations across cloud platforms, incident systems, and data pipelines
• These tools complement AWS’ Cost efficiency metric, helping organizations extract even deeper insights and achieve faster optimization outcomes.
• You can learn more in our latest product update blog, where we highlight enhancements across automation, governance, and visibility.

Conclusion

AWS’s cost efficiency metric finally provides a standardized, comprehensive way to evaluate cloud optimization performance by unifying resource optimization, commitment planning, and idle cleanup into a single, easy-to-interpret score. With daily refreshes, historical trend visibility, and full API support, it becomes an essential component of any mature FinOps framework. When complemented by platforms like Opslyft, organizations gain deeper insights, automated anomaly detection, intelligent recommendations, and faster, more scalable cost-saving outcomes.