Finops

How to benchmark cloud commitments: coverage, utilization, and savings after fees

Use our framework to compare eligible coverage, commitment utilization, and savings retained after management fees.

Priyanka

Content Strategist

Updated September 28, 2026

22 min read

Key takeaways

Coverage and utilization measure different parts of commitment performance.

Savings after fees need one consistent cost baseline.

A fair benchmark needs clear definitions, cohorts, and reporting rules.

Are your cloud commitments actually reducing what you pay after fees, or do headline metrics hide unused commitments and uncovered usage?

At Usage.ai, we frame the comparison around three questions:

How much eligible usage receives commitment pricing?

How much of the commitment you purchased is actually used?

How much savings do you retain after management fees?

You need all three.

High utilization does not tell you how much eligible usage is still running On-Demand. High coverage does not prove that the financial result is strong. And a large gross savings number can look different after management fees are included.

This article explains our proposed benchmark methodology. It does not report customer cohort results, observed percentiles, or market-wide performance.

Check coverage and utilization together

Coverage asks:

How much eligible usage receives commitment pricing?

For our proposed comparison, first define which usage is eligible for the specific commitment program. Then value covered and uncovered usage on the same On-Demand-equivalent basis.

A practical coverage formula is:

Coverage rate = On-Demand-equivalent cost of covered eligible usage ÷ On-Demand-equivalent cost of all eligible usage

Exclude charges that cannot receive the commitment discount being measured.

Unused commitment records should not be counted as eligible consumption in the coverage denominator. Their cost still matters, but it belongs in the financial result.

AWS uses an On-Demand-equivalent approach in its Savings Plans coverage reporting.

The FinOps Open Cost and Usage Specification, or FOCUS, also provides an eligibility-adjusted commitment coverage methodology, but its example uses EffectiveCost weighting.

These are not interchangeable calculations. A benchmark needs to state which basis it uses.

Utilization asks a different question:

How much of the commitment you purchased is being consumed?

You should read coverage and utilization together.

Coverage	Utilization	Next check
High	High	Check savings after fees and whether demand remains durable
Low	High	Inspect eligible uncovered usage before adding commitments
High	Low	Identify unused commitment cost and review workload timing, scope, and eligibility
Low	Low	Review uncovered usage and unused commitments separately

This table is qualitative. There is no universal percentage that makes coverage or utilization automatically “high” or “low.”

No state alone is enough to justify another commitment purchase.

Keep utilization comparable across clouds

Commitment products do not all use the same units.

That makes cross-cloud utilization harder to compare than simply placing AWS, Azure, and Google Cloud percentages in one table.

Google Cloud’s CUD analysis guidance explains that utilization cannot be calculated across aggregated CUD types when their underlying resource units are incompatible.

For our proposed benchmark, utilization should therefore be segmented by:

cloud provider,

commitment type,

compatible resource or spend unit,

and observation period.

Financial results can then be compared separately using a clearly defined currency, scope, period, and cost baseline.

A shared currency does not make unlike utilization measurements directly comparable.

Calculate savings against one defined baseline

Coverage and utilization show what is happening inside the commitment portfolio.

They do not tell you how much money the portfolio actually saved.

For that, start with one defined baseline.

Let:

B = Baseline cost

This is the cost of the same eligible workload without the commitment discounts being measured.

The benchmark must state whether B uses public On-Demand rates or negotiated no-commitment rates. These answer different questions and should not be mixed.

Then define:

C = Full in-scope cloud cost

C should include the cost of the same usage and period, including:

uncovered eligible usage,

amortized commitment cost,

and unused portions of commitments.

Unused commitment cost should be included once. Do not deduct it again later.

Then:

Gross realized savings (G) = B − C

And:

Gross ESR = G ÷ B

Do not force a negative result to zero. If the commitment portfolio cost more than the chosen baseline during the measured period, the methodology should preserve that result.

The FinOps Foundation Effective Savings Rate playbook uses an On-Demand-equivalent baseline.

FOCUS also provides an Effective Savings Rate methodology, but its example uses Contracted Cost and Effective Cost.

The important rule is consistency. Do not combine rates calculated from different baselines and present them as though they measure the same thing.

Show what remains after fees

Gross savings is not the final number a buyer should evaluate when management fees apply.

For our proposed fee-only comparison:

Savings retained after management fees = G − F

Where:

F = management fees attributable to the same scope and period

Then:

Net ESR after management fees = (G − F) ÷ B

This calculation deducts management fees only.

If you include additional costs required to achieve the savings, identify those separately rather than hiding them inside F.

Cashback should also be tracked separately from this calculation.

For example, distinguish:

Cashback that has accrued,

Cashback that has been credited,

and Cashback that has been settled.

That prevents a recovery that has not yet been settled from being treated the same as realized savings.

The goal is simple: show what the commitment portfolio saved, what management cost, and what value remained after that fee.

Build a cohort that supports a fair comparison

A benchmark becomes useful only when the underlying organizations and measurement periods are comparable.

Our proposed methodology uses six controls.

1. Define the cohort before calculating results

State the cohort size, observation period, cloud providers, commitment programs, eligibility rules, exclusions, currency treatment, and data-rights requirements.

Do not describe a small or selected customer dataset as representative of the broader market.

2. Compare like periods without assuming causation

If you compare pre-management and post-management periods, use the same metric definitions.

Also record changes in:

workload demand,

workload mix,

provider pricing,

scope,

and commitment expirations.

A before-and-after change describes what happened to the portfolio. It does not automatically prove that our management caused the full difference.

3. Use one metric contract

Coverage, utilization, B, C, G, and F should have the same definitions across the relevant cohort.

Do not change the cost basis between organizations or periods.

4. Track purchase origin and management status separately

For each commitment, record:

when it was purchased,

who initiated the purchase,

and whether it was managed through our program during the measured period.

A commitment can exist before a measurement period and still be managed later.

Portfolio savings should therefore remain separate from any estimate of incremental management impact.

5. Publish distributions, not only averages

For each comparable cohort, report:

organization count,

25th percentile,

median,

and 75th percentile.

If a cost-weighted result is also useful, calculate and label it separately.

A median organization and a cost-weighted portfolio result answer different questions.

6. Disclose the limitations

Document:

cohort selection,

missing observations,

incomplete periods,

exclusions,

data availability,

and any selection bias.

A benchmark is more useful when readers can see where the comparison is strong and where it has limits.

What should you compare before adding another commitment?

Before increasing commitment coverage, compare these three measures using the same scope and period:

Coverage: How much eligible usage already receives commitment pricing?

Utilization: How much of the purchased commitment is consumed?

Savings after fees: How much financial value remains after the management fee?

One metric cannot answer all three questions.

The objective is not to maximize coverage or utilization in isolation. It is to understand whether the portfolio is producing retained savings while keeping commitment exposure aligned with actual demand.

How Usage.ai Evaluates Cloud Commitments

At Usage.ai, we focus on the recurring work of cloud commitment optimization and management across AWS, Azure, and GCP.

Our platform analyzes usage and billing data to identify commitment opportunities. Teams can review recommendations through CoPilot or use Autopilot to manage eligible commitment decisions as usage changes.

For covered workloads, customers typically see 30–50% savings compared with on-demand pricing. We work alongside commitments you already own and manage, including AWS Savings Plans and Reserved Instances, Azure commitments, and GCP CUDs.

Eligible commitments managed through our Flex Insured Commitment Program can also include cashback protection if committed usage falls below expectations. That helps reduce the downside of overcommitting while still capturing commitment savings. See how Usage.ai calculates savings, fees, and cashback.

Before we enable purchasing, you can use the Usage.ai Savings Test with read-only access to see where additional commitment savings may exist in your current environment.

That gives FinOps and Finance teams a clearer basis for deciding whether additional commitment coverage makes sense without relying on one headline savings percentage.

Review your commitment strategy

Before you add another commitment, compare coverage, utilization, and savings after fees using the same scope and period.

REVIEW COMMITMENT STRATEGY

Review Your Commitment Strategy With Us

Talk with our team about your existing commitments, eligible uncovered usage, and the questions to ask about savings after fees.

Compare My Environment

Frequently asked questions

Is high commitment utilization always a good result?

No. High utilization tells you that purchased commitment capacity is being consumed. It does not tell you whether substantial eligible usage remains uncovered or whether savings after fees are strong.

Can I compare AWS, Azure, and Google Cloud commitment utilization directly?

Not always. Commitment structures and resource units differ. Utilization should be segmented by compatible provider, product, and unit before financial outcomes are normalized separately.

Does this article publish a Usage.ai customer benchmark?

No. This article explains our proposed methodology for building a defensible benchmark. It does not publish customer cohort results, observed percentiles, market averages, or rankings.