Commitment coverage and utilisation targets are the two dials that decide whether a committed use deal saves money or quietly drains it. Coverage is how much of your spend sits under commitment. Utilisation is how much of that commitment you actually consume. Push coverage too high and you risk a shortfall on spend you never use. Leave it too low and you forfeit discount you could have banked. This work is part of our FinOps optimization for cloud commitments practice and connects directly to commitment structuring and sizing advisory.
Defining commitment coverage and utilisation targets clearly
Coverage is the share of your eligible cloud spend that is covered by a commitment, whether that is an AWS EDP floor, an Azure MACC, a GCP committed use deal, or the reservations and savings plans layered underneath. Utilisation is the percentage of the committed amount you actually consume over the term. The two are linked. High coverage with low utilisation is the failure mode that creates shortfalls and stranded spend.
The goal is not to maximize either number on its own. It is to commit to the portion of demand that is stable and predictable, while keeping the volatile portion flexible so you are never paying for capacity you cannot use.
Cover the floor, flex the rest
Most enterprise cloud spend has a stable base and a variable top. The stable base, the workloads that run every day and are not going anywhere, is what belongs under commitment. The variable top, the spend tied to growth bets, seasonal load, and projects that may not survive, should stay uncommitted.
As of June 2026, unused commitment does not roll over or refund on the major programs, and overcommitment on an AWS EDP creates a shortfall the buyer must pay. So coverage should track confident demand, not hoped for demand. A common buyer side posture is to commit the steady state and review coverage as confidence grows.
Model utilisation before you sign, not after
Run the coverage scenario against a realistic demand range, including a downside case where a workload moves, a project is cancelled, or growth stalls. If the commitment still clears its utilisation target in the downside case, the coverage is safe. If it only works in the optimistic case, the commitment is too large.
This is where vendor ramp assumptions get tested. A proposal that assumes aggressive growth pushes coverage past what your real demand supports. Modeling utilisation against the downside is how you catch that before it is contractual.
Track coverage and utilisation as living numbers
Coverage and utilisation are not set once at signature. They move as workloads change. Track them monthly so you see drift early, while there is still time to act inside the term or prepare for renewal. Pair the tracking with clear KPIs and a regular review. We cover the measurement side in our work on FinOps KPIs and on forecasting, because targets you do not monitor are targets you will miss.
The cost of overcoverage versus undercoverage
Overcoverage and undercoverage fail in different directions. Overcoverage means committing to spend you do not use, which as of June 2026 is generally lost on the major programs and creates a shortfall on an AWS EDP. Undercoverage means leaving discount on the table by paying full rate on stable demand you could have committed.
The asymmetry matters. Overcoverage is a hard loss you cannot recover, while undercoverage is an opportunity cost you can fix at the next window. That asymmetry is why prudent coverage targets lean toward the conservative side of confident demand.
Set coverage by workload class, not in aggregate
A single estate wide coverage number hides the detail that decides risk. Break demand into classes. Always on production that will run the full term is high confidence and supports high coverage. Seasonal or batch workloads are medium confidence. Project and experimental spend is low confidence and usually belongs outside the commitment.
Set a coverage target per class, then sum them into the commitment. This bottom up approach produces a number you can defend line by line, which is exactly what a negotiation demands.
How providers treat unused commitment
Coverage decisions only make sense against the rules. As of June 2026, Azure MACC unused commitment is generally lost rather than refunded or rolled over. An AWS EDP creates a shortfall the buyer must pay if the committed spend is not met. GCP committed use discounts apply to the committed resources or spend whether or not you use them.
In every case, unused commitment is money gone. That is the entire reason utilisation targets exist, and why coverage should track demand you are confident will materialize.
Build a coverage policy you can govern
Turn the targets into a written policy so coverage decisions are consistent across teams and over time. Define the confidence thresholds for committing a workload, the maximum estate coverage, the review cadence, and who signs off on new commitments.
A policy converts coverage from a one time negotiation input into an ongoing discipline. Without it, coverage drifts as teams add commitments independently, which is how double spend and stranded coverage creep back in.