Editorial photograph of a European retailer head office boardroom with FinOps and procurement leads reviewing a GCP commit savings dashboard
Case Study · GCP · European Retailer

GCP commitment case study, a European retailer cut 38 percent.

A European retailer with $42 million annual GCP spend faced an overcommit problem. The original three year CUD commit was sized to forecast that did not materialize. A buyer side renegotiation cut commitment exposure by 38 percent.

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A European retailer engaged Redress to renegotiate a GCP commitment portfolio that had been sized to a forecast that did not materialize. The result was a 38 percent reduction in commitment exposure.

Key takeaways

  • Client: European retailer. $42M annual GCP spend.
  • Problem: Overcommitted 3 year CUD. Sized to forecast that did not arrive.
  • Plan: Renegotiate commit shape. Step down, family migration, and term restructure.
  • Result: 38 percent commit cut. $16M total savings across the remaining 24 months.
  • Engagement length: 9 months. From scoping to signature.
  • Clauses hardened: 12. Step down, exit, change of control, no worse than.
  • Reusable framework. The same approach applies to AWS and Azure overcommit scenarios.

Read this case study alongside the GCP CUD pillar, the CUD vs Savings Plan comparison, and the Google Cloud practice page.

The client name remains confidential. The numbers and the moves are real. The framework reuses across the GCP overcommit scenarios we see across the buyer side practice.

Client profile

A multi country European retailer with 800 stores and a growing online business. Headquartered in Western Europe. GCP adoption began in 2021. The original commit landed at the back of the migration phase.

Estate shape

The estate ran across three Google Cloud regions. Compute, BigQuery, and BigTable were the largest line items. The CUD commit covered all three categories.

  • Three GCP regions. Western Europe, Northern Europe, US East as DR.
  • Compute, BigQuery, BigTable. Top three line items.
  • $42M annual run rate. Steady state at engagement start.

Buyer side team

A CIO, a head of FinOps, a head of procurement, and a senior architect. Redress engaged as the buyer side advisor and the lead negotiator at the contract table.

  • CIO. Sponsor and decision owner.
  • FinOps lead. Demand forecast owner.
  • Procurement. Contract owner.
  • Senior architect. Workload and family migration plans.

The problem

The original 3 year compute CUD was sized in 2023 to a forecast that assumed 35 percent year over year growth. Actual growth landed at 8 to 12 percent. The commit ran 30 to 40 percent ahead of demand.

Shape of the overcommit

The compute commit was the largest mismatch. BigQuery slots ran close to demand. BigTable spend commit was undercommitted, not overcommitted.

  • Compute CUD: 38 percent overcommitted. Family mix also wrong.
  • BigQuery slots: 4 percent overcommitted. Inside normal range.
  • BigTable spend: 12 percent undercommitted. Paying on demand premium.

Financial impact

Annualized waste sat at $7.4M on compute alone. Across the remaining 24 months of the 3 year term the total exposure was $14.8M. Add the BigTable on demand premium and the total exceeded $16M.

  • Compute waste: $7.4M annual. Run rate at engagement start.
  • BigTable premium: $0.8M annual. On demand vs spend commit gap.
  • Total 24 month exposure: above $16M. Reversible only through renegotiation.

European retailer GCP commit renegotiation outcome

Bucket Action 24 month value Clauses added
Compute CUD28 percent step down$7.4M3
Compute familyN2 to N2D migration$4.8M2
BigQueryFlex slot reservation$1.1M1
BigTableSpend commit added$0.9M2
New 3 year paperCustom rate 8 points deeper$3.8M4
Total programCombined$16M plus12

Starting baseline

The baseline reconciliation took 6 weeks. The FinOps team and Redress mapped commit by SKU by region against actual consumption. The mismatch became precise.

Reconciliation method

The reconciliation pulled commit data from the Google billing API and consumption data from the FinOps tooling. The cross check identified every overcommit SKU.

  • Billing API pull. Commit by SKU by region.
  • FinOps tooling pull. Actual consumption by SKU by region.
  • Cross check. Mismatch identified at SKU level.

Revised forecast

A new 24 month forecast replaced the 2023 forecast. The new forecast assumed 10 percent compound growth, family migration to N2D, and partial migration of BigQuery to flex slot reservation.

  • 10 percent compound growth. Vs 35 percent original.
  • Family migration to N2D. 30 percent of compute estate.
  • BigQuery flex slot migration. Reduced commit need.

The plan

The plan combined three moves. Negotiate a step down on the existing CUD. Migrate part of the compute estate to a new commit family. Restructure the term length on the residual commit.

Step down move

The first move was a step down on the existing CUD. The target was a 28 percent reduction in committed vCPU and memory across the remaining 24 months.

  • Target step down: 28 percent. Across vCPU and memory.
  • Phased over 6 months. Smooth reduction not cliff.
  • Region by region. Western Europe first, others in second phase.

Family migration

The second move migrated 30 percent of the compute estate from N2 to N2D. The migration was already on the architecture roadmap. The CUD renegotiation accelerated it.

  • N2 to N2D migration. Lower per vCPU rate.
  • 30 percent of estate moved. Stateless workloads first.
  • New family commit. 1 year term to maintain flexibility.

Term restructure

The third move converted the residual 24 month exposure into a fresh 3 year commit with a 20 percent step down at month 24. The fresh term unlocked a deeper custom rate.

  • Fresh 3 year term. New paper, new custom rate.
  • 20 percent step down at year 2. Built into the contract.
  • Custom rate 8 points deeper. Than the public 3 year CUD.
“An overcommitted CUD is a contract problem not a usage problem. The fix sits at the contract table. Not at the deployment console.”

The buyer side moves

The contract table took five sessions over three months. The buyer side moves followed a defined sequence. Each move set up the next move.

Leverage moves

The leverage moves included a parallel AWS quote, a documented workload migration option, and a clear walk away position with a phased on demand fallback.

  • Parallel AWS quote. Compute Savings Plan equivalent.
  • Documented migration plan. 24 month workload migration option.
  • Walk away position. Phased return to on demand with cost model.

Clause moves

The clause moves added 12 buyer side clauses to the new paper. Step down, exit, change of control, audit rights, custom rate freeze, and no worse than language all landed.

  • Step down right. 20 percent at year 2.
  • Exit clause. Change of control assignment language.
  • Custom rate freeze. Locked for the full term.
  • No worse than. Protection against tier degradation.

Outcome

The renegotiation closed in month 9 of the engagement. The combined moves delivered a 38 percent reduction in commitment exposure and $16M in total savings across the remaining 24 months of the original contract plus the new 3 year term.

Numbers

The numbers split across three buckets. Existing CUD step down savings. Family migration savings. Custom rate savings on the new paper.

  • Step down savings. $7.4M across 24 months.
  • Family migration savings. $4.8M across 36 months.
  • Custom rate savings. $3.8M across 36 months.

Time invested

The engagement ran 9 months. The buyer side team invested approximately 600 hours across CIO, FinOps, procurement, and architect roles. Redress engaged at full advisor depth across the engagement.

  • 9 month engagement. Scoping to signature.
  • 600 client hours invested. Across four roles.
  • Redress advisor hours: 480. Senior partner led.

Lessons

Three lessons apply to most GCP overcommit scenarios. Forecast conservatively at original commit time. Negotiate step down into the original paper. Monitor commit vs consumption monthly.

Forecast conservatively

The original commit assumed 35 percent growth. Use the previous 24 month actual growth rate as the floor. Never commit above the floor.

  • 24 month actual growth as floor. Conservative anchor.
  • Commit at 70 to 80 percent of forecast. Use uncommitted SUD on the rest.
  • Update forecast quarterly. Adjust commit at year boundaries.

Suggested reading

What to do next

  1. Pull commit vs consumption by SKU by region monthly.
  2. Quantify overcommit exposure across the remaining contract months.
  3. Build the revised forecast at conservative growth assumptions.
  4. Model the step down, family migration, and term restructure options.
  5. Build a parallel AWS or Azure quote for leverage.
  6. Engage a buyer side advisor before opening the renegotiation.
  7. Track every clause added through to executed paper.
  8. Contact Redress Compliance to scope a GCP commit review.

Frequently asked questions

What was the headline outcome?

The European retailer cut commitment exposure by 38 percent and captured $16M in total savings across the remaining 24 months of the original contract plus the new 3 year term. The engagement ran 9 months from scoping to signature.

Why did the original commit overcommit?

The original 3 year CUD was sized in 2023 to a forecast that assumed 35 percent year over year growth. Actual growth landed at 8 to 12 percent. The commit ran 30 to 40 percent ahead of demand.

What were the three main buyer side moves?

The first move was a step down on the existing CUD targeting 28 percent reduction. The second move migrated 30 percent of the compute estate from N2 to N2D. The third move restructured the residual into a fresh 3 year commit with deeper custom rates and step down rights.

How did the buyer create leverage?

Three sources of leverage. A parallel AWS Compute Savings Plan quote. A documented 24 month workload migration plan. A walk away position with a phased return to on demand pricing modeled and ready.

What clauses landed in the new contract?

Twelve buyer side clauses. The biggest hits were step down rights at year 2, change of control assignment language, custom rate freeze for the term, and no worse than protection against tier degradation.

Does this approach work on AWS and Azure?

Yes. The same framework applies. The mechanics differ. AWS Savings Plans cannot be modified once purchased so the buyer side play shifts to the next renewal cycle. Azure MACC overcommit responds to similar renegotiation moves.

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38%
Commitment Cut
$16M
Total Savings
9 months
Engagement Length
Industry
Recognized
100%
Buyer Side

“The original commit was sized to a forecast that did not arrive. The buyer side play was to renegotiate the commit shape, not to absorb the overcommit through wasted spend.”

Fredrik Filipsson
Co Founder and Group CEO · Redress Compliance
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