Enterprise SaaS Spend Optimization
An audit-plus-optimization engagement that maps the company's SaaS stack against actual usage, identifies redundant vendors and over-provisioned licenses, models the consolidation scenarios, recommends the contract renegotiations that would maximize savings.
- Engagement
- 4–8 week audit · optional ongoing optimization
- Built for
- CFOs · CIOs · IT directors · Procurement leads
Enterprise SaaS spend has grown to 5–15% of revenue for typical mid-market and enterprise companies — and most companies don't know which licenses are actually used, which vendors are redundant, where the seat-count is over-provisioned, or what consolidation would save.
What this is
A cost-optimization engagement framed as a constrained-optimization problem. Three components:
- Usage discovery and modeling. Per-vendor and per-license usage data assembled. Where signal is direct (SSO logs, API usage), it's used; where signal is indirect (expense reports, anecdotal), it's noted with appropriate uncertainty.
- Optimization analysis. Vendor-redundancy identification, license rightsizing math, consolidation scenarios with documented assumptions and risk profiles.
- Renegotiation recommendation. The contract-renegotiation playbook against the discovered usage data — which vendors to renegotiate, what leverage exists, what target savings to anchor to.
How it's built
Data-pipeline layer to assemble usage signal (SSO integration, AP-data parsing, vendor-API pulls). Analytical layer in Python (Polars / DuckDB) with optimization math for the consolidation scenarios. Recommendation packaged as a finance-team-readable document.
What you get
- The complete SaaS-stack map with documented usage.
- The vendor-redundancy and license-rightsizing analysis.
- Consolidation scenarios with quantified savings.
- The renegotiation playbook for the procurement team.
- Optional ongoing engagement for quarterly re-audit.
Engagement is shape, not list.
Length and price are functions of the data and the destination. The shape below is the typical engagement.
- Length
- 4–8 week audit · optional ongoing optimization
- Lead
- Bogdan
- Cadence
- Async, weekly
- Bar
- Production
Scoped during the discovery call against the actual data and the operation it integrates with.
Principal engineer. Architecture and most code ships through one keyboard.
Written updates between, calls when the decision needs the room.
Async correctness, capacity under burst, observability at every boundary.
What buyers ask about this one.
How is this different from Vendr, Tropic, Spendflo, Zylo?
Those are mature SaaS spend management products — they cover the contract-management and procurement workflow well. This engagement is the analytical layer that complements them: usage modeling, vendor-redundancy identification, optimization math against the company's constraints. Companies often use both — this for the analytical recommendation, the management SaaS for ongoing procurement workflow.
How is this different from SubMagician Enterprise?
SubMagician Enterprise is the product — software the company subscribes to that runs the usage tracking and optimization ongoing. This is a productized service for companies that don't want a product subscription but want the analytical work done once (or recurring). Different commercial shape, same underlying optimization math.
What data does the audit need?
License-and-billing data from the company's vendor list, SSO logs for usage signal where available, expense reports or AP data for vendor footprint discovery. Where the company doesn't have clean inventory, the audit includes a discovery phase to assemble it.
What's the typical savings?
Per-engagement varies. Typical findings: 15–30% of licenses unused or under-used, 5–10% of vendor spend on consolidatable categories, 3–8% from renegotiation against discovered usage data. Aggregate savings typically 10–25% of total SaaS spend.
Pricing?
Fixed-fee for the audit, optional ongoing engagement. Discovery call scopes the company's SaaS spend baseline.
If the deliverable matches the gap, the next step is one call.
We'll scope length and price against your data and the operation it integrates with. No retainer, no fishing.
Bogdan and team · async-first · OP—2026