SaaS Stack Audit: A Practical Guide to Pruning Underused Platforms

Hook: Your SaaS bills are rising while productivity stalls — time to prune

If your team juggles 40+ SaaS subscriptions, duplicate features across tools, and invoices that increase every quarter, you’re not alone. In 2026 most engineering and IT teams face the exact problem they were promised SaaS would solve: fragmentation, unpredictable spend, and onboarding drag. This guide gives you a pragmatic, step-by-step SaaS audit playbook complete with metrics, scripts, a triage rubric, and cost & risk scoring so you can identify underused platforms and safely sunset them.

The bottom line up front

Run a structured audit in four phases: Inventory → Measure → Triage → Execute. Use measurable thresholds and an objective rubric to classify each tool into Keep, Optimize, Consolidate, or Sunset. Target an initial 10–25% immediate savings on SaaS license spend from license optimization and removing duplicative tools; longer-term savings of 20–40% are realistic when you consolidate and automate governance.

Why now? 2025–2026 trends changing the rules

• Consumption-based pricing accelerated in late 2025, making variable spend harder to forecast but easier to tie to usage.
• Identity platforms like Okta and Azure AD increasingly expose richer usage events and app assignment data — use that for precise activity-based audits.
• AI features and feature-tiers pushed many vendors to add paid AI tiers in 2025; that split often creates hidden upgrade costs for passive users.
• FinOps for SaaS gained traction in 2025: cross-functional teams now standardize SaaS tagging, chargeback, and budgeting.
• Regulation & data residency concerns in 2026 mean some low-use tools present outsized compliance risk and should be candidates for sunset.

Phase 1 — Inventory: Build a canonical, queryable list

Your audit fails if you can’t trust your inventory. Stop spreadsheets that go stale. Consolidate discovery from procurement, IT, finance, engineering, and SSO. Collect:

• Vendor, product name, and SKU/tier
• Contract dates, renewal windows, and billing cadence
• Monthly/yearly cost and payment owner
• SSO/SCIM provisioning status and owner
• Primary users, product owners, and integrations
• Data classification and compliance notes

Make the inventory a lightweight database (Postgres/Sheets + API) so you can join it with usage and billing data later.

Sample inventory schema (Postgres)

CREATE TABLE saas_inventory (
  id SERIAL PRIMARY KEY,
  vendor TEXT,
  product TEXT,
  sku TEXT,
  owner TEXT,
  cost_monthly NUMERIC,
  contract_end DATE,
  sso_enabled BOOLEAN,
  scim_enabled BOOLEAN,
  data_classification TEXT,
  notes TEXT
);

Phase 2 — Measure: Usage, cost, and dependency signals

For each product collect three signal groups:

1. Usage signals — active users, last login, API calls, seats assigned vs seats used.
2. Cost signals — monthly recurring cost, invoices, consumption spikes, effective per-active-user cost.
3. Dependency signals — integrations, scheduled jobs, webhooks, data exports that other systems depend on.

Essential metric formulas

• Active User Rate = active_users_last_30d / total_assigned_seats
• Effective Cost per Active User = monthly_cost / active_users_last_30d
• Usage Trend = (active_users_last_30d - active_users_prev_30d) / active_users_prev_30d

Quick scripts — examples you can run

Query your database (example: identify accounts with no logins in 90 days)

-- Active users in last 90 days
SELECT product, COUNT(*) AS active_90d
FROM users
WHERE last_login >= now() - INTERVAL '90 days'
GROUP BY product;

Pull invoices from Stripe (for self-billed SaaS)

curl https://api.stripe.com/v1/invoices \
  -u sk_live_xxx: \
  -G --data-urlencode "limit=100" \
  | jq '.data[] | {id: .id, amount_due: .amount_due, period_start: .period_start, customer: .customer}'

List app assignments from Okta (to see how many users are assigned)

curl -s -H "Authorization: SSWS $OKTA_TOKEN" \
  "https://yourorg.okta.com/api/v1/apps/{appId}/users" | jq '. | length'

Phase 3 — Triage: The rubric that removes opinion

Make decisions using a scored rubric. Score each tool 0–10 on five dimensions:

• Usage (U) — active usage signal (0 if dormant, 10 if essential daily use)
• Cost Impact (C) — monthly spend (0 for negligible, 10 for extremely costly)
• Overlap (O) — feature duplication across stack (0 = unique, 10 = full duplicate)
• Integration Complexity (I) — tech debt and dependencies (0 = no downstream, 10 = critical dependency)
• Risk & Compliance (R) — data/regulatory risk (0 low, 10 high)

Weighted score and thresholds

Use weights reflecting priorities (example weights: U=0.30, C=0.25, O=0.20, I=0.15, R=0.10). Compute:

Score = U*0.30 + C*0.25 + O*0.20 + I*0.15 + R*0.10

Interpretation:

• Score < 3.0: Strong candidate for immediate sunset
• 3.0–5.5: Optimize (license reduction, restrict to specific teams)
• 5.5–7.5: Keep with governance and tagging; re-evaluate at renewal
• >7.5: Critical — do not remove without a migration plan

Example: How scoring saved $18k/year

Product A: monthly cost $1,200, 90-day active users = 3 of 30 seats, duplicates feature with Product B. Scores: U=1.0, C=7.0, O=9.0, I=2.0, R=1.0. Weighted Score = 1*0.3 + 7*0.25 + 9*0.2 + 2*0.15 + 1*0.1 = 3.75 → Optimize or sunset. After deprovisioning, savings = $14,400/yr net, and license consolidation reduced Product B upgrades by $3,600/yr — net $18k/yr.

Phase 4 — Execute: Safe sunset playbook

Sunsetting must balance cost savings and operational risk. Follow a repeatable rollout:

1. Stakeholder notification — product and team owners + finance + security.
2. Data export — export all data and run integrity checks; record retention policy applied.
3. Feature migration — map key workflows and provide temporary alternatives or automation scripts.
4. Deprovisioning plan — disable new signups, revoke API keys, remove integrations, and then decomm SSO/SCIM assignments.
5. Billing termination — file cancellation requests well before renewal window; centralize billing communication to prevent auto-renew.
6. Post-sunset verification — monitor error rates, support tickets, and business feedback for 30 days.

Automate the safe path: a checklist

• Export data & take a snapshot (S3 or on-prem archive)
• Turn off user provisioning (SCIM/SSO) but keep read-only access for 14 days
• Run integration smoke tests after disabling webhooks
• Send cancellation confirmation and follow up until invoice stops
• Delete secrets and rotate keys after confirmation

Sample automation: revoke SCIM app assignment (pseudo-API)

curl -X DELETE "https://idp.example.com/scim/v2/Users/{userId}/appAssignments/{appId}" \
  -H "Authorization: Bearer $TOKEN"

(You can combine the above with your identity provider automation; see operational playbooks for identity signals.)

License optimization: squeeze low-hanging fruit

License optimization often gives your fastest ROI. Concrete tactics:

• Seat audit: reclaim assigned but inactive seats (automate after 30–90 days inactivity)
• Feature-tier downgrade: move passive users off paid AI/Pro tiers to free tiers
• Shared accounts: rarely recommended for security; prefer role-based limited seats
• Annual vs monthly: negotiate annual when usage is predictable, but avoid long contracts for low-use tools

Per-active-user cost calculator (1-line)

effective_cost = monthly_cost / max(active_users_last_30d, 1)

If effective_cost > target benchmark (set by your finance team, e.g., $50/user/month for productivity tools), flag for optimization.

Risk scoring: don’t cut the wrong cord

Some low-usage tools carry high business risk — e.g., a monitoring webhook used only by SREs, or a compliance reporting tool. Use a separate Risk Multiplier when deciding final actions:

AdjustedScore = Score + (RiskMultiplier * R)

Set RiskMultiplier to 0.5–1.5 based on tolerance. If AdjustedScore > 7.5, require detailed migration plan before any action.

Governance & automation to prevent re-clutter

• Catalog & Policy: Require a short catalog entry and cost justification before procurement.
• SSO-first policy: Block purchases for SaaS that can’t be onboarded to SSO/SCIM quickly.
• Automated tagging: Tag all SaaS costs in billing systems to map to teams and projects.
• Renewal guardrails: Finance or procurement must approve renewals over a threshold.
• Quarterly mini-audits: Re-run the rubric every 90 days focusing on new purchases and AI-tier upgrades; tie the cadence to your central consolidation playbook.

"You can’t save what you don’t measure. Make the inventory queryable, the metrics reproducible, and the decision process objective."

Templates & reusable artifacts

Copy these into your repo or internal docs:

• Cancellation email template that includes contract ID, renewal date, and data export instructions.
• Data export checklist: formats, retention location, access permissions, redaction needs.
• Integration map: input/output channels, downstream consumers, batch jobs.

Common gotchas and how to avoid them

• Hidden admin accounts: Some tools bill by workspace not seat; ensure workspace-level checks.
• Orphaned integrations: Cron jobs or CI pipelines may rely on token-based integrations—scan code repos for vendor-specific SDK usage.
• Data lock-in risk: Exportability matters. If export is expensive or incomplete, factor migration cost into your decision.
• Stakeholder backlash: Run small pilots, provide alternatives, and keep a rollback window.

Real-world case study (concise)

Late 2025: a 50-engineer startup ran this exact playbook. Inventory revealed 18 marketing and analytics tools. Using the rubric they identified 6 immediate sunsets and 4 license downgrades. First-year savings: 28% of SaaS spend. Time-to-onboard for new hires dropped from 3 days to 1.5 days because the stack was simplified. The CFO and CTO used the savings to fund an internal developer productivity initiative.

How to measure success — KPIs to track

• Monthly SaaS spend vs baseline
• Number of active SaaS products (goal: reduce)
• Effective cost per active user by category
• Onboarding time for new hires
• Number of incidents caused by third-party dependency changes

Advanced strategies for 2026 and beyond

• API-driven procurement: Use internal platforms to create guardrails and automatic approvals based on rubric outcomes.
• AI-assisted usage classification: Use LLMs to parse support tickets and commit history to surface hidden dependencies.
• Broker consolidation: Consider SaaS brokers or enterprise marketplaces to centralize billing and get better negotiation leverage.
• Liability-aware pruning: As data protection rules tighten, add regulatory risk scoring into your triage model.

Quick start checklist (first 30 days)

1. Create canonical inventory
2. Pull usage for 30/90 days from SSO & vendor APIs
3. Score top 30 vendors with the rubric
4. Identify 3 immediate sunsets and 5 license reductions
5. Run a 30-day sunset pilot following the safe playbook

Final recommendations

Objectivity and automation win. Replace subjective “gut” decisions with a transparent scoring model and automated telemetry. Prioritize seat reclamation and downgrading AI/Pro tiers first — those are the fastest wins in 2026’s pricing landscape. Pair financial ownership with product owners for accountability and ensure every new vendor has a clear owner, tag, and expected ROI.

Call to action

Ready to prune your stack? Export your inventory and run the rubric on your top 30 SaaS vendors this week. If you want, download our ready-to-run Postgres schema, SQL scripts, and a cancellation email template to get started — or contact our team at simplistic.cloud for a pilot that targets 20–40% SaaS spend reduction with zero disruption.

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