Procurement Optimizer

Procurement Optimizer

Most software spend reduction is not a negotiation problem. It is a measurement problem: organisations buy seats in round numbers, assign them generously, and never look at whether anyone logs in. The typical mid-size portfolio carries 20-30% reclaimable seat spend before anyone talks to a vendor, and the reclaim requires no concession from the vendor at all.

This skill works the levers in order of yield: stop paying for unused seats, then stop paying twice for the same capability, then negotiate price. Reversing that order — leading with a price negotiation on a bloated contract — is how organisations congratulate themselves on a 10% discount against 40% more seats than they need.

When to use this skill

• A budget-reduction target has landed and software spend is in scope
• A renewal is approaching and you need a defensible position before the vendor call
• SaaS sprawl audit: nobody can say how many tools the company pays for
• Post-merger consolidation where two portfolios overlap heavily
• Building a renewal calendar so contracts stop auto-renewing unexamined
• A vendor has proposed an uplift and you need leverage to counter it

Inputs the skill expects

• Spend inventory: tool, category, annual cost, renewal date, contract term
• Seat data: purchased, assigned, and — critically — active in the last 30 days
• Contract terms: notice period, auto-renew flag, term length
• Criticality per tool, and whether a capability alternative exists
• Headcount, for per-head benchmarking
• The as-of date, so renewal-window maths is reproducible

Clarify First

Before generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• Whether seat data is assigned or active — this is the single most consequential input. Assigned seats overstate usage by 30-60%, and an analysis built on them finds almost nothing
• Notice periods and auto-renew flags — a contract inside its notice window is committed for another full term, so its "savings" are not available this cycle and must not be counted toward a target
• Whether the goal is in-year cash or run-rate reduction — seat cuts at renewal reduce run-rate but may deliver nothing this fiscal year, which is the wrong answer to an in-year cash problem
• Which tools are politically untouchable — if the CRM is the CRO's and cannot be cut, that changes which opportunities are worth analysing at all

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Workflows

Workflow 1 — Find the wasted seats

Start here always. It requires no vendor conversation and no cross-team negotiation.

1. Assemble the inventory with purchased / assigned / active-30-day seat counts. If you only have assigned counts, stop and get active counts — the analysis is not meaningful without them.
2. Run the analyser. It compares active utilisation against a per-category benchmark (an LMS is not used weekly; a CRM is) and sizes reclaimable spend with a 12% safety buffer.
3. Separate the two failure modes it reports. Over-licensed means cut seats. Adoption failure means seats are assigned to people who never log in — cutting seats there treats the symptom, and the tool may simply not deserve to survive.

python3 business-operations/procurement-optimizer/scripts/license_utilization_analyzer.py \
  --input business-operations/procurement-optimizer/assets/sample_spend.json --format text

Workflow 2 — Find the tools you are paying for twice

1. Run the overlap detector. It groups by category and picks a survivor by displacement cost, not by price — moving 400 active users is expensive regardless of licence cost.
2. Check the umbrella-label warnings first. If it flags a category as an umbrella, your tagging is claiming that a wiki and a chat tool are substitutes. Re-tag by the job the tool does and re-run before believing any number in the output.
3. Treat the recovery figure as net of an assumed 20% migration cost. Consolidations that look marginal at 20% are usually negative in reality once you count the disruption.

python3 business-operations/procurement-optimizer/scripts/tool_overlap_detector.py \
  --input business-operations/procurement-optimizer/assets/sample_spend.json --format text

Workflow 3 — Rank the opportunities against the renewal calendar

1. Run the ranker with an explicit --as-of. It discounts each opportunity by how much leverage the renewal timing actually gives you this cycle.
2. Work the shortlist top-down. Time-boxed items (inside the notice window or in the ideal T-120 to T-90 negotiation window) are promoted above higher-ROI items on distant renewals, because missing a window costs a full contract year.
3. Read the locked_this_cycle figure to leadership before committing to a savings number. It is the portion of the opportunity that is genuinely unavailable this year, and discovering it after committing to a target is a bad conversation.

python3 business-operations/procurement-optimizer/scripts/savings_opportunity_ranker.py \
  --input business-operations/procurement-optimizer/assets/sample_spend.json \
  --as-of 2026-07-21 --top 10 --format text

Decision frameworks

Utilisation benchmarks by category [RECOMMENDED]

Active seats in the last 30 days, divided by seats purchased. A single flat benchmark is the most common analytical error here — it flags an LMS as catastrophically wasteful when quarterly use is its normal pattern.

Renewal timing and leverage [PROVEN]

The most valuable single practice in software procurement is serving notice by default on every auto-renewing contract at the notice deadline. It converts an automatic renewal into a negotiation and costs nothing — vendors do not walk away from customers who serve notice, they schedule a call. Organisations that do not do this are negotiating with no alternative and the vendor knows it.