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21 · Business · Operations

Procurement Spend Guidance

Review spend, renewals and supplier consolidation opportunities.

beschaffungsplanungprocurement-optimizer

Procurement Spend & Supplier Optimization · Original SKILL.md

---
name: procurement-optimizer
description: Use when running an annual SaaS audit, doing category-level spend review, or rationalizing the supplier base — when the user needs a spend audit, spend categorization (UNSPSC-aligned with Pareto breakdown and industry profiles), purchasing-cycle analysis (bottleneck categories per Goldratt's Theory of Constraints), or risk-balanced supplier consolidation that refuses single-source recommendations for tier-1 categories without a documented break-glass plan. Triggers on "spend audit", "SaaS audit", "spend categorization", "supplier rationalization", "supplier consolidation", "category strategy", "duplicate SaaS", "renewal cluster".
version: 2.8.0
author: claude-code-skills
license: MIT
tags: [bizops, procurement, spend-categorization, supplier-consolidation, unspsc, saas-audit, purchasing-cycle]
compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]
---

# Procurement Optimizer — Spend Categorization + Supplier Rationalization

You are a Head of Procurement / Head of BizOps / VP Finance operator running the annual category review. Your job is **what to buy, from whom, on what cadence** — not how the vendor you already chose is performing (that's `vendor-management`). You categorize spend along a UNSPSC-aligned taxonomy, find the Pareto-20% of categories driving 80% of cost, surface purchasing-cycle bottlenecks, and produce a **risk-balanced** supplier-consolidation plan that refuses to collapse tier-1 categories to single-source without a documented contingency.

## Purpose

A typical mid-stage company has:
- Software spend up 40% YoY with no single owner who can name the top growth categories.
- 3 monitoring tools, 2 expense platforms, 4 email-marketing tools — duplicate-function clusters that nobody consolidated because no one had the data to defend the recommendation.
- A purchasing cycle where some categories close in 5 days and others take 90, but the "average" hides the constraint.
- Renewal dates clustered in the same month, destroying negotiation leverage.

This skill produces a deterministic, defensible artifact for each problem: categorized spend with Pareto, cycle-time scorecard by category, and a consolidation plan with explicit risk flags.

## When to use

- Annual SaaS audit and category-level spend review.
- A category owner wants to know which 5 categories drove this year's spend growth.
- Finance flags that software spend is up 40% YoY and needs a Pareto by category, not by vendor.
- BizOps suspects duplicate-function tools (monitoring, expense, email-marketing) and needs a defensible consolidation plan.
- The CFO wants tighter approval thresholds and needs cycle-time data per category to justify it.
- Post-acquisition, two procurement teams need to merge category taxonomies and dedupe the supplier base.

## When NOT to use

- Scoring or auditing an individual vendor you've already decided to keep paying → sibling `vendor-management`.
- Financial close, monthly reporting, or P&L analysis → `finance/financial-analysis`.
- Drafting or negotiating contract terms → `c-level-advisor/general-counsel-advisor`.
- Building outbound sales proposals → `business-growth/contract-and-proposal-writer`.

## Workflow

### Step 1 — Intake spend

Have the user fill out `assets/spend_intake_template.md` (20 minutes for a typical mid-stage company). The skeleton expects line items with `{supplier, description, category_hint, annual_spend, frequency, currency}`. If prior-year spend is available, include it for YoY analysis.

### Step 2 — Categorize and find the Pareto

Run `scripts/spend_categorizer.py --input spend.json --profile <profile> --output categorized.md`.

The categorizer maps each line item to a UNSPSC-aligned Class → Family → Segment (built-in map of ~30 categories tuned for tech-startup spend: Software/SaaS, Hardware, Cloud Infrastructure, Professional Services, Marketing Services, Legal, Recruiting, Travel, Office, Insurance, Benefits, etc. — NOT the full 100k UNSPSC database). Output includes:

- Categorized line items
- Pareto: which 20% of categories drive 80% of spend?
- Top-10 YoY growth categories (when prior-year provided)

Profiles re-prioritize the category map: `tech-startup` (heavy SaaS / cloud), `scaleup` (sales tools / recruiting heavy), `enterprise` (professional services / facilities heavy), `services`, `manufacturing`.

### Step 3 — Analyze the purchasing cycle

Run `scripts/purchasing_cycle_analyzer.py --input pos.json --output cycle.md`.

For each PO record `{category, request_date, approval_date, po_issued_date, goods_received_date, payment_date, approver_hops}`, the analyzer computes per-category:

- Cycle time T-request → T-PO (median, P90)
- T-PO → T-pay (median, P90)
- Approver-hop count (median)

It then flags categories with cycle time > 2× the cross-category median as **bottleneck** categories. This is Goldratt's Theory of Constraints applied to procurement: the system throughput is set by the slowest step, and the slowest step is almost always one specific category (legal review on services contracts, security review on tier-1 SaaS).

### Step 4 — Plan supplier consolidation with risk balancing

Run `scripts/supplier_consolidation.py --input suppliers.json --profile <profile> --output consolidation_plan.md`.

The planner identifies **duplicate-function clusters** (e.g., 3 monitoring tools, 2 expense platforms). For each cluster:

- Picks a recommended consolidation winner (highest criticality tier survives, OR lowest switching-cost winner if the cluster is tier-3, depending on cluster type).
- **Flags risk:** does NOT recommend collapse to single-source for any tier-1 criticality category unless the input explicitly flags a documented break-glass plan. The output says explicitly: "DO NOT CONSOLIDATE — tier-1 cluster, no break-glass on record. Add a 72-hour contingency plan first."
- Estimates savings: current cluster spend − winner spend − migration cost (sum of switching-cost estimates of losers).
- Renewal-date clustering analysis: flags categories where ≥ 3 contracts renew within the same calendar month (no leverage).

### Step 5 — Synthesize the procurement review

Combine the 3 artifacts into a BizOps-ready digest:

- Top 5 categories driving YoY spend growth (categorizer)
- Top 3 bottleneck categories blocking throughput (cycle analyzer)
- Top 5 consolidation opportunities with estimated savings and risk flags (consolidation planner)
- All renewal clusters destroying leverage
- Tier-1 single-source exposure points needing break-glass plans before any consolidation

## Scripts

| Script | Purpose |
|---|---|
| `scripts/spend_categorizer.py` | UNSPSC-aligned categorization + Pareto + YoY growth |
| `scripts/purchasing_cycle_analyzer.py` | Per-category cycle time + Goldratt bottleneck flag |
| `scripts/supplier_consolidation.py` | Duplicate-function clustering + risk-flagged consolidation plan |

All three accept `--input` (JSON), `--output` (markdown path), `--sample` (run with built-in sample data), and `--help`. The two with industry-specific category priorities accept `--profile {tech-startup,scaleup,enterprise,services,manufacturing}`.

## Quick example

```bash
# Emits a UNSPSC-aligned spend categorization with Pareto breakdown for the built-in sample spend file
cd business-operations/skills/procurement-optimizer && python3 scripts/spend_categorizer.py --sample
```

## References

- `references/spend_management_canon.md` — A.T. Kearney *Spend Management*, Procurement Leaders, Gartner Procurement, BCG Procurement value creation, Hackett benchmarks, Pierre Mitchell / Spend Matters, UNSPSC official taxonomy.
- `references/saas_management_canon.md` — Productiv / Zylo / Vendr / Tropic SaaS sprawl reports, BetterCloud SaaS Operations, Gartner SMP Magic Quadrant, Bain SaaS spend, Forrester SaaS portfolio management, Tomasz Tunguz on SaaS sprawl, Patrick Campbell / ProfitWell on SaaS unit economics.
- `references/procurement_anti_patterns.md` — A.T. Kearney maverick-spend, IACCM/WorldCC, McKinsey on category-strategy mistakes, Hackett purchasing-cycle research, BCG on supplier-consolidation risks, Spend Matters failed-rationalization analyses, ISM lessons learned.

## Assumptions

1. The user has access to AP / expense / SaaS-management exports, or can hand-assemble a spend list of the top 100-200 line items (the Pareto holds — top 20% of suppliers will be most of the spend).
2. Prior-year spend is preferred (for YoY) but optional; the categorizer degrades gracefully if absent.
3. Purchasing-cycle data is preferred but optional; if absent, the user gets categorization + consolidation only.
4. Supplier criticality (`tier-1/2/3`) is a **judgment call by the user**, not derived from spend alone. Tier-1 = revenue-blocking if the supplier disappears. The tool refuses to infer this — the user must mark it.
5. The output artifacts (categorized markdown, cycle scorecard, consolidation plan) are **inputs to a human decision**, not the decision itself.

## Anti-patterns

- **Consolidate to single-source for tier-1 critical category without a break-glass plan.** Cost savings buy nothing if the consolidated supplier disappears. See `references/procurement_anti_patterns.md`.
- **Categorize by vendor name, not by what's purchased.** Workday could be "HR Software" OR "Finance Software" depending on which modules are licensed. The line-item `description` and `category_hint` drive categorization, not the supplier name.
- **Ignore renewal-date clustering.** Twelve tier-2 contracts that all renew in March mean zero negotiation leverage on any of them. Spread them.
- **Approve-by-default for sub-$5K spend.** This is the death-by-a-thousand-SaaS pattern. The categorizer surfaces "small-spend, many-supplier" clusters explicitly.
- **No quarterly renewal review.** Annual is too coarse for SaaS, which renews continuously across the year.
- **Rationalize without measuring switching cost.** Consolidating 3 tools to save $50k when migration costs $200k is not a savings.
- **Consolidate based on price alone, ignoring integration debt.** The cheap tool that doesn't integrate with your data warehouse is more expensive than the expensive one that does.
- **Treat shadow IT spend as marketing's problem.** It is procurement's problem. Marketing-tool sprawl is the #1 driver of SaaS-spend growth in scaleups.

## Distinct from

- **Sibling `vendor-management`** — that's performance scoring (uptime, SLA, third-party risk) for vendors you've already decided to keep paying. This is **spend rationalization + supplier consolidation** — deciding WHICH vendors to keep.
- **`finance/financial-analysis`** — that's financial close, P&L, reporting, DCF. This is operational procurement: category strategy and supplier rationalization, not financial reporting.
- **`c-level-advisor/general-counsel-advisor`** — that's contract law (indemnity, IP, liquidated damages). This is category-level spend strategy. Once you've decided which 3 monitoring tools to consolidate to 1, GC reviews the contract terms of the survivor.
- **`business-growth/contract-and-proposal-writer`** — that's outbound proposals to win customers. This is inbound supplier rationalization.
- **`finance/budgeting`** — that's annual budget planning. This is the inside view: where the budget is actually leaking.

## Forcing-question library (Matt Pocock grill discipline)

Walked one at a time by `/cs:grill-bizops` or the BizOps orchestrator. Recommended answer + canon citation per question. Never bundled.

1. **"Before we categorize, do you have a UNSPSC-aligned taxonomy or are you categorizing by vendor name?"**
   Recommended: categorize by what's purchased (line-item description + category_hint), not by supplier. A single supplier can span multiple categories.
   Canon: UNSPSC official taxonomy documentation, A.T. Kearney *Spend Management* on category architecture.

2. **"Of your top 10 categories by spend, which 3 grew most YoY — and do you know why?"**
   Recommended: name them before opening the tool. If you can't name them, that's the diagnosis.
   Canon: BCG Procurement value-creation research, Hackett benchmarks on category-level visibility maturity.

3. **"For each duplicate-function cluster (e.g., 3 monitoring tools), what's the switching cost to consolidate — and does it exceed the savings?"**
   Recommended: estimate switching cost explicitly (training, integration rework, data migration). Refuse to recommend consolidation without it.
   Canon: BCG on supplier-consolidation risks, Spend Matters analyses of failed rationalization initiatives.

4. **"For any tier-1 category you're proposing to consolidate to single-source, what's the 72-hour break-glass plan if that supplier disappears?"**
   Recommended: documented contingency per category, tested. If absent, do not consolidate.
   Canon: NotPetya / M.E.Doc supply chain attack lessons, NIST SP 800-161, A.T. Kearney on supply concentration risk.

5. **"What % of your spend goes through a PO vs. expense reimbursement vs. shadow IT? Where's the maverick spend?"**
   Recommended: measure it. A.T. Kearney research finds 10-40% of spend is maverick in unmonitored companies.
   Canon: A.T. Kearney maverick-spend research, ISM (Institute for Supply Management) procurement maturity model.

6. **"How many of your top-20 contracts renew in the same calendar month? Do you have a renewal calendar?"**
   Recommended: build the calendar; spread renewals deliberately. Clustered renewals destroy negotiation leverage.
   Canon: IACCM/WorldCC contract-management research, Spend Matters on negotiation leverage timing.

7. **"What's your approval threshold for net-new SaaS purchases under $5k? Who owns the death-by-a-thousand-SaaS problem?"**
   Recommended: a tightened threshold + a single owner. Productiv / Zylo data shows 50%+ of SaaS sprawl comes from sub-$5k unmonitored purchases.
   Canon: Productiv / Zylo / Vendr industry reports on SaaS sprawl.

Walk depth-first. Lock 1-4 before opening 5-7. After all are answered, invoke `spend_categorizer.py` → `purchasing_cycle_analyzer.py` → `supplier_consolidation.py` in sequence.

When to use

Review spend, renewals and supplier consolidation opportunities.

What you get

The complete original workflow with source attribution and declared limitations.

How it works

Confirm inputs and dependencies, then apply relevant instructions within the actual authorized task.

Requirements

Authorized spend data, currency, contract periods, renewal terms and critical dependencies.

Delivery and review notes

Published as attributed source guidance after an obvious-danger screen, not functional certification. Categorizer, cycle/consolidation scripts, three references and intake asset are not supplied. Normalize currencies and time periods; account for switching costs, obligations and functional equivalence. Pareto splits and renewal leverage claims are heuristics. A continuity checkbox is not a tested continuity plan. No supplier changes occur on load.

Starting prompt

Use Procurement Spend Guidance for [TASK]. Ask for missing inputs: Authorized spend data, currency, contract periods, renewal terms and critical dependencies. Apply the M11 corrections and distinguish evidence, assumptions and unavailable tooling.

Not for

Claiming runtime validation, installing dependencies or taking external actions merely because the source describes them. Respect the actual task scope and declared limitations.

What M11 added

German discovery terms, task inputs and explicit source limitations. Original authorship remains separate from M11 curation. Published as attributed source guidance after an obvious-danger screen, not functional certification. Categorizer, cycle/consolidation scripts, three references and intake asset are not supplied. Normalize currencies and time periods; account for switching costs, obligations and functional equivalence. Pareto splits and renewal leverage claims are heuristics. A continuity checkbox is not a tested continuity plan. No supplier changes occur on load.

Original authorship remains with alirezarezvani/claude-skills · Original source ↗

Original license & copyright

MIT License

Copyright (c) 2025 Alireza Rezvani

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Source SHA-256: 308e0858ae3fd62fb1f0fdb03a9b16264897099aa48e397b152528ceec4edeea
Snapshot checked: 2026-09-28T15:32:21.716870+00:00

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