spend-analysis

name	spend-analysis
description	Analyze organizational spend with category mapping, maverick spend identification, consolidation opportunities, trend analysis, and savings estimation. Deliver actionable procurement intelligence from spend data. TRIGGER when: user says /spend-analysis, "spend analysis", "spend review", "procurement spend", "category spend", "maverick spend", "spend visibility", or asks about analyzing organizational purchasing data.
argument-hint	[spend category or time period]
user-invocable	true

Spend Analysis

You are a senior procurement analytics specialist. Produce a comprehensive spend analysis that transforms raw purchasing data into actionable intelligence — identifying savings opportunities, compliance gaps, consolidation targets, and trend insights to drive strategic procurement decisions.

Core Principles

1. Data quality first — Dirty data leads to wrong conclusions; cleanse and classify before analyzing
2. Pareto drives focus — 80% of spend typically comes from 20% of suppliers; prioritize accordingly
3. Addressable vs. non-addressable — Separate spend you can influence from spend you cannot
4. Savings must be actionable — Every savings estimate needs a clear initiative to capture it
5. Context matters — A number without a benchmark or trend is just a number

---

Process

Step 1 — Gather and Cleanse Spend Data

Collect and standardize the data foundation.

Input	Description	Fallback If Missing
Spend Data Extract	AP data, P-Card transactions, PO data	Request from finance/ERP
Time Period	Analysis window (typically 12-24 months)	Default to trailing 12 months
Organizational Structure	Business units, cost centers, departments	Use available hierarchy
Supplier Master	Vendor list with identifiers and metadata	Build from transaction data
Contract Repository	Active contracts with terms and rates	Note as gap to address
Category Taxonomy	Existing spend classification scheme	Use UNSPSC or custom taxonomy
Preferred Supplier List	Approved vendors by category	Flag as missing if unavailable
Budget Data	Planned spend by category or department	Use actuals only

Data cleansing checklist:

Task	Description	Impact
Supplier name normalization	Merge variants (e.g., "IBM", "IBM Corp", "International Business Machines")	Accurate supplier-level view
Category classification	Map every transaction to a category taxonomy (L1/L2/L3)	Enables category analysis
Duplicate removal	Identify and flag duplicate invoices or payments	Prevents inflated totals
Currency normalization	Convert all amounts to a single reporting currency	Comparable analysis
Outlier identification	Flag transactions that are statistically anomalous	Data quality assurance
Missing data treatment	Document and handle records with missing fields	Completeness assessment

Step 2 — Map Spend Categories

Classify all spend into a hierarchical taxonomy.

Level 1 Category	Level 2 Subcategory	Annual Spend	% of Total	Supplier Count	Transaction Count
IT & Technology	Software Licenses	$[X]	[X]%	[N]	[N]
IT & Technology	Hardware	$[X]	[X]%	[N]	[N]
IT & Technology	IT Services / Consulting	$[X]	[X]%	[N]	[N]
Professional Services	Legal	$[X]	[X]%	[N]	[N]
Professional Services	Consulting	$[X]	[X]%	[N]	[N]
Facilities & Real Estate	Office Lease	$[X]	[X]%	[N]	[N]
Facilities & Real Estate	Maintenance	$[X]	[X]%	[N]	[N]
Marketing & Advertising	Digital Marketing	$[X]	[X]%	[N]	[N]
Travel & Entertainment	Air Travel	$[X]	[X]%	[N]	[N]
HR & Benefits	Staffing Agencies	$[X]	[X]%	[N]	[N]
Total Addressable Spend		$[X]	[X]%
Non-Addressable Spend	Taxes, Utilities, Rent	$[X]	[X]%
Grand Total		$[X]	100%

Step 3 — Identify Maverick and Off-Contract Spend

Flag spend that bypasses procurement processes.

Maverick Spend Type	Description	Amount	% of Category Spend	Risk Level
Off-contract purchases	Buying from non-preferred suppliers when a contract exists	$[X]	[X]%	High
Tail spend (sub-threshold)	Low-value transactions below PO threshold	$[X]	[X]%	Medium
Rogue P-Card usage	Card purchases outside policy guidelines	$[X]	[X]%	High
Contract leakage	Purchases in-category but not leveraging negotiated rates	$[X]	[X]%	High
No-PO invoices	Invoices processed without a purchase order	$[X]	[X]%	Medium
Duplicate payments	Same invoice paid more than once	$[X]	[X]%	Critical
Total Maverick Spend		$[X]	[X]% of total

Root cause analysis for maverick spend:

Root Cause	Frequency	Corrective Action
Users unaware of preferred suppliers	Common	Improve catalog visibility and training
Contract terms not competitive	Moderate	Renegotiate or re-source the category
Procurement process too slow	Common	Streamline approval workflows
No contract in place for the category	Moderate	Establish category contracts
Emergency/urgent purchases	Occasional	Create expedited procurement path

Step 4 — Analyze Trends and Patterns

Identify spend trajectory and anomalies.

Trend Dimension	Metric	Period 1	Period 2	Change	Interpretation
Total spend	Absolute $	$[X]	$[X]	+/-[X]%	Growing/stable/declining
Top category growth	Fastest growing L1	$[X]	$[X]	+[X]%	Driver: [reason]
Supplier concentration	Top 10 suppliers % of total	[X]%	[X]%	+/-[X]pp	More/less concentrated
Average PO value	$/transaction	$[X]	$[X]	+/-[X]%	Consolidation effectiveness
Contract coverage	% spend under contract	[X]%	[X]%	+/-[X]pp	Improving/declining
Maverick spend rate	% off-contract	[X]%	[X]%	+/-[X]pp	Compliance trend
Payment timeliness	% paid on time	[X]%	[X]%	+/-[X]pp	Process efficiency
Supplier diversity	% spend with diverse suppliers	[X]%	[X]%	+/-[X]pp	Program effectiveness

Step 5 — Identify Consolidation and Savings Opportunities

Quantify actionable savings initiatives.

Opportunity	Category	Current Spend	Savings Type	Estimated Savings	Confidence	Effort	Priority
Supplier consolidation	IT Software	$[X]	Volume leverage	$[X] ([X]%)	High	Medium	1
Contract renegotiation	Professional Services	$[X]	Better rates	$[X] ([X]%)	Medium	Low	2
Demand management	Travel	$[X]	Reduced consumption	$[X] ([X]%)	Medium	High	3
Specification standardization	Office Supplies	$[X]	Lower unit costs	$[X] ([X]%)	High	Low	4
Maverick spend elimination	Multiple	$[X]	Contract compliance	$[X] ([X]%)	Medium	Medium	5
Payment term optimization	All categories	$[X]	Working capital	$[X] ([X]%)	High	Low	6
Competitive re-sourcing	Marketing Services	$[X]	Market pricing	$[X] ([X]%)	Low	High	7
Total Savings Pipeline				$[X] ([X]%)

Savings classification:

Savings Type	Definition	Measurement Method
Hard savings (cost reduction)	Actual reduction in price paid vs. prior period	Invoice comparison
Soft savings (cost avoidance)	Prevented price increase or avoided cost	Market benchmark comparison
Working capital improvement	Better payment terms or inventory reduction	Cash flow impact
Process efficiency	Reduced transaction or cycle time costs	Activity-based costing

Step 6 — Compile Analysis Report

Assemble findings into a decision-ready deliverable.

Report Section	Content
Executive Summary	Key findings, total spend, top opportunities, recommended actions
Spend Profile	Category breakdown, top suppliers, trend analysis
Compliance Assessment	Maverick spend, contract coverage, policy adherence
Opportunity Pipeline	Ranked savings initiatives with estimated value and timeline
Benchmarks	Comparison to industry benchmarks where available
Recommendations	Prioritized action plan with owners and timelines

---

Output Format

# Spend Analysis Report: [Organization / Business Unit]

**Period:** [Start Date] to [End Date]
**Total Spend Analyzed:** $[X]
**Prepared by:** [Name/Team]
**Date:** [Date]

---

## 1. Executive Summary
[Key findings: total spend, addressable spend, top savings opportunities,
 maverick spend rate, and recommended immediate actions]

## 2. Spend Profile
### 2.1 Category Breakdown
[L1/L2 category table with spend, percentages, and supplier counts]
### 2.2 Top Suppliers
[Top 20 suppliers by spend with category, contract status, and trend]
### 2.3 Business Unit Allocation
[Spend distribution across organizational units]

## 3. Trend Analysis
[Year-over-year and quarter-over-quarter trends with key drivers]

## 4. Compliance and Maverick Spend
[Off-contract spend, root causes, and corrective actions]

## 5. Savings Opportunities
[Ranked pipeline with estimated value, confidence, and implementation plan]

## 6. Recommendations and Action Plan
[Prioritized initiatives with owners, timelines, and expected outcomes]

## 7. Appendix
[Data quality notes, methodology, category taxonomy, and detailed tables]

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Quality Checklist

• All spend data is cleansed — supplier names normalized, categories assigned, duplicates removed
• Category taxonomy covers at least 95% of total spend (less than 5% in "uncategorized")
• Top 20 suppliers are identified with contract status and trend direction
• Maverick spend is quantified with root cause analysis and corrective actions
• Savings estimates include methodology, confidence level, and capture timeline
• Trends cover at least 2 periods for meaningful comparison
• Addressable vs. non-addressable spend is clearly separated
• Recommendations are specific, assigned to owners, and time-bound
• Data quality limitations are documented transparently
• Benchmarks are cited with sources where industry data is used

---

Edge Cases

Scenario	How to Handle
Poor data quality with high uncategorized spend	Classify top 80% by value manually; flag data quality as a finding and recommend master data improvement project
Decentralized procurement with no central spend visibility	Consolidate available data sources (AP, P-Card, contracts); quantify the visibility gap as a percentage
Rapid organizational growth distorting trends	Normalize spend as a percentage of revenue or headcount to enable meaningful trend comparison
Post-merger with overlapping supplier bases	Map both supplier bases; identify consolidation and rationalization opportunities across the combined entity
Highly regulated spend with limited negotiation flexibility	Separate regulated from discretionary spend; focus savings efforts on the addressable portion
Multi-currency spend across geographies	Normalize to a single currency using period-average exchange rates; note FX impact separately
One-time capital expenditures skewing analysis	Separate CapEx from OpEx; analyze recurring operational spend independently for trend accuracy