Goal of the analysis:
The purpose of Maverick Spend Rate analysis is to quantify and understand purchases made outside approved procurement channels or contracts. For executives, this measure is a direct proxy for policy compliance, spend control, and realized savings versus negotiated agreements. Lower maverick spend correlates with reduced price variance, improved supplier leverage, better risk control (legal, ESG, data security), and stronger working capital discipline. For Supply Chain and Procurement leaders, the analysis identifies where guided buying and contract coverage are failing, which categories or sites are off-policy, and the specific process or system gaps to close.
Data required:
- Transactional spend data:
- Purchase orders (POs): PO number, line items, dates, requester, buyer, supplier, item/description, category, quantities, unit prices, contract reference (if any).
- Invoices and non-PO invoices: invoice number, supplier, line items, amounts, receipt match status, PO reference flag.
- P-card and virtual card data: merchant name, MCC code, transaction date, amount, cardholder, cost center, receipt status.
- Marketplace and punchout transactions (e.g., Amazon Business): catalog flag, supplier, item, price.
- T&E where applicable to indirect goods (often excluded but needed for scoping decisions).
- Master data and contracts:
- Supplier master: supplier IDs, preferred/approved status, risk flags, payment terms.
- Contract repository: contract IDs, effective dates, categories, suppliers, item/SKU lists, price lists, service rate cards, volume tiers, contracted sites/geographies.
- Category taxonomy and mapping (UNSPSC or internal), catalog items, preferred brand lists.
- Process and organization metadata:
- Requester, buyer, approver identities; business unit, plant/site, cost center, project codes.
- Approval workflow logs, PR-to-PO conversion (PO flip), receipt dates.
- Policy thresholds (e.g., no-PO/no-pay, P-card limits), exception codes (emergency, single-source).
- Reference and normalization data:
- Exchange rates, fiscal calendars, inflation indices (optional for time-normalized comparisons).
- Internal vendor black/white lists; regulated categories; tax/legal exclusions.
- Benchmarks and targets:
- Internal historic maverick spend performance by category/site.
- External price or category benchmarks (where available) to estimate price variance risk.
Detailed step-by-step instruction on how to conduct the analysis:
- Define scope and addressable spend.
- Include categories with available approved channels or contracts (e.g., catalogs, preferred suppliers, frameworks).
- Exclude inherently non-addressable spend (e.g., taxes, statutory fees, utilities where no alternatives, payroll, donations) and pre-approved exceptions.
- Extract data from source systems.
- ERPs (SAP ECC/S4HANA, Oracle EBS/Cloud, MS Dynamics) for POs/invoices/receipts.
- P2P suites (Ariba, Coupa, Jaggaer, Ivalua) for PR/PO detail, catalogs, approval logs.
- T&E (Concur) and P-card issuers for card spend; marketplace feeds for punchout detail.
- Contract lifecycle management system for contract metadata and price lists.
- Cleanse and normalize.
- Normalize supplier names (DUNS, vendor IDs), deduplicate credit memos, convert currencies, standardize category taxonomy.
- Align fiscal periods; flag blanket POs and recurring invoices.
- Map transactions to contracts and channels.
- Supplier-level match: if supplier and category fall under an active contract.
- Item/SKU-level match: link items to contracted SKUs or rate cards; consider volume tiers and site/geography applicability.
- Channel flag: catalog vs non-catalog, PO vs non-PO, P-card vs guided buying.
- Define maverick rules and classify.
- No-PO spend in PO-mandatory categories.
- Off-contract supplier used when a contracted supplier exists for the category/site.
- On-supplier but off-catalog or price above contract tolerance (e.g., >5%).
- Purchases from blocked/non-approved suppliers (unless exception-coded).
- Card transactions where MCC or merchant is outside approved lists for that category.
- Apply exceptions: emergency codes, single-source approvals, R&D prototypes where policy allows, pre-approved spot buys.
- Calculate metrics.
- Maverick Spend = sum of transaction amounts classified as maverick.
- Addressable Spend = total spend in scoped categories with approved channels or contracts.
- Maverick Spend Rate = Maverick Spend / Addressable Spend.
- Optional: Maverick Transaction Rate = number of maverick transactions / total transactions (addressable).
- Price Variance Opportunity = sum over maverick items of (Actual Price − Contract Price) × Quantity, where a comparable contract price exists.
- Segment analysis.
- By category/subcategory (e.g., MRO, IT peripherals, facilities), supplier, site/plant, business unit, requester, buyer, and channel.
- By geography and contract coverage level; distinguish tail suppliers vs preferred.
- Trend and benchmark.
- Monthly/quarterly trend for 12–24 months; correlate with policy changes or catalog rollouts.
- Compare to internal targets and external ranges; identify top and bottom quartile units internally.
- Root cause tagging.
- For top maverick transactions, assign drivers: missing contract, catalog gaps, urgent need, price mismatch, system usability, supplier pushback.
- Use text mining on free-text descriptions to suggest tags; validate with buyers.
- Synthesize insights and actions.
- Prioritize categories/sites with high maverick spend and large price variance opportunity.
- Quantify savings and risk reduction from closing gaps; define owners and timelines.
Format of the output of analysis:
- Executive summary slide with overall Maverick Spend Rate, trend, and estimated savings opportunity.
- Dashboard views:
- Heatmap of maverick rate by category vs site/business unit.
- Pareto charts of top requesters, suppliers, and sites driving maverick spend.
- Channel breakdown (PO, non-PO, P-card, catalog vs non-catalog).
- Price variance bar chart for items with comparable contract prices.
- Detailed transaction table for top 100 maverick items with root cause tags and recommended corrective actions.
- Benchmark comparison page (internal vs external) and target setting.
- Action plan with owners, milestones, and expected impact.
How to interpret results:
- Low Maverick Spend Rate indicates strong policy compliance, effective guided buying, and high realization of negotiated savings.
- High Maverick Spend Rate suggests gaps in contract coverage, catalog quality, system usability, or enforcement (e.g., lack of no-PO/no-pay).
- Category differences matter: higher rates are common in diffuse, ad hoc categories (e.g., MRO, marketing materials) and should be interpreted relative to contract coverage and market dynamics.
- If maverick rate is high but price variance is low, focus on channel enablement and control (process issue). If both are high, prioritize sourcing and contract execution.
- Spikes over time often align with organizational changes, budget flush periods, or system outages; sustained improvement after catalog expansion or policy reinforcement is a positive signal.
- P-card spend is not inherently maverick; interpret within policy context (approved merchants, limits, pre-approval).
Steps a company can take to improve on this measure:
- Process and policy:
- Implement and enforce no-PO/no-pay and no-PO/no-receipt policies in addressable categories.
- Mandate guided buying with preferred supplier and catalog routing; set clear exception paths (spot buy with approval).
- Introduce pre-approved P-card programs for low-value, low-risk items with merchant controls.
- Block non-approved suppliers and create lightweight onboarding for preferred alternates.
- Data, systems, and tooling:
- Expand and maintain catalogs and punchouts; ensure item coverage and accurate price lists.
- Integrate CLM with P2P for automatic contract reference and price checks; enable alerts for price overages.
- Deploy real-time guidance and nudges in requisitioning (suggest preferred items/suppliers).
- Set automated holds for non-PO invoices in controlled categories; enable exception workflows.
- Capability and governance:
- Train requisitioners and approvers; publish playbooks by category with “where to buy” guidance.
- Establish BU scorecards with maverick rate targets; tie to leadership incentives.
- Create a buyer helpdesk and category champions to resolve sourcing needs quickly.
- Run periodic audits and communicate wins (savings, risk reduction) to sustain adoption.
- Sourcing and supplier strategy:
- Increase contract coverage in high-variance categories; consolidate suppliers and negotiate catalogs/rate cards.
- Address root causes: fill catalog gaps, add substitute items, align SLAs to reduce “urgent” off-policy buys.
- Set price tolerance bands and volume tiers; renegotiate when market prices shift materially.
- If maverick is concentrated in a few suppliers, assess preferred status and harmonize terms across sites.
Benchmark comparisons:
General benchmarks:
- Overall Maverick Spend Rate (addressable spend basis): best-in-class typically under 5–10%.
- Typical organizations: 10–20%; lagging performance often exceeds 20–30%.
- Maverick Transaction Rate tends to be higher than spend-based rates due to many low-value purchases; track both.
Segment- or industry-specific benchmarks:
- MRO and facilities: 10–25% is common without strong catalogs; best-in-class can reduce to <10%.
- IT peripherals and office supplies: 5–15% with mature catalogs; can approach <5% in highly controlled environments.
- Professional services: 5–15% depending on SOW discipline and rate card adoption.
- Manufacturing plants often show higher variability by site; shared services or HQ functions tend to be lower.
- If external benchmarks are limited, construct internal benchmarks by:
- Comparing top vs bottom quartile business units/sites.
- Tracking rolling 12-month trends pre/post interventions (e.g., new catalog launch).
- Setting category-specific targets based on contract coverage and system maturity.
