7 Best Practices for Indirect Procurement Strategies Using Spend Data Analytics

With inflation, supply chain disruption, and ESG scrutiny putting the squeeze on businesses, you need to optimise every dollar spent. Trust me, spend analysis is one of your most powerful, yet often overlooked, tools to do just that.

Spend analysis transforms your scattered purchasing data into actionable insights. It’s about collecting, cleansing, and making sense of your supplier expenditure to uncover savings, reduce risk, boost supplier performance, and align spending with your strategic goals.

At its heart is spend data: detailed records of what you buy, who you buy from, what you pay, and your terms. This goes beyond purchase orders and invoices to include purchasing card transactions, contract details, and usage volumes.

Many procurement teams focus heavily on direct spend (materials tied to your core products), but here’s the kicker: the real untapped potential often sits in indirect spend.

This covers all those supporting services, marketing, IT, professional services, facilities, travel, and contingent labour. Indirect spend tends to be more scattered and less visible, making it harder to control but perfect for strategic analysis.

You might be surprised to learn that in top-performing organisations, indirect spend accounts for 15–25% of total procurement value, yet often creates a disproportionate share of complexity and missed opportunity.

The main challenge has always been visibility.

Few companies have a single source of truth for spend data. Instead, it’s scattered across different systems and spreadsheets, making it tough to extract meaningful insights. Thankfully, that’s changing. With automated data pipelines, cloud analytics, and tools like the Purchasing Index, you can now get a comprehensive view of spend that’s timely, accurate, and actionable.

Whether you’re building a case for procurement transformation or fine-tuning your current practices, this roadmap will help you unlock greater value from your spend data.

Step 1: Collect Procurement Data

In an environment where every dollar counts, procurement leaders are rethinking how they capture, and harness spend data. Fragmented, incomplete data has long been a barrier to enterprise-wide visibility, particularly in indirect spend, where purchases are decentralised and spread across cost centres, purchasing cards, and ad hoc supplier arrangements.

Getting to a Single Source of Truth

The challenge is one you’ve likely faced: siloed systems, inconsistent formats, and decentralised purchasing that prevent a unified view. This is particularly pronounced in indirect categories.

But world-class teams don’t just aggregate spend, they architect a data backbone that earns trust from Finance, business units, and the Board. This means aggregating data from ERP systems, accounts payable, purchasing cards, contract repositories, supplier portals, and even expense claims.

This data includes: items purchased over a period of time, the item description, the consumption, the prices, the related suppliers and so on. It also means collaborating with Finance to reconcile supplier-level records and ensure the integrity of financial reporting.

Data points must go beyond just “what was bought” to include contextual intelligence, supplier relationships, contract terms, consumption trends, and risk signals.

Critically, this isn’t an IT project. It’s a cross-functional operating model, with:

• Data ownership mapped by function and process
• Data quality metrics reviewed at the Procurement Governance Forum
• Quarterly refresh rates aligned to sourcing calendar and quarterly business reviews

Advanced teams automate ingestion through RPA and API ecosystems, yes, but more importantly, they embed procurement into the enterprise data fabric, allowing for real-time scenario planning and predictive insights.

The goal at this stage isn’t just data collection, it’s establishing a trustworthy, dynamic data foundation that supports predictive analytics, category planning, and executive decision-making.

It’s the foundation for procurement to shift from a reporting function to a strategic co-pilot, where decisions are faster, smarter, and anchored in shared truth.

Step 2 – Cleanse Procurement Spend Data

Reliable insights start with reliable procurement data.

For procurement to be credible at the executive table, its data must not only be accurate but auditable, explainable, and consistently governed.

Yet in indirect procurement, where spend is decentralised, often transactional, and heavily reliant on p-cards and non-PO channels, data quality issues are the norm, not the exception.

Duplicate supplier names, inconsistent classifications, mismatched currencies, and fragmented line-item details can all obscure the real story of where and how money is spent. This is why data cleansing is not just a technical task, it’s a governance issue. Leading organisations treat it as a core enabler of transparency and decision confidence.

Leading CPOs embed data quality into their operating rhythm by establishing:

• Data Quality KPIs (e.g., “>95% of addressable spend classified with high confidence”)
• Governance Cadence (e.g., “Quarterly reviews of data integrity at the Procurement Data Council, co-chaired by the CPO and CFO”)
• Clear Ownership (e.g., “Supplier master data integrity owned by Procurement Ops, classification accuracy by Category Managers, audit trail by Finance”)

Yes, cleansing includes tactical steps: deduplication, normalisation, outlier flagging. But high-performing teams extend this with:

• Machine learning models that self-correct classification errors over time
• Third-party enrichment layers for ESG scores, DUNS numbers, or supplier risk profiles
• Confidence scoring to triage low-trust data before it reaches decision-makers

This approach yields measurable impact, such as:

• 30% reduction in sourcing cycle time through accurate pre-bid supplier grouping
• 40% fewer disputes with Finance due to reconciled totals and vendor hierarchies
• Higher stakeholder adoption of insights due to transparency on data quality

But let’s be clear: this isn’t plug-and-play. Real friction arises from:

• Legacy ERPs with inconsistent naming conventions
• Low data literacy in business units
• Tensions between IT’s “perfect data model” and procurement’s need for usable intelligence

Effective cleansing begins with standard health checks: validating reported vs actual totals, deduplicating suppliers, normalising exchange rates, and identifying outliers. But the most mature teams go further, using AI- and ML-driven algorithms to automate classification, detect anomalies, and enrich records with external intelligence, like supplier risk ratings, ESG scores, or DUNS identifiers.

Just as importantly, cleansing is no longer a one-off project. It must be embedded into a data quality framework, with clear ownership, regular audits, and shared standards across procurement, finance, and IT. Manual intervention will always be part of the process, but today’s tools dramatically reduce the lift and increase accuracy.

The goal isn’t to build a perfect spend dataset, it’s to build a resilient one.

One that evolves, explains itself, and enables action at the pace of the business. At its core, this step is about building data integrity at scale so that insights generated downstream are credible, actionable, and aligned with business priorities.

Step 3: Classify Procurement Spend Data  

Classification is where procurement data starts to speak in a language the business understands. But for that language to drive action, it must be both structurally sound and strategically aligned, not just a taxonomy exercise delegated to a back-office team.

Indirect Spend Analysis Presents a Challenge

For organisations dealing with thousands of suppliers and tens of thousands of transactions, structuring that complexity into meaningful categories is the foundation for actionable insights. But in indirect procurement, where services dominate and purchase behaviours vary widely, classification requires more than just taxonomies. It demands a flexible, business-aligned model.

Spend Data Governance in Action:

• Taxonomy oversight sits with a Category Design Authority, often chaired by Procurement and with input from Finance, IT, and business units.
• Classification accuracy is reviewed quarterly, with a defined confidence threshold (e.g., “95%+ of addressable spend classified at Level 3 granularity”).
• Audit trails exist for overrides and reclassifications, especially for high-impact services like legal, consulting, or IT.

Hybrid models are the norm, combining standards like UNSPSC with business-aligned overlays:

• UNSPSC brings consistency across systems and e-procurement platforms.
• Custom categories reflect how stakeholders plan, budget, and engage with suppliers.

This dual structure ensures data is both machine-readable and human-actionable. For example, a marketing manager doesn’t care about “82101507 – Advertising services”, they care about “Media Buying – Programmatic” vs “Creative Strategy – Retainer”.

Organisational friction? It’s real.

• Procurement may want control; business units resist re-labelling “their” budgets.
• IT may push a rigid taxonomy; category leads need flexibility to reflect evolving supply markets.

Strategic Impact: Done right, classification doesn’t just clean data. It becomes the connective tissue between spend, stakeholder intent, and supplier ecosystems. It unlocks the ability to:

• Benchmark categories across geographies or BUs
• Identify aggregation opportunities at the sub-category level
• Track ESG performance or innovation investment by spend type

This is where procurement moves from visibility to strategic narrative. Not just “what did we spend?”, but “what are we doing, with whom, and why?”

A NOTE ON PROCUREMENT DATA TAXONOMIES and United Nations Standard Products and Services Code (UNSPSC)

Leading organisations apply a hybrid approach: leveraging recognised standards like the United Nations Standard Products and Services Code (UNSPSC) while tailoring categories to reflect internal structures and strategic goals.

UNSPSC is a globally recognised hierarchical taxonomy with over 80,000 codes across five levels: Segment, Family, Class, Commodity, and Business Function. It provides a consistent way to classify goods and services across industries, facilitating supplier comparison, spend tracking, and even e-procurement integration. However, it’s not always intuitive for business users, especially for nuanced service categories, so many organisations use it as a backbone, enriched with business-friendly labels.

Today’s spend analytics platforms increasingly use AI and NLP to automate classification, speeding up the process and reducing dependency on manual coding. But even with automation, strategic oversight is essential, particularly to ensure that services are not misclassified based on the supplier name, a common but costly mistake.

Ultimately, effective classification brings procurement out of the data weeds and into a position of insight leadership, connecting spend to business functions, stakeholder needs, and strategic opportunities.

Step 4: Identify Addressable Spend from Classified Procurement Data

Not all spend is created equal, but in today’s procurement context, almost all spend is influenceable.

Traditional models divide spend into “addressable” and “non-addressable,” often writing off categories like rent, utilities, or government fees as untouchable. But this binary lens is outdated.

Today, leading procurement teams apply a spectrum-based approach, identifying not just what can be directly sourced or negotiated, but what can be shaped through demand management, stakeholder engagement, supplier consolidation, or even automation.

Key Dimensions of Spend Influence:

• Sourcing Levers: Can we aggregate demand, standardise specs, or renegotiate rates?
• Demand Levers: Can we reduce volume, rationalise scope, or delay consumption?
• Compliance Levers: Can we shift tail spend onto preferred suppliers or POs?
• Process Levers: Can we automate, streamline, or digitise the buy-and-pay journey?

Spend Influence Success Metrics Might Include:

• % of spend actively influenced vs total spend
• Reduction in unmanaged suppliers per category
• Stakeholder satisfaction with procurement involvement in “grey” categories

Take marketing, legal, or professional services, classic examples of “hard-to-touch” spend. While procurement may not lead every negotiation, it can influence outcomes by:

• Standardising scopes of work
• Consolidating preferred partners
• Improving brief quality to reduce over-servicing
• Benchmarking rates across business units

This is the heart of indirect procurement strategy: working collaboratively to unlock influence in unconventional areas.

Rather than simply filtering out “non-addressable” spend, best-in-class teams use analytics to map where influence exists today, and where it can be built. This requires close alignment with budget owners, a keen eye for inefficiencies, and often a bit of creativity. Some low-control categories may still yield process efficiencies or working capital improvements, adding strategic value even when pricing control is limited.

A financial services firm reclassified certain tax outlays as “low-control, high-opportunity,” uncovering $2M in recoverable VAT through procurement-led audits, despite no direct sourcing involvement.

But let’s not pretend it’s frictionless. Misaligned incentives embedded legacy suppliers, or lack of stakeholder appetite can block progress.

This step is not about overstepping, it’s about co-creating influence. Mapping where procurement can shape outcomes, even in unconventional spend areas, helps prioritise effort and expand impact.

Step 5: Define Spend Categories 

Spend categorisation is often mistaken for a backend exercise, grouping transactions to feed reporting tools. But for a CPO, category structure is a strategic design decision. It determines how procurement engages suppliers, aligns with stakeholders, and unlocks enterprise value.

The Goal: Create a category model that mirrors how suppliers operate and how internal stakeholders make decisions.

Once influenceable spend is identified, the next step is to group it in ways that reflect both external supply markets and internal decision-making structures. This isn’t just a data exercise, it’s a strategic design challenge that determines how procurement will manage, engage, and extract value from suppliers.

Spend Categorisation Governance Matters:

• Category Taxonomy Ownership sits with a formal Category Governance Board, typically led by the Head of Procurement Excellence with cross-functional representation (Finance, BU leads, IT).
• Taxonomy reviews occur annually or post-major reorganisations, with feedback loops from Category Managers and key budget owners.
• Metrics to track effectiveness:
  • % of spend mapped to active category strategies
  • Cycle time for category planning post-realignment
  • Stakeholder adoption of new category structures (via QBR feedback)

Design Principles for CPO-Grade Category Structures:

1. Externally Coherent: Align with how suppliers bundle services, e.g. grouping “creative production” with “media buying” where agencies overlap.
2. Internally Relevant: Reflect business unit ownership. If Legal and HR both use consulting, treat them as sub-categories with distinct stakeholder journeys.
3. Flexible but Disciplined: Support multi-level trees (L1: Professional Services > L2: Legal, Audit > L3: IP Litigation, Regulatory Advisory), but maintain governance to avoid taxonomy sprawl.

Effective category structures mirror the way suppliers go to market. If multiple services or products are sourced from similar vendors or governed by the same market dynamics, they should be grouped accordingly. But that’s only half the picture. The category taxonomy must also align with how internal stakeholders perceive and manage their budgets, or risk being ignored in practice.

Especially the case in Indirect Procurement Spend

This is especially true in indirect procurement, where spend is distributed across marketing, HR, legal, facilities, and IT. Involving these business partners early in category definition ensures the result is actionable, not just analytically neat. Procurement becomes a co-creator of value, not a gatekeeper of process.

To support both granularity and usability, many organisations adopt multi-level category trees:

• Level 1: Broad categories (e.g. Professional Services)
• Level 2: Sub-categories (e.g. Legal, Audit, Consulting)
• Level 3: Transactional types or cost drivers (e.g. hourly rate, fixed-fee projects)

“Is your category structure helping or hindering supplier innovation and stakeholder buy-in? Does it reflect today’s value levers, or last decade’s cost centers?”

Case example: A global insurance provider realigned its category structure based on supplier ecosystems rather than internal cost centres, resulting in a 15% reduction in sourcing cycle times and greater stakeholder adoption. Done right, this step creates a clear, flexible structure for managing spend, and lays the foundation for opportunity assessments, strategic sourcing plans, and supplier collaboration. It’s not about forcing data into boxes. It’s about building a shared mental model of spend that supports smarter decisions across the enterprise.

Step 6: Prioritise High-Impact Spend with a Strategic Lens

Every procurement team has more categories than capacity.

The strategic question isn’t “what can we do?”, it’s “where should we focus to drive disproportionate impact?” That’s why high-performing CPOs prioritise spend based on multi-dimensional value, not just volume.

Not all spend categories offer the same return on effort, and effective procurement teams focus where the impact is greatest.

The next step is to prioritise categories based on their potential impact, aligning procurement’s focus with where it can move the needle on cost, risk, innovation, and ESG outcomes.

Not all spend categories deserve equal attention or deliver equal value. Prioritisation begins by applying the Pareto Principle: the idea that 80% of results often come from 20% of inputs. In procurement terms, a small number of categories typically account for the majority of spend, and therefore, the majority of opportunity.

This is operationalised through an ABC analysis, which segments categories based on their relative share of total spend:

• A Categories are the high-impact categories that typically make up around 80% of total spend, often across a small number of suppliers. These demand the most strategic attention, offering significant potential for cost reduction, supplier consolidation, risk mitigation, or innovation.
• B Categories contribute the next 10% of spend and may include important but less critical goods or services. These categories can often be addressed with more tactical sourcing strategies or by bundling similar items.
• C Categories account for the final 10% of spend, usually scattered across many suppliers and transactions. While they may not justify dedicated sourcing strategies, these categories can still yield “soft” benefits, such as reducing administrative effort, automating low-value transactions, or simplifying the supplier base.

Beyond ABC: Build a Multi-Factor Prioritisation Model

Yes, Pareto analysis (80/20) provides a starting point, but spend volume alone ignores risk, opportunity, or strategic alignment. Leading teams build out value-versus-effort matrices, plotting categories against:

• Strategic importance (e.g. supports core products or revenue lines)
• Supplier risk exposure (e.g. single-source or offshore dependencies)
• Innovation potential (e.g. fast-moving tech categories)
• ESG contribution or regulatory weight
• Ease of change (e.g. stakeholder readiness, contract maturity)

Procurement Prioritisation Governance in Practice:

• Category Prioritisation Framework embedded into annual planning cycles, co-owned by the CPO and business unit COOs.
• Quarterly alignment checkpoints during QBRs to reassess based on business priorities or external shifts (e.g. market volatility, supply disruption).
• Key success metrics:
  • % of high-impact categories with an active sourcing or transformation plan
  • Number of priority categories with supplier collaboration initiatives underway

Example: A tech company identified contingent labour as a “B” category by spend, but flagged it as “A” by risk due to regulatory exposure, elevating it to a priority category for compliance-driven sourcing.

This approach also opens the door to wave planning: sequencing sourcing initiatives over time to balance quick wins with longer-term transformation plays.

Organisational Friction to Navigate:

• Functional stakeholders may lobby for focus on their categories, regardless of ROI.
• Prioritisation frameworks may be seen as opaque or overly analytical.
• Some “C” categories by spend may have outsized strategic implications, requiring nuanced judgment beyond the numbers.

Ultimately, this step is about ensuring procurement is not chasing pennies in the wrong places. It’s about linking category-level insight to enterprise-level strategy, so procurement isn’t just efficient, but effective.

Case example: An energy company flagged “IT subscriptions” as a C-category by spend, but identified it as an A-category for cyber risk, shifting its sourcing into a top-tier priority.

By blending quantitative analysis with strategic context, this step ensures procurement focuses not just on big numbers, but on the categories that truly move the business forward.

Step 7 – Execute the Opportunity Analysis

With spend categories prioritised, the final step is to convert insights into targeted, executable strategies, identifying where procurement can drive the greatest value for the least effort.

At this stage, the value isn’t in the procurement data, it’s in the decisions.

With categories prioritised, high-performing procurement teams translate insight into action through a structured opportunity scan or opportunity analysis, that feeds directly into strategic sourcing roadmaps.

This is a structured analysis that maps categories and sub-categories by their potential benefit versus ease of implementation.

Typically visualised as a 2×2 matrix, the opportunity scan places:

• Potential benefit on the Y-axis, factoring in cost savings, efficiency gains, risk reduction, ESG improvement, and business value
• Ease of implementation on the X-axis, factoring in supplier switching complexity, internal stakeholder resistance, process maturity, and required investment

To populate this matrix meaningfully, teams must ask:

• How complex or fragmented is the supply market?
• Are there quick wins through demand consolidation or contract renegotiation?
• How open are stakeholders to change?
• What internal capability or governance upgrades are needed to realise value?

Example: A services firm mapped its facilities management spend as high benefit but low ease, triggering a multi-year sourcing wave plan supported by a business case and change management effort.

The resulting matrix enables procurement leaders to build a wave plan, a sequenced roadmap of initiatives, aligned to sourcing capacity, internal readiness, and enterprise priorities. High-benefit, high-ease categories become quick wins; complex but valuable areas feed into longer-term transformation strategies; low-impact areas may be bundled, automated, or deprioritised.

Examples of Actionable Output:

• High-Benefit, Low-Effort: Quick wins (e.g. consolidating travel spend across regions)
• High-Benefit, High-Effort: Strategic bets (e.g. reengineering facilities management through a global RFP)
• Low-Benefit, High-Effort: Deprioritised unless required for compliance
• Low-Benefit, Low-Effort: Candidates for automation or tactical consolidation

From here, procurement can move into execution mode, developing business cases, engaging stakeholders, and activating the right sourcing levers, from competitive tenders to supplier collaboration or contract optimisation.

Insight: High-performing teams integrate the opportunity scan into cross-functional planning cycles, ensuring sourcing strategies are co-owned with the business and aligned to broader operational goals.

Governance in Action:

• Opportunity analysis is led by Category Managers with sign-off from the Procurement Leadership Team and embedded in the annual operating plan.
• Wave plans are sequenced and resourced quarterly, aligned with procurement capacity and business unit timing.
• CPO-level KPIs include:
  • % of priority categories with executed wave plans
  • Average time-to-impact from opportunity identification to sourcing execution
  • Stakeholder satisfaction with procurement’s strategic engagement

The Friction to Expect:

• Stakeholders may resist perceived “procurement-led” agendas
• Timing mismatches between budget cycles and sourcing waves
• Insufficient procurement bandwidth to execute opportunities at scale

This final step turns the data effort into enterprise impact. It’s where procurement stops reporting on spend and starts orchestrating value across cost, risk, sustainability, and resilience.

From Spend Data to Procurement Decisions

You might recognise this challenge: many organisations still depend on fragmented systems, manual reports, or outdated taxonomies that hide more than they reveal.

However, in a business landscape where procurement needs to deliver more than just savings, spend analysis is your strategic enabler, bridging the gap between raw data and real enterprise value.

This seven-step guide gives you a fresh perspective on indirect spend analysis as a leadership capability. It’s rooted in solid procurement data analysis, accelerated by smart spend data classification, and designed to unlock tangible outcomes across cost, risk, ESG, and innovation. From getting a handle on supplier spend segmentation to using ABC analysis in procurement planning, here’s the kicker: teams who build clarity into their procurement spend analysis will outperform those still trying to navigate without a proper map.

Whether you’re an analyst looking for best practices, a CPO driving transformation, or a business partner who needs transparency, trust me, the future of procurement is powered by data.

Ready to Unlock the Full Power of Your Procurement Data?

If you’re looking to elevate your procurement data analytics capability, streamline your indirect spend analysis, or implement best-in-class spend categorisation techniques, Purchasing Index is your starting point.

Built for organisations serious about value, Purchasing Index supports advanced procurement data analysis, intuitive spend data classification, and tailored supplier spend segmentation, all in one place.

Developed by one of the leading data analytics companies in Australia (head office in Melbourne), Purchasing Index is used across Australia by procurement teams seeking excellence in spend analysis best practices and scalable indirect procurement strategies.

[Book a demo today] and discover how we help your procurement teams move from data to decisions.