How Procurement Leaders Can Drive Savings Despite Poor Spend Data

The Reality: Why Poor Spend Data Is Still a Major Barrier

For many organisations, spend data looks complete on the surface, but quickly breaks down under scrutiny.

Common issues include:

• Missing detail on what was actually purchased
• Inconsistent or incorrect categorisation
• Duplicate or fragmented data sources
• Lack of currency, contract or supplier context

Without this level of detail, procurement teams struggle to:

• Identify top suppliers
• Understand spend patterns
• Benchmark against the market
• Accurately quantify savings opportunities

In practice, this often means teams are forced into manual workarounds, reviewing contracts line by line, consolidating multiple data sources and making assumptions just to build a baseline view of spend.

Why It Matters: The Impact on Strategy and Savings

Poor data doesn’t just create operational inefficiencies, but directly impacts outcomes.

Without reliable spend visibility:

• Category strategies are built on incomplete insights
• Sourcing decisions become reactive rather than proactive
• Savings opportunities are underestimated or missed entirely
• Stakeholder confidence can be damaged

In some cases, teams even enter sourcing events with incorrect savings assumptions, only to discover mid-process that the data doesn’t support the expected outcomes.

The result?

• Rework
• Delays
• Lost credibility

What Leading Procurement Teams Do Differently

Despite these challenges, high-performing teams don’t wait for perfect data.

Instead, they focus on building a usable and structured foundation that enables action.

1. Prioritising Spend Analysis and Categorisation

Effective procurement starts with structured, consistent spend data.

Leading teams ensure that:

• Data is categorised based on what is actually being purchased
• Category structures reflect the external market, not internal systems
• Categorisation approaches are standardised and maintained over time

This creates a foundation that supports:

• Better supplier analysis
• More targeted sourcing strategies
• Clearer visibility of opportunities

2. Focusing on the 80/20 of Spend

Rather than trying to fix everything at once, leading teams prioritise:

The top 80% of spend

This allows them to:

• Quickly identify high-impact opportunities
• Engage key suppliers
• Deliver early savings

Even with imperfect data, this approach enables faster and more meaningful results, particularly when combined with tail spend management strategies.

3. Supplementing Data with External Inputs

When internal data falls short, high-performing teams don’t stop – they fill the gaps.

This can include:

• Working directly with suppliers to gather missing data
• Reviewing contracts and invoices
• Using market benchmarks and external insights

4. Establishing Clear Data Ownership and Governance

One of the most common issues in procurement data is inconsistency over time.

Leading teams address this by:

• Assigning ownership of the category structure
• Defining clear categorisation rules
• Regularly reviewing and updating data frameworks

Consistency is far more important than complexity.

How AI Is Changing Spend Analysis, And Its Limitations

AI and automation are increasingly being used to improve spend analysis and data quality.

Key use cases include:

• Automated categorisation of spend data
• Data enrichment (e.g. ESG ratings, supplier insights)
• Integration of multiple data sources into a single view

These capabilities can significantly:

• Reduce manual effort
• Improve speed of analysis
• Enable deeper insights

However, there are important limitations:

• AI is only as good as the data it is trained on
• Inconsistent categorisation leads to unreliable outputs
• External data sources may be outdated or incomplete

In other words:

AI enhances good data but doesn’t fix bad data on its own

Moving Forward: Progress Over Perfection

The most important takeaway is this:

You don’t need perfect data to deliver value.

Procurement teams that succeed are those that:

• Accept data limitations
• Focus on high-impact areas
• Apply structured, consistent approaches
• Continuously improve over time

By doing this, they shift from reactive procurement to proactive, strategy-led decision-making, reducing maverick spend and improving overall performance, even in imperfect conditions.

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Watch the Full Webinar

If you’re dealing with limited visibility across your spend data, the full session explores these challenges in more depth, including real examples and practical approaches you can apply immediately.

In the webinar, we cover:

• Real-world examples of poor data impacting savings
• Step-by-step approaches to improving data visibility
• How to build category strategies despite data gaps
• Where AI delivers value, and where it doesn’t

Watch the full webinar here