Procurement leaders face rising demands amid data gaps

ProcureAbility has published its 2026 Chief Procurement Officer benchmark study, which found that procurement leaders face rising expectations despite constraints in staffing, data and technology.

The study drew on responses from 160 senior procurement leaders at large enterprises with annual spend ranging from USD $50 million to more than USD $10 billion. Respondents represented 21 industries and organisations with global operations.

The central finding is a widening gap between what procurement teams are expected to deliver and what they can realistically execute. While 61% of respondents said savings expectations had increased from the previous year, 71% described their teams as moderately or highly capacity-constrained.

That tension appears most acute when procurement is brought into decisions late. Some 43% of respondents said late procurement engagement was the biggest barrier to achieving savings, suggesting teams are often involved only after major decisions on costs, suppliers and specifications have already been made.

"Procurement delivers the greatest impact when it is engaged as a strategic partner from the start," said Conrad Snover, Chief Executive Officer, ProcureAbility.

"Once plans are locked in, many opportunities for value creation have been lost, and even the strongest sourcing cannot recover them."

Risk pressures

The report also points to a shift in how procurement teams assess risk. Geopolitical disruption was cited by 62% of respondents and logistics disruption by 55%, indicating that attention has shifted towards maintaining supply continuity rather than focusing primarily on supplier financial health.

Despite that shift, few teams appear to have advanced monitoring tools in place. Only 6% said they had predictive or real-time monitoring tools, while 62% still relied on manual or periodic methods.

That leaves many functions trying to manage faster-moving external risks with limited visibility. The gap matters as supply chains continue to face disruption from political tensions, transport bottlenecks and changing trade conditions.

"Procurement teams need to invest in driving predictive capabilities to better anticipate and manage an increasingly volatile risk environment," said Snover.

Staffing strain

Capacity pressures run through several parts of the study. More than four in ten respondents, or 42%, said they were dealing with both higher expectations and constrained team capacity at the same time.

Yet relatively few are adding headcount. Only 19% said they were bringing in additional team members, while 46% were investing in upskilling existing staff.

That suggests many organisations see workforce development as a more realistic response than expansion, particularly as finance leaders continue to seek savings and efficiency from support functions. It also indicates that procurement departments may be under pressure to broaden their role without a matching increase in resources.

Automation is another route some teams are pursuing. Around 31% of respondents said they were using automation to reduce workload, but many are finding it difficult to expand the use of artificial intelligence because of weak underlying data.

Data problems

Data quality emerged as a recurring issue across procurement operations. Half of respondents said poor data quality was the main barrier to scaling AI, 51% called it the biggest gap in analytics, and 44% said it was the main challenge in supplier management.

The consistency of those responses points to a basic operational problem rather than a narrow technology issue. If procurement teams cannot rely on core information, analysis, supplier oversight and automation efforts all become harder to scale.

That may help explain why AI deployment remains limited in many procurement functions despite growing corporate interest in automation. Only 11% of respondents said they had scaled AI across multiple procurement processes.

The findings suggest that one area of improvement could affect several performance issues at once. Better data governance, clearer ownership and more consistent standards could improve analytics, support supplier management and make wider AI use more practical.

"Procurement organizations have access to more data than ever, yet many still struggle to turn it into reliable insights for decision-making," said Darshan Deshmukh, President, ProcureAbility. "The answer starts with strong master data governance, including clear ownership, consistent standards, and accountability for data quality across the enterprise. With that foundation in place, procurement leaders can trust their data and use it to make faster, more informed decisions."