Cost excellence has become a strategic imperative in pharma and a new dimension is emerging. This article outlines how leading pharma organizations are unlocking sustainable savings across direct and indirect categories, and why AI developments on the supplier side are opening an additional layer of opportunity that procurement cannot afford to ignore.
- 4–12% savings in direct spend and 7–13% in indirect are achievable by combining commercial, technical, and demand levers – through structural efficiency, not one-off cuts (based on Inverto’s benchmarking across pharma engagements)
- Indirect spend, roughly two-thirds of total external spend, holds the largest untapped savings potential in pharma, despite receiving the least strategic attention
- AI is structurally lowering supplier cost bases – in CDMOs and API producers through yield and process automation, and in service providers through GenAI
Procurement in pharma is entering a new phase. With mounting cost pressures, complex supply networks, and rising expectations from Finance and R&D, the function is moving from a tactical cost center to a strategic value driver. At Inverto, we see leading pharma organizations embracing a new definition of efficiency – one that combines cost excellence, structural agility, and commercial discipline.
From Cost Pressure to Cost Excellence
Cost optimization remains a top priority in pharma, but the easy gains are long gone. Leaders are shifting from short-term cost reductions to a long-term model of cost excellence, governance, and resilience. The most significant results are emerging from both direct and indirect categories, where structured cost levers deliver measurable, lasting impact.
Pharma External Spend Landscape
Approximate allocation of total external spend in a typical pharma company: Indirect categories account for roughly two-thirds of total external spend, but still hold the highest untapped optimization potential.
External spend breakdown for biopharma companies
Company with heavier branded portfolio - illustrative+++ High cost pressure
++ Moderate cost pressure
| SPEND | CATEGORY | GROUP | PRESSURE | KEY COST DRIVERS | |
|---|---|---|---|---|---|
|
DIRECT |
15% | Raw materials |
Product related
32%
|
+++ | Geopolitical supply shocks Material shortages Currency-driven price swings Regulatory compliance costs |
| 11% | Finished goods | ||||
| 6% | Packaging | ||||
|
INDIRECT |
19% | Marketing |
Growth drivers
34%
|
++ | Regulation in advertising campaigns AI transformation in marketing & R&D Clinical-trial setup costs Inflation in lab supply & consumables |
| 15% | R&D | ||||
| 16% | MRO, FM & Capex |
Assets & logistics
21%
|
++ | Cold-chain transport & warehouse storage Depreciation of GMP equipment Energy & facility management costs | |
| 5% | Logistics | ||||
| 4% | HR |
G&A transversal
13%
|
+ | Increase in labor costs & daily rates across all geographies AI changing professional services delivery | |
| 4% | Prof. services | ||||
| 3% | Digital |
What makes this moment different is a shift most procurement teams haven’t yet fully acted on: AI is changing cost structures on the supplier side. Suppliers across categories are integrating AI into delivery and production, structurally reducing their own costs. Procurement that doesn’t engage with this is leaving savings on the table that already exist – just not yet claimed.
Cost excellence in pharma isn’t built from isolated initiatives. It comes from systematically managing spend across three dimensions: commercial, technical, and demand. Commercial levers create market tension through competitive benchmarking, structured sourcing events, and disciplined contract management. Technical levers optimize specifications and open the door to supplier competition. Demand levers eliminate hidden inefficiencies by right-sizing what the business actually needs. Companies that combine these three lenses achieve 4–12% savings in direct categories and 7–13% in indirect – not through short-term cuts, but through structural efficiency and smarter decision-making. Every lever here needs a partner outside procurement to land safely: Quality and Regulatory sign off before a specification changes; Finance owns the savings once they’re booked; Manufacturing validates that a supplier switch doesn’t disrupt continuity. The levers below show where procurement can create the case – not where it can act alone. Raw materials, finished goods, packaging Where to focus: High-cost, high-complexity categories – APIs, packaging components, specialized manufacturing – where small technical changes or sourcing shifts can deliver substantial savings. These categories are typically managed for supply continuity, not competitiveness. That default creates headroom structured procurement can unlock. How: Index-based pricing to manage commodity exposure on raw materials and APIs; structured e-auctions to reintroduce competitive tension in categories that have drifted into single-supplier relationships. Design-to-cost to challenge specifications set by R&D without cost input – identifying where material grades, tolerances, or packaging standards can flex without compromising quality or compliance (any change here goes through Quality and Regulatory before it’s counted as a saving). Demand alignment through S&OP integration, ensuring order volumes, batch sizes, and material specs reflect actual consumption rather than legacy assumptions. AI as an accelerator: AI-supported should-cost modelling builds a granular, bottom-up view of supplier inputs – enabling a fact-based challenge of supplier pricing rather than relying on market benchmarks alone. Predictive analytics and AI-driven market intelligence help anticipate price movements on key inputs and API supply risk, so procurement can time sourcing decisions rather than react to them. Why it works: Direct categories are often managed for continuity, not competitiveness. Structured transparency and technical alignment create savings that endure beyond a single RFP cycle. Marketing, IT, logistics, HR & professional services, R&D support Where to focus: Categories with fragmented ownership and legacy contracts, where spend is dispersed and visibility is low. How: Volume bundling across sites and business units, and competitive RFPs to reintroduce market tension. Spend transparency and process standardization – mapping fragmented indirect spend across business units to identify duplication, standardize specifications, and build the data foundation for credible competitive sourcing. Zero-based budgeting and service-level differentiation to right-size internal demand without undermining operations – a conversation Finance and the business owners need to be part of, not just procurement. The AI supply-side opportunity: Renegotiate contracts to reflect AI-driven productivity improvements on the supplier side – re-specifying scope, introducing AI-productivity benchmarks into SLAs, and scouting AI-native providers as competitive leverage. AI-driven spend classification and contract intelligence can also map fragmented indirect spend to categories, flag maverick buying, and surface contracts due for renegotiation or consolidation. Why it works: Indirect categories hide the largest untapped potential. Structure and governance deliver savings quickly – but the lasting benefit is improved transparency, fewer suppliers, and stronger internal alignment.
The Levers of Cost Excellence
Direct Spend Optimization: Unlocking Competitiveness in High-Stakes Categories
Indirect Spend Optimization: The Largest Untapped Opportunity
Case Examples
Indirect spend continues to offer the broadest opportunity for quick and lasting savings. Two examples show how pharma and medtech companies have turned procurement into a value engine.
An international biopharma company needed to build a global procurement organization, deliver a savings target to fund the scale-up of its oncology division, and de-risk its API supply base across multiple geographic hubs.
We ran a full supply risk assessment – scored by supplier, location, and API and built a mitigation strategy with clear countermeasures.
A 10-month savings pipeline followed: API contract renegotiations, geographic diversification, CDMO switching evaluation, and indirect category optimization, alongside a target operating model designed to sustain savings beyond the engagement.
Result: more than 10% savings across the addressable spend base within 10 months, alongside a more resilient, de-risked API supply network.
A global MedTech company had historically focused procurement efforts on agency fees alone, leaving media placement costs, more than 85% of total media spend in this account, entirely unaddressed. With a single global agency in place and a major product launch expected to increase the budget further, the opportunity was clear.
We benchmarked the agency’s AI-driven efficiency gains in content production and media placement, and used them directly as a commercial lever.
Strategic partnership meetings with the agency, backed by a prepared RFP as credible alternative, met the savings target without triggering a tender. Contractual safeguards protected the outcome: an at-risk bonus tied to savings and service quality, and a budget variation index against in-year shifts.
Result: $28 million in savings, more than 10% of the total media budget, delivered over two years, with the agency relationship strengthened, not strained.
What’s Different Now: AI on the Supplier Side
Digital tools – spend analytics, e-sourcing, contract management -have been part of procurement’s toolkit for years. What’s genuinely new is the speed at which AI is changing supplier cost structures in service-heavy indirect categories.
Marketing agencies are deploying GenAI for content at scale. IT providers are automating delivery workflows. R&D service firms are cutting project headcount as AI accelerates documentation and analysis. These are structural changes to supplier economics, not temporary productivity gains and they’re already showing up in supplier P&Ls.
The dynamic holds in direct categories too, just less visibly. Contract manufacturers and API producers are deploying AI for process optimization, yield improvement, and automated quality control – reducing cost per batch structurally. Unlike indirect categories, where the gain shows up as reduced headcount or faster delivery, direct-side AI gains are embedded in production economics and harder to see from outside. That makes proactive engagement more important, not less: procurement teams that build AI-cost transparency into supplier relationships – through should-cost models reflecting AI-driven yield improvements – negotiate on what production actually costs today, not what it cost three years ago.
The implication is straightforward: contracts negotiated two or three years ago were priced on a cost base that no longer exists. Procurement teams that engage – benchmarking supplier AI adoption, re-specifying scope, renegotiating on reduced effort – capture savings that didn’t exist at the last contract cycle. Teams that don’t risk paying today’s price for yesterday’s cost base.
This isn’t only a procurement conversation. Finance needs visibility into how renegotiation affects margin and cash-flow assumptions. Manufacturing and Quality need to validate that AI-driven process changes haven’t altered output specs before procurement uses them as negotiating leverage. Treated as a system-level question, this is a partnership conversation with suppliers, not a pressure campaign against them.
Internally, AI is also accelerating execution – faster RFP cycles, automated should-cost modelling, predictive spend analysis. These tools amplify good procurement practice. They don’t replace category strategy, supplier relationships, or structured governance.
Looking Ahead: From Efficiency to Sustained Value
The foundations for cost excellence in pharma procurement are well understood. The organizations pulling ahead apply them with greater precision, broader category coverage, and stronger governance – while capturing the new opportunities AI developments on the supplier side are opening up.
Sustainable value creation requires both: the structural discipline of commercial, technical, and demand levers applied consistently across direct and indirect categories, and the commercial agility to recognize when supplier economics have shifted and renegotiate accordingly.
Organizations that move first negotiate from a position of information advantage – before AI efficiency gains are absorbed into supplier standard pricing. As adoption matures, the opportunity doesn’t disappear, but it shifts: from capturing existing gains to anticipating the next wave of AI-driven cost reduction before it reaches the market.
For pharma procurement leaders, the priority is clear: build the cost excellence foundations where they’re missing, apply them where they exist but aren’t fully exploited, and ensure AI developments on the supplier side are reflected in the next round of contract negotiations.
Interested in how your organization can strengthen procurement’s role in achieving cost excellence?
Contact our experts in pharmaceuticals
Stefan Oprée
Managing Director
Cindy Oswald
Principal
Further Pharma Insights
