Escaping the cost trap: When efficiency programs stall in life sciences

Life sciences finance teams are actively managing cost. Yet, in our sample, relatively few believe those efforts are delivering the intended results. In Deloitte’s recent Finance Trends study¹—a global survey of 1,326 CFOs and senior finance leaders—the life sciences subset of 35 leaders shows that just 14% (5 of 35) met or exceeded their cost-management goals, even though most reported using multiple cost levers (figure 1).

Our hypothesis is that this gap exists because cost is often managed as a set of functional efficiency initiatives and stacked levers, rather than as an integrated enterprise system measured against cash, risk, and control outcomes. This is a directional interpretation grounded in survey patterns and practitioner experience (see Methodology).

The priority now isn’t adding new cost levers, but ensuring existing ones work together, especially as AI reshapes how work is designed and delivered across the enterprise. Many organizations adopted location strategy, outsourcing, cloud platforms, and automation in separate waves.² But without periodically redesigning the underlying process architecture and governance, these layers can compound complexity and dilute enterprise impact. Treating cost transformation as an enterprise design discipline helps leaders evaluate trade-offs up front, ensuring savings are real, durable, and aligned with business performance.

Moving from expense reduction to enterprise impact

Captive centers, outsourcing, and AI-enabled automation are commonly used among surveyed life sciences finance organizations (figure 1). These approaches can reflect a relatively mature cost infrastructure. Yet, reported satisfaction with cost outcomes is low (14%).

One explanation may lie in how success is defined and measured. Cost programs are often evaluated through function-level efficiency metrics—for example, whether headcount declined, cost per transaction fell, or automation increased within a particular department. Those metrics matter, but when they dominate, they can reward local optimization at the expense of enterprise outcomes.³

Sometimes, organizations meet short-term cost goals through disruptive actions—such as workforce reductions or one-time structural shifts—but without follow-on redesign, those gains are often unsustainable.

An “investment mentality” reframes cost decisions around enterprise impact. Leaders can ask:

• What is the net cash impact after implementation costs and working capital effects?
• What structural, operational, tax, or compliance risks does it introduce?
• Will the benefits endure over a multi‑year horizon?

When these broader considerations aren’t addressed up front, savings that look attractive in isolation can diminish over time through rework, workflow inefficiencies in other departments, or control and compliance friction.

Sector dynamics may further shape how cost discipline takes hold. In biopharma, strong margins and pipeline cycles can reduce sustained pressure for operating model redesign; cost initiatives may intensify around patent cliffs or periods of late-stage uncertainty and ease when revenue visibility improves.⁴  In medtech, margins are tighter and pricing pressure more constant, while product-line and regional structures often carry significant commercial accountability.⁵ These dynamics don’t determine outcomes, but they can influence when and how aggressively operating model changes are pursued.

Shifting the focus from layered evolution to integrated design

Survey responses from the life sciences subset and the broader data set suggest that organizations tend to deploy digital levers (such as AI and automation) separately from structural models (such as captive centers and outsourcing). This separation may reflect sequencing rather than intent: location-based models matured first, followed by cloud, automation, and AI as a more recent wave.⁶  Each wave can address a specific cost challenge. What many organizations operate today may be the accumulation of these waves rather than a deliberately integrated design.

Layering isn’t inherently a problem. However, when structural and digital changes are introduced at different times without reassessing the underlying process architecture, governance model, and enterprise objectives, complexity can compound. Redesigning the system periodically is necessary to ensure existing levers work well together.⁷ The risk is heightened now, as some organizations may be tempted to apply AI to processes and delivery models that haven’t been reviewed end to end.

Designing cost transformation as an enterprise system

With cost levers already widely embedded, further gains are less likely to come from adding tools and more likely to come from reassessing how existing elements work together. In our view, durable cost outcomes require alignment across four interdependent domains. These domains reinforce one another: a change in one affects the others, and sustained impact depends on evaluating them as a system.

• Process architecture: Simplify and harmonize finance processes and policies. Identify redundant or low-value activities, clarify ownership, and assess upstream and downstream dependencies.
• Structural model: Reevaluate how finance work is delivered across locations, governance, legal entities, and incentives. Structural decisions can affect compliance, transfer pricing, controls, and coordination across the business. As a result, operating expense reductions may be lower once tax, compliance, and transfer pricing effects are fully accounted for.
• Digital and data enablement: Align enterprise platforms and data architecture with redesigned processes and governance structures. When modernizing or retiring legacy systems, validate that reporting, control, and workflow dependencies remain intact.
• Workforce and governance: Redesign roles, spans of control, and capabilities to reflect the operating model. Delivering cost outcomes often requires cross-enterprise collaboration, risk assessment, and trade-off evaluation. Incentives should align to enterprise outcomes, not just functional targets.

Measuring what matters

Low satisfaction may reflect ambitious targets, macroeconomic volatility, shifting strategic priorities, or timing effects rather than execution gaps alone. But the use of multiple cost levers alongside low satisfaction also points to a potential issue of emphasis. Many cost programs are still evaluated primarily through functional metrics, such as headcount reduction, cost per transaction, and automation rates. While important, these measures can reinforce siloed optimization if they define success on their own.

Enterprise performance can be assessed more broadly: how efficiently capital is deployed, how reliably profit converts to cash, how quickly cash moves through the business, and how stable control and compliance environments remain as processes evolve. Looking across end‑to‑end value streams, rather than isolated cost actions, shifts accountability from expense reduction to the health of the financial system as a whole.

From cost programs to cost discipline

Given the level of adoption already in place, incremental impact is more likely to come from integrating existing levers through end-to-end design and governance than from adopting more tools. Aligning process architecture, structural design, digital enablement, and workforce capabilities around clearly defined enterprise outcomes can help shift cost from a periodic exercise to an ongoing discipline.

When approached this way, cost management becomes more than a pursuit of efficiency. It can improve cash conversion and benefit durability, support more predictable earnings, strengthen governance, and position life sciences finance leaders to navigate volatility and capture greater value from AI and other digital investments. In dynamic markets, cost discipline can become a driver of financial and organizational performance, not just a tool for reducing expenses.

¹ Steve Gallucci et al., “Finance Trends 2026: Navigating the expanded scope of finance,” Deloitte Insights, October 6, 2025.

²Anisha Jha, “Order-to-cash automation: Processes, benefits, and industry Insights,” HighRadius, March 30, 2026; Jahangir Aziz, Steven Palacio, and Armstrong Mbi, FDI: Shifting from outsourcing to securing supply chains, JPMorgan, March 6, 2026; JPMorgan, Outlook 2026: Promise and pressure, 2025; Chatterjee et al., AI changes the stack, not the relevance of vendors!, Avendus Spark Research, 2026; Deutsche Numis Research, Thin end of the wedge?, Deutsche Bank Group, March 11, 2026

³Aparajita Rathore and Graylin Reif, “Welcome to the center office,” Deloitte Insights, July 30, 2020.

⁴Angus Liu, “Large pharma companies reduced headcounts by more than 22K in 2025 as $300B patent cliff looms,” Fierce Pharma, March 23, 2026; Eli Lilly, “Lilly reports full Q4 2024 financial results and provides 2025 guidance,” press release, February 6, 2025; Chie Hoon Song and Jeung-Whan Han, “Patent cliff and strategic switch: Exploring strategic design possibilities in the pharmaceutical industry,” SpringerPlus 5, no. 1 (May 23, 2016): p. 692.

⁵Peter Ehrhardt and Michael Keller, “Prioritizing pricing excellence for sustainable growth in medtech and diagnostics,” Simon-Kucher, May 23, 2024.

⁶Jha, “Order-to-cash automation”; Aziz et al., FDI: Shifting from outsourcing to securing supply chains; JPMorgan, Outlook 2026: Promise and pressure; Chatterjee et al., AI changes the stack; Deutsche Numis Research, Thin end of the wedge?

⁷Ankush Bhadrish and Sonal Bhagia, “Achieving digital transformation in shared services organizations,” Deloitte Insights, September 15, 2021.