The playbook that built private equity returns over the past decade is losing its edge. Multiple expansion has compressed. Leverage is more expensive and harder to access. Market timing is less reliable. What remains, and what now accounts for a growing share of fund-level returns, is operational value creation: margin expansion, cash discipline, and the capabilities to sustain both.
Operating partners often feel this pressure most directly. Many own the performance trajectory of assets from day one. And they know that episodic cost cutting—a round of procurement savings here, a hiring freeze there—does not produce the kind of durable, defensible margin improvement that holds up at exit.
Zero-based transformation offers a different model. In a PE context, ZBT is not an annual budgeting exercise. It is a ground-up reset of the cost base and operating model, where every dollar, role, and activity must justify its existence against the value creation thesis. The goal is not to shrink the business but to redirect capital toward what drives value and strip away what does not.
When done well, ZBT strengthens EBITDA, improves cash conversion, and frees up resources for reinvestment in growth. Those combined effects move valuation, not through accounting tricks but through a more credible and better-structured operating story.
Recent advances in analytics and automation, powered by AI, have made this approach executable within PE timelines. Advanced analytics classify millions of transactions in days. Workforce diagnostics can break down roles into discrete activities and flag where effort is misallocated. GenAI tools accelerate knowledge work, and digital agents absorb repetitive operational tasks. The result: operating partners can rethink how work gets done across the enterprise—cutting steps, simplifying workflows, and compressing decision cycles—without waiting for a 12-month transformation program to deliver impact.
Why Episodic Cost Cutting No Longer Works
Most cost programs follow a predictable pattern: a top-down mandate sets a savings target, procurement renegotiates a few contracts, headcount comes down in select areas, and the initiative is declared complete. Margins tick up for a quarter or two. Then costs drift back.
The problem is not effort, but design. Traditional programs optimize within existing structures. They negotiate price but never question demand. They reduce headcount but never redesign the work. And because they lack embedded governance, they depend on management attention that inevitably shifts to the next priority.
ZBT breaks that pattern by resetting the conversation entirely. This shift is visible in three reinforcing dimensions:
- Horizontal Cost Visibility. Rather than reviewing spend function by function, ZBT creates enterprise-wide transparency. Duplication, demand inflation, and structural inefficiency become visible across the full organization, not just within silos.
- Necessity Over Price. The question shifts from “How do we get this cheaper?” to “Should this activity exist at all, and at what scale?” That reframing consistently unlocks larger opportunities than negotiation alone.
- Locked-in Accountability. Savings are written into budgets, reinforced by new processes, and governed by mechanisms that prevent cost creep once leadership attention moves elsewhere.
This is the distinction that matters: ZBT does not trim costs within the current model. It rebuilds the cost structure from first principles.
Resetting the Cost Base and Reallocating Capital—Fast
Operating partners work within a compressed credibility window. The first 100 to 180 days of ownership set the tone for the hold period—with the board, lenders, and management. A ZBT diagnostic can deliver transaction-level visibility across both people and non-people spending within that timeframe, creating a foundation for immediate action while deeper operating model redesign runs in parallel.
Consider a PE-backed industrial manufacturer facing volume declines and rising fixed costs. Leadership deployed a zero-based program across roughly €300 million in spending. Instead of applying across-the-board cuts, the team built a bottom-up view of every activity, role, and cost line tied directly to the value creation thesis. They challenged demand at its source, eliminated work that no longer served a strategic purpose, and redesigned workflows across functions.
Within months, the team had a clear line of sight into organizational structure and SG&A composition. The program delivered reductions of approximately 15% in both people and non-people costs, with category ownership and tracking mechanisms embedded to sustain gains.
Another example: a European discount retailer operating across multiple countries applied a zero-based approach to bring transparency and discipline to a complex cost base. Leadership established a bottom-up view of approximately $1.5 billion in spend, analyzing 27 million transactions and organizing them into a detailed cost taxonomy across more than 100 subcategories. They used cross-functional workshops to identify and validate savings opportunities.
The program identified more than $110 million in savings opportunities, with more than 70 initiatives defined. Implementation plans and governance were established to track delivery and maintain impact.
These examples illustrate a deeper point: ZBT focuses on capital reallocation, not cost removal. Every spending line falls into one of three categories—value creating, value protecting, or value consuming—and the discipline lies in aligning resources to the first two while eliminating the third. Companies use the freed-up capital to fund commercial acceleration, pricing capability, technology enablement, or integration.
This same approach applies to structural complexity. A PE-backed global beauty company used a zero-based reset to untangle overlapping structures, unclear P&L ownership, and redundant activities spanning multiple functions. Through functional and regional redesign, centralized procurement, and granular cost diagnostics, the team identified more than $100 million in savings within the first year. Equally important, the program streamlined organizational layers, reduced fragmentation, and clarified governance.
Because the logic is consistent, the approach scales across deal types: buyouts, growth equity, carve-outs, and multiasset platforms. The question for operating partners shifts from “How deep can we cut?” to “Where should capital sit to maximize value over the hold period?”
AI Makes It Work at PE Speed
For ZBT to deliver at the pace PE demands, it must function as a system, not a project. That means integrating transparency, workforce redesign, process automation, operating model changes, and financial tracking into a single, coordinated effort.
AI-enabled advanced analytics and automation are what make this feasible within a compressed timeline. These technologies do not change the core principles of ZBT. Instead, they accelerate them by bringing speed to diagnostics, deepening insight into how work is performed, and allowing organizations to redesign processes and roles with far greater precision.
Radical Cost Transparency. Every ZBT starts with a clean baseline. That means bottom-up visibility into both people and non-people spend at the level of individual roles, activities, and transactions. This single source of truth is what allows operating partners to size the opportunity, set credible targets, and measure progress—with management, the board, and lenders all working from the same fact base.
At one global beauty and personal-care company, a ZBT program created visibility across 45 million transactions, identified approximately $400 million in recurring annual run-rate savings, and self-funded in year one. More than 250 people were engaged and upskilled to sustain the approach across eight major cost categories.
AI-powered classification tools have compressed the timeline for this step dramatically. Large cost bases that once required months to normalize can now be mapped in days, enabling faster alignment around the size and shape of the opportunity.
Workforce Productivity Diagnostics. Traditional cost programs target headcount without examining how work actually gets done. That approach is blunt and often counterproductive; it removes people without removing the work, which just redistributes the burden.
AI-enabled diagnostics allow for a better approach: breaking down roles into discrete activities, quantifying how time is spent, and classifying each task as value adding, automatable, or redundant. Across knowledge-intensive functions, this analysis consistently reveals significant productivity headroom without compromising critical capabilities. Instead of blanket cuts, leadership redesigns roles around the work that matters and shifts repetitive tasks to automation or AI agents.
A large utility applied an AI-enabled workforce diagnostic across thousands of overhead activities. Leadership used the findings to restructure roles around higher-value work, embed automation, and put governance in place to sustain the gains. The result was lasting efficiency improvement without any hollowing out of institutional knowledge.
Bionic Use Cases: Automation, Augmentation, and Agents. The opportunities to apply AI extend to execution. Routine reporting, reconciliation, documentation, and coordination tasks can be automated. GenAI can accelerate drafting, analysis, and internal communications. Agent-based systems can manage structured workflows and repetitive decision rules. These “bionic” interventions reshape the cost base by reducing the effort required per task.
At the enterprise level, this allows leadership to reset SG&A, redesign shared services, and compress management span. At the individual level, it means people spend more time on judgment-intensive work and less on administrative overhead.
Operating Model Redesign. Transparency and workforce diagnostics are only valuable if they lead to structural change. The strongest implementations use ZBT findings to redesign the operating model: clarifying roles, right-sizing spans and layers, resetting demand between functions, and eliminating legacy activities that no one has had the mandate to challenge. These are deliberate choices about how the organization should support its strategy, not blanket reductions. And because they reshape daily operations, they must be anchored in clear governance, decision rights, and accountability.
Disciplined Tracking of EBITDA and Cash. The final component is financial discipline. ZBT integrates earnings and cash metrics into a single tracking framework. On the EBITDA side, this covers organizational redesign and SG&A optimization. On the cash side, it extends to working-capital improvement, vendor term alignment, procurement efficiency, and capex prioritization.
These financial metrics are tracked alongside leading operational indicators—span ratios, service-level adherence, and process cycle times—to confirm that new ways of working are holding. Operating partners can see not only where savings were booked but whether the underlying work has actually changed.
What Is Needed for ZBT to Work in PE
ZBT is broadly applicable, but making it work in a PE context requires a specific ownership mindset. Five conditions separate the programs that deliver from the ones that stall:
- Sponsor–Management Alignment from Day One. CEO and CFO sponsorship is necessary but insufficient. The operating partner and investment team must be aligned on objectives, savings targets, and reinvestment priorities, and those must be embedded in the value creation plan and reflected in board discussions from the outset.
- Accountability Within the 100-Day Cadence. Senior executives must own major cost categories and show measurable progress within the first two quarters. Multiyear timelines are not credible in a PE context.
- Savings Locked In Before Reinvestment Begins. Capital reallocation only works if the savings are real and durable. Embedding agreed-upon reductions into board-approved budgets before authorizing new spending enforces discipline and minimizes leakage.
- Governance That Survives Diligence. Every initiative must be tracked alongside operational KPIs and financial performance, with clear escalation paths. Gains need to be defensible under buyer scrutiny and credible to lenders.
- Willingness to Confront Legacy Structures Early. Duplication, unclear decision rights, and entrenched spending patterns do not resolve themselves. PE ownership creates the mandate to challenge them, but only if sponsors use that mandate in the first months, not the final ones.
From Single-Asset Wins to Portfolio-Wide Advantage
The most disciplined PE firms are no longer treating ZBT as a one-off initiative. They are embedding it into the operating playbook: running zero-based diagnostics during diligence, activating cost and capital resets within the first 100 days, and reinforcing discipline through ongoing portfolio governance.
Some sponsors deploy rapid transparency diagnostics across the entire portfolio to establish a consistent baseline and surface value potential, then concentrate deeper transformations on priority assets. This two-speed model—breadth for visibility, depth for impact—allows operating partners to move quickly without spreading resources too thin.
Over time, the benefits compound. Diagnostic cycles shorten. Benchmarks sharpen. Lessons from one portfolio company inform the approach at the next. The capability becomes institutional, not episodic.
This matters most at exit. Buyers and lenders increasingly scrutinize whether margin improvements are structural or temporary. A zero-based cost structure, with redesigned operations, embedded automation, and measurable KPIs, reduces skepticism during diligence. The improvements are demonstrable and durable, not dependent on temporary controls.
Looking Ahead: The AI-Native Operating Model
When ZBT is executed as an integrated system, with AI embedded throughout, its cumulative effect points toward something more fundamental: a reimagining of how companies are built and run. The endpoint of a well-run ZBT program is not a leaner version of the old operating model. It is an AI-native one.
In an AI-native operating model, the work most amenable to standardization—such as data processing, reporting, compliance checks, and routine approvals—is fully automated. What remains for humans is not a diminished role but an elevated one: orchestrating processes rather than executing steps within them. Managers and specialists move to a supervisory posture, working across dashboards that surface exceptions, flag anomalies, and enable real-time course correction. They oversee the flow of work rather than stand inside it. This shift from participant to process supervisor represents a step change in organizational productivity.
Realizing that potential, however, depends on a prerequisite that is often underestimated: well-defined, consistently applied processes shared across the organization. Without that foundation, AI-native workflows cannot operate at scale.
For PE-backed companies, this also changes the exit story: a business designed around AI-led workflows is not just leaner; it is structurally more scalable, with a cost base that does not grow linearly with volume and a management layer focused on judgment rather than administration.
To drive differential returns, operating partners need approaches that deliver fast, measurable, and defensible value creation. AI-enabled ZBT—deployed as a repeatable system, not a one-time project—is proving to be one of the most effective. Sponsors who institutionalize this discipline are building structural advantage: not just within individual assets but across funds and market cycles.
