A private equity sponsor needed to test whether a fast-growing pharmaceutical returns business could scale as projected
How Leverage pressure-tested operations and automation economics in two weeks, validating the proposed approach while revealing the execution risks behind the growth plan.
2 Weeks
Pre-exclusivity diligence completed
>38%
Modeled automation IRR
~44%
Forecast volume covered by phase-one automation
Client
Private Equity Sponsor
Sector
Healthcare / pharmaceutical reverse logistics
Location
United States
Scope
Pre-exclusivity operational and automation diligence
Services
Financial / M&A; Supply Chain Optimization; Technology & Automation
A growth story approaching operational limits.
A private equity sponsor was evaluating a pharmaceutical returns and reverse logistics business serving manufacturers, wholesalers, and pharmacies across the U.S. The target had strong compliance practices and a growing customer base, but its existing operation was nearing labor and space capacity.
Automation was central to the investment thesis: it was expected to expand throughput and improve margins. Before exclusivity, the sponsor engaged Leverage for a rapid, independent assessment of whether the operation, automation design, and projected returns would hold up in practice.
What stood in the way, and what we were asked to deliver.
What stood in the way
-
Capacity nearing its limits
Processing and staging space was already under pressure as pharmaceutical returns volumes increased. -
Labor-intensive workflows
Only about 35% of labor activity was directly value-adding, with re-handling and peak congestion limiting productivity. -
Partial automation coverage
The initial automation phase was designed to handle only about 44% of forecast volume, requiring a hybrid operating model.. -
Execution-dependent economics
Projected productivity and returns depended on staffing, quality assurance, systems integration, and disciplined rollout.
What we were asked to deliver
-
Validate operating scalability
Determine whether the processing, labor, and staging model could support forecast growth while maintaining compliance. -
Assess automation readiness
Confirm that the proposed technology was suitable, correctly staged, and aligned with future volume requirements. -
Pressure-test investment economics
Evaluate the projected labor productivity, capital timing, and financial returns underlying the automation plan. -
Define execution risks
Identify the staffing, integration, and process changes required to protect throughput and returns after implementation.
Pressure-testing growth assumptions through operational diligence.
Leverage combined data-room analysis, onsite observation, and automation review to test the target’s growth assumptions against operating realities.
Throughput and labor model reconstruction
Rebuilt throughput and labor models from diligence materials, checking unit definitions and processing assumptions. Tested forecast productivity, cost, and margin improvements against operating data and benchmarks.
Onsite process and capacity assessment
Reviewed workflows from receiving through sortation, processing, and disposition to identify bottlenecks and re-handling. Assessed labor deployment, space constraints, and leadership readiness for higher volumes.
Automation design and ROI validation
Reviewed the proposed sorting system and compared phase-one capacity with projected volume growth. Modeled the dependencies between induction staffing, quality assurance, WMS integration, and the investment return profile.
Investment decision and execution guidance
Delivered operational diligence findings, automation economics, and a map of key implementation risks. Outlined operating-model priorities and mitigations the sponsor could use to evaluate the investment and future value creation.
Leverage turned an automation-led growth thesis into a decision-ready view of what could scale, what the economics supported, and which execution risks could affect the investment.
What the client got.
Automation approach validated with conditions
The proposed system was assessed as technically suitable for staged growth, while phase one would cover only about 44% of forecast volume. A hybrid operating model and disciplined implementation remained necessary.
Modeled investment returns quantified
The analysis indicated an automation IRR above 38% and payback in under three years, contingent on the modeled assumptions. Labor productivity was projected to increase from approximately 69,000 to 89,000 billed units per FTE.
Scalability risks made actionable
The assessment identified labor, staging, quality-control, and WMS integration constraints that could limit throughput or delay savings. These findings established priorities for execution and operating-model design.
Investment diligence completed rapidly
Within approximately two weeks, the sponsor received independent operational validation, a quantified automation assessment, and a risk-informed roadmap. The approach also provided a framework for evaluating future healthcare logistics opportunities.
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