From backlog to flow: Global operations transformation

The life sciences industry is experiencing unprecedented operational pressure. Demand volatility, portfolio proliferation, regulatory complexity, and global supply disruptions have exposed structural weaknesses across manufacturing, quality, and supply chain processes.

Many organizations face a paradox: high inventory levels but low service reliability, driven by fragmented information flows, manual processes, and limited end-to-end visibility. At the same time, growth in key product families exposes these structural weaknesses, requiring a step change in operational stability, planning accuracy, and capacity utilization.

Against this backdrop, leading companies are shifting from siloed, reactive operations to integrated, flow‑driven, digitally enabled value streams. This case study illustrates how one global life sciences organization executed a comprehensive E2E transformation across three critical sites to unlock capacity, stabilize service, and build a scalable foundation for future growth.

Transforming operations at scale: Company, context, and strategic challenge

A global leader in life sciences was facing structural operational challenges that undermined service reliability, constrained capacity, and created persistent backlog across three of its most critical production and distribution sites.

Despite holding unusually high inventory levels, service performance remained unstable. Certain product families operated at low OTIF (On Time in Full) levels, and operational volatility was increasing.

At the same time, the company was preparing for significant demand growth, including forecasted volumes up to 2 times historical shipments, without the operational stability required to absorb this increase. Key symptoms included:

• High and persistent backlog.
• Fragmented, manual processes.
• Disconnected information flows.
• Long and variable lead times.
• High changeover variability.
• Low daily management maturity.
• Supplier OTIF variability and long lead times.

The organization needed an end‑to‑end transformation to stabilize service, unlock capacity, and build a scalable operational foundation for future growth.

The integrated operating model behind the transformation

The transformation mobilized more than 500 employees and was supported by extensive gemba observation, data analysis, and structured problem‑solving.

The program combined:

• Value Stream Analysis (VSA).
• SMED and Non-Added Value reduction.
• Pull Planning and supermarket design.
• QC flow redesign and LT reduction.
• Daily Management System (Tier 0–3).
• Process confirmation and governance routines.
• Supplier performance and risk management.
• Digital dashboards and KPI standardization.

Three major operations were included in sites A, B, and C.Each site had distinct constraints, but all shared a common pattern: fragmented processes, low stability, and limited visibility.

Identification of key flow blockers

A cross‑site diagnostic exposed a set of structural blockers across operations, quality, and planning. Although each site had its own constraints, the underlying patterns were consistent: fragmented flows, manual processes, and limited cross-functional synchronization.

Operations (downfilling, packaging, assembly)

Operational performance was heavily constrained by inefficiencies in changeovers, material flow, and work allocation. Nearly half of the changeover time was not value-adding, and operators were frequently pulled away from core tasks.

• ~50% of changeover time was non‑value‑added.
• Operators absorbed logistics, coordination, and administrative work.
• Multiple non‑standardized buffers and material stops disrupted flow.
• Planning was push‑based, with no capacity‑aligned sequencing.
• Real cycle times exceeded standards by 30–80%.

Overall, operations were running with high variability and low flow stability, limiting throughput and increasing exposure to backlog.

Quality Control (QC Labs)

QC emerged as a major contributor to the end-to-end lead time. The process was dominated by manual handling, excessive movement, and limited alignment between workload and available capacity.

• Total QC LT reached 21 days.
• QC testing represented ~50% of the total LT.
• On‑Time Release dropped to 63% in the last 6 months.
• High WIP and excessive sample movement across rooms.
• Paper‑based documentation and double transcription.
• Analysts pulled work individually, without demand‑capacity alignment.

The QC system lacked flow, visibility, and workload balance — creating delays that cascaded into planning, production, and service.

Supply chain and planning

Planning processes were unable to absorb the volatility and growth expected for the coming year. Forecasts were significantly higher than historical shipments, but the planning system lacked the mechanisms to translate demand into stable execution. This misalignment manifested in the following key issues:

• Forecast volumes projected at 2x historical shipments.
• Lack of mix adherence across production areas.
• No FIFO or supermarket logic between operations.
• Frequent re‑planning and limited KPI visibility.
• Supplier OTIF around 75%, with long lead times (exceeding 70 days).

The result was a planning environment that reacted to issues rather than preventing them, amplifying variability across the value stream.

Solutions implemented: End‑to‑end and cross‑functional

The transformation addressed these blockers through a coordinated set of operational, quality, planning, sourcing, and governance interventions. The goal was not isolated improvements, but a fully synchronized value stream.

Operations and efficiency

Operational stability was strengthened through standardization, flow redesign, and elimination of non‑value‑added work. This was achieved through the following initiatives:

• Standard Work for operators and supervisors.
• Integrated flow from downfilling to packaging and lastly to shipping.
• Removal of paper‑based steps and digitalization of critical information.
• Redesigned internal logistics with fixed replenishment cycles.
• Full SMED program in downfilling and assembly.

Figure 1 – SMED board

These changes reduced variability, freed operator capacity, and created the foundation for predictable flow.

Planning and flow

Planning was rebuilt around capacity, priority, and flow logic — replacing reactive scheduling with structured, forward‑looking control. This transformation was delivered through a set of targeted interventions:

• Capacity model based on hours and labor requirements.
• Sequencing aligned to promise date and true operational priority.
• Mix adherence KPI and hourly production control.
• 4‑week rolling planning horizon with clear governance.
• Supermarkets and FIFO between operations.

Figure 2 – Supermarket layout example

The result was a planning system capable of stabilizing execution and supporting growth.

Quality and lead time

QC improvements focused on reducing LT, eliminating manual waste, and aligning workload with available capacity. In practice, this translated into the implementation of:

• Redesign of sample and information flow.
• Digital documentation to eliminate double transcription.
• Clear role definition to maximize analyst testing time.
• Daily performance management for QC.
• Demand‑capacity alignment and workload leveling.

QC became a more predictable, flow‑driven process, reducing delays that previously constrained the entire value stream.

Sourcing and supplier management

Supplier variability was addressed through structured governance and improved data accuracy. Key improvements included:

• Taskforce for critical suppliers.
• Updated lead time and reliability data.
• Stocking agreements and dual sourcing.
• Supplier scorecards and structured governance.

This strengthened upstream reliability and reduced planning noise.

Daily management and governance

To ensure sustainability, the organization embedded new routines, KPIs, and leadership behaviors.

• Redesigned tier 0–3 meetings.
• Standardized KPIs and digital dashboards.
• Process confirmation routines.
• Reliability rooms for cross‑functional decision‑making.

Governance shifted from reactive firefighting to proactive, data‑driven performance management.

Tangible, sustainable results delivered at scale

The transformation delivered measurable, cross‑site improvements in backlog reduction, throughput, service performance, and operational productivity. While each site started from a different baseline, all three achieved significant and sustainable gains, demonstrating the effectiveness of an integrated, end‑to‑end approach.

Site A: Assembly operations

Site A experienced the most dramatic backlog recovery, driven by improved sequencing, capacity alignment, and strengthened daily management. The combination of flow stabilization and leadership routines created a step‑change in execution discipline. Key results achieved:

• ‑65% total backlog.
• ‑90% capacity‑related backlog.
• +25% labor efficiency.
• +10% assembly output.
• Daily management maturity: +65pp (MH) and +40pp (Assembly).

Overall, Site A shifted from reactive scheduling to predictable, capacity‑driven execution — unlocking capacity and restoring service stability.

Site B: Downfilling and supply chain

Site B saw a strong uplift in throughput and service performance, supported by SMED, flow redesign, and improved planning logic. The site also absorbed higher-order intake while reducing backorder exposure. Results obtained:

• ‑20% backorder (excluding bulk).
• +35% throughput.
• +2pp fill rate.
• +10% order intake growth.
• Stabilized changeovers and improved mix adherence.

These improvements positioned Site B to handle future volume growth with greater resilience and operational stability.

Site C: Packaging and distribution

Site C delivered significant productivity gains and backlog reduction through improved flow, staffing alignment, and strengthened daily management. The site also improved service performance despite persistent demand volatility. Key results:

• ‑20% backlog (excluding bulk).
• +20% throughput.
• +1.5pp fill rate.
• ‑25% backorder.
• +50% posting productivity.

Site C’s results highlight the impact of disciplined flow, clear roles, and consistent performance routines on both productivity and service.

Strategic impact

The transformation delivered:

• Capacity to absorb 100% demand growth in key portfolios.
• Stabilized service and reduced operational variability.
• Structural LT reduction across QC, downfilling, and logistics.
• 25–40% productivity improvement across operations.
• 30–50% WIP reduction.
• A strengthened culture of continuous improvement supported by standards, governance, and digital visibility.

The organization shifted from reactive, fragmented operations to a predictable, integrated, flow-driven system, with a direct impact on service reliability, operational costs, and growth readiness.

Sustainability and next steps

To ensure the transformation remains stable and continues to scale, the organization is now focused on embedding the new ways of working, strengthening capabilities, and expanding proven practices across the global network.

• Consolidation of standards and RACI, ensuring clarity of ownership and consistent execution across teams.
• Ongoing capability building in RCPS (Root Cause Problem Solving), flow, and DMS (Daily Management System), reinforcing problem‑solving discipline and daily performance routines.
• Expansion of supermarkets and pull planning, extending flow logic to additional product families and upstream processes.
• Further digitalization of KPIs and workflows, increasing visibility, reducing manual effort, and enabling faster decision‑making.
• Scaling of proven practices to additional global sites, leveraging the playbook developed during this transformation.
• Evolution toward integrated and predictive planning, strengthening scenario management and long‑term capacity alignment.

Conclusion: From fragmented to flow‑driven, and ready to scale

This transformation marks a decisive shift from fragmented, reactive operations to a fully integrated, flow‑driven value stream capable of delivering consistent performance at scale. By redesigning material and information flows, strengthening planning and quality processes, and embedding disciplined daily management, the organization unlocked capacity, stabilized service, and built a resilient operational backbone ready for future growth.

More importantly, the program proved that operational excellence is not a collection of isolated initiatives — it is a system. When planning, quality, sourcing, logistics, and operations are aligned, performance accelerates, variability collapses, and teams gain the clarity and confidence to execute at a higher level.

The result is a supply chain that doesn’t just cope with volatility — it absorbs it, adapts to it, and ultimately turns it into competitive advantage. This is the new standard for high‑complexity life sciences operations: predictable, digital, disciplined, and built for growth.

We respect our clients’ confidentiality agreements. While names have been changed or omitted, the results are real.