For decades, Life Sciences supply chains were designed around reliability and compliance. Stable markets, recurring prescriptions and strong margins enabled organizations to plan over long horizons. This model proved resilient. Today, it is showing its limits.

The environment has fundamentally changed: demand volatility, increasing regulatory complexity, fragmented industrial networks and rising ESG requirements. Life Sciences companies are no longer shielded from the instability reshaping global supply chains. This article explores the key planning challenges facing the industry, the limitations of current tools and the practical value of a more structured planning approach.

An increasingly unstable environment

Demand has become harder to forecast

Life Sciences markets long benefited from structural predictability. That is no longer the case. Product launches now generate difficult-to-anticipate demand peaks, especially for innovative therapies whose adoption curves remain uncertain. Epidemic cycles create sudden disruptions: the Covid-19 pandemic exposed the fragility of historical planning models when faced with major supply shocks. The rapid evolution of oncology and targeted therapies accelerates portfolio turnover and complicates demand planning.

The consequences are immediate: service levels deteriorate precisely where criticality is highest, while inventory levels rise due to insufficiently responsive trade-offs.

Urgent flows are weighing on margins

Urgency has become a recurring operating mode. Air freight usage has increased across several segments, driven by shorter lead times and supply tensions. Air transport costs on average four to six times more than ocean freight. Balancing high service levels with logistics cost control has become one of the central trade-offs for Supply Chain teams.

More complex and variable networks

Tariffs and geopolitical tensions have reignited discussions around industrial footprints. Several pharmaceutical groups are reassessing sourcing strategies to reduce exposure to geographic concentration risks. Production regionalization, driven by healthcare sovereignty concerns, is reshaping logistics networks: new CMOs, multi-site flows and market-specific supply configurations.
These transformations significantly increase network complexity, while planning tools have not evolved at the same pace.

Pressure on inventory and cash flow

Life Sciences companies invest heavily in R&D. These long cycles increase pressure on working capital requirements. The dilemma is structural: maintaining sufficient safety stock to guarantee service levels without immobilizing cash already tied up in clinical projections. This is not a question of intent. It is a matter of planning models and tools.

Sector-specific constraints remain decisive

Regulation and traceability

Regulatory requirements define the framework for every Supply Chain decision in Life Sciences. Any change in supplier, process or manufacturing site requires a documented qualification process, sometimes lasting six to eighteen months.
Upstream, teams maintain visibility over subcontractors, critical components and process changes through structured change-control procedures. Downstream, batch traceability, market allocation obligations and recall procedures require precise documentation all the way to the final distribution point.
When multiple industrial partners are involved, coordinating this traceability becomes a major operational challenge.

Shelf-life management and strategic inventory

Life Sciences products have limited shelf lives. Inventory destruction risks are real and costly. Effective planning integrates expiry constraints directly into allocation decisions: which batch, for which market and at what date.
In addition, some markets impose mandatory minimum stock levels equivalent to four to six months of coverage. These requirements are non-negotiable. They must be integrated into distribution plans and aligned with available industrial capacity.

Time-to-market and ESG challenges

Commercialization timelines directly impact the value of new therapies, especially when patent exclusivity windows are limited. Managing time-to-market requires close coordination between clinical, regulatory, industrial and Supply Chain teams – coordination that fragmented systems struggle to support.

ESG commitments now add another layer of complexity. Emission reduction targets include Scope 3 emissions, meaning the entire value chain, including suppliers. Integrating sustainability criteria into allocation decisions and partner qualification is no longer optional: it is now an operational parameter that planning models must be able to manage.

Why traditional tools are no longer sufficient for Life Sciences Supply Chain Planning

The question is not whether existing tools worked. In many cases, they worked well. The real question is whether they are still suited to today’s challenges.

Gartner data highlights the scale of the gap: Supply Chain costs represent on average 37.3% of the total cost of patient care, yet only 19% of Life Sciences organizations are redesigning capabilities to better anticipate demand, compared with 23% across all industries.
Even more revealing: fewer than 44% use technology to simulate the impact of different scenarios on business objectives. The transformation potential remains largely untapped.

Traditional ERPs and advanced spreadsheets now face four structural limitations in this context.

• Slow integration of new partners.
  Incorporating a new CMO or an acquired entity may require weeks of configuration, while industrial networks evolve within months.
• Limited simulation capabilities. Modeling the impact of a regulatory constraint or comparing multiple inventory strategies remains difficult. Decisions are often made without sufficient quantitative visibility.
• Rigid models unsuited to multi-horizon planning.
  Life Sciences planning requires simultaneous management of short-term horizons (batches, shelf-life alerts), mid-term horizons (S&OP) and long-term horizons (industrial capacity planning). Traditional systems struggle to connect these layers coherently.
• Insufficient cross-functional coordination.
  Supply Chain, Quality, Regulatory, Operations and Finance teams often work in separate systems. The lack of a shared framework creates delays, duplicate entries and disconnected decisions.

These limitations produce concrete consequences: late issue detection, urgent decision-making and an inability to build alternative plans in real time.

What Life Sciences companies expect from a planning platform

The shift is already underway. More and more organizations, particularly in the mid-market segment, are redesigning their application landscapes. The rise of fabless operating models, where manufacturing is outsourced to specialized CMOs, makes multi-party coordination even more critical.
These organizations need a platform capable of integrating new partners quickly, without multi-year IT programs.

Functional expectations are converging around five key requirements.

1. Rapid scenario planning. Simulate the impact of a supplier disruption, embargo or qualification delay within hours.
2. Multi-party coordination. Align Supply Chain, Finance, Quality and Regulatory teams around a shared framework without data fragmentation.
3. Progressive use-case integration. Start with a focused scope and expand progressively according to organizational maturity.
4. Supply and Finance alignment. Connect distribution plans with cash-flow projections, inventory destruction provisions and budget forecasts.
5. Flexible integration. Incorporate new sites, partners or logistics flows without redesigning the data model.

The OneHive approach: a practical response to Life Sciences challenges

Anaplan as a planning foundation

This is where Anaplan provides a relevant answer. The platform offers the flexibility required to model complex business rules, simulate scenarios quickly and progressively extend coverage to new use cases. It does not require lengthy deployment cycles to create value.

Several critical use cases can be supported in a Life Sciences environment:

• Multi-market S&OP, integrating regulatory constraints and country-specific stock obligations.
• Demand Planning to improve forecast accuracy and responsiveness.
• Distribution Planning to optimize allocations and reduce inventory destruction.
• What-if scenarios, to anticipate the impact of supply disruptions or logistics changes.
• R&D time-to-market management, coordinating clinical, regulatory and industrial milestones within a shared roadmap.
• CMO collaboration, through modules enabling secure sharing of inventory and forecast data.
• Green S&OP and ESG reporting, integrating sustainability criteria into allocation and partner selection decisions.

The platform’s agentic AI capabilities reinforce these use cases through anomaly detection in plans, prioritization of critical alerts and recommendation engines based on historical data. Diagnostics accelerate and team response times decrease.

The OneHive value proposition

Deploying Anaplan in a Life Sciences environment requires far more than technical expertise. It demands a deep understanding of business processes, regulatory constraints and sector-specific decision-making dynamics.

This is precisely what OneHive brings. As a premium consulting and integration firm and strategic Anaplan partner, OneHive brings together more than 50 consultants from leading engineering schools, combining technical expertise with deep business knowledge, including in the Life Sciences sector.

Our approach is built around three concrete commitments.

1. Fast results. Our MVP (Minimum Viable Product) methodology delivers a first operational version within three to six months, then progressively enriches the platform through iterative deployments. Investments are secured from the very first weeks.
2. Guaranteed adoption. We involve key users from the design phase and support teams until they achieve full autonomy. Our projects consistently achieve adoption rates above 95%.
3. International coverage. Through our strategic alliance with Argon & Co, present across all continents, we support multi-country deployments with the same level of quality and rigor.

On highly specific challenges such as S&OP, CMO management, distribution planning, production planning or ESG reporting, our combined business and technical expertise makes the difference between a deployed tool and a tool that is truly adopted.

Conclusion

Life Sciences Supply Chains are entering a new phase. Compliance remains necessary. It is no longer sufficient.
The organizations that will succeed are those capable of implementing integrated planning: shared data, real-time scenario simulation and coordinated decision-making across functions.

At OneHive, we support these transformations with rigor and method. Because the performance of a Life Sciences Supply Chain is not declared, it is built, use case by use case, with the right teams and the right tools.

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