Market volatility is not slowing down. How are manufacturers adapting?

Building resilient planning systems capable of responding in real time to demand fluctuations and supply disruptions

Introduction

Market volatility renders production plans obsolete within hours. Those responsible for planning find themselves recalculating scenarios continuously, often using tools designed for a context that no longer exists.

Disruptions do not originate solely from financial markets. Over the past few years they have accumulated: the 2021-2022 semiconductor crisis, the Suez Canal blockage, the logistical repercussions of the Ukraine conflict on energy and raw materials, and the destabilisation of Red Sea shipping lanes. Since late February 2026, the Strait of Hormuz crisis has added another layer of pressure, a direct consequence of the conflict involving the US, Israel, and Iran: according to UNCTAD, daily transits collapsed from approximately 130 to 6 vessels within a matter of weeks, affecting 20-30% of global oil and gas trade. For many manufacturing sectors dependent on energy, petrochemicals, fertilisers, and aluminium from the Gulf, available stocks cover only a few weeks. When demand swings by 40% month on month, as happened in automotive and consumer goods in recent years, and energy and logistics costs spike unpredictably, traditional systems and static forecasts simply cannot keep up.

What is needed is a platform that automatically recalculates scenarios and integrates real-time data to support decisions at the moment they matter. sedApta's adaptive planning solutions shift planning departments from reactive to proactive, enabling them to maintain service levels and optimise inventory investment even during the most turbulent periods.

Key takeaways

• Integrate collaborative sales forecasting with algorithmic models to improve forecast accuracy, especially in high-variability contexts
• Use multi-scenario planning to prepare contingency responses before disruptions materialise
• Measure the ROI of adaptive planning through OTIF improvements and safety stock reduction
• Build cross-functional alignment between commercial, operations, and supply chain teams through shared planning platforms
• Measure planning cycle frequency (monthly, weekly, daily)
• Map manual steps and approval bottlenecks
• Calculate the time between a demand signal and a production plan adjustment
• Connect ERP, MES, and demand planning systems
• Implement automated data validation and exception reporting
• Create a single source of truth for inventory, capacity, and demand
• Define 3-5 standard volatility scenarios with predefined responses
• Build finite capacity models that automatically flag feasibility limits
• Establish escalation protocols for plan changes that exceed defined thresholds
• Replace monthly planning meetings with weekly check-ins
• Create shared dashboards showing plan performance and variances
• Introduce daily stand-ups for critical resource allocation decisions
• Monitor plan stability metrics alongside traditional efficiency measures
• Track forecast accuracy across multiple time horizons
• Receive alerts on constraint violations before they affect customer commitments
• Develop planner skills in finite capacity optimisation
• Build cross-training programmes for critical planning roles
• Create standard operating procedures for the most common disruption scenarios
• Conduct weekly plan-versus-actual comparisons
• Track the correlation between working capital velocity and customer service levels
• Run quarterly planning process reviews with stakeholder feedback

Market volatility: the impact on industrial planning

Supply chain disruptions are not easing. The McKinsey Global Supply Chain Leader Survey 2024 found that nine out of ten supply chain executives faced significant challenges during 2024, with geopolitical tensions, tariff volatility, and demand fluctuations making traditional planning structurally inadequate. Two thirds of respondents are investing in Advanced Planning and Scheduling (APS) systems precisely because classical processes cannot withstand this level of instability. Yet only 10% have completed adoption.

The gap between having a planning system and having the right planning system is significant. McKinsey's research on integrated supply chain planning documents that companies adopting integrated planning approaches reduce inventories by 10-20% while simultaneously improving service levels and revenues by 3-4%. Those that continue using rigid, periodic processes achieve the opposite: excessive stock during stable periods and shortages at demand peaks, sometimes simultaneously across different product lines.

The automotive sector offers a concrete example. During the 2021-2022 semiconductor crisis, manufacturers with static planning systems took weeks to readjust production schedules, while those with adaptive planning capabilities responded in days. The difference was not abstract technology: it was the ability to recalculate scenarios on a continuous basis rather than waiting for the monthly cycle.

Food and beverage and pharma face analogous pressures, between seasonal demand, raw material price volatility, and shifts in consumer preferences. The Deloitte 2023 Consumer Products Industry Outlook found that 62% of CPG executives expected significant supply chain challenges, with more than half working to shorten supply chains to reduce exposure to demand variability. Companies with adaptive planning maintained higher OTIF levels during periods of greatest instability compared to those relying on traditional periodic systems.

The limits of traditional planning in volatile contexts

Traditional systems break down when demand volatility exceeds the narrow parameters they were designed for. These systems assume stable lead times, predictable demand patterns, and linear supply chain relationships: assumptions that hold less and less. When automotive demand collapsed in Q2 2020 and then rebounded in Q3, traditional systems generated thousands of exception alerts that paralysed planning teams and delayed critical decisions.

Gartner research confirms that forecast accuracy and demand variability are the two main obstacles to achieving supply chain objectives. According to Gartner's analysis on demand planning, modern AI and machine learning algorithms can integrate a variety of data sources to build far more accurate forecasting models, to be combined with the collaborative forecasting aspects of the sales force. But this is only possible when companies move beyond the approach based exclusively on historical data, which still characterises most traditional implementations.

Intelligent forecasting: beyond the traditional forecast

Those who manage planning in a manufacturing company know the problem well: traditional forecast models break down precisely when the market becomes unpredictable. Industry analysis (Kearney, 2023, cited by Kinaxis) shows that effective demand sensing implementation produces forecast accuracy improvements of between 5% and 20%, with safety stock reductions of 5% to 10%. For a manufacturer with hundreds of SKUs across multiple markets, these percentages translate directly into millions of euros of freed working capital.

sedApta's planning platform integrates multiple demand signals in real time, going beyond simple historical pattern recognition to capture market volatility as it emerges. The system processes point-of-sale data, customer order patterns, and external indicators to generate dynamic demand signals, updated continuously across the entire planning horizon.

One often underestimated aspect concerns collaborative forecasting with the sales force. Algorithmic models work better when fed by commercial forecasts: those who manage customer relationships have visibility into opportunities, cancellation risks, and volume changes that no algorithm can derive from historical data. sedApta allows these inputs to be systematically integrated into the S&OP process, combining statistical accuracy with direct market knowledge. The result is a forecast that accounts for both quantitative patterns and qualitative information circulating through the commercial network.

A major automotive supplier implemented sedApta's demand sensing capabilities during the semiconductor crisis. While competitors relied on monthly forecast updates, this manufacturer began adjusting production plans daily, taking into account supplier availability and customer priorities in real time. The result was a measurable reduction in stockouts and an improvement in service levels during the most volatile period the sector had seen in years.

Dynamic planning that responds to disruptions

The McKinsey Supply Chain Risk Pulse 2025 documents that 82% of companies are affected by new tariffs and market disruptions, with 39% reporting increased sourcing costs. In this context, the speed at which a planning department can recalculate and resequence production directly determines its ability to protect margins and service levels.

sedApta's planning engine recalculates production sequences in minutes, not hours or days. When demand patterns change or supply disruptions occur, the system immediately evaluates alternative scenarios across multiple simultaneous constraints: resource availability, changeover times, quality constraints, and delivery commitments.

A contract pharmaceutical manufacturer experienced this capability during the scale-up of Covid vaccine production. Traditional planning required hours of manual work each time priorities changed, which happened multiple times per week. sedApta's planning system drastically reduced these recalculation times, allowing the manufacturer to respond to urgent requests from health authorities without compromising existing commercial commitments.

Planning optimisation considers finite capacity constraints across multiple production stages, automatically identifying bottlenecks and suggesting capacity reallocation options. When market demand shifts towards higher-margin products, the system immediately recalculates sequences to maximise contribution while respecting technical constraints such as changeover times and quality hold periods.

Integrated visibility across planning horizons

Fragmented visibility creates blind spots that amplify during volatile periods. The McKinsey 2023 supply chain survey found that 76% of companies have APS systems, but a critical gap persists: 41% of APS users still report that their systems require too many manual interventions and are not synchronised with the shop floor and management systems (ERP). The difference between having a planning system and having an integrated planning environment lies precisely here: the ability to connect strategic horizons with operational execution without the friction of manual handoffs.

sedApta provides unified visibility from long-term strategic planning through to daily execution, ensuring that responses to volatility remain aligned across all horizons. The platform connects commercial forecasts, production capacity, supplier availability, and inventory positions in a single decision-making system.

This integrated approach proved decisive for a specialty chemicals manufacturer facing quarterly raw material price swings of over 40%. Previously, strategic planning, tactical planning, and operational execution worked from different datasets and assumptions, generating conflicting priorities and resource conflicts. sedApta's unified planning environment enabled simultaneous optimisation across all time horizons.

The manufacturer was able to evaluate long-term contractual commitments against short-term spot opportunities, verifying production feasibility and resource availability in real time. Working capital improved significantly while maintaining service levels above 96%, despite unprecedented raw material cost volatility. The key was connecting strategic market positioning with real-time operational execution capabilities, rather than relying on monthly planning cycles.

Building competitive advantage through adaptive planning

sedApta's approach transforms planning from a periodic exercise into a continuous capability. Production and supply chain managers report that plan adjustments that previously required weeks of coordination now happen in hours. This speed differential becomes decisive when market windows open and close rapidly.

Making the transition: concrete steps

Assess current planning maturity

• Measure planning cycle frequency (monthly, weekly, daily)
• Map manual steps and approval bottlenecks
• Calculate the time between a demand signal and a production plan adjustment

Build real-time data foundations

• Connect ERP, MES, and demand planning systems
• Implement automated data validation and exception reporting
• Create a single source of truth for inventory, capacity, and demand

Design scenario-based planning processes

• Define 3-5 standard volatility scenarios with predefined responses
• Build finite capacity models that automatically flag feasibility limits
• Establish escalation protocols for plan changes that exceed defined thresholds

Implement cross-functional planning rhythms

• Replace monthly planning meetings with weekly check-ins
• Create shared dashboards showing plan performance and variances
• Introduce daily stand-ups for critical resource allocation decisions

Develop dynamic KPIs and alerts

• Monitor plan stability metrics alongside traditional efficiency measures
• Track forecast accuracy across multiple time horizons
• Receive alerts on constraint violations before they affect customer commitments

Train teams on adaptive decision-making

• Develop planner skills in finite capacity optimisation
• Build cross-training programmes for critical planning roles
• Create standard operating procedures for the most common disruption scenarios

Measure and improve continuously

• Conduct weekly plan-versus-actual comparisons
• Track the correlation between working capital velocity and customer service levels
• Run quarterly planning process reviews with stakeholder feedback

Market volatility demands planning systems that adapt at the speed of disruptions, not quarterly review cycles. Manufacturers that implement unified, finite capacity planning platforms achieve systematically superior results compared to those that continue relying on manual coordination and siloed optimisation. The question is not whether instability will continue: it is whether your planning capabilities can evolve faster than market conditions.

Want to understand how it works in practice? Explore sedApta's adaptive planning solutions and discover how manufacturers maintain competitive advantage through operational agility.