Why Forecasting Complexity and Demand Volatility Are Now the Defining Challenge for Spare Parts Leaders

During six weeks of interviews with spare parts and service logistics, and supply chain leaders from Europe’s leading industrial manufacturers a key challenge a key challenge stands out. The recurring theme was forecasting complexity and demand volatility-especially as organisations manage vast SKU ranges spanning new, ageing, and discontinued equipment. Leaders repeatedly stressed that forecasting failures directly affected service levels and inventory costs, and that legacy systems simply can’t keep up.

This pressure is particularly acute in sectors such as automotive, construction equipment, agricultural machinery, MedTech, and heavy industrial OEMs, where product lifecycles can extend 20-30 years. Companies like Iveco, BDR Thermea Group, Ariston Thermo Group, Fastems, Husqvarna Construction, ArcelorMittal, and Bobst all described the same problem during interviews: demand signals for spare parts are increasingly erratic, while customer expectations for rapid availability are rising.

Several factors sit at the heart of this volatility. First, spare-parts portfolios continue to explode - some manufacturers manage hundreds of thousands of SKUs across new and old models. Second, obsolescence is accelerating as suppliers discontinue low-volume parts, pushing OEMs to hold more stock or face long service disruptions. And third, the European market itself is shifting: ageing vehicle fleets, tightening sustainability expectations, and increasingly complex cross-border logistics all heighten the risk of forecasting errors.

Given these pressures, it’s unsurprising that forecasting accuracy is becoming a competitive differentiator. Leaders from Fastems, Iveco, and Lynk & Co noted that poor forecasts cascade into stockouts, premium freight, excessive safety stock, or dissatisfied customers-each creating cost and service penalties that compound over time. Many also highlighted that customers now expect next-day delivery for even niche components, adding another layer of forecasting precision.

Solution Providers Are Ramping Up Innovation

The consensus across our conversations is clear: there will be stronger investment in AI- and ML-enabled forecasting and demand planning solutions over the next 12–18 months. Key vendors- Syncron, Logility, Blue Yonder, Baxter Planning, Kinaxis, o9 Solutions, ToolsGroup, and others - are already tailoring offerings specifically for spare parts environments.

Across the provider landscape, several themes stand out:

• Predictive maintenance-linked forecasting, integrating real-time equipment data to smooth volatility
• Multi-echelon inventory optimisation to balance availability with cost across global networks
• Automated obsolescence management, helping OEMs manage long-tail, ageing SKUs
• AI-driven anomaly detection to spot and react to sudden demand spikes
• Sustainability-aligned planning, recognising that inventory, transport, and packaging footprints increasingly influence decision-making

Vendors interviewed - including Blue Yonder, BCI Global, Carousel Logistics, Time:matters, and TVS Supply Chain Solutions -confirmed that demand for advanced forecasting and inventory solutions is rising sharply, specifically from heads of spare parts logistics across Europe.

The Bottom Line

Forecasting complexity and demand volatility aren’t just operational problems - they are strategic risks. Industrial manufacturers now recognise that service continuity, working-capital control, sustainability goals, and customer satisfaction all hinge on smarter, more adaptive forecasting. The next wave of digital investment is already underway, and those who move early stand to gain a decisive advantage.

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