AI-Driven Demand Forecasting

Eduards Trailer Factory shifted from manual forecasting to AI-driven forecasting, unlocking more accurate demand insights and optimizing both inventory and production planning.

Challenge

Understanding and overcoming operational inefficiencies

With trailers built from a wide range of external components, Eduards Trailer Factory encountered challenges in balancing planning, timely delivery, and inventory management, mainly due to long supplier lead times and inefficiencies in the forecasting processes.

Long and unpredictable lead times
Some parts necessary for assembly had lead times of 8 to 10 weeks, while customers expected delivery within 8 working days, forcing the company to plan very far ahead.

Large product-range complexity
With over 3,000 distinct items (components) to manage, variation in parts, demand patterns, and supply made forecasting extremely complex.

Poor visibility and error in forecasts
Forecasting had been done via Excel – very time-consuming and insufficient in revealing future trends; this led to frequent overstocking or understocking.

Approach

Implementing an AI platform embedded in business operations

To tackle those challenges, we introduced AI-based forecasting integrated with their ERP through our 4 step approach.

01

Pre-project & Problem Definition
We defined the scope, objectives and what “success” looks like. Next, we clarified what data is available and what business decisions the forecast needs to support.

02

Proof of Concept (POC)
We delivered a first forecasting model for one product or product group to validate assumptions and test performance under real conditions.

03

Scale Up
We expanded the forecasting to cover more products or product groups and extended the model coverage by incorporating more data.

04

Iterative improvements
In close collaboration with Eduards, we delivered the integrated forecasting solution to maximise demand insights and forecast quality for their unique business needs.

Results

Substantial improvements in accuracy, cost, and delivery performance

The new AI-driven system delivered several concrete benefits.

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Low forecast error

Average forecast error across all items was only 2.06%, indicating very high accuracy.

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Better inventory balance

Because forecasts are precise, Eduards now avoids both excessive stock and shortages, improving inventory turnover, reducing holding costs, and minimizing risk of stockouts.

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More reliable delivery performance

With component availability improved and planning more aligned to real demand, Eduards can better meet its promise of fast delivery (8 working days) even though suppliers may have much longer lead times.

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Strategic insight and competitive positioning

Beyond operational gains, insights into what drives demand help in strategic decision-making; the company strengthens its competitiveness and is better prepared for growth.

Forecast with Confidence, Plan with Precision

Discover how AI-powered demand forecasting can reduce errors, optimize inventory, and improve delivery reliability – let’s transform your operations.

Ready to overcome stock challenges and start forecasting with confidence? Contact us today to see how we tailore our forecasting platform to your unique needs.

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