March 4, 2025
Consider the journey of a successful tissue business in Europe:
A medium-sized tissue manufacturer struggled with inefficiencies in demand planning. In 2020, the company embarked on a transformative journey following a thorough pre-study and vendor analysis. The business objectives centered around reducing inventories and working capital, improving OEE (Overall Equipment Effectiveness), enhancing planning agility and efficiency, lowering forecasting errors, and increasing overall service levels.
The case company is part of larger conglomerate with a multi-billion annual turnover.
IDENTIFYING THE OPPORTUNITY
The tissue manufacturer recognized an opportunity to significantly improve customer service levels by enhancing forecast accuracy for its make-to-stock operations. However, several challenges needed to be addressed:
- Demand Forecasting Accuracy: The company prioritized improving its demand forecasting capabilities, which were critical to aligning production and inventory with market needs.
- Wide Product Portfolio: A diverse range of products added complexity to forecasting efforts.
- High Level of Promotional Activity: Frequent promotions created demand variability, further complicating accurate predictions.
- Expansion Complications: Initially focused on two main production facilities, the company later acquired new businesses to increase market share, adding operational sites in Spain and the UK, requiring planning model adjustments. This expanded footprint introduced additional complexity to planning processes.
SOLUTION
To address these challenges, the company embarked on a comprehensive initiative to enhance its planning processes, technical capabilities, and supply chain expertise. One of the cornerstones of this transformation was the implementation of a modern, cloud-based S&OP (Sales and Operations Planning) platform, putting the initial focus on demand planning. Additionally, a collaborative demand planning process was established to align stakeholders effectively. This platform was chosen for its piloted ability to improve demand forecasting and forecast accuracy, and its modular nature, with opportunities to support future supply chain planning extension needs. Each step of the implementation also included the automated bi-directional integration between the new planning system and the company’s core ERP.
RESULTS
The demand planning implementation step of the transformation delivered remarkable results:
- +20 percent Improvement in Forecast Accuracy: The statistical forecasting solution increased average forecast accuracy from 57 percent to 72 percent at the SKU level. The subsequent integration of AI further refined predictions, enabling better resource allocation and operational precision.
- Reduction of Demand Planning Effort by +50 percent: Automation significantly reduced the time required for generating, analyzing, and collaborating on forecasts, freeing up resources for strategic activities.
- Reduction in Inventory Costs: Optimized inventory levels minimized carrying costs and reduced waste, directly impacting the company’s bottom line.
- Improved On-Time Delivery Rates: Enhanced demand planning ensured timely product deliveries, boosting customer satisfaction and loyalty.
- Reduction in Production Waste: Improved alignment between demand forecasts and production schedules minimized material waste, contributing to the company’s sustainability goals.
IMPACT
This transformation not only delivered substantial operational and financial benefits, but also reinforced the company’s reputation as a reliable and efficient supplier. By leveraging modern planning technologies and fostering collaboration, the company set a strong foundation for future growth and resilience in a competitive market.