A large-scale consumer goods manufacturer, operating a network of multiple plants across Europe, faced annual volatility driven by pronounced seasonal demand peaks. Their existing planning process used fixed monthly schedules, which resulted in either expensive over-capacity during trough periods or missed sales and poor service levels during the critical peak season. Each plant housed diverse production lines, each with unique changeover times and shift costs (fixed setup cost per shift, variable labour).
The business challenge was to move from rigid monthly plans to a dynamic, tactical weekly planning cycle. They required a system that could intelligently determine the optimal number of shifts to run on every single production line across the entire network, week-by-week, to fulfil fluctuating demand. Crucially, this had to be achieved while maintaining the lowest possible total cost, integrating production costs, inventory holding, and distribution logistics.
The Solution: Weekly Tactical Supply Network Planning
The manufacturer implemented Sophus X for tactical Supply Network Planning (SNP), shifting the planning frequency from monthly to weekly. The model was designed as a living, continuously refreshed digital twin of the production environment.
The Sophus X model was configured to make binary decisions (run shift A, run shift B, etc.) on over 100 individual production lines simultaneously. This allowed the model to:
- Integrate Production Costs: Precisely model the fixed cost of initiating a shift, the variable cost of running it, and the capacity gained, linking this directly to the required volume to meet weekly demand.
- Optimize Capacity Flexibly: Use the shift patterns as a flexible capacity lever. Instead of guessing how much to produce, the model calculated the precise cost of operating the necessary shifts to cover firm orders and forecast demand.
- Weekly Refresh Cycle: A key requirement was establishing a continuous improvement loop. The model was set up to be refreshed by planners weekly, incorporating the latest demand signals, actual inventory levels, and updated logistics costs, ensuring the plan remained agile and highly relevant to immediate operational needs.
Key Insights and Outcomes
The deployment of the weekly tactical SNP model transformed the manufacturer’s ability to navigate seasonality, delivering immediate and measurable cost benefits:
Optimized Production Cost Profile
By removing unnecessary shifts in the shoulder and trough seasons, and running only the mathematically required capacity during the peak, the manufacturer achieved a 4% reduction in total annual production costs, driven primarily by reduced variable labour and energy expenditure.
Improved Service Levels in Peak Season
The ability to model the total impact of running an extra shift—including the subsequent reduction in expedited shipping—ensured that critical production capacity was deployed correctly, drastically reducing the rate of stock-outs and improving service delivery across the peak period.
Empowered Planning Team
The weekly refresh cycle of supply network planning, enabled by Sophus X’s speed and data handling capabilities, transitioned the planning team from simple data aggregation to scenario analysis and continuous operational improvement. They now use the platform to proactively test the cost and service implications of different shift patterns against variable raw material availability or potential logistics disruptions.
The move to weekly, shift-level optimization allowed the manufacturer to finely tune capacity to match demand volatility, turning a significant annual planning hurdle into a manageable, cost-controlled, continuous process.
