Advanced Analytics
Predictive Modeling
Scenario Simulation
Nuno Pedro
Our AI-generated summary
Our AI-generated summary
A major player in the cable manufacturing sector faced the challenge of aligning its production capacity with ambitious commercial growth targets over a 3 to 5 year-horizon. The company needed to:
- Project future capacity requirements based on commercial forecasts.
- Test the impact of efficiency improvements and capacity increases, including the addition of new production equipment (and taking into account alternative purchasing options).
- Optimize resource allocation (machines, labor, and shifts) to maximize margin and meet demand.
- Integrate diverse data sources such as management control, machine efficiencies, and labor costs to support robust scenario analysis.
Key performance indicators (KPIs)included total production volume, machine occupancy rates, gross margin per ton, and payback periods for new investments.
To address these challenges, we implemented a comprehensive analytics solution structured around scenario modeling and predictive forecasting:
- Development of the model:
A modular analytics platform was created to simulate production scenarios over a 3 to 5-year horizon, integrating commercial forecasts, machine data, and cost structures. The solution encompasses an analytical forecasting and a state-of-the-art optimization module. - Scenario Generation:
Multiple scenarios were tested, including:
o Baseline (AS-IS) and commercial plan projections.
o Efficiency improvement scenarios (e.g.,+20% efficiency).
o Capacity expansion through the acquisition of new equipment.
o Optimization of shift regimes and resource allocation.
- Data Integration:
The model consolidated inputs from management control systems, historical production data, machine efficiency metrics, and labor cost structures. - Validation and Calibration:
The model was validated against actual production data, ensuring high accuracy in forecasting and scenario outcomes. - Optimization Algorithms:
Advanced optimization techniques were used to maximize margin, considering constraints such as equipment payback periods and operational feasibility.
The analytics-driven approach delivered significant benefits:
- Dynamic Planning Tool:
The client now possesses a flexible model to rapidly update forecasts and test new scenarios as market conditions evolve, enabling a monthly update exercise with updated efficiency and budget execution data. - Production Volume Growth:
In the following 3-years, the model projects a 40% increase in production volume, driven by efficiency gains and strategic equipment investments. - Margin Improvement:
Gross margin per ton is expected to grow by 11% in the same period, with the most notable gains in medium and high-tension cable segments. - Resource Optimization:
Machine occupancy rates are projected surpass 90%, and the model supports optimal shift and equipment allocation, reducing unnecessary costs and maximizing asset utilization. At the same time, the exercise allowed the manufacturer to uncover product lines with sparing capacity. - Investment Support:
The scenario analysis provided clear payback calculations for new equipment, supporting confident capital investment decisions. - Strategic Foresight:
Predictive modeling enables the anticipation of market trends and proactive adjustment of production strategies.
Our AI-generated summary
Our AI-generated summary