The Mission
Over the years, a window systems manufacturer expanded its portfolio with unique configurations designed to meet customers’ individual requirements. This resulted in a highly complex product portfolio, making it difficult to determine the contribution of individual features and configurations to customer value and portfolio profitability.
Therefore, the client needed to understand which factors drove margins and which elements primarily added complexity. The objective was to use these insights for portfolio optimization, increase profitability, and identify opportunities to lower manufacturing costs.
The Approach
We connected portfolio analysis with product and process optimization. We started by developing a realistic view of the portfolio, then used this foundation to identify the main drivers of profitability and complexity. Finally, we examined cost-saving opportunities.
1 | Build a Fact-Driven Portfolio Baseline
The first step was to create transparency across the portfolio. We consolidated the available data on costs, complexity, and profitability to create a common basis for comparing products and their configurations.
2 | Identify the Drivers of Profitability and Complexity
To determine which product features created value and which added cost or complexity, we built an interactive dashboard. This dashboard visualized profitability and complexity across thousands of product configurations and supported comparisons with selected reference products. Based on these insights, the client could focus its portfolio decisions on configurations and features with business value.
3 | Identify Redesign Opportunities
The final step was to extend the analysis from the portfolio structure to the underlying products and operations. We identified cost-saving opportunities in three areas: product design, manufacturing processes, and the use of common parts.
This created a connection between portfolio decisions and redesign-to-cost considerations. Consequently, together with the client, we could evaluate which configurations created value and where adjustments to products and processes could reduce manufacturing costs.
The Result
By combining portfolio transparency with an analysis of the key drivers of value and complexity, the project established a data-driven basis for portfolio optimization and redesign-to-cost decisions, identifying a 12% savings potential.
