Accurate and efficient cost estimation is crucial in today's globalized economy, especially in competitive industries like mechanical engineering. Companies must optimize their pricing processes to maintain competitiveness and profitability.

DMG Mori AG, a global leader in machine tool manufacturing, sought to enhance its cost estimation methods for sheet metal components, constituting a significant portion of its overall expenses.

To address this need, DMG Mori's Product Cost Optimization (PCO) team compared Non-Linear Performance Pricing (NLPP) with Bottom-Up Calculation to identify the most effective approach for determining target prices. This case study explores the implementation and results of this comparison, highlighting the advantages of NLPP in optimizing cost structures.

The PCO team at DMG Mori decided to evaluate and compare two primary cost estimation methods:

• Non-Linear Performance Pricing (NLPP): This statistical method uses multiple regression techniques to identify and model non-linear relationships between price and various value drivers. NLPP leverages benchmark lines (Worst-Practice, Market, and Best-Practice) to provide a comprehensive price range.
• Bottom-Up Calculation: This traditional cost-plus approach involves summing up all direct and indirect costs associated with manufacturing a component. This method includes a detailed process cost calculation to allocate overheads accurately.

The goal was to determine which method could more efficiently and accurately establish target prices for sheet metal components, strengthening DMG Mori's negotiating position with suppliers and improving overall cost management.

The implementation involved several key steps:

1. Data Collection: Using Spendscape, a spend analytics software by McKinsey, the PCO team gathered data on sheet metal components, including descriptions, material groups, material IDs, prices, and supplier information.
2. Value Driver Identification: A team meeting was conducted to identify key value drivers for sheet metal components. These included the number of bends, whether the part was a subassembly, surface treatment, painting, presence of welds, material type, material thickness, number of threads, net weight, and part surface area. The team decided to focus on a homogeneous set of parts to avoid point suspensions in the analysis.
3. Data Verification: Relevant value drivers were extracted from the technical drawings of 247 sheet metal components and systematically documented.
4. Statistical Model Creation: The collected data was uploaded into the NLPP software provided by Saphirion AG. The software was used to identify patterns, create statistical models, and establish benchmark price levels.as soon as.
5. Model Validation: The NLPP software automatically handles non-linear relationships, reducing the need for manual adjustments. The model was evaluated to ensure that the components with the highest and lowest performance values aligned with expected values.
6. Measure Definition: Price reduction opportunities were identified by comparing components with similar performance values but different prices. The software automated the identification of comparable parts, enhancing efficiency.
7. Bottom-Up Calculation: A selection of 20 sheet metal parts was subjected to bottom-up costing, which utilizes Tset software to perform a detailed analysis of each process step to determine the respective costs precisely. Tset uses process cost and surcharge calculations, using extensive databases with information from various companies.

The comparison of NLPP and Bottom-Up Calculation yielded the following results:

1. Target Price Accuracy: Both methods demonstrated high accuracy in determining target prices. The deviation between the two methods was only about 0.27%. This indicated that both approaches effectively identified and weighted the essential cost parameters.
2. Time Efficiency: NLPP proved to be significantly more time-efficient, requiring an average of 2 minutes and 39 seconds per component (including all six steps mentioned above), compared to approximately 10 minutes for Bottom-Up Calculation.
3. Applicability: NLPP was particularly effective for analyzing large portfolios of similar components. Bottom-Up Calculation was better suited for individual components with specific requirements.

The implementation of NLPP at DMG Mori generated significant value:

• Enhanced Negotiation Power: By providing a clear understanding of the price-performance relationship, NLPP enabled DMG Mori to justify target prices to suppliers with solid, data-driven arguments. The visual representation of cost drivers and price benchmarks in the NLPP software facilitated constructive dialogue and agreement with suppliers.
• Improved Cost Transparency: NLPP helped identify overpriced components and provided insights into the factors driving these costs. This transparency allowed for better cost management and resource allocation.
• Increased Efficiency: The automated features of NLPP, such as identifying comparable parts, significantly reduced the time and effort required for cost analysis. This efficiency enabled the PCO team to focus on strategic cost optimization initiatives rather than manual data collection and analysis.
• Strategic Supplier Development: NLPP facilitated the comparison of different suppliers and their products, enabling DMG Mori to identify cost-effective suppliers and foster strategic partnerships.
• Foundation for Future Price Adjustments: Agreement on a transparent target price formula for each product eliminates time-consuming request for quotation processes while ensuring objective and calculable price adjustments.

The case study at DMG Mori AG demonstrates that Non-Linear Performance Pricing (NLPP) is a valuable tool for optimizing costs for sheet metal components. Its ability to efficiently analyze large datasets, identify non-linear price relationships, and provide clear, data-driven insights makes it an excellent choice for companies seeking to improve their cost management strategies. While Bottom-Up Calculation remains essential for analyzing individual, complex components, NLPP offers a scalable and efficient solution for managing costs across a broad portfolio of parts. The efficiency and transparency gains from NLPP can lead to significant cost savings and enhanced competitiveness in the global market.

By embracing NLPP, DMG Mori could enhance its negotiation power, improve cost transparency, increase efficiency, and foster strategic supplier development, ultimately leading to better cost management and improved profitability.