Procurement Glossary
Should-costing: Transparent cost analysis for strategic purchasing decisions
November 19, 2025
Should-costing is an analytical method for the detailed breakdown and evaluation of the theoretically optimal manufacturing costs of a product or service. This technique enables buyers to examine the cost structure of suppliers transparently and develop well-founded negotiating positions. Find out below what exactly Should-Costing means, which methods are used and how you can use this analysis strategically for better purchasing results.
Key Facts
- Should-costing analyzes the theoretically optimal production costs based on materials, working time and overheads
- The method creates transparency in supplier cost structures and strengthens the negotiating position
- Typical areas of application are complex manufacturing products, services and strategic procurement projects
- Should-costing requires detailed market and process knowledge as well as access to benchmarking data
- The analysis provides sustainable support for make-or-buy decisions and supplier evaluations
Contents
Definition: Should-Costing
Should-costing is a systematic cost analysis method that aims to determine the theoretically optimal manufacturing costs of a product or service.
Basic components of should-costing
The analysis includes a detailed breakdown of all cost-relevant factors. Material costs, working hours, machine costs and overheads are considered and evaluated separately.
- Material costs based on current market prices
- Labor costs taking into account regional wage structures
- Machine costs including depreciation and operating costs
- Overheads for administration, sales and profit margin
Should-costing vs. target costing
While target costing starts from the desired market price and calculates backwards, should-costing works bottom-up from the production costs to the fair price. This method optimally complements target costing.
Importance of should-costing in Procurement
Should-costing significantly strengthens the negotiating position as it creates objective cost transparency. The method supports strategic decisions when selecting suppliers and enables a well-founded cost-benefit analysis of different procurement options.
Methods and procedures
The practical implementation of should-costing requires structured analysis methods and access to reliable cost data.
Clean sheet calculation
The clean sheet calculation forms the basis of should-costing. The product is broken down into its individual components and each cost factor is evaluated separately.
- Define material quantities and specifications
- Analyze production steps and working times
- Consider machine capacities and set-up times
Cost Breakdown Analysis
A systematic cost breakdown structures the cost analysis into logical categories. This method makes it possible to identify cost drivers and uncover optimization potential.
Benchmarking and market data analysis
External benchmarks and market prices validate the should-cost calculations. The integration of price index data ensures up-to-date and realistic cost estimates for a well-founded procurement strategy.
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Important KPIs for should-costing
Measurable key figures evaluate the effectiveness and accuracy of should-cost analyses in the procurement process.
Cost variance (Should vs. Actual)
The difference between calculated should-costs and actual supplier prices shows the accuracy of the analysis. Deviations of less than 10% are considered very good, up to 20% acceptable.
- Absolute cost variance in euros/percent
- Categorization according to product groups
- Trend development over several periods
Negotiation success and savings
Should-costing-based negotiations should generate measurable savings. The ROI in Procurement quantifies the value contribution of the analysis method.
Analysis efficiency and throughput times
The time from the inquiry to the completed should-cost analysis influences the procurement speed. Optimized processes and digital tools reduce throughput times while maintaining the same quality of pricing.
Risks, dependencies and countermeasures
Should-costing poses specific challenges that can be minimized through appropriate measures.
Data quality and availability
Incomplete or outdated cost data leads to incorrect should-cost calculations. The quality of the analysis depends largely on the timeliness and accuracy of the information used.
- Regular validation of data sources
- Building reliable supplier partnerships
- Investment in professional market databases
Underestimation of complexity
Hidden cost factors such as quality assurance, logistics or regulatory requirements are often overlooked. A comprehensive cost driver analysis minimizes these risks.
Supplier resistance
Transparent cost analyses can lead to tensions with suppliers if they see their margins threatened. Constructive communication and win-win approaches are crucial for successful price negotiations.
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Practical example
An automotive supplier carries out should-costing for a complex cast component. The analysis includes aluminum prices, casting process, post-processing and quality inspection. Through a detailed breakdown of material costs (60%), manufacturing costs (25%) and overheads (15%), the purchasing team identifies a savings potential of 12% compared to the original supplier offer.
- Break down technical specification into individual components
- Research market prices for raw materials
- Calculate production times and costs
- Use the result as a basis for negotiation
Current developments and effects
Should-costing is constantly evolving due to technological innovations and changing market conditions.
Digitalization and AI integration
Artificial intelligence is revolutionizing should-costing through automated data analysis and pattern recognition. AI systems can process large volumes of data and provide more precise cost estimates.
- Automated market price analyses in real time
- Predictive analytics for cost trends
- Machine learning for benchmarking optimization
Sustainability-oriented cost analysis
Environmental and social costs are increasingly being incorporated into should-cost models. This development reflects the growing importance of sustainable procurement and total cost of ownership.
Global supply chain complexity
Volatile commodity prices and geopolitical uncertainties require dynamic should-cost models. The integration of commodity indexation and risk factors is becoming increasingly important for realistic cost forecasts.
Conclusion
Should-costing is establishing itself as an indispensable tool for strategic procurement decisions and transparent supplier negotiations. The method creates objective cost transparency and strengthens the negotiating position in the long term. By integrating digital technologies and AI-supported analyses, should-costing is becoming increasingly precise and efficient. However, successful implementation requires high-quality data, methodical expertise and constructive supplier relationships.
FAQ
What distinguishes Should-Costing from other costing methods?
Should-costing works bottom-up from the actual production costs and creates objective transparency. In contrast to market-based price comparisons or top-down calculations, this method analyzes the fundamental cost drivers and enables precise negotiation arguments.
What data is needed for a should-cost analysis?
Technical specifications, material quantities, production processes, working times, machine capacities and current market prices are required. Regional labor costs, energy prices and industry-specific overhead surcharges are also included in the calculation.
How accurate are should-cost calculations?
The accuracy depends on the data quality and analysis experience. Professionally conducted should-cost analyses typically achieve deviations of 5-15% from actual production costs. Regular validation and market data updates continuously improve accuracy.
When is Should-Costing worth the effort?
Should-costing is worthwhile for strategic procurement projects, high purchasing volumes or complex products with non-transparent cost structures. As a rule of thumb: for procurement volumes over 100,000 euros per year or critical components, the knowledge gained justifies the analysis effort.
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