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Christopher Helm
Christopher Helm

Christopher Helm founded Helm & Nagel GmbH in 2016 after studying Information Technology at TU Munich and Business Administration at the University of Mannheim. He leads the company's technical strategy and personally reviews production deployments.

A German Precision Tools Engineering company in Hesse initiated a project to improve manufacturing efficiency and pricing strategy through the implementation of intelligent pricing logic in their existing SAP Business One system. to develop an application that automatically calculates prices based on cost or value-based approaches for both new and existing products. With thousands of products already in their catalog, this project aimed to streamline and optimize the pricing process significantly.

Company Overview

Company Profile

This company is a leading manufacturer and supplier of high-precision tools and machining solutions, specializing in the production of cutting tools, milling cutters, and other precision instruments. With decades of experience in the industry, the company has established a strong reputation for quality, innovation, and reliability. Its products are widely used across various sectors, including automotive, aerospace, medical, and general manufacturing.

Product Portfolio

The company maintains a broad product portfolio of thousands of different tools and components. These products are designed to meet the demanding standards of modern manufacturing processes, ensuring high performance, durability, and precision. The portfolio includes standard items as well as custom solutions tailored to specific customer requirements.

Sales Channels

The company operates through multiple sales channels, serving both resellers and direct B2B customers. This dual approach allows the company to maximize its market reach and support a diverse customer base. Resellers benefit from the extensive product range and the company's reputation for quality, while direct B2B customers receive tailored solutions and dedicated support.

Challenges in Managing a Large Product Portfolio

  1. Complex Inventory Management
    • Managing a large inventory with thousands of SKUs is inherently complex. The company must ensure that it has the right products in stock to meet customer demand while avoiding overstocking and obsolescence. This requires sophisticated inventory management systems and accurate demand forecasting.
  2. Pricing Strategy
    • Setting the right price for each product is crucial, especially when dealing with such a varied portfolio. The company must balance competitiveness with profitability, taking into account production costs, market demand, and competitor pricing. An automated pricing system that can dynamically adjust prices based on these factors is essential.
  3. Product Customization
    • Many B2B customers require customized solutions, which adds another layer of complexity to product management. The company must have flexible production processes and efficient communication channels to handle custom orders without disrupting the overall workflow.
  4. Quality Control
    • Maintaining consistent quality across a vast range of products is a significant challenge. The company must implement rigorous quality control measures at every stage of the production process to ensure that all products meet the required standards.
  5. Logistics and Distribution
    • Efficient logistics and distribution are vital for managing a large product portfolio. The company must coordinate the movement of goods from manufacturing facilities to customers and resellers, ensuring timely deliveries and minimizing transportation costs.
  6. Customer Relationship Management
    • Building and maintaining strong relationships with both resellers and direct customers is key to sustained success. The company must provide excellent customer service, technical support, and after-sales service to foster loyalty and encourage repeat business.

Project Overview

To optimize production processes, Helm & Nagel GmbH leveraged its AI advisory expertise to develop a specialized interface to capture and analyze setup and cycle times. This system enabled detailed tracking of each process step in the milling cutter production, supporting accurate personnel resource planning and better capacity management prior to order placement.

Integration of Data Sources

In addition to leveraging data available in SAP Business One, the payroll journal was utilized to allocate costs accurately. An exemplary excerpt from the payroll journal demonstrates the level of detail included in the calculations:

Employee ID Total Gross Tax Class Income Tax Health Ins. Care Ins. Pension Ins. Unemployment Ins. Net Pay
1001 50,000.00 V 5,000.00 2,000.00 300.00 4,000.00 500.00 38,200.00
1002 42,000.42 III 4,200.00 1,800.42 270.00 3,200.00 420.00 32,109.00
1003 36,500.75 I 3,650.08 1,460.50 200.00 2,900.00 365.00 27,925.17

These data enabled precise cost allocation to various production steps and a detailed analysis of personnel costs.

Incorporation of Current Catalog Prices

To ensure accurate and up-to-date pricing, current catalog prices were integrated into the software. An excerpt of the product data showcases the variety and specifics of the products:

Item No. Item Description Price Before Discount
2001 Quarter Circle Cutter V2023 123.45 €
2002 Quarter Circle Cutter V2023.2 101.10 €
2003 Quarter Circle Cutter V2021 99.99 €

Managing Director's Remarks

The CEO provided essential insights into data collection and processing, emphasizing the importance of clearly allocating production and administrative costs and accurately recording machine and repair costs. These inputs were critical in refining the project's scope and execution.

Detailed Machine Data Integration

The project also incorporated detailed machine-related data, such as the names, depreciation durations, power consumption, and repair costs of the machines. This data was essential for accurately calculating machine costs and integrating them into the overall pricing model.

Machine No. Name Depreciation Duration New Price Depreciation per Year Power Consumption (Nominal) Power Consumption (Actual) Repairs 2015 Repairs 2016 Fixed Costs per Year
1 The Terminator 20 years 100,000.00 € 5,000.00 € 10 Kwh 15 Kwh 1,000.00 € 500.00 € 6,500.00 €
2 Mr. Grind 15 years 150,000.00 € 10,000.00 € 20 Kwh 25 Kwh 2,000.00 € 1,000.00 € 13,000.00 €
3 Dr. Smooth 10 years 200,000.00 € 20,000.00 € 15 Kwh 18 Kwh 500.00 € 750.00 € 21,250.00 €

Smart Pricing Formula: Learning from Internal Cost Structures

The integration of BWA (Business Management Analysis) and asset data enabled the development of a unique, automated pricing formula. This formula learns from internal cost structures to provide dynamic, value-driven pricing for both existing and new products. Similar intelligent automation can be achieved through purpose-built AI agents that continuously adapt to changing data. This approach ensures that each product's price accurately reflects its actual production cost and market conditions.

Item No. Direct Costs Overhead Costs Total Cost per Unit Margin Total Cost incl. Margin Catalog Price (gross)
2001 15.00 € 10.00 € 25.00 € 5.00 € 30.00 € 123.45 €
2002 12.00 € 9.00 € 21.00 € 4.20 € 25.20 € 101.10 €
2003 10.00 € 8.00 € 18.00 € 3.60 € 21.60 € 99.99 €

This dynamic pricing model considers:

  1. Material Costs: Direct costs of raw materials used in production.
  2. Overhead Costs: Indirect costs allocated to the product, such as administrative costs, energy, and machine depreciation.
  3. Personnel Costs: Wage costs directly and indirectly attributed to production.
  4. Machine Costs: Operating costs of machines, including depreciation and maintenance.
  5. Packaging and Shipping Costs: Costs for packaging and shipping products.
  6. Sales Costs: Costs for advertising, trade shows, and sales.
  7. Administrative Costs: General administrative costs not directly attributable to a product.
  8. and many more

Value-Driven Approach

The value-driven pricing approach ensures that prices not only cover costs but also include an appropriate margin, enabling the company to operate profitably and remain competitive. This comprehensive strategy meticulously accounts for every cost factor, resulting in a sustainable and market-reflective pricing model.

Granular Personnel Resource Tracking

One significant improvement was the granular tracking of personnel resources over three months. This tracking allowed for more precise planning and allocation of human resources, ensuring that the right personnel were available for each production stage, ultimately improving efficiency and reducing downtime.

Current and Future Capacity Planning

The system was designed to enhance capacity planning before order placement. By using detailed data on machine and personnel availability, the precision tools company could better manage their production schedules, optimize resource usage, reduce lead times and thereby increase their margin.

Considering the Supply Side

One aspect not considered in this project is the supply side, particularly seasonal fluctuations and industry-specific prices. This presents significant optimization potential. For example, prices could vary based on the season to maximize demand or minimize inventory. Industry-specific prices could help increase competitiveness in certain market segments. These factors offer additional price optimization opportunities that should be explored in future projects.

General Remarks for Pricing Improvement in Smaller Enterprises

Specific Details on SAP Business One Interface Development

Developing a customized interface in SAP Business One for tracking setup and cycle times is essential. This interface provides real-time data, allowing for more accurate cost assessments and pricing adjustments. Smaller enterprises can benefit from such systems by ensuring that every step of the production process is cost-effective, leading to overall margin improvements.

Payroll Journal Integration and Granular Personnel Resource Tracking

Accurate cost allocation using payroll journals combined with detailed tracking of personnel resources enables companies to understand the exact labor costs involved in production. By systematically allocating these costs to specific production tasks, companies can price their products more precisely, ensuring that labor-intensive products are priced appropriately. Small enterprises can optimize their workforce deployment, reducing labor costs and improving efficiency, which prevents underpricing and supports more accurate and profitable pricing.

Incorporation of Machine Data

Integrating detailed machine data, including depreciation, energy consumption, and repair costs, allows for a comprehensive understanding of production costs. Small enterprises can use this data to optimize machine usage and maintenance schedules, reducing downtime and improving cost efficiency, which contributes to better pricing strategies and higher margins.

Detailed Process of Price Calculation for New Products

Implementing a detailed, step-by-step price calculation process for new products ensures that all cost factors are considered. This systematic approach helps in setting competitive yet profitable prices. Smaller enterprises can improve their pricing accuracy and ensure that new products contribute positively to the bottom line.

Specific Product Data and Calculation Examples

Providing detailed product data and examples of price calculations helps in standardizing the pricing process. Smaller enterprises can use these examples as benchmarks, ensuring consistency and transparency in their pricing models. This practice can lead to more informed pricing decisions and improved profit margins.

Feedback from the Managing Director

Incorporating feedback from key stakeholders, such as the managing director, ensures that practical challenges are addressed. This collaborative approach can lead to more refined pricing strategies that align with the company's overall objectives, ultimately enhancing profitability.

Current and Future Capacity Planning

Effective capacity planning ensures that production resources are used optimally, preventing bottlenecks and underutilization. By accurately forecasting future production needs, smaller enterprises can better manage their resources, leading to more stable production costs and improved pricing strategies.

Use of Additional Data Sources

Leveraging various data sources, such as payroll journals, machine data, and market trends, provides a holistic view of production costs. Smaller enterprises can integrate these data points to develop comprehensive pricing models that reflect true production costs, leading to more competitive and profitable pricing.

Improvement and Optimization of Production Catalog

Regularly updating and optimizing the production catalog ensures that all products are priced based on the latest cost data. Smaller enterprises can eliminate outdated pricing models, ensuring that all products contribute positively to the overall profit margin.

Consideration of the Supply Side

Factoring in supply-side variables, such as seasonal demand and industry-specific price fluctuations, can significantly enhance pricing strategies. Smaller enterprises can adopt dynamic pricing models that adjust based on these variables, maximizing revenue during peak demand periods and maintaining competitiveness during off-peak times.

Explanation of Terms Used

  • SAP Business One: An ERP software solution designed specifically for small and medium-sized enterprises to manage their business processes.
  • Interface: A connection between different software systems that enables data exchange.
  • Setup Time: The time required to prepare a machine for production.
  • Cycle Time: The time needed to complete a production step.
  • Payroll Journal: A record of employee payrolls used to calculate personnel costs.
  • BWA (Business Management Analysis): A tool for analyzing a company's economic situation based on accounting data.
  • Assets: Company assets such as machines and buildings.
  • Overhead Costs: Indirect costs not directly attributable to a product but incurred for the overall production.
  • Margin: The difference between the selling price and the total cost of a product, representing profit.
  • Contribution Margin: The amount remaining after deducting variable costs from the selling price, contributing to covering fixed costs.
  • Automated Price Calculation: A system for calculating product prices based on data and algorithms, replacing and optimizing manual pricing.

Conclusion

The implementation of this project has led to significant improvements in production processes and optimized their Free Cash Flow. By integrating intelligent systems for detailed recording and analysis of setup and cycle times, along with personnel and machine data, more precise capacity and cost planning was achieved. This enabled optimized pricing and better utilization of production capacities.

The detailed documentation and continuous improvement of calculation methods ensure that our customer outperforms competition and efficiently manages its production processes. Exploring the unconsidered supply side offers additional price optimization potential. Enterprises with large product portfolios can utilize our pricing approach to enhance their pricing models, leading to increased margins and overall profitability. For additional examples of data-driven optimization, see our logistics case study.

Further Resources