Sales Order Planning System for Custom Product Delivery
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Solution Overview
Problem
Current order management systems face challenges in reducing lead times and increasing agility in responding to customer-specific demands, particularly in make-to-order scenarios, where customers often face long wait times and limited product options due to decoupled production and sales processes.
Innovation Solution
The system maintains master data and forecasts material requirements, generates sales order confirmations and production plans based on product requirement specifications, and determines sources of supply, allowing for flexible production planning and delivery, including options like down-binning to reduce lead times and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If make-to-order production is used to satisfy customer-specific demands, then product customization and adaptability are improved, but lead time and production duration increase
Solution Approach 1:
The system performs preliminary actions by maintaining master data with product configurations and components in advance, and by procuring components before actual sales orders are received. The material requirements are forecasted and components are ordered ahead of time, so when a customer places an order, the components are already available or can be quickly assembled, thereby reducing lead time while maintaining customization capability.
2Adaptability or versatility
If make-to-order process is used to cover individual customer demands, then customer-specific requirements are satisfied, but total lead time across production levels becomes longer
Solution Approach 1:
The system applies preliminary action by forecasting material requirements before sales orders are received and by maintaining master data with pre-configured product information. This allows the system to prepare components and production plans in advance, reducing the total lead time across all production levels while still meeting individual customer demands.
Solution Approach 2:
The system segments the production process into distinct levels (first production level and second production level) with different lead times. By segmenting, the system can optimize each level independently - using faster production for critical components and allowing less time-consuming processes for non-critical items, thereby reducing overall lead time while maintaining customization.
3Speed
If goods are sold from stock, then delivery speed is improved, but product options and variants are limited by stock availability
Solution Approach 1:
The system creates a universal approach by maintaining master data that encompasses multiple product configurations and variants. This master data serves multiple functions: it enables the system to quickly assemble custom products from pre-configured components (maintaining speed) while also supporting a wide range of product options and variants (maintaining adaptability). The system can thus sell from stock for standard items while quickly customizing for specific customer needs.
4Adaptability or versatility
If components are procured for make-to-order production, then customization capability is maintained, but procurement quantity and complexity increase
Solution Approach 1:
The system applies preliminary action by forecasting material requirements before actual sales orders are received. This allows the system to procure components in advance based on predicted demand patterns, maintaining customization capability while optimizing procurement quantities to avoid over-ordering. The master data with pre-configured product information enables accurate forecasting and thus more efficient procurement.
Data Source
AI summary
In various implementations, sales orders are received and product requirement specifications are generated based on the sales orders. Planning for the production of the goods occurs based on the product requirement specification and the goods are produced based on the plan.