Ecommerce Cost Optimization System for Non-Stock Items
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Solution Overview
Problem
Ecommerce systems lack efficient tools for optimizing production and delivery schedules to deliver non-stock goods on a selected delivery date at an optimal price, often leading customers to choose longer production schedules over quicker shipping, which is more expensive.
Innovation Solution
An ecommerce tool that allows users to select quantity, delivery location, and delivery date, enabling vendors to control production and delivery schedules, providing optimized pricing options based on these selections, and offering alternatives to balance costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If customers choose shorter production schedules, then delivery speed is improved, but production cost increases
Solution Approach 1:
The system changes the parameter of production schedule duration and calculates corresponding cost variations. By presenting multiple production schedule options (e.g., 2-day rush production vs. 7-day standard production) with their respective costs, the system enables customers to adjust the production time parameter while understanding the cost impact, thus resolving the contradiction between delivery speed and production cost.
2Speed
If customers choose shorter delivery schedules, then delivery speed is improved, but delivery cost increases
Solution Approach 1:
The system allows customers to adjust the delivery schedule parameter (e.g., overnight shipping vs. ground shipping) and automatically calculates the corresponding delivery cost. By presenting delivery options with varying time and cost parameters, customers can optimize their choice based on their specific needs, resolving the contradiction between delivery speed and delivery cost.
3Quantity of substance
If customers have bias toward longer production schedules, then cost is reduced, but delivery time increases
Solution Approach 1:
The system dynamically adjusts production and delivery schedule options based on customer input and requirements. Rather than presenting static options, the system adapts to customer needs by showing relevant schedule combinations, enabling customers to dynamically balance cost and time preferences. This dynamic approach helps overcome natural biases by presenting optimized alternatives that may not be immediately obvious.
4Adaptability or versatility
If ecommerce systems provide multiple production and delivery options, then customer choice is improved, but system complexity increases
Solution Approach 1:
The system segments the complex optimization problem into distinct components: production schedule selection, delivery schedule selection, and cost calculation. By breaking down the decision-making process into separate, manageable steps with clear options at each stage, the system provides extensive customer choice while maintaining operational simplicity. Customers make sequential decisions rather than overwhelming simultaneous choices.
Data Source
AI summary
An ecommerce cost optimization system includes: a display including information identifying an item; a quantity selection tool; a delivery location selection tool; an optimized offer presentation tool that provides at least one optimized option through the display component, wherein the at least one optimized option is optimized based on the selected quantity and the selected delivery location; and an order placement tool to place an order from amongst the options provided by the optimized offer presentation tool. A method of providing optimized offer for non-stock item transactions through an ecommerce application includes receiving a user selection including a selected quantity of the item and a selected delivery location and determining an optimized offer based on analysis of the possible combinations of a production schedule and a delivery schedule for the selected quantity and delivery location.