Order Allocation Server for Demand-Supply Matching
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Solution Overview
Problem
In the restaurant industry, there is often a temporary mismatch between demand and supply, leading to degraded services for busy restaurants and unsatisfied customers, exacerbated by food delivery apps that can cause sudden surges or drops in demand, with no effective channel to redirect excess demand to nearby restaurants with available capacity.
Innovation Solution
A server system that determines a list of merchants within a predetermined area, ranks them based on minimum selling price, and allocates orders to the highest-ranked merchant, allowing for real-time reevaluation of merchant information and order allocation to ensure efficient demand distribution without revealing the merchant to the user until delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If food delivery apps are used to generate demand, then user convenience is improved, but demand-supply mismatch is worsened due to sudden surges or drops in demand
Solution Approach 1:
The system introduces a demand pooling mechanism where multiple users' order requests are aggregated and managed centrally. The server acts as an intermediary that receives demand signals, evaluates merchant availability in real-time, and allocates orders to appropriate merchants, thereby smoothing out demand surges and improving match reliability while maintaining user convenience
Solution Approach 2:
The system dynamically adjusts order allocation based on real-time merchant availability, capacity, and demand patterns. The server continuously monitors merchant status and reallocates orders as needed, enabling the system to adapt to changing demand-supply conditions and maintain optimal matching under varying conditions
2Loss of time
If orders are allocated to the nearest merchant, then delivery time is reduced, but demand cannot be effectively distributed to merchants with available capacity
Solution Approach 1:
The system changes the allocation parameter from purely distance-based to a multi-factor evaluation that includes merchant capacity, current demand levels, and availability status. This parameter transformation enables the system to allocate orders to merchants with available capacity regardless of distance, improving overall demand distribution efficiency while still considering delivery time factors
3Adaptability or versatility
If merchants offer discounts to attract customers, then user appeal is improved, but profitability for participating restaurants is reduced
Solution Approach 1:
The system implements a feedback mechanism where merchants can set discount parameters and the server evaluates the impact on order allocation and profitability. The system provides feedback to merchants about their performance and can adjust allocation strategies to optimize profitability while maintaining user appeal through strategic discounting
Solution Approach 2:
The system applies different discount strategies to different merchants and order types based on local conditions, merchant capacity, and demand patterns. Rather than uniform discounts, the system tailors pricing strategies to specific contexts, allowing merchants to maintain profitability while offering appealing prices to users when and where appropriate
Data Source
AI summary
A system configured for managing orders is disclosed. The system may include one or more processor(s) which may determine a plurality of merchants selling a product within a predetermined area; determine an original price of the product sold by each merchant of the plurality of determine a discount that each merchant of the plurality of merchants is willing to offer on the product; determine a minimum selling price of the product based on the original price and the discount from each merchant of the plurality of merchants; rank the plurality of merchants based on the minimum selling price of each merchant and determine top N merchants out of the plurality of merchants, wherein when a user puts in an order for the product, the system allocates the order to a highest rank merchant out of the top N merchants.