Remote Beverage Order Dispatching to Reduce Bar-Counter Waiting
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Solution Overview
Problem
The process of ordering alcoholic beverages at retail establishments is inefficient, often requiring significant time and causing frustration due to varying establishment sizes, drink options, customer decisiveness, and queue lengths, especially during peak hours, and does not accommodate individual preferences or inventory availability, leading to revenue loss and customer dissatisfaction.
Innovation Solution
A beverage ordering manager service that utilizes a standardized product schema to map inventory data, predict user preferences, and generate order images across multiple establishments, facilitating efficient transactions through user and retailer devices, including friend ordering and entry pass services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If customers order beverages at the bar counter, then they can receive their drinks, but they must wait in line for several minutes which reduces socialization time and increases frustration
Solution Approach 1:
The system performs preliminary actions by allowing customers to place orders remotely via mobile devices before arriving at the bar counter. The ordering system receives and processes orders in advance, prepares the beverages, and notifies customers when ready, eliminating the need to wait in physical line
Solution Approach 2:
A mobile device application serves as an intermediary between the customer and the bar counter system. The application transmits order information wirelessly to the ordering system, enabling customers to place orders without physically approaching the counter, thus reducing waiting time and improving ordering efficiency
2Reliability
If servers manually check inventory and availability, then they can determine if customer preferences are available, but this process adds delays and requires additional personnel consultation
Solution Approach 1:
The ordering system continuously receives real-time inventory data from the establishment's inventory system and provides immediate feedback to customers about product availability. When a customer places an order, the system automatically checks current inventory levels and notifies the customer if the requested item is unavailable, eliminating the need for manual server verification
Solution Approach 2:
The system performs self-service by automatically checking inventory availability and validating orders without requiring server intervention. The ordering system independently queries the inventory database, determines availability, and communicates results to customers, reducing order processing time and eliminating the need for additional personnel consultation
3Productivity
If establishments operate at full capacity, then they maximize revenue potential, but they create lines outside and force potentially paying customers to wait
Solution Approach 1:
The system allows customers to place orders before physically entering or approaching the establishment. By enabling remote ordering via mobile devices, customers can initiate the ordering process in advance, reducing the need for physical queueing at the entrance and improving access ease while maintaining full capacity operation
Solution Approach 2:
The system transitions the ordering process from a physical spatial dimension (queuing at the counter) to a digital wireless dimension. Orders are transmitted electronically through mobile devices, allowing customers to bypass physical lines and access the establishment more easily while the establishment maintains full operational capacity
Data Source
AI summary
Systems and methods include onboarding services for retailer devices, guest user services for a user device, and operational services provided to the retailer devices and the guest user services for dispatching beverage orders. The onboarding services map retailer inventory of a retail establishment to a standardized product schema. Upon detecting that the user device is within a predetermined distance of the retailer device, the system generates and presents a user preference by performing a rationalized perato analysis on an order history associated with the user device. The order history and the preference are mapped to the standardized product schema. The user device receives a beverage order selection and, in response, the system generates a randomized order image to be presented at the user device and the retailer device. A transaction corresponding to the beverage order selection is executed at a point-of-sale (POS) system.