Predictive Home Service Scheduling System
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Solution Overview
Problem
Homeowners face challenges in scheduling and obtaining reliable, high-quality repair services for their properties, often dealing with unpredictable costs and difficulties in finding suitable service providers.
Innovation Solution
A home services system and method that utilizes data sources, analytics, and information technology to facilitate the provision of maintenance and repair services, including modules for scoring items and service providers, pricing services, and managing claims.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional home warranty services are used, then homeowners can access repair services, but the costs are unpredictable and scheduling is difficult
Solution Approach 1:
The system performs preliminary actions by predicting failures before they occur using analytics on entity data. This allows the system to proactively schedule repairs and notify homeowners in advance, making costs and scheduling predictable rather than reactive and unpredictable
Solution Approach 2:
The system implements feedback loops where analytics continuously monitor entity performance data, compare it against failure patterns, and adjust predictions accordingly. This feedback mechanism improves the accuracy of failure predictions and cost estimates over time, enhancing both reliability and predictability
2Adaptability or versatility
If service providers are searched manually, then homeowners can find repair services, but the process is time-consuming and quality is uncertain
Solution Approach 1:
The system enables self-service by automatically matching predicted failures with appropriate service providers based on entity characteristics and provider capabilities. This eliminates the need for homeowners to manually search and compare providers, significantly reducing time loss while maintaining access to qualified services
Solution Approach 2:
The platform serves multiple functions: it predicts failures, identifies appropriate service providers, schedules repairs, and manages communications. This multi-functional approach consolidates what would otherwise require separate manual processes into a single automated system
3Reliability
If reactive repair services are provided, then costs are covered after failures occur, but preventive maintenance opportunities are lost
Solution Approach 1:
The system performs preliminary maintenance actions by predicting failures before they occur and scheduling preventive repairs. This shifts the model from purely reactive cost coverage to proactive maintenance, improving service efficiency while maintaining cost coverage through better resource planning
Solution Approach 2:
The system converts the potential harm of unexpected failures into benefit by using analytics to predict failures beforehand. This transforms reactive cost coverage into proactive maintenance opportunities, improving both efficiency and service quality while maintaining cost coverage
Data Source
AI summary
Disclosed is a system for creating service requests for appliances or equipment, receiving various data inputs relating to prior service requests with outcomes and diagnostic data, predicting whether each of the different types of repair jobs for which a respective prior service request was initially requested did in fact require the need for a service provider to be bound to them, predicting a date range of failure of the appliances or equipment based upon the data inputs, and scheduling a repair job in advance of the failure based on whether such repair job should be bound to a service provider and an analysis of a comparison of performance metrics of each service provider associated with prior jobs performed by each of the service providers.