Predictive Order Status System for Cloud Provisioning
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Solution Overview
Problem
IT representatives in enterprises face challenges in obtaining accurate and comprehensive status updates on computing resource provisioning, often receiving incomplete or misleading information, which can lead to uninformed decisions due to the lack of real-time monitoring and predictive analytics in cloud computing environments.
Innovation Solution
A predictive order status system that monitors task items for computing resources, providing a graphical user interface with simulated percentage-based order status and exception notifications, enabling central IT users to track progress and make informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive status information is provided, then information completeness is improved, but information overload and difficulty in understanding increase
Solution Approach 1:
The patent segments comprehensive order status information into distinct categories including current status, predicted status, exception status, and task item details. Each segment is presented with specific visual indicators (progress bars, color-coded exceptions, hierarchical task lists) that organize the data logically, allowing users to comprehend complex provisioning status without being overwhelmed by the volume of information.
2Measurement precision
If real-time monitoring is implemented, then status accuracy is improved, but system complexity increases
Solution Approach 1:
The patent introduces an order status application as an intermediary layer between the complex provisioning infrastructure and users. This application consolidates status data from multiple sources (order management system, provisioning system, task items) and presents unified, simplified views including current status indicators, predicted completion times, and exception alerts, thereby achieving real-time monitoring accuracy without exposing system complexity to users.
3Loss of information
If detailed task item monitoring is provided, then status comprehensiveness is improved, but information processing complexity increases
Solution Approach 1:
The patent segments task item monitoring into hierarchical levels: overall order status, resource-level status, and individual task item status. Each level aggregates information from the level below it, allowing comprehensive tracking of all task items while presenting summarized views at higher levels. This segmentation reduces processing complexity by enabling incremental aggregation of status data rather than processing all detailed information simultaneously.
Data Source
AI summary
A predictive order status system includes one or more processors to receive a request for a current order status of an order for a computing environment, the order having at least one task representing a segment of an order process for completing the order and the request associated with a unique order identifier, determine the current order status for the order for the computing environment, the current order status comprising a simulated percentage value that is based on an amount of elapsed time since the order was placed divided by a total order process time to complete the order, determine an exception status for the order for the computing environment, the exception status being one of on track to be completed within the total order process time to complete the order, possibly at risk for being completed within the total order process time to complete the order, and at risk for being completed within the total order process time, and send a graphical user interface representation of the current order status and the exception status.