Mobile Device Usage Optimization via Automated Compliance
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Solution Overview
Problem
Enterprises face challenges in optimizing mobile device usage across a large number of devices, leading to inefficiencies and increased costs due to unmonitored and unevaluated usage, which existing methods fail to address effectively.
Innovation Solution
A method that involves obtaining mobile device data through APIs and screen scraping, normalizing it, indexing the data, and creating an optimized usage plan by comparing it against available services, with automated adjustments and remediation actions to ensure compliance and minimize costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring and evaluation of mobile device usage is performed, then compliance can be ensured, but the complexity and time consumption increase significantly
Solution Approach 1:
The system automatically monitors, evaluates, and adjusts mobile device usage without requiring manual intervention. The automated nature of the system allows it to serve itself in detecting non-compliance and implementing corrections, thereby ensuring reliability while minimizing complexity.
Solution Approach 2:
The patent replaces manual mechanical monitoring processes with an automated electronic system that uses software algorithms to detect non-compliance and execute remediation actions, significantly reducing the complexity associated with manual oversight while maintaining or improving compliance reliability.
2Productivity
If comprehensive mobile device usage monitoring is implemented, then usage optimization can be achieved, but the loss of time and resources increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring compliance rules and remediation workflows before non-compliance occurs. This allows the system to quickly respond to usage issues without requiring extensive real-time analysis, thereby optimizing productivity while minimizing time loss.
Solution Approach 2:
The system continuously monitors mobile device usage and provides immediate feedback when non-compliance is detected. This feedback mechanism enables real-time optimization of resource allocation and usage patterns without requiring lengthy analysis periods, thus improving productivity while reducing time loss.
3Extent of automation
If automated remediation actions are implemented, then compliance efficiency improves, but the device complexity increases
Solution Approach 1:
The system automatically executes remediation actions without human intervention, allowing it to self-correct compliance issues. This self-service capability maximizes automation while managing complexity by using standardized remediation protocols that can be applied consistently across multiple devices.
Solution Approach 2:
The system manages complexity by changing parameters in a controlled manner - adjusting device settings, usage limits, and configuration parameters automatically based on pre-defined compliance rules. This approach enables high automation while keeping the system manageable through parameter-based control rather than complex structural changes.
4Measurement precision
If detailed mobile device data analysis is performed, then usage patterns can be optimized, but the loss of information and processing overhead increases
Solution Approach 1:
The system extracts only the specific data elements and usage patterns that are relevant for compliance and optimization purposes, rather than processing all available data. This selective extraction maintains measurement precision for critical metrics while reducing processing overhead by filtering out unnecessary information.
Solution Approach 2:
The system applies partial analysis by focusing on the most impactful usage patterns and compliance-critical data points rather than performing exhaustive analysis on all device data. This approach achieves sufficient measurement precision for optimization goals while minimizing information loss and processing overhead through targeted analysis.
Data Source
AI summary
Systems and methods for mobile device usage optimization are described herein. These methods can include automated mobile device usage data collection, analysis, usage optimization through device level pooling, reallocation, and/or other device plan optimizations.