Mobile Device Usage Optimization via Automated Plan Adjustment
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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, as existing methods lack automation and comprehensive data analysis to adjust plans effectively.
Innovation Solution
A method that involves obtaining mobile device data through APIs and screen scraping, normalizing it, indexing for relational analysis, and automatically adjusting plans by comparing usage trends against available services to ensure compliance and minimize costs, with remediating actions for non-compliant devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual monitoring and evaluation of mobile device usage is performed, then comprehensive data analysis can be achieved, but labor costs and time consumption increase significantly
Solution Approach 1:
The system enables automatic self-service through automated data collection via APIs and screen scraping, normalization of usage data, compliance evaluation against policies, and automatic plan adjustment without human intervention. The system monitors its own usage data and adjusts plans autonomously based on predefined optimization criteria.
Solution Approach 2:
Manual mechanical processes of data collection, analysis, and plan adjustment are replaced with automated computational systems. The system uses automated web scraping, data normalization algorithms, compliance evaluation logic, and automatic plan modification to substitute human-operated mechanical processes with automated information processing.
2Productivity
If automated systems are implemented for plan adjustment, then efficiency and speed improve, but system complexity increases
Solution Approach 1:
The automated system performs multiple functions within a single integrated platform: data collection from multiple sources (APIs, screen scraping), data normalization, compliance evaluation against multiple policies, optimization calculation, and automatic plan adjustment. This multi-functional approach consolidates complexity into a unified system rather than separate components.
Solution Approach 2:
The system introduces an automated intermediary layer between usage data and plan adjustment decisions. This intermediary automatically collects, normalizes, evaluates, and processes data to determine optimal plans, serving as a mediator that translates raw usage information into actionable plan modifications without human intervention.
3Measurement precision
If comprehensive mobile device data is collected and analyzed, then optimization accuracy improves, but data processing requirements and computational resources increase
Solution Approach 1:
The system extracts only the essential and relevant usage data needed for compliance evaluation and optimization decisions, rather than processing all possible data. It focuses on extracting key metrics that directly impact plan optimization, filtering out unnecessary information to reduce computational burden while maintaining analysis accuracy.
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.