IT Service Resource Forecasting for Cost-Aware Optimization Decisions
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Solution Overview
Problem
Existing IT service optimization models fail to integrate business and technical departments effectively, leading to increased costs and suboptimal resource allocation, as they prioritize disorder minimization over economic feasibility, resulting in inefficient management and decision-making.
Innovation Solution
A service providing system that integrates business and technical departments by using an optimization algorithm to analyze resource usage and capacity, applying neural networks and big data analysis to predict optimal service environments, and support decision-making through economic feasibility analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If technology prioritizes disorder minimization and expansion through duplicating and tripling, then service reliability is improved, but investment and costs increase
Solution Approach 1:
The patent applies parameter changes by transforming the optimization criteria from traditional reliability-focused parameters to economic feasibility parameters. The system changes the decision-making parameters to include cost-benefit analysis, ROI calculations, and economic impact assessments, enabling resources to be allocated based on both reliability requirements and economic viability rather than solely on disorder minimization.
Solution Approach 2:
The patent introduces an intermediary decision support system that mediates between technical departments (focusing on reliability) and business departments (focusing on costs). This intermediary layer provides integrated analysis that considers both reliability metrics and economic factors, facilitating balanced decision-making that satisfies both technical and business requirements without excessive investment.
2Loss of time
If business focuses on present status and ROI evaluation, then decision-making speed is improved, but service optimization quality deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-calculating and pre-analyzing the impact of potential service optimizations before final decisions are made. The system performs preliminary cost-benefit analysis, predicts future performance metrics, and prepares optimization scenarios in advance, enabling rapid decision-making while maintaining high optimization quality through thorough preliminary evaluation.
Solution Approach 2:
The patent implements feedback mechanisms that continuously monitor service performance, investment returns, and optimization outcomes. This feedback loop provides real-time information about the actual impact of optimization decisions, allowing for rapid adjustment and refinement of future decisions while maintaining both speed and quality through iterative improvement based on measured results.
3Reliability
If technique focuses on service quality management, then service quality is improved, but economic feasibility is overlooked
Solution Approach 1:
The patent applies universality by creating a multi-functional decision support system that simultaneously handles technical service quality management and economic feasibility analysis. The same system performs both reliability assessment and cost-benefit evaluation, ensuring that service quality improvements are always weighed against economic implications, thus preventing technique-focused decisions from overlooking financial viability.
4Ease of operation
If separate operation management systems are constructed for business and technique, then departmental autonomy is improved, but organic cooperation deteriorates
Solution Approach 1:
The patent applies merging by integrating business and technical operation management systems into a unified platform that maintains departmental autonomy while enabling organic cooperation. The combined system allows both business and technical departments to access shared data, perform joint analysis, and make coordinated decisions without requiring complete system consolidation, thus preserving autonomy while improving collaboration.
Data Source
AI summary
The present disclosure relates to a service providing system and method for supporting service optimization operation maintenance and decision-making. In more detail, the present disclosure relates to a service providing system and method for supporting service optimization operation maintenance and decision-making, the system and method being able to create prediction information about the usage and capacity of each of resources optimized through an optimization algorithm on the basis of current status-related status information about the usage and capacity of each of resources that are invested into a service when using an IT service (information communication service), being able to support decision-making for service optimization by providing a result of an optimal service driving environment considering an economic feasibility through comparison analysis using the status information and the prediction information, and being able to support automation of such service optimization.