Operations Maturity Model for Event-Based IT Assessment
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Solution Overview
Problem
It is challenging for organizations to determine and maintain a high level of computer operations maturity due to varying needs, resources, and expertise, making it difficult to compare and improve their operations effectively.
Innovation Solution
An operations maturity model is implemented using an operations management system that associates events with organizations, generates sub-scores based on event metrics, and provides a weighted operations maturity score, along with recommendations for improvement, while considering geolocation and sensor information for localized adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If organizations implement comprehensive monitoring and evaluation systems to assess computer operations maturity, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent segments the operations maturity assessment into multiple distinct metrics including incident response time, problem resolution time, service availability, and customer satisfaction. Each metric is measured and evaluated separately, then aggregated to provide a comprehensive maturity assessment. This segmentation allows for precise measurement of each aspect without requiring a single complex monolithic system.
Solution Approach 2:
The patent creates a universal operations maturity model that can be applied across different organizations and IT environments. The same set of metrics and evaluation framework is used universally to assess maturity levels, enabling comparison between organizations while maintaining measurement precision through standardized methodologies.
2Productivity
If organizations adopt standardized best practices to improve computer operations, then productivity improves, but adaptability decreases
Solution Approach 1:
The patent implements a dynamic maturity model where organizations can select and weight different metrics based on their specific needs and priorities. The evaluation framework adapts to each organization by allowing customization of which metrics are most important, while still providing standardized measurement methodologies. This enables organizations to adopt best practices while maintaining flexibility to prioritize areas most relevant to their operational context.
3Measurement precision
If detailed event metrics are collected and analyzed, then measurement precision improves, but loss of information increases due to data volume
Solution Approach 1:
The patent extracts and focuses on specific key metrics from the vast amount of operational event data, such as incident response time, problem resolution time, service availability, and customer satisfaction. Rather than attempting to analyze all available data, the system identifies and measures only the most critical metrics that directly indicate operations maturity, thereby maintaining measurement precision while avoiding information overload.
Solution Approach 2:
The patent transforms raw event data into meaningful metrics by applying specific transformations and aggregations. Event data is converted into measurable parameters like response time and availability percentages, which are then used for maturity assessment. This parameter transformation reduces data volume while preserving the essential information needed for accurate measurement.
Data Source
AI summary
Embodiments are directed towards an operations maturity model. An operations management system may associate events with one or more organizations. Event metric information may be provided based on the events for one or more sub-scores. The sub-scores may be scaled to fit within a defined range. An operations maturity score may be provided for the organizations that may be based on the scaled sub-scores. One or more recommendations may be provided to increase the operations maturity score for the organizations based on operations maturity scores that correspond to the one or more organizations. Providing the recommendations, includes providing a correlation of operations practices and the sub-scores and providing configuration recommendations based on the operations practices that are correlated with above average sub-scores.