Automated Process Performance Analysis Platform
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Solution Overview
Problem
Conventional methods for evaluating and analyzing network and operations management processes are time-consuming, costly, and require significant human monitoring, often relying on external consulting firms to identify inefficiencies.
Innovation Solution
A remote network management platform that automatically collects and logs process performance data, enabling automated statistical analysis to evaluate and improve process performance by classifying processes into categories like incident management, request management, and problem management, and generating graphical representations for performance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional manual monitoring and observation methods are used to evaluate process performance, then human expertise and subjective judgments can be applied, but the process becomes time-consuming, costly, and requires significant human resources
Solution Approach 1:
The patent replaces manual human monitoring and observation with an automated computer-implemented system that collects process data from databases and generates performance evaluations automatically. The system uses software algorithms to analyze process instances, states, and transitions without requiring human operators to manually observe and assess process performance, thereby eliminating the time and resource constraints of conventional methods
Solution Approach 2:
The system enables process performance evaluation to be self-performing through automated data collection from existing process databases, automatic analysis of process instances using predefined criteria, and automated generation of performance reports. The evaluation process serves itself by utilizing already-collected process data and applying analytical rules without external human intervention, making the evaluation efficient and continuously available
2Measurement precision
If external consulting firms are engaged to analyze process inefficiencies, then expert analysis and recommendations can be obtained, but the cost and complexity of the evaluation process increases significantly
Solution Approach 1:
The system performs process performance evaluation and inefficiency identification automatically using computer-implemented algorithms that analyze process data from existing databases. The system self-configures by collecting process instances, states, and transitions from the database, applies analytical criteria, and generates evaluations without requiring external consulting resources, thereby reducing both cost and operational complexity
Solution Approach 2:
The evaluation system is designed to be universally applicable across multiple process types and organizational contexts. It can evaluate various process instances (incident management, request management, problem management) using the same automated framework, eliminating the need for specialized external consultants for each different process type and reducing overall system complexity through standardization
3Loss of information
If manual process observation is conducted to identify inefficiencies, then detailed process understanding can be achieved, but the ease of operation and accessibility of evaluation results deteriorates
Solution Approach 1:
The system replaces manual observation with automated computer-implemented data collection and analysis that continuously monitors process instances, states, and transitions from the database. This automation preserves detailed process information through structured data capture while simultaneously improving ease of operation by making evaluations automatically available through user interfaces without requiring manual intervention or specialized access procedures
4Measurement precision
If comprehensive process data collection and analysis is performed, then accurate performance insights are obtained, but the productivity and speed of getting evaluation results decreases
Solution Approach 1:
The system performs preliminary data collection by continuously gathering process instances, states, and transitions from the database in advance of any specific evaluation request. This pre-collected data is readily available when evaluation is needed, allowing the system to quickly generate accurate performance insights without the delay of ad-hoc data collection, thereby simultaneously maintaining measurement precision and improving productivity
Solution Approach 2:
The system maintains continuous operation by constantly collecting and analyzing process data from the database, ensuring that performance evaluations are based on the most current and comprehensive information available. This continuous data collection and automated analysis pipeline enables the system to deliver accurate performance insights rapidly, as the analytical engine is always ready to process new data without interruption or manual initiation
Data Source
AI summary
A system and method is disclosed for performance analysis of processes in a managed network. Processes may be represented as sets of activities, and an audit database may be configured for logging activities within the managed network. Database may include fields to identify process instances, process classes, process states, and process transitions. A server device may receive a request from a client device to view information representative of multiple process instances. The server device may select a plurality of process instances according to filter criteria applied to the data fields of the audit database records, and generate a graphical representation of interconnections between the one or more data fields of the selected plurality based on a statistical analysis of the one or more data fields of the audit database records corresponding to the selected plurality of process instances. The server may then transmit the graphical representation to the client device.