Intelligent Self-Service Advisor for IT Service Catalog Navigation
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Solution Overview
Problem
The process of executing a change ticket in IT service management is often costly and time-consuming due to skill, experience, knowledge, and resource constraints, leading to inconsistent execution and delays, as experts navigate through extensive service catalogs with thousands of options.
Innovation Solution
An intelligent self-service delivery advisor utilizing machine learning to analyze change requests, user input, and computer system information, providing dynamic user interfaces with suggested solutions and confidence values, and adapting to user skill levels to facilitate accurate and efficient service ticket execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If experts manually navigate through extensive service catalogs with thousands of options, then they can find appropriate service solutions, but the process becomes time-consuming and costly
Solution Approach 1:
The system enables self-service by automatically analyzing change requests and generating service suggestions without requiring manual navigation through catalogs. The intelligent advisor autonomously processes service data, identifies categories, selects relevant catalogs, and provides recommendations, allowing the system to serve itself rather than relying on expert manual intervention.
Solution Approach 2:
The intelligent advisor acts as an intermediary between the change request and the service catalog. It receives service data, processes it through multiple analysis stages (category identification, task identification, catalog selection), and translates the raw request into structured suggestions with confidence values, bridging the gap between unstructured requests and the extensive service catalog.
2Adaptability or versatility
If experts rely on personal skill and experience to execute service tickets, then they can handle complex scenarios, but execution becomes inconsistent across different experts
Solution Approach 1:
The intelligent advisor system performs multiple functions within a single unified platform: it identifies service categories, identifies specific service tasks, selects appropriate catalogs, generates suggestions, and provides confidence values. This multi-functional system replaces multiple expert knowledge domains with a single universal system that consistently applies the same analytical framework to all service requests.
Solution Approach 2:
The system transforms the subjective parameters of expert skill and experience into objective, measurable parameters. It converts unstructured expert judgment into structured suggestions with quantifiable confidence values (0-1 scale), enabling consistent evaluation and comparison across different service requests and eliminating variability introduced by individual expert differences.
3Adaptability or versatility
If the service catalog contains thousands of options to cover all service needs, then comprehensive service coverage is achieved, but navigating and selecting from it becomes complex and difficult
Solution Approach 1:
The system extracts only the relevant information needed for service suggestion from the extensive catalog. Instead of presenting all thousands of catalog options to the user, it selectively extracts and presents only the top suggestions with confidence values, filtering out unnecessary options and reducing the cognitive load on users while maintaining comprehensive service coverage behind the scenes.
Solution Approach 2:
The system segments the complex service catalog navigation task into distinct analytical stages: category identification, task identification, catalog selection, and suggestion generation. Each stage processes specific aspects of the service data independently, breaking down the overwhelming complexity of navigating thousands of options into manageable, sequential steps that culminate in focused recommendations.
Data Source
AI summary
The present invention provides a method, system, and computer program product of an intelligent self-service delivery advisor. In an embodiment, the present invention includes, in response to receiving computer system service data, identifying, by a second computer system, a computer system service category among a plurality of computer system categories, identifying, by the second computer system, one or more computer system service tasks, based on the computer system service data and the computer system service category, selecting, by the second computer system, a catalog among a plurality of catalogs, based on the one or more computer system service tasks and the computer system service data, generating, by the second computer system, one or more suggestions based on the catalog and the one or more computer system service tasks; and displaying, displaying by the second computer system, the one or more suggestion on a display logically coupled to the computer system.