Case Analysis System for Service Request Cost Allocation
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Solution Overview
Problem
Conventional case analysis applications face challenges in providing detailed cost information and efficient classification of service requests, often relying on manual processes that result in inconsistent analyses and limited breakdown of technical support costs.
Innovation Solution
A case analysis system that utilizes text analytics to classify service requests, automatically generates SQL queries and R code for cost allocation, and employs a hierarchical classification system with user-defined keywords and rules to link costs to specific product issues, enabling detailed cost analysis and prioritization of initiatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual processes are used for classifying service requests and analyzing costs, then flexibility and customization are maintained, but consistency and efficiency deteriorate
Solution Approach 1:
The system enables self-service through automated text analytics that independently classify service requests and allocate costs without requiring manual intervention. The text analytics engine automatically processes service request data, extracts relevant information, and performs cost allocation based on predefined rules, eliminating the need for manual classification while maintaining consistency and accuracy.
2Measurement precision
If detailed cost breakdowns are implemented, then cost analysis precision is improved, but system complexity increases
Solution Approach 1:
The system segments cost analysis into distinct components by categorizing service requests into different problem types, domains, and components. The text analytics engine breaks down cost data into granular segments such as labor costs, parts costs, and logistics costs associated with specific defect types, enabling detailed cost breakdowns while managing complexity through structured classification.
Solution Approach 2:
The text analytics engine serves as an intermediary between raw service request data and cost allocation outcomes. It automatically extracts meaningful information from unstructured text data, maps it to predefined classification categories, and facilitates accurate cost allocation without requiring complex manual processing or intricate system configurations.
3Productivity
If automated text analytics are deployed, then productivity and consistency are improved, but implementation complexity and initial setup time increase
Solution Approach 1:
The system performs preliminary action by pre-configuring classification rules, defect categories, and cost allocation parameters before actual service request processing begins. The text analytics engine is pre-trained with domain-specific vocabulary and classification schemas, enabling it to immediately process service requests with high accuracy without requiring complex real-time decision-making or extensive runtime configuration.
Data Source
AI summary
Case analysis is provided in which costs are associated with case information such as service request data. A description of defect classifications may be defined using keywords and attributes. A database query is generated based on the description of defect classifications to classify case information by problem type to a domain and a component. The description of defect classifications may be applied to a result of the database query to perform problem classification analysis. A cost analysis may be performed by problem group based at least on the case information associated with cost information and the result of the database SQL query.