Contextual Support Message Generation for Multi-Layer Systems
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Solution Overview
Problem
Conventional support systems for enterprise software deployments are inefficient, fault-prone, and time-intensive, leading to increased costs due to inefficient routing of support requests, inadequate context description, and lack of structured mechanisms for symptom identification and error resolution.
Innovation Solution
A method for generating contextual support messages by collecting data from multiple layers of a computing system, including user interface, services, business object, and application server layers, to provide intelligent, context-specific support, allowing for efficient incident identification, assignment, and resolution, and enabling the creation of a knowledge base for repeatable processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional support systems are used for enterprise software deployments, then support requests can be handled, but the costs increase and efficiency decreases as the number of users increases
Solution Approach 1:
The system enables self-service by automatically collecting context data from multiple system layers and generating support messages without requiring manual intervention from support staff. The automated context collection and message generation allow the system to serve itself in preparing support requests, reducing the need for human operators.
Solution Approach 2:
The invention changes the parameters of support request handling by collecting data from multiple layers (user interface, services, business object, application server) and transforming this data into structured context information. This parameter transformation enables more efficient routing and handling of support requests, improving productivity without proportionally increasing staff.
2Ease of operation
If conventional support routing is used, then support requests can be directed to support entities, but requests are often not routed to the correct entities leading to inefficiency
Solution Approach 1:
The system implements feedback by collecting context data from multiple system layers and using this information to determine the appropriate support entity for routing requests. The context information provides feedback about the incident's nature and location, enabling accurate routing decisions that reduce resolution time and improve operational ease.
Solution Approach 2:
The system performs preliminary action by collecting and analyzing context data before routing the support request. This advance preparation of context information allows the system to pre-determine the appropriate support entity, eliminating delays associated with manual routing decisions and improving both ease of operation and time efficiency.
3Loss of information
If users provide support requests without adequate context, then support requests can be submitted, but the situation requiring support cannot be adequately described or simulated
Solution Approach 1:
The system applies segmentation by dividing context collection into distinct layers: user interface layer, services layer, business object layer, and application server layer. Each layer contributes specific context data, ensuring comprehensive information collection without overwhelming complexity. This segmented approach systematically captures all necessary context while maintaining manageable system architecture.
4Reliability
If conventional support processes are used, then support requests can be handled, but the processes are not repeatable as a structured mechanism for symptom description and cause identification
Solution Approach 1:
The system achieves repeatability by standardizing parameters for context collection across all support requests. By defining consistent data collection points at each layer (user interface, services, business object, application server) and using uniform message generation processes, the system creates a repeatable structured mechanism that maintains reliability without excessive complexity.
Data Source
AI summary
User-generated input may be received to initiate a generation of a message associated with an incident of a computing system having a multi-layer architecture that requires support. Thereafter, context data associated with one or more operational parameters may be collected from each of at least two of the layers of the computing system. A message may then be generated on at least a portion of the user-generated input and at least a portion of the collected context data. Related apparatuses, methods, computer program products, and computer systems are also described.