Centralized Rule Generation Microservice for Product Definitions
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Solution Overview
Problem
The existing systems for product definition processing across front, middle, and back offices face inefficiencies due to manual data maintenance, redundant systems, and lack of versioning, leading to wasted computing resources and time due to toxic combinations of product requirements and rules.
Innovation Solution
A method and system for centrally modifying rules in product definitions using a cloud-based architecture, which includes a dynamic database, a rules engine serverless architecture, and a catalog rules architecture, allowing for real-time updates, versioning, and smart approval processes to ensure compatibility and reduce resource wastage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If product definitions are independently established by front office, middle office, and operations in separate systems, then each office can maintain its own requirements and attributes, but this leads to redundant computing resources, data inconsistencies, and wasted time due to toxic combinations of rules
Solution Approach 1:
The patent merges the previously separate product definition systems of front office, middle office, and operations into a single centralized system. This unified system allows all offices to access and contribute to product definitions through a common interface, eliminating redundant computations and data inconsistencies while maintaining the ability to independently establish requirements through coordinated rule generation.
Solution Approach 2:
The system performs preliminary rule generation and validation before product definitions are finalized. By generating rules upfront and checking for toxic combinations in advance, the system prevents wasted computing resources on incompatible product definitions and eliminates the need for repeated back-and-forth modifications between offices.
2Ease of operation
If product definitions are manually maintained across multiple systems, then flexibility in modification is maintained, but this leads to data redundancy, version control issues, and inefficient resource utilization
Solution Approach 1:
The system enables automatic rule generation through templates and predefined parameters, reducing the need for manual maintenance. Users can define product requirements using standardized templates that automatically generate consistent rules across all offices, eliminating data redundancy and version control issues while maintaining operational flexibility.
Solution Approach 2:
The system uses parameterized templates and structured data formats to define product requirements. By changing parameters within standardized templates rather than manually editing free-form definitions, the system maintains flexibility while ensuring consistency and eliminating redundant data across systems.
3Adaptability or versatility
If multiple offices independently process product definitions, then each office can customize its requirements, but this creates toxic combinations of rules and requires repeated back-and-forth modifications, wasting time and resources
Solution Approach 1:
The system performs preliminary rule generation and validation across all offices before product definitions are finalized. By checking for toxic combinations of rules in advance using centralized validation logic, the system eliminates the need for repeated back-and-forth modifications and reduces iteration time while maintaining office-specific requirements.
Solution Approach 2:
The system implements centralized feedback mechanisms that validate product definitions against all office requirements simultaneously. When toxic combinations are detected, the system provides feedback to relevant offices for modification, preventing wasted time on incompatible definitions and reducing the number of iteration cycles needed.
Data Source
AI summary
A method and system for centrally modifying a rule in a product definition are disclosed. The method includes receiving, from a user, a change to a product subject to a set of rules, determining whether the change is incompatible with the set of rules, and when the change is determined to be incompatible with the set of rules, prompting the user to modify the change without storing the data associated with the change in a dynamic database residing on the cloud network. However, when the change is determined to be compatible with the set of rules, capturing data associated with the change in the dynamic database residing on a cloud network for first updating rules data, generating and uploading a data object as a microservice based on the first updated rules data, and versioning the product based on the set of rule objects associated with the product.