Configurable RFQ Engine with Meta-Model Designers
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Solution Overview
Problem
Existing RFQ engines are either industry-specific and not applicable to diverse industries or overly generic, failing to meet the complex needs of businesses across various sectors, leading to inefficiencies in generating and executing requests for quotes.
Innovation Solution
A customizable RFQ engine with a data and metrics designer, state transition designer, and workflow designer that uses meta-models to create tailored data, state transition, and user interface workflows, allowing businesses to configure and execute RFQ processes based on specific industry and transaction requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If an RFQ engine is designed to be industry-specific, then it can fulfill detailed industry requirements, but it cannot be applied to businesses in other industries
Solution Approach 1:
The RFQ engine is designed as a universal system that can serve multiple industries through configurable templates. The engine incorporates industry-agnostic core functionality while allowing customization through templates that can be configured for different industries, thus achieving multi-functionality without requiring separate industry-specific systems
Solution Approach 2:
The system uses dynamic configuration where RFQ templates, data models, and workflows can be adjusted based on industry requirements. The engine allows users to modify template parameters, add custom fields, and reconfigure processes without changing the underlying system architecture, enabling adaptability across different industries
2Adaptability or versatility
If a generic RFQ engine is designed to apply to multiple industries, then it has broad applicability, but it is too simplistic to fulfill specific business needs
Solution Approach 1:
The RFQ engine is segmented into distinct configurable components including templates, data models, workflows, and validation rules. Each component can be independently configured to meet specific industry requirements while maintaining overall system coherence, allowing the engine to be both broadly applicable and specifically tailored
Solution Approach 2:
The system implements local quality by allowing specific portions of the RFQ process to be customized for different industries while maintaining standard processes elsewhere. Users can apply industry-specific configurations only where needed, keeping the rest of the system simple and universally applicable
3Adaptability or versatility
If custom RFQ processes are implemented for each industry, then specific needs are met, but the system becomes too complex to maintain and deploy
Solution Approach 1:
The system provides pre-configured RFQ templates and industry-specific configurations that have been prepared in advance. Users can select from pre-built templates and make minor adjustments rather than configuring everything from scratch, reducing the complexity and time required to implement custom processes
Solution Approach 2:
The configuration system uses a nested structure where general RFQ templates contain configurable parameters that can be further specialized. Industry-specific configurations are nested within the general framework, allowing layers of abstraction that manage complexity while maintaining customization capability
Data Source
AI summary
A request for quote (RFQ) engine (10) includes a data and metrics designer (22) that generates, in response to input from a user, a data and metrics model (42) for an RFQ template using a data and metrics meta-model (32). The RFQ engine (10) also includes a state transition designer (24) that generates, in response to input from the user, a state transition model (44) for the RFQ template using a state transition meta-model (34). Furthermore, the RFQ engine (10) includes a workflow designer (26) that generates, in response to input from the user, a user interface workflow (46) for the RFQ template using a workflow meta-model (36). In addition, the RFQ engine includes an execution engine (40) that executes the RFQ template that includes the data and metrics model (42) generated by the data and metrics designer (22), the state transition model (44) generated by the state transition designer (24), and the user interface workflow (46) generated by the workflow designer (26). The RFQ template is executed to generate an RFQ.