Data Driven System for Automated Business Operations
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Solution Overview
Problem
Traditional business processing systems are human-driven, delayed, and inflexible, unable to automatically execute business operations in response to immediate data changes, leading to inefficiencies and challenges in adapting to changing business scenarios.
Innovation Solution
A data-driven system and method that includes a data change sensing module, a data-driven module, and a data footprint module, which automatically detect changed data, execute relevant tasks, and record processing data, enabling real-time and automated business operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional human-driven business processing systems are used, then business operations can be performed with human judgment and experience, but the system cannot automatically execute business operations in response to immediate data changes, resulting in delays and reduced efficiency
Solution Approach 1:
The system enables self-service automation where the data-driven system automatically detects data changes and executes business operations without human intervention. The data change sensing module autonomously monitors data, the data-driven module autonomously selects and executes tasks, and the data footprint module autonomously records processing data, eliminating the need for manual business processing while reducing time loss.
2Adaptability or versatility
If traditional business processing systems are used, then the system structure is simple and easy to operate, but the business model is solidified and cannot adapt to changes in various business scenarios
Solution Approach 1:
The system introduces dynamic adaptability through the data-driven module that can flexibly select and execute different tasks based on real-time data changes. The system dynamically adjusts business processing workflows according to changing scenarios rather than following a fixed solidified model, enabling adaptation to various business situations while maintaining manageable complexity through modular architecture.
3Loss of information
If traditional human-driven systems are used, then business processing knowledge and experience can be applied, but the transfer of business processing experience and knowledge is difficult and time-consuming
Solution Approach 1:
The system replaces the mechanical process of manual knowledge transfer with an automated data-driven approach. Business processing knowledge is encoded into the data-driven module, which automatically applies appropriate tasks and processing logic based on data changes, eliminating the need for manual knowledge transfer while maintaining the effectiveness of business experience and knowledge application.
Data Source
AI summary
A data driven system and a data driven method are provided. The data driven system includes a storage device and a processor. The storage device stores a data change sensing module, a data driven module, and a data footprint module. The processor is coupled to the storage device. The processor executes the data change sensing module to detect changed data. The processor executes the data driven module to obtain business data according to the changed data, and executes a task according to the business data to generate an execution result. The processor executes the data footprint module to record processing data generated during execution of the task.