Business Process Versioning with Effectivity Dates
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Solution Overview
Problem
Business process orchestration is inefficient due to the need for IT designers to manage multiple versions and effectivity dates, leading to inconvenience and time-consuming deployments, and a disconnect between business analysts' models and implemented processes.
Innovation Solution
A system that allows users to define business processes with effectivity dates and versioning using a user interface, storing this information in a runtime table for dynamic execution, enabling flexible and automated version management without IT intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If IT designers manually manage multiple versions and effectivity dates of business processes, then version control is achieved, but deployment time and operational complexity increase significantly
Solution Approach 1:
The system enables automatic version management where the business process engine automatically handles versioning, effectivity date validation, and deployment scheduling without requiring manual IT designer intervention. The system self-manages the complexity of multiple versions through automated runtime checks and metadata-driven process selection.
Solution Approach 2:
Version information and effectivity dates are pre-configured in the process metadata before execution. The system performs preliminary validation of effectivity dates and automatically selects the appropriate process version based on the current date, eliminating the need for manual version specification at deployment time.
2Manufacturing precision
If IT designers are involved in every version update and deployment, then process accuracy is maintained, but operational efficiency decreases
Solution Approach 1:
Business analysts can independently manage and update business process definitions without requiring IT designer involvement. The system automatically validates the updates against technical constraints and manages the deployment process, allowing business users to maintain process accuracy while significantly improving operational efficiency.
Solution Approach 2:
The system acts as an intermediary between business analysts and the execution environment, automatically translating business process definitions into executable processes. This intermediary layer maintains process accuracy through automated validation while eliminating the need for manual IT designer intervention in the update workflow.
3Adaptability or versatility
If multiple versions of business processes are maintained with different effectivity dates, then business flexibility is improved, but system complexity increases
Solution Approach 1:
The system adds a temporal dimension to process management by incorporating effectivity dates as a metadata attribute. This allows multiple versions of business processes to coexist with automatically managed lifecycle control, providing business flexibility without requiring complex manual version management mechanisms.
Solution Approach 2:
The system dynamically selects the appropriate process version at runtime based on the current date and effectivity date metadata. This dynamic version selection mechanism enables business flexibility to adapt to changing requirements while the system automatically manages the complexity of maintaining multiple versions through metadata-driven process resolution.
4Loss of information
If business analysts model processes without IT designer involvement, then model fidelity improves, but technical implementation quality may decrease
Solution Approach 1:
The system serves as an intelligent intermediary that automatically translates business analyst models into technically sound executable processes. It preserves model fidelity by directly implementing business logic while ensuring technical quality through automated validation, version management, and effectivity date checking, eliminating the need for manual IT designer translation.
Solution Approach 2:
Business analysts can independently create and update process models with confidence that the system will automatically handle technical implementation details. The system self-validates the models against technical constraints and manages deployment, maintaining both model fidelity and implementation quality without requiring business analysts to have technical expertise.
Data Source
AI summary
Particular embodiments generally relate to the orchestration of an order fulfillment business process using effectivity dates and versioning. In one embodiment, a plurality of services in the order fulfillment business process are provided. A definition of a business process including one or more services is received from an interface. The one or more services may be defined in steps to be performed in the order fulfillment business process. An effectivity date associated with the definition is also received from the interface. For example, the effectivity date may be associated with the business process or individual steps in the business process and may specify a period of time during which the process or step can be used. The effectivity dates and versioning may then be enforced at run-time.