Exception Filtering for Forecasting and Replenishment Systems
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Solution Overview
Problem
Automated forecasting and replenishment systems generate a large number of business exceptions that are difficult to manage due to their transient nature and lack of filtering mechanisms, leading to unresolved issues as they are either overwritten or buried in queues, making it challenging for users to address them effectively.
Innovation Solution
A system and method for storing, selecting, filtering, and resolving exceptions generated by forecasting and replenishment processes, allowing users to browse, search, filter, and respond to exceptions based on predefined business profiles and areas of expertise, using a database system that associates exceptions with attributes and business areas, enabling targeted exception handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated forecasting and replenishment systems generate exceptions for manual review, then error detection capability is improved, but the large volume of transient exceptions makes them difficult to locate and resolve
Solution Approach 1:
The system stores exceptions in a database before they are lost or overwritten, performing the action of preserving exception data in advance. This allows exceptions to be retrieved and reviewed later, preventing information loss while maintaining automated error detection.
Solution Approach 2:
A database serves as an intermediary between the forecasting system and users. Instead of exceptions being transient dialog messages, they are stored in a persistent database that mediates between generation and review, enabling reliable retrieval and filtering.
2Speed
If exceptions are displayed as transitory dialog messages, then immediate review is possible, but they are overwritten or queued making them hard to locate later
Solution Approach 1:
Exceptions are stored in a database in advance, preserving them before they would be lost. This preliminary storage action enables both immediate access when needed and long-term retention, resolving the contradiction between quick review and later locatability.
Solution Approach 2:
The system moves exceptions from a transient, single-dimension display (dialog messages) to a persistent, multi-dimensional storage structure (database with filtering capabilities). This dimensional change allows exceptions to be accessed both immediately and later through various filter criteria.
3Quantity of substance
If all exceptions are presented to users without filtering, then complete information is provided, but users cannot efficiently find exceptions relevant to their expertise
Solution Approach 1:
The system segments the large set of all exceptions into smaller, manageable subsets based on user expertise and business areas. Instead of presenting all exceptions at once, they are divided and organized by category, allowing users to efficiently find relevant exceptions while maintaining access to complete information when needed.
Solution Approach 2:
Different users receive different filtered views of exceptions based on their local needs and expertise areas. The database provides local quality filtering where each user sees exceptions relevant to their specific business area, while the complete exception data remains stored and accessible.
Data Source
AI summary
A system, computer-readable storage medium and method for storing, filtering, selecting and manipulating business exceptions generated by forecasting and replenishment processes and systems. When an exception is generated, it will be associated with attributes corresponding to those business objects and business areas to which the exception relates. Exceptions may also be associated with administrative attributes such as status, priority and generation date, as well as information identifying the specific business process that generated the exception. Alternatively, forecasting and replenishment exceptions may be logged or stored in a database for future review and treatment. Within an exceptions monitor or workbench tool, a business replenishment specialist may browse, search, select, review, filter, rearrange, edit, forward and/or respond to generated exceptions. Exceptions may be filtered tacitly according to a user profile associated with the business replenishment specialist. Alternatively, exceptions may be filtered according to explicitly supplied selection criteria.