Inventory Valuation Engine Using Residence Time Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional inventory valuation techniques overestimate inventory values by failing to account for relevant factors that predict future sales, such as the age of items in inventory and their residence time, leading to either overstocking or understocking.
Innovation Solution
A computer-executed method that generates a future sales estimate for items in inventory by considering prior performance data and inventory residence time, adjusting valuation based on the item's staleness, and using this data to adjust notification policies and pricing strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional inventory valuation techniques are used, then simplicity of valuation process is maintained, but measurement precision of inventory value deteriorates
Solution Approach 1:
The patent segments the inventory valuation process into distinct components: accessing inventory data, determining residence time, retrieving performance data, and generating future sales estimates. This segmentation allows each component to be optimized independently while maintaining overall system manageability, resolving the contradiction between precision and complexity.
Solution Approach 2:
The system performs preliminary actions by pre-accessing and storing performance data and residence time information before the actual valuation is needed. This preparation work is done in advance so that when valuation is required, the complex calculations can be executed efficiently using pre-retrieved data, thereby improving precision without proportionally increasing operational complexity.
2Measurement precision
If inventory residence time and prior performance data are considered, then measurement precision of future sales estimate is improved, but loss of time in data processing increases
Solution Approach 1:
The patent implements preliminary action by pre-retrieving and caching performance data and residence time metrics from databases before they are needed for valuation. This advance preparation reduces the actual processing time during valuation operations, as the system doesn't need to query and process raw data in real-time, thus improving accuracy without proportionally increasing processing time.
Solution Approach 2:
The system uses feedback mechanisms where prior performance data from historical sales is continuously incorporated into future sales estimates. This feedback loop allows the system to learn from past patterns and improve prediction accuracy over time without requiring proportional increases in processing time, as the feedback is integrated into an efficient computational framework.
3Productivity
If accurate future sales estimates are generated, then productivity of inventory management is improved, but device complexity increases
Solution Approach 1:
The patent implements a multi-functional valuation system that not only generates future sales estimates but also determines inventory residence time, accesses performance data, and provides recommendations for inventory decisions. This universal system consolidates multiple functions into a single integrated platform, improving overall inventory management productivity while managing complexity through functional integration rather than separate systems.
Solution Approach 2:
The system employs self-service mechanisms where the valuation engine automatically retrieves necessary data, performs calculations, and generates estimates without requiring manual intervention for each valuation task. This automation improves productivity by eliminating repetitive manual processes, while the standardized self-service framework actually reduces operational complexity compared to manual methods.
Data Source
AI summary
Certain embodiments provide a computer-executed method for generating a future sales estimate for an item. The method includes programmatically accessing, from a dataset via a network device, an inventory residence time period of an item. The method also includes programmatically accessing, from the dataset via the network device, prior performance data associated with the item. The method also includes programmatically executing an inventory valuation engine to generate a future sales estimate for the item based on the inventory residence time period and the prior performance data. The method further includes executing a notification generation engine to adjust a notification policy defining a frequency or other characteristic of electronic marketing communications indicating the item transmitted to consumer devices based on the future sales estimate.