Location-Entity Workflow Data Attribution for Supply Chain Delay Analysis
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Solution Overview
Problem
Current supply chain monitoring tools only track stoppage time and do not provide sufficient information to determine the actual causes of delays or inefficiencies, making it difficult for transport and logistics providers to remedy these issues effectively.
Innovation Solution
Systems and methods that process location- and entity-based workflow data to attribute stoppage times and activities to specific locations or entities, generating statistics that help identify and address delays and inefficiencies within the supply chain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If current supply chain monitoring tools track stoppage time, then time measurement capability is improved, but information completeness for determining actual causes of delays deteriorates
Solution Approach 1:
The patent segments the supply chain into discrete locations and entities (carriers, drivers, facilities) and attributes stoppage time to specific segments. This allows granular tracking of where time is lost and by whom, transforming aggregate stoppage data into location- and entity-specific metrics that reveal actual causes of delays.
Solution Approach 2:
The system establishes feedback loops by continuously collecting location data, entity data, and workflow data, then attributing stoppage time to specific entities and locations. This feedback mechanism enables carriers and drivers to see their performance metrics and take corrective actions to reduce their contribution to supply chain delays.
2Device complexity
If workflow data is aggregated without entity attribution, then data processing simplicity is improved, but ability to identify and remedy delays deteriorates
Solution Approach 1:
The patent segments workflow data by location and entity identifiers, creating discrete data elements that can be attributed to specific carriers, drivers, and facilities. This segmentation enables targeted analysis of delay causes without requiring complete reprocessing of all workflow data, maintaining operational simplicity while improving reliability.
Solution Approach 2:
The system introduces location data and entity data as intermediary layers between raw workflow data and analytical insights. These intermediaries enable automatic attribution of stoppage time to specific entities without complex manual analysis, bridging the gap between simple data collection and reliable delay identification.
3Adaptability or versatility
If location data and entity data are collected separately, then data collection flexibility is improved, but data correlation capability deteriorates
Solution Approach 1:
The patent implements continuous collection of location data, entity data, and workflow data through integrated monitoring systems. This continuous data stream ensures that all three data types are consistently captured and correlated in real-time, maintaining both collection flexibility and correlation precision without requiring periodic batch processing.
Solution Approach 2:
The system uses feedback mechanisms to continuously correlate location data with entity data and workflow data, automatically updating attributions as new information becomes available. This continuous correlation process maintains measurement precision while allowing flexible data collection from multiple independent sources.
Data Source
AI summary
Implementations relate to systems and methods for processing workflow data and providing location-based and/or entity-based workflow statistics. A processing module or other logic can receive workflow data related to operations of vehicles though a supply chain network comprising a set of locations. The processing module can process the workflow data by generating various context views, filtering out some of the data, and other functions. A user or entity can request the processing module for different views or results of the workflow data to gauge efficiencies or inefficiencies in the supply chain. The user or entity can perform modifications to components of the supply chain based on results of the workflow data.