Service Territory Set Evaluation Using Historical Route Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Service providers face challenges in modifying territory sets due to the rigid organization of warehouses, loading docks, and service contracts, which are based on existing territory sets, making it difficult to adapt to changing service preferences and constraints.
Innovation Solution
A method to determine a preferred territory set based on historical service event data, generating candidate territory sets, and evaluating their servicing values to identify improvements over the current set, allowing for reorganization of warehouses and fleet management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the territory set is modified to improve service efficiency, then service delivery optimization is improved, but the organization of warehouses, loading docks, and service contracts becomes difficult to maintain
Solution Approach 1:
The system performs preliminary evaluation of candidate territory sets by calculating servicing values based on historical service event data before implementing changes. This allows the service provider to assess the impact of territory modifications on route efficiency, vehicle utilization, and labor costs before actually reorganizing warehouses, loading docks, and service contracts, thereby resolving the contradiction between improving service delivery efficiency and maintaining organizational stability
Solution Approach 2:
The system establishes a feedback mechanism that continuously monitors service event data and recalculates servicing values for territory sets. This feedback loop enables the service provider to understand how current territory configurations perform in practice and makes informed decisions about when and how to modify territory sets, balancing the need for optimization with the stability requirements of warehouse and loading dock organization
2Productivity
If historical service event data is analyzed to determine preferred territory sets, then route efficiency is improved, but data processing complexity increases
Solution Approach 1:
The system extracts only the essential elements needed for territory set evaluation from historical service event data, such as service locations, dates, and event types. By focusing on extracting only the relevant data elements required for calculating servicing values rather than processing all available data, the system improves route efficiency while limiting the increase in data processing complexity
Solution Approach 2:
The system creates simplified representations or models of historical service event data that capture the essential patterns and relationships needed for territory set evaluation. These simplified data models enable efficient analysis of route efficiency without requiring the complex processing of raw historical data, thereby resolving the contradiction between improving route efficiency and managing data processing complexity
Data Source
AI summary
Processors obtain instances of service event data and generate a plurality of territory sets. The processors determine a plurality of respective servicing values based at least in part on the instances of service event data. A respective servicing value is determined for each territory set of the plurality of territory sets. A respective servicing value for a respective territory set is determined based at least in part on at least one path that links the respective service locations located within a particular territory of the territory set on a particular service date. Based on the plurality of respective servicing values, a preferred territory set is identified from the plurality of territory sets. Responsive to determining that the preferred territory set satisfies one or more provision criteria, the processors cause information corresponding to the preferred territory set to be provided.