SSFTD Capacity Planning Using Wait Time Analytics
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Solution Overview
Problem
Current methods for determining the need for additional self-service financial transaction devices (SSFTDs) like ATMs focus solely on utilization, neglecting other factors that affect the end-to-end user experience, such as wait times and usage patterns, leading to suboptimal user experiences.
Innovation Solution
A system that collects and analyzes transaction-level, session-level, and user wait time data using an enhanced SSFTD user wait time model to identify recommendations for installing additional SSFTDs, incorporating hardware and software components for data measurement and storage, and employing statistical outputs to optimize user wait times and overall experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If capacity planning is based solely on utilization statistics, then the planning process is simple and straightforward, but the user experience is suboptimal due to neglecting wait times and usage patterns
Solution Approach 1:
The patent changes the parameters used for capacity planning from simple utilization statistics to a comprehensive set of metrics including wait times, usage patterns, and user behavior data. This transforms the planning approach from a single-parameter model to a multi-parameter analysis system that captures the full complexity of user experience factors.
Solution Approach 2:
The patent introduces an intermediary analytical layer that processes raw utilization data and enriches it with additional user experience metrics. This intermediary system acts as a mediator between simple utilization tracking and comprehensive capacity planning, adding value through integrated analysis of multiple data sources.
2Reliability
If comprehensive user wait time data is collected and analyzed, then user experience optimization is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent segments the data collection and analysis system into distinct functional modules: data collection components, data processing components, and analysis components. Each module handles specific aspects of the comprehensive data analysis, making the overall complex system more manageable and maintainable through functional decomposition.
Solution Approach 2:
The system implements self-service capabilities where the capacity planning system automatically collects, processes, and analyzes user wait time data without requiring manual intervention. The system serves itself by generating capacity planning recommendations based on automated analysis of comprehensive user experience metrics.
Data Source
AI summary
Systems and methods are disclosed for determining when installation of additional self-service financial transaction devices (SSFTDs) may be desired at a site to improve end-to-end user experience. The system may collect and store transaction-level data, session-level data, user wait time data, and/or other data, and use an enhanced SSFTD user wait time model to identify recommendations and other statistical outputs. The SSFTD may include hardware and software to assist in measuring and collecting various useful readings.