Geographical Call Display for Automatic Call Distributor Optimization
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Solution Overview
Problem
Current Automatic Call Distributor (ACD) systems lack an effective means to visually display real-time geographical call data, which limits managerial and administrative efficiency in call center operations, particularly in geographically distributed call agent environments.
Innovation Solution
A system and method that integrates an Automatic Call Distributor (ACD) with a display to map the geographic locations of callers and call agents, providing a visual representation of their relationship, including allocation of call agents based on relative proximity and skill sets, using location data and Interactive Voice Response (IVR) information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional ACD systems are used without geographical display, then system complexity remains low, but managerial and administrative efficiency is limited
Solution Approach 1:
A graphical user interface (GUI) is introduced as an intermediary between the ACD system and managers/administrators. The GUI displays geographical information, call data, and agent locations on maps, enabling efficient monitoring and management without requiring direct access to complex system data. This intermediary layer resolves the contradiction by providing simplified visual information that improves productivity while masking the underlying system complexity.
2Productivity
If call agents are allocated based solely on skill sets, then skill matching is optimized, but geographical proximity and communication efficiency are compromised
Solution Approach 1:
The call agent allocation system is made dynamic by incorporating multiple variables including skill sets, geographical proximity, and real-time location data. The system can adapt allocation decisions based on changing conditions such as agent availability, caller location, and skill requirements. This dynamic approach resolves the contradiction by allowing the system to optimize communication efficiency through geographical proximity while maintaining the flexibility to adjust allocations based on various factors.
Solution Approach 2:
The allocation parameters are expanded beyond traditional skill-set matching to include geographical location, distance metrics, and real-time agent status. By changing the parameters used for allocation decisions to incorporate spatial information, the system achieves better communication efficiency while maintaining adaptability through multi-criteria evaluation.
3Productivity
If real-time geographical display is implemented, then call handling optimization is improved, but data processing requirements increase
Solution Approach 1:
The system extracts and processes only the necessary geographical and call data elements required for optimal call handling, rather than processing all available data. By selectively extracting location information, agent status, and call parameters, the system achieves call handling optimization while minimizing data processing requirements and energy consumption.
4Ease of operation
If geographical location data is collected and displayed, then agent-caller proximity is optimized, but information processing complexity increases
Solution Approach 1:
The system creates visual representations (copies) of geographical data and call information through graphical interfaces. Instead of processing complex raw data directly, the system converts location coordinates and call parameters into visual maps and displays, simplifying the information processing complexity while maintaining ease of operation for agent allocation.
Data Source
AI summary
In a call center, a caller's geographical position may be mapped together with a geographical position of a call agent allocated to handle the call. A map may display tags depicting the respective positions of the caller and the call agent with a visual link indicating the call connection. The call agent may be selected dependent on the relative proximity to the caller.