Customer Center Information Discovery System
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Solution Overview
Problem
Customer centers face difficulties in tracking and recording contacts and activities of agents due to the use of different telephones and computers over time, especially when agents use laptops with various customer center telephones, making it challenging to identify and map workspace information accurately.
Innovation Solution
A system and method for discovering customer center information that involves receiving and correlating data from multiple sources, such as customer center agent computers, telephones, CTI servers, and human resources computers, to determine the identity of agents and their corresponding workspaces, enabling accurate tracking and recording of contacts and activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If agents use different telephones and computers over time, then agents have flexibility in using various resources, but it becomes difficult to track and record contacts and activities corresponding to each agent
Solution Approach 1:
The system continuously collects data from multiple information sources including telephones, computers, and authentication systems, and uses this feedback to dynamically update and correlate agent identity information. This ongoing feedback loop ensures that even when agents switch resources, the system maintains accurate tracking by constantly refreshing its data from various sources.
Solution Approach 2:
The system introduces an intermediary correlation process that connects disparate information sources (telephone data, computer data, authentication data) to agent identities. This intermediary layer processes and correlates the data from multiple sources to maintain accurate agent-resource mapping, solving the tracking problem without restricting agent flexibility.
2Measurement precision
If the system collects data from multiple information sources to accurately identify agents, then tracking accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the complex task of agent identification into multiple independent data collection channels, each handling a specific information source (telephone data, computer data, authentication data). This segmentation allows the system to manage complexity by organizing data collection into discrete, manageable segments that can be processed independently and then correlated.
Solution Approach 2:
The system creates a universal correlation mechanism that can handle multiple types of information sources through a single integrated process. This multi-functional approach allows the same correlation logic to process data from telephones, computers, and authentication systems, reducing overall system complexity despite the diversity of data sources.
Data Source
AI summary
A method for discovering customer center information includes receiving a plurality of customer center information from a plurality of respective information sources, and correlating the plurality of customer center information to determine an identity of a customer center agent accessing customer center resources.