Contact Center Model Optimization via Historical Data Simulation
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Solution Overview
Problem
Traditional contact center telecommunications networks lack the capability for rapid analysis and planning of staffing, budgeting, and service quality goal setting, and are unable to accurately assess the impact of changes in staff, budgets, and service goals on performance.
Innovation Solution
A network configuration optimization system that analyzes historical data to derive and optimize model parameters, creating a contact center model that can simulate different scenarios and provide rapid analysis and planning for staffing, budgeting, and service quality goal setting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional contact center telecommunications networks are used, then the system structure is simple, but the capability for rapid analysis and planning of staffing, budgeting, and service quality goal setting is lacking
Solution Approach 1:
The patent introduces an intermediary analytical system that sits between the contact center operations and the decision-making process. This intermediary layer processes historical data, runs simulations, and generates forecasts without requiring fundamental changes to the core telecommunications network structure, thus enabling rapid analysis while maintaining system simplicity.
Solution Approach 2:
The patent replaces manual mechanical planning processes with automated computational models and simulations. Instead of manually analyzing historical data and creating plans, the system uses computer-based analytical models that automatically process data, run multiple scenario simulations, and generate optimized staffing and budgeting recommendations, dramatically improving productivity.
2Measurement precision
If traditional contact center networks are used, then the system is easy to operate, but the ability to accurately assess the impact of changes in staff, budgets, and service goals is limited
Solution Approach 1:
The patent implements feedback mechanisms where the analytical system continuously processes actual contact center performance data, compares it against forecasts and simulations, and refines its models. This feedback loop enables increasingly accurate impact assessments as the system learns from actual operational outcomes, while the automated nature of the feedback process maintains ease of operation.
Solution Approach 2:
The patent performs preliminary simulations and forecasts before actual changes are implemented. By running multiple what-if scenarios in advance and assessing potential impacts beforehand, the system provides accurate predictions about the effects of staffing changes, budget adjustments, and service goal modifications without requiring complex real-time calculations during operation.
3Manufacturing precision
If historical data is analyzed to create optimized models, then planning accuracy improves, but data processing and model construction complexity increases
Solution Approach 1:
The patent segments the complex data processing task into distinct modular components: data extraction from historical sources, data cleaning and transformation, model parameter estimation, simulation execution, and result analysis. This segmentation allows each component to be optimized independently and simplifies the overall process by dividing complexity into manageable, sequential stages.
Solution Approach 2:
The patent changes the parameters and structure of analytical models based on the specific characteristics of the contact center data and business requirements. By adapting model parameters to match actual operational patterns and using flexible model structures that can be configured for different scenarios, the system achieves high accuracy without requiring overly complex processing procedures.
Data Source
AI summary
A method and system for creating contact center models are described. Model parameters may be derived from and optimized using historical data. The model parameters may be used to construct an analytic model, which said analytic model may be used to create a contact center model using the optimized parameters. In an embodiment, a distribution may be determined that is demonstrative of a virtual representation of the historical environment of the contact center operation environment at different time intervals. The distribution may be used to transform inputs where there is a discrepancy between the simulation model time interval and the time interval for a generated forecast.