Dynamic Contact Volume Forecasting for Staffing Optimization
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Solution Overview
Problem
Seasonal businesses face challenges in adjusting staffing and resources due to unpredictable and varying contact volumes, making it difficult to provide satisfactory customer service and manage costs effectively.
Innovation Solution
A system and method for contact volume forecasting that uses multiple models, such as event-driven and quantitative models, to initially forecast contact volumes at the beginning of a season and repeatedly revise them as the season progresses, ensuring accurate resource allocation across different contact channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If staffing resources are increased to meet high contact volume, then customer service quality is improved, but staffing expenditures increase
Solution Approach 1:
The patent implements dynamic staffing adjustment by continuously monitoring contact volume in real-time and automatically modifying staffing levels according to actual demand. This allows the system to increase staff during high-volume periods to maintain service quality while reducing staff during low-volume periods to control expenditures, thereby resolving the contradiction between service quality and staffing costs.
Solution Approach 2:
The system employs feedback mechanisms by continuously measuring actual contact volume and comparing it with forecasted values, then using this information to adjust staffing resources. This closed-loop control ensures that staffing levels are optimized based on actual performance data, maintaining service quality while minimizing unnecessary staffing expenditures.
2Quantity of substance
If staffing resources are decreased to reduce expenditures, then staffing expenditures are reduced, but customer service quality deteriorates
Solution Approach 1:
The dynamic adjustment mechanism ensures that staffing is reduced only when contact volume genuinely decreases, preventing service quality deterioration. The system continuously adapts staffing levels to match actual demand, so cost reductions are achieved without compromising service during periods when service is actually needed.
Solution Approach 2:
The system performs preliminary forecasting of contact volume to anticipate future demand patterns. This allows staffing adjustments to be made in advance, ensuring that sufficient staff are available before contact volume increases, thereby preventing service quality deterioration while avoiding unnecessary staffing during low-demand periods.
3Measurement precision
If multiple forecasting models are used to improve forecast accuracy, then forecast accuracy is improved, but system complexity increases
Solution Approach 1:
The patent divides the forecasting system into multiple independent model components, each handling specific aspects of contact volume prediction. This segmentation allows the system to use diverse forecasting approaches (statistical models, machine learning models, rule-based models) for different scenarios while maintaining manageable complexity through modular architecture and clear division of responsibilities.
Data Source
AI summary
Various embodiments of a planning and execution process used to forecast contact volumes that will occur over the course of a season and determine resources necessary to handle the contact volumes are disclosed. The planning and execution process may be used to determine staffing resources necessary to service contact volumes across a plurality of support channels. The contact volume forecast may be continually updated over the course of the season, and different models may be used to generate the contact volume forecast at different times during the season.