ACD Interval Analytics for Accurate Contact Center Staffing
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Solution Overview
Problem
Existing contact center systems inaccurately calculate staffing requirements due to counting work items only at the beginning or end of interactions, leading to erroneous scheduling and agent assignment issues, particularly for digital interactions that span multiple intervals with breaks and delays.
Innovation Solution
A computerized method that converts time-based work item-handling data from ACD applications into activity-based measurements, calculating total handle and hold times for each interval, and transmitting this data to a WFM system for accurate scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If work items are counted only at the beginning or end of interactions, then the system is simple to implement, but the staffing requirement calculations become inaccurate
Solution Approach 1:
The patent segments the interaction timeline into multiple time intervals and counts work items at each interval boundary. This segmentation allows the system to capture work item changes throughout the interaction period rather than relying on a single count at the beginning or end, thereby improving measurement precision while maintaining implementation simplicity through automated interval-based processing
Solution Approach 2:
The patent performs preliminary counting of work items at each time interval boundary before calculating staffing requirements. By establishing the work item count at multiple predetermined intervals rather than waiting for the interaction to complete, the system proactively captures accurate staffing data without delaying the overall calculation process
2Device complexity
If work items are counted only once at the end of contact, then the calculation process is simple, but the forecasting accuracy deteriorates
Solution Approach 1:
The patent transitions from a static single-point-in-time counting method to a dynamic multi-interval counting approach. The system continuously monitors and counts work items at each time interval boundary, capturing the evolving nature of interactions. This dynamic approach provides richer data for forecasting while the automated processing keeps the calculation process manageable in complexity
Solution Approach 2:
The patent maintains continuous monitoring of work item counts throughout the interaction period by recording counts at each time interval boundary. This continuous action ensures that all relevant information about work item changes is captured and available for forecasting, eliminating the gaps and inaccuracies present in single-point counting methods
3Productivity
If digital interactions with breaks and delays are treated as single units, then the data processing is simple, but the activity-based measurements become inaccurate
Solution Approach 1:
The patent segments digital interactions into discrete time intervals and counts work items at each interval boundary. This segmentation allows the system to accurately measure activity changes during interactions with breaks and delays, capturing the true activity pattern while maintaining processing efficiency through automated interval-based evaluation
Solution Approach 2:
The patent employs periodic counting at regular time interval boundaries to measure work item changes. This periodic action provides consistent, comparable data points throughout the interaction period, enabling accurate activity-based measurements even for digital interactions with breaks and delays, while the regularity of the intervals simplifies the processing logic
Data Source
AI summary
A computerized-method for enabling true-to-interval analytics from an ACD-application. The computerized-method includes during a shift-schedule having time-intervals, (i) for each time-interval, a. every preconfigured time-period in the time-interval: i. polling data-feed from the ACD-application; and ii. obtaining true-to-interval parameters from the polled data-feed and storing the true-to-interval parameters with start-time of the preconfigured time-period. The true-to-interval parameters include for each contact: 1) a state of activity; 2) handle-time duration; and 3) hold-time duration. b. calculating number of contacts having the activity state, based on the true-to-interval parameters; c. calculating total interval-handle-time and total interval-hold-time for each contact; (ii) calculating total handle-time for all contacts during the time-interval; and (iii) retrieving the calculated total handle-time and total hold-time of each time-interval and a total handle-time of one or more shift-schedules from the tti-database and transmitting it to a WFM application, over a communication channel to enable the WFM application true-to-interval analytics.