FREE Call Center Workforce Management Principles Questions and Answers Flashcards
6 cards from real Call Center practice questions. Tap to flip, then mark Knew It or Still Learning โ missed cards come back until you master them.
Read the first 6 FREE Call Center Workforce Management Principles Questions and Answers flashcards as text
What is the primary purpose of an Erlang C formula in call center workforce management?
Answer: To predict the number of agents needed to handle call volume at a desired service level
The Erlang C formula is a standard traffic engineering model used to calculate the number of agents required to meet a target service level based on predicted call volume and handle time.
Which metric measures the percentage of calls answered within a specified time threshold?
Answer: Service Level
Service level measures the percentage of calls answered within a defined time threshold, such as 80% of calls answered within 20 seconds.
What does schedule adherence specifically track in workforce management?
Answer: How closely agents follow their assigned schedules for login, breaks, and logout times
Schedule adherence measures how well agents conform to their planned schedules, including start times, break times, and end times.
In workforce management, what is shrinkage?
Answer: The percentage of paid time where agents are unavailable to handle contacts
Shrinkage accounts for the percentage of scheduled time lost to breaks, training, meetings, absenteeism, and other non-productive activities.
What is the main risk of understaffing during a forecasted peak interval?
Answer: Service levels will drop and abandon rates will increase significantly
Understaffing during peak periods leads to longer wait times, which directly causes service level deterioration and higher call abandonment rates.
Which forecasting approach uses historical call data patterns to predict future contact volumes?
Answer: Time-series analysis using historical trends and seasonal patterns
Time-series analysis examines historical call volume data to identify trends, seasonality, and patterns that can be projected into future periods.