Power of One

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Achieving Service Level

The ROC and Intraday management teams in WFM strive to meet service level goals throughout every interval of the day, even when unexpected situations arise. The ROC applies intraday management tactics to mitigate unforeseen events such as frontline staff calling in sick, weather events, sudden technical troubles, or unexpectedly high call volumes. And while the ROC takes action to make adjustments to maintaining service level in the face of these events, the WFM teams rely on strong partnerships with call handling agents and supervisors to jointly execute recovery plans.

The "Power of One" was a book published originally by Penny Reynolds and the Call Center School in 2005. Within the book, there were a few short chapters on "Staffing for Speed" and "sharing the Workload". These concepts demonstrated the importance of everyone playing their role and being available to handle the next call and general adherence to schedule.

One of the strongest concepts in the "Power of One" stresses how in a queue of 50 people, the difference of just a single person can impact service level.

Why Service Level?

Power of One - Small Queues

Service level is considered the call center industry standard performance metric.

By monitoring service level and adjusting staff levels by interval, a contact center operation can ensure it is operating at optimal efficiency when measuring availability to customers.

The power of the service level metric is derived by its sensitivity for interval level performance to alert to either poor customer performance or potential waste in over-staffing.

What do we mean by service level sensitivity?

WFM teams leverage software systems which use various statistical models, the most popular being Erlang-C, to predict the waiting time and staffing required to meet the service level objective.

Erlang-C expresses the probability that an arriving customer will be offered to a queue vs. being immediately answered.

For forecasting activities, the Erlang formula is used to determine the precise number of customer service representatives needed to staff a queue, based on a specified target probability of queuing, or service level.

For managing real-time operations, if a queue is overstaffed or understaffed by a single representative, the interval service level will alert operations to potential waste in expenses (overstaffed) or negative impact of availability to customers (understaffed).

Shiny & R Studio

R Studio and Shinyapps allow dynamic visualization and working models, exposing to an online interface. In this example, we've created an online visualization of the "Power of One" - showing the importance of how losing (or gaining) a single call center rep can dramatically impact interval service level.