Power of One
Achieving Service Level
WFM teams strive to meet service level goals throughout every interval of the day, even when unexpected situations arise. Automation is critical for intraday management tactics to mitigate unforeseen events such as frontline staff calling in sick, weather events, sudden technical troubles, or unexpectedly high call volumes. While WFM teams take action to make adjustments to maintaining service levels in the face of these events, WFM teams can not respond quickly enough alone, without automation, to maximize opportunities to optimize service levels when variance is introduced.
The "Power of One" was a book published originally by Penny Reynolds and the Call Center School in 2005[1]. Within the book were a few short chapters on "Staffing for Speed" and "sharing the Workload." These concepts demonstrated the importance of everyone playing their role, being available to handle the next call, and general adherence to their schedule. Even with automation, the power of one is an important concept for leadership to understand.
One of the most substantial 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?
Service level is considered the call center industry-standard performance metric.
By monitoring service levels and adjusting staff levels by interval, a contact center operation can ensure it operates optimally when measuring customer availability.
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 that 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 the negative impact of availability to customers (understaffed).
How significant is the impact?
If we examine a queue requiring 50 people to staff, using a demand interval that requires 175 calls with an AHT of 450 seconds, we see we'd need 50 reps to achieve an 80% of calls answered within 30 seconds. We would reach an 82% service level in this scenario, illustrated below. If we lose just a single resource, we see with 49 agents, the service level will drop to 76% and continues to decline rapidly as 2, 3, or more agents are not staffed and ready to take the next call.
In addition, the average speed of answer grows dramatically. If the queue were staffed missing five agents, the average speed of answer would increase by almost 5x, growing from 19 seconds to 285 seconds:
This is a static view based on 175 calls with an AHT of 450 seconds - but what if I want to model a different size queue or different service level objectives? Below is a tool for dynamically calculating different size queues:
Power of One Calculator
A working interactive calculator is available at powerofone.wfmlabs.com. The tool lets you dynamically model different queue sizes, AHT values, and service level objectives, and observe how the loss or gain of a single call center representative changes interval service level.
The previous RStudio Connect / Shiny deployments — Small Queues, Long Queues, and a Japanese variant — have been decommissioned and consolidated into the single calculator linked above.
Power One — full-spectrum staffing impact
A companion tool, Power One (powerone.wfmlabs.com), extends the Power-of-One concept across the full understaffing-to-overstaffing spectrum. Where the calculator above visualizes the loss-of-one-agent move at the interval, Power One renders the entire curve: at the sweet spot, service level is strong and occupancy is sustainable; below the line, burnout risk rises as occupancy spikes; above the line, boredom risk rises as occupancy drops. The two visualizations together capture the tension between service level, occupancy, and cost as staffing moves up or down.
Maturity Model Position
The Power of One concept is foundational, not maturity-bounded — Erlang behavior at the interval is the same at every level. What changes across the WFM Labs Maturity Model™ is how the operation uses the concept:
- Level 1 — Initial (Emerging Operations) — Power of One is unknown to the operation. Service level misses are explained as "we were short" without quantifying the interval-level math.
- Level 2 — Foundational (Traditional WFM Excellence) — Power of One is a training concept that explains why one absent agent matters more than intuition suggests. Used in supervisor education and adherence policing.
- Level 3 — Progressive (Breaking the Monolith) — Power of One is the operational basis for real-time intervention. Variance harvesting decisions (recall a meeting, cancel coaching, pull from off-phone) are quantified against Power-of-One math at the interval.
- Level 4 — Advanced (The Ecosystem Emerges) — Power of One is the demand-side intuition for cost-per-producing-FTE decisions. The cost of one absent agent can be priced explicitly; the cost of one understaffed interval can be quantified in dollars and CSAT impact. The concept feeds the Three-Pool Architecture and the Value-Based Planning Model.
- Level 5 — Pioneering (Enterprise-Wide Intelligence) — Power of One is automated: the operation's autonomous systems continuously evaluate the marginal value of one more agent on each queue, in each interval, and execute. The math runs constantly; humans set policy.
Power of One is structurally relevant to both the real-time operations cluster (interval-level service-level management) and the capacity planning cluster (FTE-marginal-value reasoning). It serves both.
See Also
- Real-Time Operations — cluster hub
- Resource Optimization Center (ROC) — operational home for Power-of-One application in real-time
- Daily ROC Routine — pre-shift, active monitoring, and post-shift cycles where Power-of-One reasoning applies
- Variance Harvesting — the operational principle Power-of-One quantifies
- Event Management — Sev 2-3 thresholds rest on Power-of-One math
- Real-Time Schedule Adjustment — the lever-toolkit that uses Power-of-One reasoning
- Real-Time Cause and Effect Fishbone — the diagnostic Power-of-One feeds into
- Capacity Planning Methods — Power-of-One is structurally a capacity-planning concept
- Workforce Cost Modeling — the cost-side complement; Power-of-One is the demand-side intuition
- Demand calculation — Erlang math behind the interval-level effect
- WFM Labs Erlang-O™ — Erlang formulation extended for outbound and abandonment
- WFM Labs Maturity Model™ — maturity framework
- Future WFM Operating Standard — broader operating standard
References
- ↑ Reynolds, P. (2005). "The Power of One". Call Center School Press.
