When the Existing Workforce Model Could No Longer Scale
THE SITUATION
When I joined Energy Federation, Inc. (EFI), the Customer Service operation was already under significant pressure.
The organization supported energy-efficiency and rebate programs for more than 140 utility relationships across multiple states, including major utilities such as Duke Energy, Eversource, American Electric Power, and Xcel Energy.
The operating environment was unusually complex.
There was no single standardized utility program. Contract requirements, incentive structures, customer processes, and program rules varied by utility and geography.
Customer Service supported three distinct areas of work:
Rebates/Incentives • Marketplace • Data Processing
The contact center was receiving approximately 14,000 to 30,000 calls per month, with demand changing significantly based on seasonality and changes to state and federal energy-efficiency programs.
Yet the organization was attempting to support that environment with approximately 16 Customer Service representatives.
Headcount Is Not Capacity
On paper, there were 16 people.
Operationally, there were not.
One of the first issues I identified was the difference between organizational headcount and actual productive capacity.
A 16-person roster does not produce 16 continuously available agents.
Breaks, lunches, PTO, absenteeism, coaching, one-on-ones, training, meetings, after-call work, and back-office responsibilities all reduce the number of employees available to handle customer demand at any given time.
With shrinkage approaching approximately 30–35%, a nominal 16-person workforce could translate into only 10–11 available agents during portions of the operating day.
That distinction was critical.
The organization wasn't experiencing an isolated performance problem.
It had a structural capacity problem.
Even during lower-volume periods, workforce modeling indicated that the operation required substantially more productive capacity than the existing staffing model could consistently provide.
During peak periods, the gap became extreme.
At volumes approaching 30,000 monthly calls, modeling indicated that approximately 35 agents needed to be actively available to support service-level and abandonment objectives.
Once shrinkage was incorporated, that translated into a workforce requirement approaching 50 employees.
The existing model had approximately 16.
THE BUSINESS RISK
This was not simply a workforce-planning exercise.
The consequences were already reaching customers.
The service objective was approximately:
70% of calls answered within 30 seconds
with an abandonment objective of:
3% or less.
Under constrained conditions, service level could fall into the single digits—at points approaching 2%—while abandonment could climb dramatically, sometimes reaching 40–60% during severe periods of demand and understaffing.
Average speed of answer deteriorated.
Customer complaints increased.
Better Business Bureau complaints began appearing.
Customers increasingly bypassed EFI and contacted their utility providers directly.
That created a much larger business risk.
EFI was not simply serving individual consumers.
It was operating on behalf of utility companies.
When customers could not reach EFI, the service failure did not remain inside the contact center.
It traveled upstream to the client.
Utility partners began expressing concern about service performance. Some indicated that they were evaluating alternative providers, making the risk of contract loss increasingly real.
One smaller utility relationship was ultimately lost.
More importantly, several substantially larger relationships were potentially exposed.
At that point, the problem was no longer:
How do we improve contact-center KPIs?
It was:
How do we create enough stable capacity to protect the customer experience and the client relationships supporting the business?
The Obvious Answer Was More Employees
Capacity modeling made one conclusion difficult to avoid:
EFI needed substantially more staffing.
But identifying the staffing requirement and economically supporting it were two different problems.
The domestic operating model carried significantly more cost than the hourly wage visible on a job posting.
An employee earning approximately $16 per hour represented substantially greater fully loaded organizational expense once benefits and the infrastructure required to support the employee were considered.
That included not only direct compensation, but portions of:
Supervision • Quality Assurance • Training • Workforce Management • CCaaS/Telephony • Facilities • Corporate and G&A Support
Using the organization's internal cost methodology, the fully loaded annual cost of a domestic agent was approximately $83,000–$86,000.
That created an uncomfortable economic reality.
The operation needed considerably more capacity.
But simply scaling the existing domestic model to the required headcount would have created millions of dollars in additional annual operating expense.
Temporary Staffing Was the First Alternative
Before moving toward outsourcing, I evaluated a less disruptive option.
Temporary staffing appeared to offer greater flexibility.
If demand increased, temporary workers could be added.
If volume declined, the workforce could contract.
In theory, that addressed one of EFI's largest challenges: highly variable demand.
In practice, it did not solve the underlying problem.
The work was too complex for a simple contingent-labor strategy.
Training for either Marketplace or Incentives could require approximately six weeks, followed by roughly two weeks of nesting before an employee became independently productive.
Cross-training into the second area could require another six weeks.
That meant EFI could not simply add temporary employees when demand increased and remove them when demand declined.
By the time employees were recruited, trained, nested, and productive, the demand environment could already be changing.
Turnover made the problem worse.
The organization found itself repeatedly recruiting and training replacements without creating enough stable capacity to materially improve service.
The temporary model gave us labor flexibility. It did not give us workforce stability.
Service performance remained challenged.
Abandonment remained elevated.
Complaints continued.
And management capacity was increasingly consumed by a cycle of recruiting, training, losing, and replacing employees.
The Problem Was the Workforce Model
That led to a different conclusion.
EFI did not simply need more people.
It needed a workforce model capable of expanding capacity without making the economics of the operation unsustainable.
Any viable alternative had to solve several problems simultaneously.
It needed sufficient capacity to support highly variable demand, a stable workforce capable of absorbing significant training, scalability during seasonal and program-driven peaks, service coverage aligned with U.S. customers, appropriate controls for a regulated utility environment, strong quality and performance governance, and economics that allowed the organization to staff closer to actual demand.
Those requirements changed the outsourcing conversation.
The question was no longer:
Can labor be purchased somewhere for less?
It became:
Can we design a different delivery model that gives the organization the capacity it needs at an economically sustainable cost?
THE ECONOMIC REALITY
A nearshore model in the Dominican Republic emerged as a viable alternative.
The proposed approximately $16-per-hour rate was materially different from the $16 hourly wage paid to a domestic employee.
The nearshore figure represented a largely bundled vendor rate covering the agent and significant portions of the infrastructure required to employ and support that person.
At approximately $16 per hour, the modeled annual vendor cost was roughly:
$33,280 per agent
compared with an internally calculated domestic fully loaded cost of approximately:
$83,000–$86,000 per agent.
At the modeled seat-cost level, the difference approached 60% before retained governance, transition, and other internal costs were considered.
At scale, the economics became significant.
A 25-agent domestic workforce using the existing cost structure could represent more than $2 million in annual expense.
At 50 agents, the cost could exceed $4 million.
The nearshore model created the possibility of adding the capacity the operation actually required without scaling cost at the same rate.
Labor Arbitrage Wasn't Enough
The modeled economics were compelling.
But lower labor cost alone was not sufficient to justify the decision.
EFI served utility clients operating within highly regulated environments, and the work required significant training, quality control, operational oversight, and consistency.
A lower-cost workforce that introduced greater customer, operational, or compliance risk would simply replace one problem with another.
The nearshore model therefore had to be evaluated as an operating strategy—not a labor-rate exercise.
The Dominican Republic offered a combination of materially different workforce economics, scalability, close alignment with U.S. Eastern operating hours, and the ability to build a dedicated team around EFI's processes.
That combination made the strategy viable.
THE DECISION
Moving work outside the United States was not culturally easy for the organization.
There was understandable concern about outsourcing customer interactions, particularly given the complexity of the programs and importance of the utility relationships.
But the alternatives had been tested against operating reality.
Maintaining the existing staffing model was not sustainable.
Scaling the domestic model to the capacity required was economically difficult.
Temporary staffing had not produced the workforce stability necessary to solve the problem.
And continuing without sufficient capacity was creating increasingly serious customer and contractual risk.
The decision to pursue nearshore delivery was therefore not primarily a decision to reduce labor cost.
It was a decision to redesign the workforce model.
The lower unit economics made it possible to build the capacity the operation needed.
But the business objective was larger:
stabilize service, protect utility relationships, create scalable capacity, and restore confidence in the Customer Service operation.
THE LEADERSHIP INSIGHT
The workforce analysis reframed the problem for leadership.
The organization had been experiencing the symptoms:
High abandonment.
Low service levels.
Long waits.
Customer complaints.
Employee turnover.
Utility dissatisfaction.
The capacity model connected those symptoms to a structural cause.
The organization was attempting to deliver a level of service that its existing workforce model could not consistently support.
That distinction matters.
Performance problems are often treated as execution failures.
Hire faster.
Coach harder.
Improve adherence.
Reduce handle time.
Ask employees to do more.
Those actions may improve performance at the margins.
But they cannot solve a structural mismatch between customer demand and available capacity.
Sometimes the leadership decision is not how to make the existing model perform better.
It is recognizing when the existing model itself has become the constraint.
THE OUTCOME
The analysis changed the organization's understanding of the problem.
What initially appeared to be a contact-center performance issue was ultimately a structural mismatch between customer demand, workforce capacity, and the economics of the existing delivery model.
The decision was made to pursue a nearshore strategy in the Dominican Republic, creating a path to build substantially greater capacity without reproducing the cost structure that had constrained the domestic model.
But choosing a different labor market did not solve the problem by itself.
The next challenge was considerably more complex:
How do you turn an outsourcing decision into a high-performing operating model?
That became the next phase of the transformation.
CONTINUE THE TRANSFORMATION
Case Study 002: Beyond Labor Arbitrage
How a Nearshore BPO Strategy Became a Scalable Operating Partnership
— Steven Waltz
About the Author
Steven Waltz is a Customer Operations and Customer Experience executive focused on service transformation, operational excellence, global delivery, BPO strategy, AI-enabled operations, and enterprise customer experience strategy.
