Rethinking Workforce Management: Lessons from Two Decades in the Industry

Three Unsolved Challenges in WFM

After more than 20 years in workforce management, I’ve seen technologies change, new methodologies emerge, and contact center strategies evolve. But despite all this progress, three fundamental challenges persist:

• The need for a structured approach to WFM maturity – Too many contact centers struggle with the same issues year after year because they lack a roadmap for improvement.

• The limitations of traditional staffing models – Pre-planned staffing strategies often fail to account for real-world variance and volatility.

• The flaws in capacity planning and budgeting – Many organizations rely on fragile, single-value forecasts that don’t withstand real-world fluctuations.

Each of these challenges stems from outdated thinking and legacy constraints. Over the years, I’ve seen organizations either remain stuck in inefficient cycles or break through by adopting more dynamic, risk-informed workforce strategies. This article captures some of those key learnings.

Challenge #1: The Workforce Management Maturity Journey

Workforce management isn’t just about forecasting and scheduling—it’s about evolving how an organization approaches staffing, automation, and real-time adaptability.

Through my experience, I’ve found that contact centers typically progress through five stages of WFM maturity:

Level 1 - Initial / Manual

At this stage, workforce management is either informal or nonexistent. Schedules are built on instinct, and staffing decisions are made reactively when service levels drop. The focus is survival—handling as many customer interactions as possible, often leading to inconsistent service levels and high operational costs.

Level 2 - Foundational / Legacy WFM Practices

Most contact centers today operate at this level. Forecasting and scheduling are formalized, but the approach is rigid—plans are built assuming minimal variance, and staffing adjustments are largely manual. Shrinkage activities like coaching and training are pre-scheduled, often leading to cancellations when queues get busy. While Level 2 provides stability, it lacks adaptability, leaving operations vulnerable to volatility.

Level 3 - Progressive / Automation-Enabled

This is where organizations shift from pre-planned staffing models to real-time adaptability. Intraday automation plays a key role in dynamically rescheduling breaks, coaching, and off-phone work based on queue conditions. Instead of manually firefighting when things go off-plan, organizations at this stage use automation to balance service levels, employee experience, and cost in real time.

Level 4 - Advanced / Risk-Based Planning

At this stage, organizations move beyond single-point estimates in forecasting and start incorporating variance, volatility, and probability into capacity planning. Advanced techniques like Monte Carlo simulation help leaders understand the likelihood of meeting service goals under different scenarios, making budgeting and staffing plans more resilient. Instead of treating variance as an exception, organizations proactively build variability into their plans.

Level 5 - Pioneering / AI & Workforce Orchestration

Organizations at this level go beyond traditional WFM models, integrating AI-driven forecasting, sentiment analytics, and human-centric scheduling. AI assistants and digital agents are incorporated into staffing models, flexing alongside human agents to stabilize service levels. Rather than focusing purely on efficiency, workforce planning at this stage balances customer experience, employee well-being, and cost optimization.

Most contact centers today operate at Level 2, with some making strides toward Level 3. The challenge is breaking out of rigid, pre-planned thinking and embracing automation, flexibility, and risk-based planning—leading us to the next major lesson.

Challenge #2: Rethinking Net-Staffing & The Case for Erlang-O

For decades, Erlang-C and Erlang-A have been the industry’s go-to staffing models. But they come with a major flaw—they assume the world operates in predictable, static intervals.

The reality? Variance and volatility are constant.

• Call arrival rates fluctuate unpredictably.

• Handle times vary by customer, channel, and issue complexity.

• Shrinkage activities (breaks, coaching, alternative work) are treated as fixed when they could be dynamically adjusted.

  
  

The Problem with "Net-Zero" Staffing

Traditional staffing approaches aim to schedule just the right number of agents to meet demand—assuming everything goes exactly as planned. When it doesn’t, contact centers scramble, canceling coaching sessions, shifting breaks, or adding overtime. 

How Erlang-O Solves This

Erlang-O builds on existing staffing models but accounts for real-world volatility by introducing three critical components:

• Minimal Interval Variance (MIV) – Adjusts staffing to account for natural fluctuations in call arrivals that forecasting can’t eliminate.

• Volatility Factor (VX) – Incorporates demand spikes that traditional models ignore, ensuring staffing plans are resilient.

• Intraday Shrinkage (IS) – Instead of rigidly pre-scheduling off-phone work, shrinkage activities are dynamically scheduled in response to real-time queue conditions.

  
  

Why This Works

Instead of treating variance as an afterthought, Erlang-O bakes it into staffing plans from the start. Some argue that adding extra staffing buffers is just overstaffing, but the key is introducing automation technology to redistribute resources in real time, allowing organizations to optimize both service levels and productivity.

Rather than manually reacting to demand shifts, contact centers using Erlang-O + automation can dynamically:

• Push training or coaching when demand dips

• Redirect resources to alternative channel work

• Minimize unnecessary overstaffing during slow periods

This approach moves WFM from a rigid, pre-planned model to a real-time, adaptable strategy.

Recognizing the Importance of the Employee

A key advantage of Erlang-O is that it doesn’t view extra capacity as idle time but rather as an opportunity to invest in employees. By strategically repositioning the delivery of off-phone activities—such as training modules, coaching sessions, and microbreaks—organizations can improve agent well-being (EX) and protect service levels. Modern WFM automation can:

• Dynamically insert microbreaks into schedules to reduce fatigue.

• Release agents for coaching or skill development during intervals of lower demand.

• Safeguard these investments without harming daily SLAs, thereby reducing burnout and improving retention.

Through technology-enabled automation, Erlang-O allows you the best of both worlds – investments in employees and protecting service level, all while continuously optimizing your staff line – and hence the expenses.  This is the proverbial “have your cake and eat it too!”

Challenge #3: Smarter Capacity Planning with Risk Awareness

One of the biggest lessons I’ve learned is that bad budgets kill call centers.

Many organizations still rely on single-value forecasts, assuming one demand number, one shrinkage percentage, and one staffing plan will work. But in reality, workforce planning exists on a spectrum of possibilities—and the more fragile your plan, the more likely it is to fail.

A Better Approach: Risk-Based Capacity Planning

Instead of betting everything on a single forecast, organizations should quantify their operational risk by assessing:

• Monte Carlo Simulation – Running thousands of possible demand scenarios to understand staffing resilience.

• Flexibility Indexing – Measuring how adaptable schedules and staffing models are to unexpected changes.

• Risk-Adjusted Staffing Models – Incorporating variance, volatility, and automation to proactively address fluctuations.

  
  

What This Looks Like in Practice

• Low-Risk Plans – Have built-in flexibility, allowing for variance without major disruptions.

• Medium-Risk Plans – Depend on some real-time adjustments but may struggle with large shifts in demand.

• High-Risk Plans – Are fragile, requiring overtime, cancellations, or urgent hiring when forecasts are off.

Rather than asking, “What’s our forecast?” the better question is, “How confident are we in this plan, and how will we adjust when things change?”

Conclusion: Moving Toward Smarter Workforce Management

While the contact center industry has evolved, workforce management practices in many organizations remain outdated. The good news? It’s not too late to modernize.

• Moving up the WFM maturity curve gives organizations a roadmap for progress.

• Embracing Erlang-O and automation allows for more adaptive staffing models.

• Using risk-based capacity planning ensures smarter budget decisions and staffing strategies.

By shifting from static, fragile planning to dynamic, risk-aware staffing, organizations can improve service levels, reduce costs, and create a better employee experience—all at the same time.

About the Author

Ted Lango is a seasoned operations executive and founder of Kyōdō Solutions and WFM Labs. With over two decades of experience in contact center transformation, Ted focuses on balancing technology, workforce optimization, and human-centered design.