The Pooling Principle in Contact Centers: What Every Manager Should Know

Why can larger groups of Contact Center Agents appear more productive than smaller ones? The answer lies in a mathematical principle known as the Pooling Principle.

This article is part of our Contact Center Management Series — a collection of articles that bring together practical guidance and insights to help Contact Centers run better and deliver stronger results.

Here’s a scenario for the morning

It’s Monday morning and the calls are pouring in.

But you planned well and you’ve got the right Agent capacity in place.

For the morning interval of 9:00AM – 9:30AM, here’s what your statistics look like using a simple Erlang C calculator:

Your Service Level objective is 80/30.

And based on a Talk Time of 4 minutes, an After Call Work time of 2 minutes and a volume of 1,000 calls, you require 209 Agents to log in to capacity so that you can achieve your 80/30.

Thank you, Erlang C. All good.

A quick note on my Erlang C images

I’ve included screenshots from my personal Erlang C calculator to illustrate the calculations, although they may be a little difficult to read.

If you know how to use an Erlang C calculator and have access to one, I encourage you to follow the calculations on your own.

If you don’t, don’t worry.

You don’t need to understand Erlang C to understand the Pooling Principle. But it helps.

Now let’s look at the Occupancy statistics for this interval

In this same scenario, you can see that the Occupancy Rate — which is an outcome or result — stands at 96%.

That’s really busy.

Simply put, that means during this 30 minute interval, your Agents are talking or doing their after call work for 29 minutes.

That means that they will experience only 1 minute of Available Time over the course of that half hour (not much).

What about the Number of Calls Handled per Agent?

Well, if we are receiving 1,000 calls distributed across 209 Agents, that works out to an average of 4.8 calls per Agent for that interval.

Here’s a scenario for the same Center — in the afternoon

In this Center, the Call Load drops significantly in the afternoon.

For the afternoon interval of 4:00PM – 4:30PM, here’s what your statistics look like using our Erlang C calculator:

Your Service Level objective remains at 80/30 (that should be obvious).

Based on a Talk Time of 4 minutes, an After Call Work time of 2 minutes (kept at the same levels as the morning interval for purposes of simplicity) and a volume of 150 calls, you require 35 Agents to log in to capacity so that you can achieve your 80/30.

Thank you, Erlang C.

But notice how Occupancy has changed

You can see that the Occupancy Rate — which is an outcome or result — has fallen from its morning 9:00AM – 9:30AM level of 96% down to a 4:00PM – 4:30PM level of 86%.

Even though we are still meeting the same Service Level of 80/30.

What about the Number of Calls Handled per Agent?

Using simple math — with 150 calls distributed across 35 Agents — that works out to an average of 4.3 calls per Agent for that interval.

This average of 4.3 calls per Agent in the afternoon interval compares to the average of 4.8 calls per Agent in the morning interval.

So if we are using Number of Calls Handled per Agent as a productivity measure in our Center, it looks like productivity declined.

But be careful before drawing that conclusion.

Don’t start telling everyone that the Agents in the afternoon are less productive than the ones working in the morning.

Let’s see what is really going on.

So are the afternoon Agents less productive than our morning Agents?

On an individual Agent level the answer is no.

The Agents who are logged into capacity in the afternoon interval of 4:00PM – 4:30PM are operating in a smaller group of 35 — enough to meet Service Level for that interval.

Compare and contrast that with the morning interval.

From 9:00AM – 9:30AM in the morning we needed 209 Agents to meet Service Level. Obviously that’s a much larger Agent group in the morning as compared to later in the afternoon.

And this is where the Pooling Principle comes into the picture.

What the Pooling Principle teaches us

At the same Service Level objective, Occupancy changes with Agent group size.

At any given Service Level objective — 80/30, 90/10, or 60/120 — smaller groups of Agents naturally experience lower Occupancy than larger groups.

When I teach this principle for certification exam purposes, I summarize it like this:

At the same Service Level objective:

• Larger Agent group → Higher Occupancy
• Smaller Agent group → Lower Occupancy

This is a mathematical reality of the inbound Contact Center.

A dynamic that everyone from senior management through to individual Agents should understand.

How Contact Centers Still Get Productivity Measurement Wrong

Measuring individual Agents by Number of Calls Handled as an indicator of productivity is simply wrong.

There are mathematical realities at work in the Contact Center over which Agents don’t have control.

One of those mathematical realities is the Pooling Principle.

When meeting the same Service Level objective, Agents working in larger groups are naturally busier than those working in smaller groups.

So all things being equal, Agents working in larger groups will handle more calls.

Not because they’re more productive. They’re just busier.

Returning to our original example, would it be fair to claim that the Agents who worked from 9:00AM – 9:30AM on Monday were more productive than those who worked from 4:00PM – 4:30PM?

No — it’s not fair.

Agents don’t control the mathematical outcomes of working in larger or smaller groups.

They simply log in when they are scheduled to do so.

And yet around the world, many Contact Center leaders still judge their Agents by how many calls they take.

A practice that can contribute to poorer quality, increased Agent stress, and unfair performance comparisons.

Another strategic learning about the Pooling Principle

If you are operating with large pools of Agents across many intervals — keep your eye on the Occupancy rates they are experiencing.

The purpose is not to judge them — but to help them.

Industrial psychologists have documented that when Agent Occupancy hits 88% and above for long periods of time (day after day, week after week, month after month), burnout sets in.

Understanding the Pooling Principle also helps leaders make better queue design decisions.

For example whether to split a large queue into smaller queues — or combine smaller queues into a larger queue.

What about Call Handling Normalization?

The Pooling Principle is a topic that should be covered in a fundamentals course.

We’ve taught it for over 20 years and have found it to be an eye-opener for participants who believed that # of Calls Handled by Agent was a valid productivity measure.

For the advanced reader, there are normalization techniques that help you understand an apples-to-apples call handling rate across groups with different Occupancy rates.

In the Contact Center, it’s called the True Call per Hour normalization technique and I’ve written about it here.

Looking Beyond the Numbers

One of the things I’ve learned after decades of teaching Contact Center management is this:

Some of the most important lessons in our industry aren’t intuitive.

The Pooling Principle is one example.

At first glance, the numbers suggest that one group of Agents is more productive than another.

But the mathematics tells a different story.

That’s why understanding the principles behind the metrics matters just as much as measuring them.

Thank you for reading

I regularly share stories, strategies, and insights from our work across Contact Centers, Customer Service, and Customer Experience. If this article resonated with you, I’d be pleased to stay connected.

Feel free to get in touch anytime, or explore more of our work below.

Daniel Ord
[email protected]
www.omnitouchinternational.com