How to use the True Calls per Hour Calculation in the Contact Centre

In this article I share how to use the True Calls per Hour calculation in the Contact Centre.

We get into a bit of advanced operations here.  But it’s something that Contact Centre leaders should know and be able to use.


When you hear folks talk about Contact Centre productivity they’re usually talking about the Agents

Usually when we hear people talk about productivity they have their finger pointed firmly at their Agents.

“How can we get our Agents to be more productive?” they ask.

When we ask “What do you mean by productivity?” the most common answer is –

“How can we get the Agents to handle more calls or live chats per hour (day/week)?”

But Quantity Handled per Agent is and always has been a problematic measure

Productivity in a Contact Centre is not about how many calls or chats are handled.

This measure – when directed at Service Level based contacts – has always been problematic.

There are very real mathematical realities at work that put the number of calls or chats handled outside the direct control of the Agent.

When you stop and look at it, the key factors that drive contact quantity up or down per Agent include:

  • The Service Level set and its resulting Occupancy rate
  • The health of the Forecasting, Staffing, Scheduling & Real Time Management process at the interval level
  • The size of the Queue at any given time (known as the Pooling Principle)
  • The undeniable mathematics of random contact arrival (which is why we have Erlang C)

What you need to know about the Pooling Principle in Contact Centers

For Centres that have sorted this out and no longer target Agents on quantity handled – congratulations.

You’re well on the way to enhancing Agent and Customer Experience.

But let’s pause a moment.

Ok Dan (you might say).  Got it.  We don’t (or won’t) target Agents on Quantity Handled for Service level based contacts.  

But for planning, comparative and high level management purposes is there some way we can analyze the quantity handled across different shifts, cities and even countries?

Well I’m glad you asked.

Let me show you how.


The True Calls per Hour calculation

When I teach this in workshops, I like to use the example of making pizzas in a Pizza outlet.

See if you can answer the question posed in the picture below for our fictional Pizza Palace company.


What makes this difficult to answer is that our Delhi outlet is busier than our Chennai outlet.

Perhaps our Delhi outlet is located on the ground level of a busy mall while our Chennai outlet is off the beaten track in a low traffic area.

But we can’t possibly hold Prachi or Sangeetha accountable for how busy (or not) their outlets were – they’re not in the Sales & Marketing Team.

They were hired to make pizzas.

Got your answer?

Ok – let me show you how we normalize the figures so that we can compare them fairly.


In order to correctly compare both Prachi and Sangeetha, you take what they actually ‘did’ (in this case how many pizzas they made) and divide that by the Occupancy rate they experienced during that time.

Once you normalize the data as you see above, we can calculate the ‘rate’ at which both of these people are working.

The use of the word rate is important.

Prachi is working at the rate/speed of 25.3 pizzas per hour.  In other words if her Occupancy rate had been 100% this is how many she would have made.

Sangeetha is working at the rate/speed of 28.3 pizzas per hour. In other words if her Occupancy rate had been 100% this is how many she would have made.

So we can now compare both of our pizza chefs on the same basis because we have factored out the impact of the different Occupancy rates.

That’s how the True Calls per Hour calculation works.

Just substitue calls for pizzas.


But could we have a problem?


Typically at this point in the discussion the topic of Quality comes into the picture.  How good (or not) the pizza looks & tastes.

What we don’t know (or haven’t figured out) yet

What we don’t know in this exercise (at least so far) is the appropriate or best rate at which we should be making pizzas.

Because we want Customers to come back again. And if we don’t give Quality – then what we’re doing is pointless.  We’ll never run a sustainable pizza business.

Studies must be done

Fast food companies are well known for conducting very scientific time & motion studies on how many can be ‘done’ and still deliver the required level of quality.

Contact Centres could learn from their example.

It is very likely that Pizza Palace has conducted in depth time and motion studies.

For purposes of this article let’s assume that they discovered that a pizza chef operating at the rate of 22 – 25 pizzas per hour was ideal.

The required quality standards were achieved without any obvious pick up or loss in productivity.

Now that we have a viable quality range to look at, we can draw some conclusions about the pizza chefs in this story.

Prachi is probably ‘doing fine’.  She’s operating at the upper end of the range and is within range.  But we should still taste her pizza now and then for quality assurance purposes.

On the other hand, Sangeetha is operating outside of the range – and on the high side.  We’d better go taste her pizza to ensure quality hasn’t been compromised.

Of course, if someone looks like they’re operating outside the range and on the high side it could be either:

a) they are in fact working too fast (and thus Quality falls – such as the taste of the pizza)

b) they’ve discovered some kind of process or quality innovation that should be studied and replicated across our other chefs

The best Contact Centres

The best Contact Centres don’t target Agents individually on the quantity of contacts handled (for Service Level based contacts – that caveat must always be there).

But when they want to conduct comparative quantity analyses they use the same normalization technique we used in this story for pizzas.

Some of the conclusions I’ve seen Clients come up with using this technqiue include:

  • For Ireland/Germany/Singapore (name your market or city) we know that on a Saturday afternoon shift the right rate of call handling that delivers on quality is about 12 – 15 calls per hour
  • Our night shift Team calls per hour achievement will always be lower than our day shift Team calls per hour achievement
  • The true calls per hour rate for Japan will always be lower than our calls per hour rate for IndiaWe know that if we see variations in the rate we need to explore the underlying reasons (conduct root cause analysis) and not just blame Agents or push them to go faster

Notice that none of these learnings had to do with targeting individual Agent calls handled.


Why are you still talking about Average Handling Time?

In conclusion for True Calls per Hour

If you seek to compare the rate of contact handling for different times of day, for different shifts, for different cities or countries or across a time period – an educated implementation and use of True Calls per Hour calculation can help.

It’s an advanced operations technique – for advanced Centres – but very powerful.

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