Workforce Engagement Management

I've noticed something unusual for low volume planning groups. For background, our forecasters manually add the forecast to Genesys and in this case, they'll take the seven forecasted calls and spread that out eventually over the hours of operation. So seven calls is about 0.32 calls per 30-minute interval. Genesys generates the FTE requirement.

I understand that an AHT increase also increases the workload, and therefore the FTE requirement. But why would it calculate that I need nearly a whole person? I understand that more idle time is needed in order to meet the service level objective, but it still seems oddly high to me. It appears the high FTE requirement for low-volume planning groups rolls up and can inflate the overall FTE requirement. I admit I'm not an expert at forecasting, so any help is greatly appreciated.

Queue A

7 calls forecasted for the day

0.2 FTE requirement per interval

AHT is 6:59

Service goal template is set to 60s ASA

Queue B

7 calls forecasted for the day

0.7 FTE requirement per interval

AHT is 8:56

Service goal template set to 60s ASA

Has slighter more calls for the week as a whole over Queue A

#CapacityPlanning
#Forecasting

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Linsey Edn
Workforce Management
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Hello Linsey, 

It can at first sight looks inflated, but it's actually consistent with how queueing models behave under low volume.

Staffing is calculated per interval, not averaged.

Genesys uses queueing theory to meet your service goal in every interval.

With:

~0.32 calls per 30 minutes
A 60-second ASA target

The system isn't thinking "7 calls per day." It's thinking:

"What staffing ensures I can answer any call that might arrive right now within 60 seconds?"

At such low volume:

Many intervals = 0 calls
Some = 1 call
Occasionally = 2 calls close together

Even though the average is tiny, the variance is huge relative to the mean.

To protect your ASA target, the model prepares for:

"What if a second call arrives while the first is still in progress?"

Your key difference:

Queue A - ~7 min AHT
Queue B - ~9 min AHT

That ~2-minute increase significantly raises the chance that:

Call #2 arrives while Call #1 is still active

So the model reacts by increasing staffing toward having:

"someone always available just in case"

That's why Queue B jumps toward ~0.7 FTE, even though workload is still tiny.

A 60s ASA at this volume is very strict.

At low volume, hitting that target often requires:

An agent being idle much of the time because even one delayed call can break service level.

So staffing shifts from:

"Cover the workload" to "Guarantee immediate availability"

It inflates your total FTE because many small, separate queues each require their own "just-in-case" capacity.

So instead of:

1 agent handling all low-volume work you get 0.5–0.8 FTE per queue - which adds up artificially.

So the reason Queue B is so much higher than Queue A, even with similar total volume is:

Higher AHT
Same strict ASA
Same low arrival rate

This leads to a much higher probability of overlap, which forces staffing up disproportionately.

I hope this helps you.