AHT (Average + Handle + Time)

I worked for many years in Call Centre / Contact Centre environment and enjoyed it for most of the time except when management, in times of strong pressure, roll back to – as I call it - ‘Extreme Tactical behaviour’.

As Peter Senge, in his famous book ‘The fifth Discipline’ explains, “Management live in the illusion of taking charge…. all too often, proactiveness is reactiveness in disguise. “

What is most disturbing however the inability of managers, in charge of a business, to understand what an ‘average’ or ‘mean’ is, when and how to use it and when not.

One definition of AHT out there is: “Average handle time (AHT) is a call centre metric for the average duration of one transaction, typically measured from the customer's initiation of the call and including any hold time, talk time and related tasks that follow the transaction.”

The simple translation is: Total amount of work time related to the case…divided by the number of cases handled.

In a call centre it is: AHT= Average Talk Time + Average Hold Time + Average Call Waiting Time (ACW) / Total Contacts

In a contact Centre it is the actual processing time not including Customer Hold or 3rd party hold.

 

Why do we use AHT?

AHT is one of the important metrics required to determine the required workforce. However we must consider Takt time as a good scientific alternative, and I would even prefer to use the Theory of constraints to measure flow, then use takt time to determine the workforce required considering the Customer demand and availability of the operators.

Achieving Service Level Agreement (SLA) depends largely on the forecast/prediction of the volume (customer demand), the number of agents and the average handling time.

 

Why we should not use AHT:

- AHT can easily be manipulated

- AHT should not be used to plan for head-count. It is simplistic and usually inaccurate since it does not take into account hourly and daily fluctuations in call volume, or the dead time between cases, or the impact of major failures on both volume and processing time.

- AHT cannot be used in isolation because it does not measure SLAs, Efficiency, Quality, outcome of Customer experience of the call.

- AHT has been used to put the fear of God into staff and points often to a lazy employees without looking at the distribution of the data.

- The focus is on average: averages are at the mercy of outliers. One over-complicated case can ruin the average handling time.

 

To get a good idea of the processing time (or any data for that matter) we must observe 3 points:

              - Central tendency (Average, Median, Mode)

              - Dispersion (Standard deviation, Range, Variation)

              - Shape of the data (distribution) – usually skewed in a call / contact centre see below

What do we need?

  • A Balance between efficiency (AHT/Processing time/Cycle time and other Performance Indicators measuring Flow) and effectiveness (First time resolution). These two have to be in balance.
  • What do we need to achieve this balance between efficiency and effectiveness?
    • Training
    • Help for agents/operators (e.g. .knowledge base)
    • Events (policy changes, rule updates etc…) Check root causes, spikes, statistical analysis
    • Agents to be truly ready at the start of the case or chat -> when taking on the case. Focus on the case until it has been completed and closed.
    • Proper observation of what is requested and involved.
    • The agents must be familiar with the Customer’s business
    • Never allow frustration, boredom or anger to be detectable in a case.
    • Simple cases are easy to keep in line with the preferred AHT. The challenge is with the exceptions and complex cases.
    • What comes next? Agents need to be clear at each step in the process as to what comes next.
    • Control of the case. Too much up and down emailing to get information -> ask the right questions, Structures questions list; 3rd party and Customer Hold…
    • Closing the case. Making sure all is well. Agent is self-checking on accuracy and completeness.
    • Keep seeing AHT as an output metric, not as an input metric.

 

How do we measure Processing time AHT?

Measuring the processing time of easy cases is easy enough and there is usually little variation for that type of cases.

Measuring complex cases is more difficult:

 

Measuring the AHT/Processing time can be done by

  • Video Capture
  • Sample based Time & Motion
  • Interpolation
  • Linear Extrapolation
  • Regression
  • Methods-Time Measurement (MTM)

 

 and

 

- AHT data is available and could be used if put into context with the Monthly variation of volume.

- Time-study agents who work on complex cases. (As I mentioned above simple cases will not differ much in processing time). Next calculate the weighted average and take into CONSIDERATION that AHT varies in time (time of the day, day of the week, month in the year etc.) and varies from agent to agent as well as seasonal volume variation.

 

 ‘Weighted Averages’, NOT by averaging the AHT – since AHT is already an average!

 

Calculating weighted average in Excel:

Week

# Cases

AHT (min)

1

1500

40

2

1800

45

3

2000

48

4

3500

55

Total

8800

188

Weighted Average

48.81

 

 

Formula = (((B2/B6)*C2) + ((B3/B6)*C3) + ((B4/B6)*C4) + ((B5/B6)*C5))

In this case averaging the averages would give us 47 min, not a lot different from 48.81, but that is because there is not a big difference between the # of cases.

 

At this point, after writing all of the above, I realise that we can bring a horse to water but we cannot make it drink. Often I see people using averages of averages; worse, relying on averages and building reports and making decisions without understanding the average and seeing its context in the data and the reality it is supposed to reflect.

Data is there for us to help make up our mind about what it is it is telling us and how it fits in to the overall understanding of a situation. Too often data is used/misused blindly. Every ‘Measurement System Analysis’ I complete reminds me of the dangers of blindly using data and or using bad data. 

To remain in business you have to make the right decisions and understand the limitations as well as the advantages of data. Base your decisions on good reliable data and understand what the data is telling you. The make up your mind and forward your decision.

I hope this blog was useful.

Yours sincerely

Georges Van Cauwenbergh, Master Black Belt