Posts Tagged ‘Model’

Basics steps to create call centre schedules

Wednesday, January 4th, 2012

In order to accurately calculate the FTE requirements, interval data must be identified for the number of calls answered by the specified group of agents planned within the schedule.  You would need to know the call volume and the AHT, per interval.  To do so, you would use the historical data available.  Ultimately, if shrinkage data is also available per interval, this would be useful in obtaining requirements from a broader perspective..  this aspect we will discuss later.

Depending on your phone system setup or capacity, historical data by interval may not be available for more than 30 to 60 days.  I would therefore recommend that you test your system, and archive if needed, in a tabulator.  Most likely, you will want to create your schedules for the upcoming few weeks.  Depending on your call centre model, the last 4-6 weeks may be very similar to the next 4-6 weeks.  If not, you may want to verify the model of those weeks from previous year(s).  Again, the data availability is key…

Depending on the type of schedules you are creating, classic 5 X 8 schedules on 5-day week vs 4 X 10 on a 7-day week, you may want to gather your interval data in different ways.

For a classic 5-day week, where agents always have the same schedule, you would want to create your model on an average day. To do so, you would calculate the average call volume per interval, and a weighted average for the AHT.

For a 7-day week, where agents have different scheduled start times, you would want to create your model for each day of the week.  This is more time consuming, yet necessary per accuracy of your calculations.

Now that you have your model in place, you would need to calculate the FTE requirements per interval.  To do so, you should use your WFM system, or Erlang C for Excel, as an example.  To find FTE requirements, Erlang C would use the call volume and AHT of the interval, the TSF objective, and the TSF threshold.

From this FTE requirement, you would then need to apply your shrinkage.   Please note, your historical shrinkage may be (is) different per interval.  This being said, you may want to apply your average shrinkage to each interval.  For example, if you have for the same period a 30% shrinkage, you would multiply the FTE requirement by 1.3.  Please note, I think you should be careful with opening and closing FTE requirements.  For example, let’s take an example where you have 3 agents opening your call centre at 8am.  If one of those noted agents are on vacation the following  week, would you be proactive and replace the agent with another ?  If so, I would not apply the same shrinkage percentage to this interval.

From this FTE requirement, with shrinkage, you would then build schedules based on the number of agents you have in this group.  Please note, I will be posting  on the different types of schedules in the near future.

If you have more agents/schedules than required, you should consider confirming any pending time off waitlists for the specified period. Therefore, allowing an increased availability to confirm time off requests, encouraging more time for off the phone activities/trainings etc.

If you have less agents/schedules than required, your business would then need to make a decision:  Are you staffing at the bare minimum during some intervals, or are you averaging the gap throughout the day?

Once you have the schedules created, you would then have the agents bid on the schedule patterns accordingly.  There are different types of bidding processes:  Based either on seniority, rotating schedules, performance etc… We may also encounter a different mix of each.  The pros and cons of each process will be highlighted in a future post… stay tuned.

Why do you need Call Centre Management?

Tuesday, January 12th, 2010

The short answer to “Why do you need Call Centre Management?” is that you need to analyze past data to forecast the future volume in your Call Centre.

To do so, you need to create a model.  Here is a simple example.

Let’s take an ice cream sandwich manufacture and a road side assistance call centre.

Ice cream sandwich manufacture:

  • Open 24/7
  • Objective: 21 000 boxes / week

Road side assistance call centre:

  • Open 24/7
  • Objective: 80/20 (We will talk about this soon!)
  • Two incoming call flows:
    • Sales
    • Assistance needed

For the ice cream sandwich manufacture, the management team would create schedules around the objective.  One of the possible solutions is to have three 8-hours shift per day with the objective of 1 000 boxes per shift.  Which would mean 3 000 boxes a day and 21 000 boxes a week.

For the Road side assistance Call Centre needs to “wait” for the calls to come in.  To a certain extent, the Call Centre do not control how busy it will be.  The idea is to use a model.  A model based on historical data.

For this example, I have created the below model for some intervals in a day.  In real life, it would have been an average day, per interval, including call volume and AHT – Average Handle Time.  (We will talk about this soon!)

As you can see, the call pattern for an average day where the morning starts slow, growing busier, slower around lunch time, then growing busier in the afternoon and finally slowing down at the end of the day.

In this case, we would would obviously try to set the lunch breaks at the middle of the day.  Your staffing model (graph curve) would need to follow the model curve.

If your are scheduling your call centre staff with a pen and paper vs a workforce management application, you would need to create many different models.

Here are some exmaples:

Average Monday, average Tuesday, average Wednesday, (…)  Those daily models would then bring you to a day of the week factor.  Through out the year, your call volume will change.  You will not receive the same call volume every month.  Your call volume and your AHT will differ monthly and weekly.

After gathering your interval data every day, you will get to a point where you have a pattern you can apply to your schedules.  Obviously, you will not receive the same number of calls you gathered from your historical data but you will have at least the model on how the day/week/month will look like.

Next post: What else should I consider besides historical data?

Luc Denis