okay so I'm going to take you through a short presentation of the Erlang
calculator and first of all, I just want to explain what an Erlang calculator is. In
essence it's very simple. It works out the number of people that you need to handle
a given number of phone calls. So for instance you've got 200 phone calls an
hour. It will work out how many people you need in a call centre to handle that number
off calls. So it's quite straightforward quite a straightforward concept and very
useful thing to use if you're planning in a contact centre. So why is it called
Erlang? It's called Erlang as its named after
the Danish mathematician AK Erlang who developed the formula over 100 years ago
in 1917, and here's a copy of his original paper which was really the
landmark paper and it's amazing that's still so fresh and vibrant over 100
years on and basically works at the probability that call has to wait in the
contact centre and it can convert the number of calls, something called the
average handling time, to go into a little bit better and a service level
into the number of staff that you need. It is very robust and it is in
very widespread use. It's based on something called the Erlang C formula.
Now the Erlang C formula, here's the maths involved behind, it fact it's part of the maths,
believe me the maths does get very scary, very quickly, so it can get quite complex
you need to be able to do series, factorial numbers, exponents and so on.
But luckily for you you don't have to get into all of that maths because an
Erlang calculator does all of that for you and basically what the Erlang
calculator does is it takes a number of inputs. So things like the number of
calls per period, the Average Handle, the average time to handle,
which was known as the average handling time and a service level target and then
based on that it works out the number of advisers that is needed. So in terms of
the inputs typically what you do is you can work out the number of calls
throughout a period in this case we've set it here to 30 minutes. You work out
what the average handling time is, now that effectively is a combination of
both the average time it takes to handle a telephone call but also or the average
amount of talk time, but also the average amount of paperwork that is required
after that call that is specific to a call. You put the two together
and it's called the average handling time and then you put in a service level
target, so for instance answering 80% of calls in 20 seconds now 80% of calls in
20 seconds is the is the typical standard figure if you like use within
the contact center industry a lot of the better contact centers of late have been
adopting a model of answering 90% of calls within 15 seconds. Now some people
say well why can't we answer 100% of calls in 4 rings, that's typically
something that a chief executive will come down, so we're gonna answer 100% of
calls within 4 rings well the problem with that is that probabilities don't do
100%, you can put in 99%. But if you're gonna have 99% of calls answered in 4
rings you need north lot of awful lot of people because sometimes you get calls
bunching up and a lot of the time it can be a bit quiet so a good rule of thumb
is 90% of calls in 15 seconds or a 80% of calls in 20 seconds you can
adjust that and then you can work out the number of advisers needed. That's all
built into the and I calculate we'll do a demonstration in short while and to
give you a rough idea of some of the outputs that come through here some of
the here are some of the outputs work out the number of agents what the
percentage they're likely to be answered within a certain threshold something
called the occupancy. We don't need to get into that quite yet and also the
number of calls and then it produces a graph showing the
number of people you needed and also what happens if you adjusted the number
of people up and down what would happen to the service level it's a very
straightforward nice easy answer. One extra level of complication is that
because the number of calls vary across the day it also has a day planner
built-in that takes account of the variation of contacts across the day. So
for instance in lots of call centers it gets busy mid-morning gets also busier
during the afternoon slackens off a bit lunch time and then it tails off across
the course of the day. Now that does very much depend from one contact center
to another so that is a quick introduction to an Erlang calculator