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So, let's walk through the model.
I've kept the overarching themes here on the left.
So, you can see what is the motivation for each of these sections.
We start with the number of opportunities we expect the person to close annually.
Average price per unit is the average price per unit or product for manufacturing.
If you work in a sales SaaS company,
this would be the average price per seat.
Average units per opportunity is the average number of
units you can expect to sell per opportunity.
Average contracts month per opportunity is the average length
of time in months that sales contract can be for.
Next, we get to the average opportunity size.
You just take the product of these three numbers,
average price per unit,
average units per opportunity and average
contract months per opportunity to get this number of bookings.
This is the average booking size we expect this salesperson to create on an annual basis.
Next, we see how we are going to get to these booking sites.
We start with the assumption that the center ramp or the length of time we can
expect the new seller to reach full productivity after being hired is three months.
So, we have the projector and hire date here and we use dummy coding.
Dummy coding refers to when you give a value of zero or one to
a sale because it means something's got to represent something has happened.
It's kind of one and zero are dummies for the presence of something happening.
So, in the sales hiring schedule,
we're trying to create dummy coding for the projected hire date and after that,
indicating a one for the person having been hired.
For this, we use two XOR functions.
One is end of month and the other is today. Let's start with today.
So, for sales person one, say,
we are going to hire them on 12/16.
So, we start with the today function just says okay.
Whatever today's date is,
just add 30 days to it.
Well, since I'm doing the recording on 11/16,
it is just adding 30 days to that and so on.
Here, we're adding 60 days to it and here we are adding 90 days to it.
End of month allows you to state that today date
and add months to that date and give that final date.
So, today's date is 11/16 and is adding
zero months to it but it's giving me the end of the month, which is 11/30.
It does the same thing,
giving it a one-month laps,
two-month laps and a three-month laps.
So, now we can see that the hiring schedule shows that once a person has hired,
a month from then,
they will be employed and available to start generating leads,
and that's what this table is showing.
For the center productivity schedule,
we borrow the end of month function again and get
three months for every month from today.
So, because we are trying to generate
the schedule when the seller is going to be productive,
we want to give the seller three months of ramp time.
So, starting from today,
end of the month of today's month,
just add three months to that.
So, that's what end of month does here.
We're just giving it C14,
which is this month,
this date here and it's adding three months to that,
same here and use the dummy coding to create
the productivity schedule that shows three months since the person was hired,
the person is going to be productive or not.
This matrix describes the productive discussion.
Finally, we get to our projections for when a seller
will be productive and the projected bookings based on that.
Since we only need the bookings the seller will generate per month,
we're trying to calculate that dollar amount per month.
We need to multiply the productivity dummy variable,
here with the projected average booking that we expect based on this number.
So, let me break that down.
So, this is telling us that,
start with this booking number,
130,000 per person times
the number of opportunities the person will be generating per month,
that's this number, and multiply that with this value,
which is whether the person is productive or not.
So, it generates that projected booking per person for
that month based on this and then we can get our total bookings at the bottom.
I made a copy of the CSV,
so you can look at the CSV file yourself too.
Feel free to watch this video again,
slowly, as you follow along with the file on your computer.
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