"Annual income twenty pounds, annual expenditure
nineteen six, result happiness. Annual income twenty pounds, annual expenditure
twenty pound ought and six, result misery." - Charles Dickens David Copperfield
"A
nickel ain't worth a dime anymore." - Yogi Berra
After reviewing costs, sales projections, and compiling our
cash flow projections over the previous 3 weeks, we turn this week to analyzing
our statements using sensitivity analysis and discussing the use of different
financial scenarios.
Now that we have our completed financial projections we can
begin playing with the numbers to better understand our company. First we need
to think about the figures we just developed and try to determine the key
assumptions that were made. Do we think that everything hinges upon the sales
price we used? Maybe we think it is our ability to secure a certain cost of
materials, or to charge and collect a certain amount of shipping revenue?
If, for example, our figures were created with a sales price
of $10.00 per unit, what happens to our cash needs (from Part V of our series,
the amount of money needed to get our company to a cash flow positive state) if
we can only sell our item for $9.00? We need to understand how vulnerable our
company is to changes to our assumed figures. It may be that a change in sales
price from $10.00 to $9.00 makes it impossible for this company to ever become
profitable. It may be that the change has virtually no effect. If the change is
drastic than we know our company is very sensitive to the sales price, but
maybe we can find something to alleviate that sensitivity (maybe increasing
shipping fees or find an additional source of revenue) or maybe the company is
a no-go due to that sensitivity. Either way we would want to know prior to moving
forward.
The other thing that sensitivity analysis can do is uncover
hidden dangers. Perhaps we are certain about our cost of materials but find out
that a slight increase in those costs could be devastating. Once we've studied
our company's sensitivity to our assumptions we can make changes to our
assumptions, or even modify the company's business model.
In this manner we need to play with our spreadsheet, alter
the numbers in our assumptions, or alter combinations of our assumptions (e.g.,
what happens if we adjust our sales price and
our rent?) and see the effect these have on our projections. This helps us to
understand the interplay between the components making up our revenues and
costs.
Now we can also create separate financial projections for
different scenarios. We can make full sets of projections with different
assumptions to show what could happen if we have to sell for $9.00, or if our
material costs are higher than estimated. This can lead to
"optimistic", "pessimistic" and "most likely"
scenarios.
After conducting sensitivity anaylsis and compiling different
optimistic, pessimistic and most likely scenarios you may begin to wonder just
what are your actual cash needs? Well there are a few ways to answer that
question. You can simply use your original financial projections and chalk the
extra work up to better understanding the key characteristics of your company.
There are also a few methods others have suggested for what
to do with your different scenarios. Say you have a pessimistic scenario with
cash needs of $25,000, an optimistic scenario with cash needs of $10,000 and a
most likely scenario with cash needs of $22,500. Which should you use as the
real cash need for your company when considering whether or not to start this
business?
One is to simply take the highest number, but this may be the
least realistic of any approach as it does not take into account the likelihood
that this would be your true need. In our example the highest cash need comes
from the pessimistic scenario but how likely is this scenario to happen?
Another method is to take the average of your pessimistic,
optimistic and two-times your most likely scenario. So in our example: $25,000
+ $10,000 + 2x$22,500 = $80,000 / 4 = $20,000. This method factors in the
pessimistic and optimistic scenarios while weighting the final number with the
most likely cash need.
Another method we've heard of is to take the greater
difference between either your most likely and optimistic, or your most likely
and pessimistic, and then add that difference to your most likely number. So
$22,500 - $10,000 = $12,500 (most likely minus optimistic); $25,000 - $22,500 =
$2,500 (most likely minus pessimistic). The greater of the two is $12,500 and
we add that to our most likely number $22,500 + $12,500 = $35,000. This method
is designed to provide more of a safety net.
You can also simply weight each scenario based upon your
understanding of the true likelihood of each scenario and come up with your
figures that way.
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