Stephanie,

now I see... Well, I don't think you should call this data cyclical. At
first I thought you were talking about a product with seasonal behavior
but this is not the case. Judging from the headers and having charted
the data: We have an overall growth pattern but large fluctuations from
month to month, which is to be expected. Problem is, the fluctuations
are rather large and they do not follow a specific pattern.

In this case we have two choices: linear and exponential, unless there
exist some other market-dependent conditions which would dictate a
different type of function, e.g. quadratic. I give you two equations:

Linear:
=122198.98*K2+13264930
Exponential:
=12055159.54*EXP(0.0131488112808613*K2)

In both cases, K2 should contain the number of months between the start
of your data and the month you want the projection for. You can use the
function DATEDIFF(date2,DATE(2004,1,1),"m") to calculate this. For
date2 you should use DATE(yr,month,day), i.e something like
DATE(2007,5,1) for May 2007.

However, I am afraid this is as far as my statistics will go. The
number you will produce with these formulas is an estimate, however
with low confidence. Maybe one of the resident experts, like Jerry
Lewis, will jump in and direct you further so that you can also
calculate the plus-or-minus expected fluctuation from the projection.

HTH
Kostis Vezerides

steph44haf wrote:
This stuff is great, but it might be a little over my head. Here is my data,
unfortunately I didn't follow how to do the equations. I sort of figured out
how to use Solver, but I wasn't sure what data I need in what columns, since
I only have two rows right now. If you can't help me any more, I understand
but I want to say thank you for your help already Kostis!

Month Year Default Claims Paid
Jan-04 17,414,897.94
Feb-04 10,699,109.47
Mar-04 18,332,334.50
Apr-04 14,275,140.03
May-04 12,305,352.33
Jun-04 13,907,155.18
Jul-04 11,963,018.44
Aug-04 19,201,480.28
Sep-04 15,623,457.98
Oct-04 7,077,725.63
Nov-04 15,740,422.12
Dec-04 13,761,418.33
Jan-05 21,340,245.83
Feb-05 9,409,514.83
Mar-05 10,572,805.35
Apr-05 12,339,659.95
May-05 11,986,746.47
Jun-05 10,252,392.46
Jul-05 12,416,685.61
Aug-05 17,892,569.26
Sep-05 26,618,694.92
Oct-05 7,581,879.50
Nov-05 15,579,836.07
Dec-05 21,710,331.63
Jan-06 21,665,556.58
Feb-06 13,653,795.27
Mar-06 14,457,680.21
Apr-06 18,774,698.52
May-06 17,775,539.97
Jun-06 16,774,408.35