The Portable MBA in Finance and Accounting, 3rd Edition

(Greg DeLong) #1
Forecasts and Budgets 191

Net cash f lows from financing activities consist of changes in borrowed
funds (short and long term), changes in other long-term liabilities, changes in
common stock, and dividends paid. The only financing activities in this exam-
ple are increases (decreases) in bank loans outstanding. The bank line of credit
is the buffer that keeps assets equal to liabilities and stockholders’ equity. As
assets grow with increases in inventories and accounts receivable, bank loans
increase as well to finance this growth. And as the inventories are sold and the
receivables collected during slower periods, the excess cash is used to repay
the amounts borrowed. Banks typically require that the line of credit be paid
in full at some point during the year. Any excess funds generated after repay-
ment of the bank loans are invested in short-term marketable securities until
required again to finance seasonal growth in assets.


FORECASTING


Sales budgets are inf luenced by a wide variety of factors, including general
economic conditions, pricing decisions, competitor actions, industry conditions,
and marketing programs. Often the sales budget starts with individual sales
representatives or sales managers predicting sales in their particular areas. The
basic sales data are aggregated to arrive at a raw sales forecast that is then
modified to ref lect many of the variables mentioned previously. The resulting
sales budget is expressed in dollars and must include sufficient detail on prod-
uct mix and sales patterns to support decisions about changes in inventory lev-
els and production quantities.
In addition to the input from sales personnel, companies frequently uti-
lize a number of statistical techniques to estimate future sales. For example,
Exhibit 6.6 is a graph of the quarterly sales of Kellogg Company from 1990 to
2000.
The sales appear to demonstrate some variation around an upward trend.
How would one forecast sales for the next 12 quarters? Projecting from the
most recent sales level might overstate the estimates if the last quarter was
unusually high because of, say, the effects of a major advertising campaign or
new-product introduction, or seasonal increases. An alternative is to estimate
the underlying trend in quarterly sales. Exhibit 6.7 presents such a graph.
In Exhibit 6.7, I have estimated a trend line for Kellogg’s quarterly sales
using a statistical technique called regression analysis. This line was estimated
with a statistical software package called Minitab,but the analysis is also avail-
able in Microsoft Excel and many other software programs. The equation for
the trend line is


where Salestis the sales for time t(t=41 for the first quarter estimated, since
our data ended at quarter number 40). Our forecasts for the next 12 quarters


Salest=+×$, , $, .1 475 002t 8 357 73
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