Cheat Sheet

Excel Sales Forecasting For Dummies

From Excel Sales Forecasting For Dummies by Conrad Carlberg

For confidently and quickly forecasting your sales, Excel is an effective tool. Use some simple rules for establishing your baseline (past data); and then the Excel sales forecasting toolpak, forecast functions, or LINEST function will help you predict your sales with ease.

The Analysis ToolPak in Excel Sales Forecasting

The Analysis ToolPak in Excel sales forecasting figures out what's going on with your data without your having to enter formulas. Excel's Analysis ToolPak has three useful tools for directly forecasting — Moving Average, Exponential Smoothing, and Regression — along with others that can help. Here's a list of some tools that are part of the Analysis ToolPak:

Tool What It Does
ANOVA There are actually three different ANOVA tools. None is specifically useful for forecasting, but each of the tools can help you understand the data set that underlies your forecast. The ANOVA tools help you distinguish among samples — for example, do people who live in Tennessee like a particular brand of car better than those who live in Vermont?
Correlation This tool is an important one, regardless of the method you use to do your forecast. If you have more than one variable, it can tell you how strongly the two variables are related (plus or minus 1.0 is strong, 0.0 means no relationship). If you have only one variable, it can tell you how strongly one time period is related to another.
Descriptive Statistics Use the Descriptive Statistics tool to get a handle on things like the average and the standard deviation of your data. Understanding these basic statistics is important so you know what's going on with your forecasts.
Exponential Smoothing I hate this tool's name — it sounds ominous and intimidating, which the tool is not. When you have just one variable — something such as sales revenue or unit sales — you look to a previous actual value to predict the next one (maybe the previous month, or the same month in the previous year). All this tool does is adjust the next forecast by using the error in the prior forecast.
Moving Average A moving average shows the average of results over time. The first one might be the average for January, February, and March; the second would then be the average for February, March, and April; and so on. This method of forecasting tends to focus on the signal (what's really going on in the baseline) and to minimize the noise (random fluctuations in the baseline).
Regression Regression is closely related to correlation. Use this tool to forecast one variable (such as sales) from another (such as date or advertising). It gives you a couple of numbers to use in an equation, like Sales = 50000 + (10 * Date).

Excel Sales Forecasting Functions

Give these sales forecasting functions in Excel a good baseline and you can get a handle on future sales business. Some Excel forecast functions and their actions appear in the following chart — keep it handy:

Function What It Does
CORREL The worksheet version of the Analysis ToolPak's Correlation tool. The difference is that CORREL recalculates when the input data changes, and the Correlation tool doesn't. Example: =CORREL(A1:A50, B1:B50). Also, CORREL gives you only one correlation, but the Correlation tool can give you a whole matrix of correlations.
LINEST You can use this function instead of the Analysis ToolPak's Regression tool. (The function's name is an abbreviation of linear estimate.) For simple regression, select a range of two columns and five rows. You need to array-enter this function. Type, for example, =LINEST(A1:A50, B1:B50,,TRUE) and then press Ctrl+Shift+Enter.
TREND This function is handy because it gives you forecast values directly, whereas LINEST gives you an equation that you have to use to get the forecast. For example, use =TREND(A1:A50,B1:B50,B51) where you're forecasting a new value on the basis of what's in B51.
FORECAST The FORECAST function is similar to the TREND function. The syntax is a little different. For example, use =FORECAST(B51,A1:A50,B1:B50) where you're forecasting a new value on the basis of the value in B51. Also, FORECAST handles only one predictor, but TREND can handle multiple predictors.

The LINEST Function in Excel Sales Forecasting

The LINEST (or linear estimate) function in Excel sales forecasting uses formulas to calculate a regression equation and related statistics. This chart shows the information the Excel LINEST function will give you:

Column 1 Column 2
Row 1 The coefficient you multiply times the X values The intercept
Row 2 The standard error of the coefficient The standard error of the intercept
Row 3 The R-squared value, or coefficient of determination. The standard error of estimate
Row 4 The F-ratio The degrees of freedom
Row 5 The sum of squares for the regression The sum of squares for the residual

Setting Up Your Baseline in Excel Sales Forecasting

You need to provide a solid baseline (history) in order for your Excel forecast functions to work accurately in Excel sales forecasting. This chart shows you some ways to arrange data for your baseline:

The Issue How to Deal with the Issue
Order Put your historical data in chronological order, earliest to latest.
Time periods Use time periods of approximately equal length: all weeks, all months, all quarters, or all years.
Same location in time If you're sampling, then sample from the same place. Don't take January 1, February 15, March 21. Instead, use January 1, February 1, March 1, and so on.
Missing data Missing data is not allowed. If you have every month except, say, June, find out what June's sales were. If you can't, get the best estimate possible — or start your forecasting with July.
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