# Learning about Predictive Analysis – Sales Forecasting

Hi at all,

in this blog i would describe a typical scenario of predictive: Sales Forecasting.

This is the scenario that i will devevelop by SAP Predictive Analysis:

The regional manager of an airline company wants to develop strategies to increase business and fine-tune operations. The airline passengers’ data such as flight date and number of passengers traveled, is stored in a CSV file. The manager would like to analyze the trend in business since 2000 and wants to forecast the number of passengers flying in the next year (for example, 2012).

This example assumes that the manager has some basic knowledge in statistical analysis and data mining techniques.

Using SAP Predictive Analysis, the manager creates a forecasting analysis. Since the airline passenger data is seasonal in nature, he selects the Triple Exponential Smoothing algorithm for forecasting.

If you are interested on mathematical details about Triple Exponential Smoothing algorithm, you can go on : http://en.wikipedia.org/wiki/Exponential_smoothing

We have a CSV file, that reppresent the data source and contain the number of passenger by month from  January 2000 to February 2012.

So the first step is, after launch SAP Predictive Analysis, select “New Document”.

Then specify the CSV file as data source and indicate the file to acquire:

Here is possible to indicate also some acquisition options.

After the acquisition of csv file, in the Predict panel from the Algorithms tab, double-click the Triple Exponential Smoothing algorithm.

The algorithm component is automatically connected to the data reader component.

Now Right-click the Triple Exponential Smoothing algorithm and choose Configure Properties for specify the following details

1. Select Forecast as the output mode, as you want to forecast the data.
2. Select Airline Passenger column as the dependent column.
3. The algorithm forecasts the data based on the Airline Passenger column.
4.   In the Missing Values field, select Remove.
5.   In the Period field, select Month(12)
6.   Enter 2000 as the start year.
7.   Enter 1 as a start period. As the period is Month(12), 1 implies first month of the year (January).
8.   Enter 12 for the number of periods to predict
9.   Retain the default values for the advanced properties
10.   Choose Save and Close.

From the Data Writers tab, double-click the CSV Writer component.

Right-click the CSV Writer component and choose Configure Properties for indicate the CSV that will contain the forecast result.

Now  the SAP Predictive Analysis model is completed and it can execute choosing   .

The fitted and forecast results are stored in the CSV file.

Select Results for switch to the analysis visualization view.

In the Components Selector pane, select Triple Exponential Smoothing; by default, the results of the component are displayed in the Grid pane.

To view the visualization chart, switch to the Charts pane.

The SAP Predictive Analysis model can be saved: from the File menu , select Save.