Today I am going to discuss about, how we can achieve Forcast Automation using predictive Analytics Scenario.

Predictive Scenario :  In Simple words in SAC using predictive scenarios  we can predict patterns and trends based on Past and current data by applying automatic predictive algorithm.

When you use predictive scenario on the model having present and/or Past data SAC automatically apply predefined predictive algorithm create a training model with all the possible forecasting trends.

Then Trained model has been deployed and applied to generate the forecast data. Using of predictive forecasting reduce the error percentage.

There are three type of predictive scenarios, we can use in SAC to generate Plan/ Forecast Data :

1.Time Series Forcast Predictive Scenario :

Time series forecasting is the use of a model to predict future values based on previously observed values i.e. present and/or past data.  Time series is a Sequence of data point taken at successive equally spaced points in time and apply algorithm on it to predict future trends.

In Time series forecasting  we will create a training model then generate future trends.

When you select Time series as your predictive scenario : When we predict future Forcast/Plan data is based on data points fluctuations over time, variables and sessions then use this scenario.

2. Regression Predictive Scenario : This scenario based on Regression analysis which deals  is a set of statistical processes for predicting the value of a KPI based on the  relationships between another corelated entity value fluctuation or change. The co- related entity called the

The most common form of regression analysis is Linear regression.

When you select Time series as your predictive scenario : When we required to Forecast/Predict Value of a KPI based on the change on driving measures or Dimensions behind it.

For example :  Predict/Forecast of Material Stock Quantity in a warehouse  with respect to change of  in Shipping Date.

Today we will generate Plan Forcast data for 2024 from Actual data of 2023 using predictive scenario Time series Forecast.

3.Classification Scenario: If you’re trying to predict about the occurrence of something to happen, Use a classification scenario.

For example : Try to predict the next year Membership probability in “Yes/NO” based , Market acceptability of a product based on weather etc.

## Today I am going to discuss about the Time Forecasting predictive scenario – where we have source Actual data for 2023 and based on that we will generate a training model and apply the train model to generate the Forcast data for 2024.

The task execution diagram should look like below –

Step A:  We created a Target Plan with Blank Data with name “Time series Forcast 2024” in which we generate forecast data based on predictive forecasting. Created a tory base on both actual and Forcast Version side to view –

Step B : Train and Forecast to generate trends and Training Model. Provide proper source data model, Target KPI (Here Quantity) and entity which will act as a value driver.

Step C : The new training  model will be generated with the trends : 

Step D : Select the predictive model  and save the forecast Model :

Step E : Save the Forecast to the private version and  open the story we developed, You can see the Forcast generated using predictive scenario:

When applied you can see in the below progress log :

The Generated Forecast using time forecasting is generated below –

Next blog . I am going to discuss about the Input Form and SAP Snalytics Cloud.