Using Time Series Analysis

Objective

After completing this lesson, you will be able to use time series analysis.

Time Series Analysis

The figure shows you the result of a Time Series Analysis in SAP IBP.

Time Series Analysis: Process

The process consists of the following steps:

  1. You set up the rules for the analysis in the Manage Forecast Automation Profiles app.

  2. You schedule and run the time series analysis in the Application Jobs app.

The properties of time series data can be useful inputs for several automatic and manual forecasting processes. In the current version of SAP Integrated Business Planning, they can be leveraged automatically by XYZ segmentation only.

If you save the properties in an attribute and other results in key figures, you can use those attributes and key figures for limiting and filtering your planning views in the SAP IBP, add-in for Microsoft Excel.

You could modify the values of time series property attribute in the add-in for Microsoft Excel if you wish. However, that is not recommended because the changes you make do not influence the automated forecasting processes.

In addition to filtering planning views, you can also use the saved attributes to filter the set of available planning objects in the Assign Forecast Models app. This app allows you to assign the most suitable forecast model to each planning object.

Currently, this is the only section that you can use for setting the rules for times series analysis. The analysis can assign the following properties to any planning object in the selected planning area:

  • Trend - A continuous time series in which the values consistently increase or decrease.

  • Seasonality - A continuous time series in which the values increase or decrease repeatedly with a certain frequency.

  • Irregular - A continuous time series with high volatility, but no specific pattern.

  • Intermittent - A time series that contains intervals of various lengths between the subsequent sale dates.

  • Lumpy - An intermittent time series in which relatively large deviations can be observed.

  • Continuous - A time series with few missing values and no other patterns.

You can use more categories during the analysis. These categories define the level of details by which the system assigns properties to the analyzed planning objects.

You can choose one or more of the following options by setting the respective buttons to on:

  • Separate Categories per Type of Seasonality:

    The system not only assigns the seasonality property to planning objects, but also the type of seasonality, which can be multiplicative or additive.

  • Separate Categories per Length of Seasonal Cycle:

    The system also saves the length of the seasonal cycles in addition to the seasonality and, if chosen, the additive or multiplicative properties.

  • Separate Categories per Trend Direction:

    The system not only assigns the trend property to the planning object, but also the direction of the trend, which can be upward or downward.

  • Separate Category for Lumpy Demand:

    The system calculates a CV Squared value that shows the volatility of intermittent time series data. If the CV Squared value is higher than the threshold you specify in the next field, the lumpy property is assigned to the planning object.

The categories assigned to a planning object are combined to form property groups such as intermittent with additive seasonality (6) or multiplicative seasonality with trend.

You can choose attributes and key figures for saving the results of the time series analysis at various calculation levels. Choosing an output is not mandatory because the system saves all properties in the background anyway.

Note

If you do not select any attributes or key figures, you cannot check the results of the time series analysis anywhere, not even in the application logs.

If you save the results in specific attributes and key figures, you can use them for limiting and filtering your planning views in the SAP IBP, add-in for Microsoft Excel and for filtering the set of available planning objects in the Assign Forecast Models app, which can help you assign the most suitable forecast model to each planning object.

The figure provides you an overview of Time Series Analysis and Forecasting Algorithms.

Use Time Series Automation Analysis

You want to perform a time-series analysis of your products. The automation of forecasting processes allows efficient planning cycles that require less resource and often result in more accurate forecasts than conventional forecast calculations.

Steps

  1. Create a Forecast automation profile in the Manage Forecast Automation Profiles app using the data in the table provided.

    ParameterValue
    Planning areaIBP600
    Input for analysisActuals Qty
    Unit of Measure to IDKG
    Calculation LevelCustomer ID, Location ID, and Product ID
    PeriodicityMonthly
    Frequency of reanalysis0 Months
    Sensitivity for the Seasonality Test0.2
    Separate Categories per Type of SeasonalityOn
    Significance of Trend Test0.05
    Separate Categories per Trend DirectionOn
    Probability for the White Noise Test0.9
    Intermittency Detection MethodAverage demand interval = 1.33
    Separate Categories for Lumpy DemandOn
    Attribute for Time Series PropertiesTime Series Property (I_TIMESERIE­SPROPERTY)
    1. In the SAP Fiori launchpad, in the Demand Planner group, choose the Manage Forecast Automation Profiles tile.

    2. Choose Create and in the displayed screen, add the data from the table provided.

    3. Choose Save and record the number ID assigned to your profile, next to the Planning Area IBP600.

    4. Choose Home to return to the SAP Fiori launchpad.

  2. Execute the newly created Forecast automation profile.

    1. In the General Planner group, choose the Application jobs tile and choose Create.

    2. Choose the Forecast automation job template, select Start immediately, choose the IBP600 planning area, and choose the forecast automation profile with the number ID you recorded in the previous step.

    3. Use your filter.

    4. Choose Schedule.

  3. View the results of the Time Series Property entry in customer source in the add-in for Microsoft Excel using Master Data Workbook.

    1. In the add-in for Microsoft Excel, in the Master Data section of the SAP IBP ribbon, choose Create.

    2. Choose Master Data Type Customer Source.

    3. Choose OK to view the report.

    4. On the Customer Source tab, filter for your products ending in your ## number.

    5. Scroll to locate the Time Series Property attribute column and view the type of demand entered by the forecast analysis run.

    6. When you finish your analysis, close the view without saving.