Planning Promotions

Trade promotions are a key sales driver in many businesses. In the consumer products industry, for example, promotions may drive up to 50% of the overall sales volume. Instead of providing dedicated promotion planning functionality, SAP Integrated Business Planning (SAP IBP) focuses on the integration of promotions that are planned in a Trade Promotion planning system. The key goals to use promotional data in the planning and forecasting process in SAP Integrated Business Planning are:

• Get transparency on promotional sales lift in the planning process.

• Consider promotional sales uplift in a special way during forecasting and demand sensing.

• Facilitate collaboration and alignment on promotions between sales/marketing and demand planners.

• Distribute promotions sales to locations (distribution centers) according to certain rules.

Promotions can be loaded using SAP Cloud Platform Integration for data services (CPI-DS) or by a .csv file upload into SAP IBP. In the case where CPI-DS is used, transformations, and mappings can be performed there. Loaded promotions must contain a product reference. They contain the following additional references: product groups, customers, customer groups, brands, categories, or locations (when the location split was done outside of SAP IBP). Note the following:

• The sales lift or total value stored at the Promotion Level in SAP IBP is not changed.

• The promotion data is distributed to locations (distributions centers) using Advanced Copy operators.

• The Demand Planner uses the Analyze Promotions app to analyze promotions and their allocation to locations. If needed, they can adjust the location split.

• In a forecasting/demand sensing run, promotions can be eliminated from historical data using a dedicated pre-processing step.

• To calculate the consensus demand, future promotions are added to the statistical forecast.

SAP IBP for demand can process promotion data that is stored in a Trade Promotion planning system, such as Trade Promotion Management in SAP CRM. Usually, these systems focus on the sales and financial effects of the promotions, not on the supply chain planning aspect. Typically, they store the data without location information. Data, therefore, must still be disaggregated to the promotion disaggregation level, which also includes the location, in the demand application. You can then do forecasting that takes promotions into consideration.

To use promotions in SAP IBP for demand, your planning area must fulfill some prerequisites. These prerequisites are checked during the activation of the planning area.

In SAP IBP you need, for example, a dedicated planning level for promotions where a key figure with business meaning Promotion Uplift (Source) or Promotion Total (Source) exists.

If a planning area includes promotion key figures with business meaning Promotion Uplift (Source) or Promotion Total (Source), a set of checks is applied during planning area activation:

1. Promotion Level Checks:

   • The promotion level is the planning level at which the promotion source key figure exists.

   • A planning area can have only one promotion level.

   • The aggregation mode of the promotion source key figure has to be sum or custom.

   • Attributes with business meaning Promotion ID and Promotion Source ID have to be assigned as Root.

   • The promotion level must contain an attribute representing product (business meaning Product ID).

   • Up to four more master data type attributes should be selected as Root (for example, PRODUCTID, CUSTOMERID, PRODUCTGROUPID, and BRANDID). Only a warning is raised if this condition is not fulfilled.

2. Promotion Disaggregation Level Checks:

   • Promotion disaggregation level is the planning level at which the key figure with business meaning Promotion Final exists.

   • Aggregation mode of the key figure with business meaning Promotion Final has to be sum or custom.

3. Additional Consistency Checks:

   • The promotion disaggregation level must have the time attribute assigned (for example, weeks) that is defined as Root at the promotion level. In the SAP6 planning area, weeks are used as root time level at the promotion level and technical weeks are used as root time level at the promotion disaggregation level. In addition, weeks are selected as a possible time level at the promotion disaggregation level.

   • Several attributes of the promotion master data type (for example, S6PROMOTION) are used in the Analyze Promotions app (for example, IBPPROMOSTATUS). If they are missing, the system displays a warning message.

The following are the main process steps when processing promotions:

1. Load/calculate location split factors.

   • Controls how the sales lift for a product is split to locations (distribution centers).

   • Are typically product-specific, but may depend on additional attributes, such as customer region.

   • Are stored as a key figure at the Promotion Location Split level.

   • Should be stored using the same time periods as the promotion disaggregation level.

   Ways to upload/calculate Location Split Factors:

   • Upload using SAP Cloud Platform Integration for data services (CPI-DS).

   • Upload from a .csv file.

   • Calculate from historical key figures using the Advanced Copy operator with period offset.

   • Calculate from historical key figures using time periods in key figure calculations.

2. Load promotion master data, then sales lift or Promotion Total values.

   • Load Promotion Master Data (using CPi-DS or a .csv file upload).

   • Load sales lift key figure of promotions (using CPI-DS or a .csv file upload).

3. Check the promotions transferred in the Analyze Promotions app.

   This step is optional. Customers can decide if they want to check loaded promotions. In the case of problems, the Demand Planner may decide to start a clarification with the responsible promotion planner, and to temporarily exclude a promotion from the planning.

4. Distribute promotion data to locations.

   The promotion sales lift from the promotion level is disaggregated to the promotion disaggregation level according to the factors defined on the location split level. This is realized by the following steps:

   1. Calculate an initial location split of the promotion sales lift at the promotion disaggregation level using the calculated Helper Key Figure for Promotion Split. The resulting location split may not have the correct absolute values yet.
   2. To store the initial location split, the Helper Key Figure for Promotion Split is copied to the stored Promotion Uplift key figure using the Advanced Copy operator.
   3. Disaggregate the promotion sales lift from the promotion level to the Promotion Uplift key figure at the promotion disaggregation level proportionally to its existing values (that is, the initial location distribution calculated previously) using the Advanced Copy operator. Depending on your modeling, a time disaggregation may also happen in this step.
5. Check or adjust the distribution of promotion data to locations in the Analyze Promotions app.
6. Run forecasting/Demand Sensing with the Promotion Sales Lift Elimination pre-processing step.

   Use the Promotion Sales Lift Elimination pre-processing step to remove promotion sales uplift from the sales history key figure. This improves the data basis for the forecasting/Demand Sensing run.

7. Calculate Consensus Demand as a forecast result and add future promotions.
8. Check the forecast result in Excel and use the Analyze Promotions app for further analysis.

The Analyze Promotions app allows you to calculate the success of past promotions. Promotion success is calculated in the root periodicity of the promotion level and can only include data that was loaded before the current period.

Before you trigger the calculation, you must select the key figure that contains the sales data for which you need to determine the average number of sold items. By default, the key figure with the business meaning Actual Sales is selected. If you select another key figure instead, the next time you trigger a calculation, this key figure is displayed.

The result of the success calculation is displayed in the Promotion Success column. By clicking on the percentage value, you can navigate to the details.

For promotions based on key figures with the Promotion Total or Promotion Uplift business meaning, the promotion success is calculated as follows:

• Promotion Total business meaning: Average number of sold items in promotion periods divided by the average number of sold items in periods without promotions
• Promotion Uplift business meaning: Average number of sold items in promotion periods minus the average number of sold items in periods without promotions divided by the average planned uplift

These formulas do not require a baseline calculation.

A period without promotions is a period where no promotion exists for the relevant objects, for example, for product and customer if product and customer are the root attributes of the promotion level. Periods directly before and after promotions are not considered as periods without promotions because of possible pre-dip and post-dip effects.

Promotion success is negative if fewer items are sold in promotional periods than in periods without promotions.

To consider the seasonal behavior of the sales of a product, you select a specific number of periods per season. The following prerequisites apply:

• You specify the number of periods per season at the root time level of the promotion level, that is, the time level in which the promotion is loaded.

• If the number of periods per season is 0 or 1, seasonality is not considered.

• If the number of periods per season is greater than 1, only those past periods in the sales key figure are used for the calculation of the average number of sold items in un-promoted periods that fit to the given seasonality.

To calculate promotion success, the system uses an algorithm with exponential smoothing for calculating the average number of sold items in periods without promotions. Only the periods before the promotion in question are considered for calculating the average. Using this strategy, you take the trends into account that could be observed before the promotion took place. The periods closer to the promotion are given more weight in the exponential smoothing algorithm than the periods further in the past.