01 Forecasting for SAP Sales

➡️ Sales forecasting is the process of predicting how much of something (a product or a service) someone (a company, a salesperson, a retailer etc.) will sell.

➡️ By predicting the demand correctly, you can maintain right level of inventory (reducing operational cost) at the right fulfillment location (reducing delivery expense) and deliver to their customer quickly (improving customer satisfaction).

➡️ Reliable sales forecasting can play a major role in an organization’s success as it enables important downstream decisions like:

Strategic forecasting: what is the projected growth in terms of total sales/revenue? Where should the business be (more) active geographically?

Operational forecasting: How many units of each product should be purchased from the vendors and with what lead time, and also, in what region should they be placed? How much manpower is required to meet demand?

Tactical forecasting: How should promotions be run? Should products be liquidated? Which geography they should run in?

Sales forecasting in SAP with Amazon Forecast

Over the years, Amazon.com has remained a leader in sales forecasting:

  1. Amazon Forecast is a fully managed service, so there are no servers to provision, and no machine learning models to build, train, or deploy. You pay only for what you use, and there are no minimum fees and no upfront commitments.

  2. You only need to provide historical data, plus any additional data that you believe may impact your forecasts. For example, the demand for a particular color of a shirt may change with the seasons and store location. This complex relationship is hard to determine on its own, but machine learning is ideally suited to recognize it.

  3. Once you provide your data, Amazon Forecast will automatically examine it, identify what is meaningful, and produce a forecasting model capable of making predictions that are up to 50% more accurate than looking at time series data alone.

  4. Amazon Forecast is a fully managed service, so there are no servers to provision, and no machine learning models to build, train, or deploy. You pay only for what you use, and there are no minimum fees and no upfront commitments.

➡️ Lab Agenda: We will see, how SAP S/4HANA (or earlier releases of SAP ERP) can be integrated with Amazon Forecast to predict future sales considering date of sale as the feature.

  1. Extracting Data from SAP S/4HANA: Sales line item data in SAP resides in table VBAP with header information in table VBAK. We will write an ABAP report to extract data understanding the schema and format in which Amazon Forecast expects the data.

  2. Upload this data to an S3 bucket in the region where you want to consume Amazon Forecast: There are a couple of options to automate this process. For example, consume Amazon S3 REST API or call an external OS command (aws s3 cp) configured in SM49 via SAP function module SXPG_COMMAND_EXECUTE in the data extraction ABAP report.

  3. Configure Amazon Forecast: Once the data is in S3 bucket, all it takes is a few clicks to generate a forecast in Amazon Forecast console.

  4. Consume predicted data in SAP S/4HANA or SAP Fiori for reporting: Once the forecast is ready for consumption, we must make it accessible from the SAP system. We use the following additional AWS services.