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In order to ensure that a cross-data source reporting is possible after uploading all the different data sources like Point-of-Sale data (e.g. from retailers) or Market Research data (e.g. a Retail Panel from syndicated data providers), it needs to be taken care of that the data itself is consistent across the sources.
This is done through data harmonization. It establishes the link between the internal views of products and locations to those of the retailers, distributors and syndicated data providers. Such a linkage comes along with some key benefits when talking about enterprise reporting capabilities:

  1. Consistent, shared data and best practices that can be leveraged across retail accounts and internal departments’ lead to more process efficiency… during operations and decision making.
  2. Improved collaboration with the retailers by talking the language of the retailer, using his product or store ID and names e.g. during negotiations.
  3. Reduced costs through better internal and external collaboration that is based on all participants sharing a common view of the business.  

With that, harmonized data creates a 360 degree view of the business.

Easy example:
While a certain product that is produced by the manufacturer “Taste” is called “Chili Chocolate” in-house at the manufacturer, the different retailers and syndicated data providers might have other names, such as “CHILI_CHOC_1254”, “Chocolate_Taste_Chilli”,“03-TAS-chil”, etc. How does the manufacturer know which ones represent his internal product so that he can later on be sure to report based on the same data?

Some use cases for cross-data source reporting

  1. Sell-in vs. Sell-Out Comparison:
    e.g. the manufacturer wants to analyze deviations between the quantity that he shipped to his retailers compared to what has been sold to the end consumer. This helps to uncover situations in which the retailer build up stock on purpose e.g. during trade promotions as well as provides answers to the questions “Did the sales to the end consumers increase accordingly?” Or “Did the retailer just increase stock level on their side and the manufacturer can expect a decline in his own sales soon?”
  2. Cross-Country sales performance of acertain retailer
    e.g. the manufacturer wants to get an aggregated view of the retailer’s sales performance in U.S., Canada and U.K. He also wants to compare KPIs and trends for the different countries. For this, a harmonized reporting based on the retailer’s POS data of the three countries is needed.
    Benefit:  Internally, the manufacturer can view the data in his own view = his own product IDs and descriptions….When talking to retailer, he can also see the data in the language of retailer by using the Product IDs and descriptions of the retailer.
  3. Brand performance in a certain country
    e.g. the manufacturer wants to report the performance of the different products that belong to a certain brand in a certain country but which is split in between different product categories and therefore is split in different Market Research databases.
    Questions like “What is the Market Share of the brand in this country?” or “Who are the main competitors and how are they performing?” can be answered with this reporting.
  4. Sales performance in one country but across retailers
    e.g. the manufacturer wants to analyze the sales performance of the different retailers in Canada and compare their Sell-Out data with his own Sell-In data (e.g. Shipments). For that, a combination and harmonization of the various retailers’ POS data with his own ERP sales data in Canada is needed.

Challenges of external master data harmonization

Different master data keys and number ranges are usually used by different external (e.g. Retailers, Syndicated Data Providers) and internal (e.g. ERP) sources. Furthermore, GTINs (Global Trade Item Number) provided by these sources might not always be correct or are even not provided at all. What is missing in such a case is a “golden key” that links all data that is of the same kind (e.g. the same product or the same retailer store) to one single data set which exclusively identifies the product, no matter in which data source it appeared and independent from its description, GTIN or ID that was provided by the different sources.

How it is done in SAP Demand Signal Management

The data harmonization within SAP Demand Signal Management determines which products belong together by creating a unique Product ID and linking all the different external numbers representing a single manufacturer product together. This enables a holistic mapping of all external master data against internal master data coming from the manufacturers ERP system, for example. Moreover, the manufacturer can now compare different internal and external views on data from different sources based on a single product or location.
More information can be found here: