Supply chain transparency is a new must-have feature in the wake of the latest supply chain disruptions caused by the coronavirus, unusual weather and various transportation capacity shortages. New in SAP Data Warehouse Cloud (SAP DWC) is Camelot’s Supply Chain Resilience Cockpit.
Problems in global and, in some cases, regional supply chains have accumulated in recent years due to a variety of external and internal influences. This makes it increasingly difficult for companies to bring transparency into the supply chain and create precautions against changes or disruptions — the magic word here is supply chain resilience.
Combining Analyzes with External Data in SAP DWC
The Supply Chain Resilience Cockpit combines data from the SAP S/4 system in various analysis procedures with external data, such as weather forecasts or from the general news situation. The advantages are:
- improved transparency in the supply chain,
- visualization and risk analysis become possible, and
- the ability to integrate with analytics and hyperscalers.
Specifically, data such as inbound and outbound goods movements are analyzed from SAP S/4. This provides insight into supplier on-time delivery performance. The key figure Time-to-Sustain can be calculated in combination with external factors such as weather effects or influences such as strikes. It tells us how long the company will be able to meet customer demand with current inventories and future deliveries. The cockpit warns of foreseeable problems in the supply chain.
Solution Architecture for High Resilience
Disruptive influences on the supply chain must be detected as early as possible and the resulting situations must be managed quickly. The Supply Chain Resilience Cockpit accesses current data in the S/4 system to enable the often time-critical decisions. Live data access from the SAP Data Warehouse Cloud to the S/4 Views enables virtual access; as a result, no data replications in the Data Warehouse Cloud are necessary.
External web APIs are integrated into the data architecture to include location information and external data sources for weather information. In this way, weather information on the individual locations is retrieved and persistently written to the data model in the event of a weather warning. If historical weather developments at supplier locations are integrated, this data can become the basis for further use cases.
Data Modeling with Real-Time Data
The reporting layer presents the processed data. The reporting layer serves as the basis for the built-in SAP Analytics Cloud Dashboard, which connects live to the data from the Data Warehouse Cloud. Complete virtual data modeling means that changes in the data in the S/4 system show up directly in the reporting.
From the dashboard’s home page, users can trigger a detailed analysis of individual suppliers, as well as get a highly aggregated overview of the supply chain using a map. Current problem regions for which there are weather warnings are highlighted. The affected components or products can be viewed directly in the detailed view. In addition, alternatives can be triggered if, for example, alternative deliveries from other suppliers come into question or internal redistribution between individual locations is possible.
ContentPackage Supply Chain Resilience Cockpit for Transparency in SAP DWC
In the version provided free of charge, the analysis includes weather information by location. Interested parties can implement this version of the Supply Chain Resilience Center for the Data Warehouse Cloud themselves. The instructions, Python code and the Data Warehouse Cloud Object List are available in this download (zip file). Further solutions increase the prediction accuracy with additional data.
Camelot’s Supply Chain Resilience Cockpit emerged from the successful candidate involved in the SAP Packathon for the SAP Data Warehouse Cloud. It is now available as a free content package for the DWC and combines Camelot’s expert knowledge from the Supply Chain Resilience Competence Center with the technical know-how of SAP Analytics experts.