I currently have a job with Collins Aerospace in Cedar Rapids where we work in SAP and other systems to input data and process transactions for the company. I work on analyzing different supply chain metrics using data extracted from SAP to find different improvements that can be made. For this reason, I am interested in some use cases of machine learning in SAP.
1. Data Attribute Recommendation
There are two main types of data companies use: transactional data and master data. Transactional data are those tied to different transactions (invoices, sales orders, movement of product, etc.). Master data often is used to describe parts, customers, suppliers, etc. Master data does not change often as opposed to transactional data. Some of the main issues are the large maintenance and the inconsistency of master data which can cause delays to processing orders or shipments. Data Attribute Recommendation uses free text, numbers and categories as input to classify entities such as products, stores and users into multiple classes and also to predict the value of missing numerical attributes in your data records. You can use Data Attribute Recommendation, for example, to classify incoming product information and predict the price of commodities based on their description.
2. Purchase Order Processing
For the procurement organizations of manufacturing companies, the timely availability of purchased goods and reliable planning are key for smooth production processes. Operational purchasers need to prevent production delays and rescheduling. Using machine learning technologies to automatically predict delays in supplier deliveries, manufacturers can prevent gaps in raw material availability and avoid production rescheduling.