[Decision Micro Classroom] A must-read article for enterprises: Understand the latest enterprise-level AI solution released by SAP in one article!
Time: 2023-10-07 
Views: 689
On September 26, the 42nd issue of [Decision Micro Classroom] was conducted by Decision and SAP experts in a live broadcast to give an in-depth explanation of the AI-powered SAP ERP cloud. The live broadcast was extremely popular and gathered people from the SAP industry from all over the world. Everyone lamented that they had benefited a lot and gained a lot. They not only thanked the teacher for his wonderful sharing, but also thanked Decision for providing such a high-quality platform for sharing pure dry goods, which received constant praise from the audience.
Friends who missed this live broadcast can review the key contents of this live broadcast with us, or click "Read the original text" to review the exciting content.
01｜SAP AI - artificial intelligence built for business
02｜SAP ERP Cloud powered by AI
As shown in the figure above, SAP strategy is committed to building smart enterprises for customers, and the smart enterprise architecture is based on cloud ERP as the core, BTP (Business Technology Cloud Platform) as the technical base, and above the cloud ERP, it is surrounded by industry-specific and sustainable Ecosystem solutions include human capital management, expense management and business network, as well as customer relationship management, and serve as an extension and supplement to cloud ERP, ultimately helping customers create a complete business process powered by AI.
02.SAP Business AI
SAP AI is AI built specifically for enterprises and is positioned as Business AI. As shown above, the first thing you see is the business data, which is developed using extensive, industry-specific data and SAP's more than 50 years of rich industry knowledge and processes. Enterprises can create data based on business data. Business process specific artificial intelligence.
Enterprise-level AI functions include document processing, suggestions, predictions, generative artificial intelligence, and digital assistants. They are directly embedded in SAP applications used daily by enterprises. They are out-of-the-box artificial intelligence, such as ERP cloud, Human capital management, expense management and business network and customer relationship management.
03. The most comprehensive artificial intelligence functions
SAP AI provides the most comprehensive artificial intelligence capabilities for every functional department, covering the six core processes of the enterprise, including sales and service, finance, supply chain, procurement, marketing and commerce, human resources and cross-functional, To help companies complete simple operational tasks, control costs, and reduce risks.
04.SAP S/4HANA Cloud related intelligent technologies
It mainly includes four aspects: interaction, execution, optimization and prediction:
• Interaction: divided into two types
- Human-to-human interaction (Calibration Manager)
- Human-computer interaction (Digital Assistant)
What is currently implemented in China is the integration of S/4HANA Cloud with Microsoft Teams, and Teams can be used for corresponding interactions.
• Execution: Based on SAP build process automation, such as SAP RPA, the process is automated through robot workflow.
• Optimization: Use machine learning to learn from historical records and anomalies to predict and assist user actions, automate certain operations or optimize user decisions.
• Prediction: Situation Handling launched by SAP can detect anomalies, notify corresponding users, and provide options from insight to action.
05.SAP S/4HANA Cloud and SAP BTP
As the core and backbone of digitalization, SAP S/4HANA Cloud has built-in intelligent technologies in the system, including situation processing, machine learning, and analysis. It also includes two parts, one is the pre-built use cases in the system. The other is an extension in S/4HANA Cloud. In addition, it can also be expanded in parallel through the SAP Business Technology Cloud Platform to provide more intelligent industry functions, including situation processing, machine learning, digital assistants and chat robots.
06. Situation handling
Situation handling is a framework in SAP S/4HANA that automatically detects abnormal situations and notifies specific user groups based on defined teams and responsibilities. SAP has a corresponding APP to notify relevant personnel.
In addition, there will be corresponding contextual messages in the corresponding business applications, and there will be an automatic notification in the SAP Fiori quick launch pad. Users can set the email address they receive in SAP Fiori to make corresponding settings.
Situation capture captures current business event conditions and outcomes, and it supports two scenarios:
① Object-based situation: You can specify the conditions under which the situation is created.
②Message-based situations: refers to situations where warning and error messages appear during system operation or reporting.
Object-based situations define conditions, and message-based situations select system messages to create situations.
07.Machine Learning
For embedded in SAP S/4HANA Cloud:
• Typically “simple” use cases such as trend analysis or forecasting
• Algorithms with low CPU-RAM-data requirements such as regression, clustering, etc.
• A large machine learning algorithm library that implements TensorFlow integration through embedded machine learning.
Machine learning and business logic actually reside in SAP S/4HANA Cloud.
08. Intelligent situational automation
Intelligent situation automation extends the situation processing in ERP on the BTP platform. It processes situations and uses business rules to automatically solve them. It can be based on rules and engines and SAP Intelligent RPA, and can define rules for automatically solving situations in a configurable way. And can use API calls to email alerts, or customer-created actions to build solutions to situations.
In addition, it can support the construction of intelligent business insights and action recommendations based on machine learning, allowing situation data to be monitored and analyzed to make corresponding situation improvements.
09.SAP Build process automation
SAP Build allows everyone to automate workflows and tasks without writing code. Users can create forms, manage decision logic, and build and adjust organizational processes through drag and drop, and use no-code, low-code features or the built-in automation recorder. Automate repetitive manual tasks.
All in all, the entire SAP Build simplifies process and task automation. The key is to allow business users to operate a variety of process aspects without writing code.
10.SAP AI technology product portfolio
The picture above shows the services currently covered by SAP AI products. Examples are as follows:
11. Integrate and run AI/machine learning in SAP S/4HANA Cloud
The figure above shows the process of integrating and running AI/machine learning in SAP S/4HANA Cloud:
① Discover and set up scenes - specify an AI scene to be built
② Prepare data set, train and deploy - train the data model
③ Activation, testing and application - check the training results and activate them if they are correct
12. Two modes of applying AI/machine learning
In the SAP ERP public cloud, AI provides two modes:
• Embedded: pre-made and can be used directly in the SAP ERP public cloud.
• Parallel: Based on the SAP BTP platform to build more complex or intelligent scenarios expected by customers.
13. Two application modes of embedded AI/machine learning
For embedded mode, it is divided into two modes:
• Pre-configured: Embedded in the ERP public cloud. SAP has been pre-configured and users can directly train and activate it for use.
• Customization: Customers can choose which data sets to train and apply, and train and activate this data model.
14. Pre-configured AI/ML scenarios embedded in SAP ERP public cloud
In the SAP ERP public cloud, as shown in the figure above, AI technology is mainly used to provide purchase orders, contract management, sales planning, inventory management, goods movement, tax compliance and other solutions in the system.
15.ISLM (Intelligent Scenario Lifecycle Management)
ISLM (Intelligent Scene Lifecycle Management) provides a single entrance, which corresponds to the two APPs shown in the figure: one is intelligent scene and the other is intelligent scene management. Through these two APPs, all preconfigured intelligent scenarios can be uniformly trained, activated and other corresponding operations performed. In addition, ISLM itself does not charge additional fees.
16. Intelligent scene examples
The above is an example of a custom intelligent scene process:
① Define scene name
② Select scene type
③ Selection algorithm
④ Select training and application data sets
⑤ Specify target value
⑥ Training model
⑦ Check score
⑧Activate model
Enterprises are undergoing major changes unseen in a century and facing complex internal and external environments. Over the past seventeen years, Decision has always taken SAP as the cornerstone and is committed to helping more and more enterprises improve the quality of SAP implementation. Through a strong global Delivery capabilities, comprehensively help enterprises successfully achieve digital and intelligent transformation, cultivate elite teams, and build digital cores.
In the future, Decision will also bring more course sharing to people in the SAP industry. Follow the Decision official account to get the latest news on [Decision Micro Classroom] as soon as possible and get more event information!
Friends who missed this live broadcast can review the key contents of this live broadcast with us, or click "Read the original text" to review the exciting content.
Guest introduction
Lecture summary
01｜SAP AI - artificial intelligence built for business02｜SAP ERP Cloud powered by AI
- Intelligent technology embedded in SAP ERP cloud
- More intelligent capabilities with SAP Business Technology Cloud Platform
- SAP ERP public cloud AI technology application principles
- SAPERP public cloud has built-in AI intelligent scenarios
- SAPERP public cloud intelligent scenario configuration and expansion
Practical information
01.SAP StrategyAs shown in the figure above, SAP strategy is committed to building smart enterprises for customers, and the smart enterprise architecture is based on cloud ERP as the core, BTP (Business Technology Cloud Platform) as the technical base, and above the cloud ERP, it is surrounded by industry-specific and sustainable Ecosystem solutions include human capital management, expense management and business network, as well as customer relationship management, and serve as an extension and supplement to cloud ERP, ultimately helping customers create a complete business process powered by AI.
02.SAP Business AI
SAP AI is AI built specifically for enterprises and is positioned as Business AI. As shown above, the first thing you see is the business data, which is developed using extensive, industry-specific data and SAP's more than 50 years of rich industry knowledge and processes. Enterprises can create data based on business data. Business process specific artificial intelligence.
Enterprise-level AI functions include document processing, suggestions, predictions, generative artificial intelligence, and digital assistants. They are directly embedded in SAP applications used daily by enterprises. They are out-of-the-box artificial intelligence, such as ERP cloud, Human capital management, expense management and business network and customer relationship management.
03. The most comprehensive artificial intelligence functions
SAP AI provides the most comprehensive artificial intelligence capabilities for every functional department, covering the six core processes of the enterprise, including sales and service, finance, supply chain, procurement, marketing and commerce, human resources and cross-functional, To help companies complete simple operational tasks, control costs, and reduce risks.
04.SAP S/4HANA Cloud related intelligent technologies
It mainly includes four aspects: interaction, execution, optimization and prediction:
• Interaction: divided into two types
- Human-to-human interaction (Calibration Manager)
- Human-computer interaction (Digital Assistant)
What is currently implemented in China is the integration of S/4HANA Cloud with Microsoft Teams, and Teams can be used for corresponding interactions.
• Execution: Based on SAP build process automation, such as SAP RPA, the process is automated through robot workflow.
• Optimization: Use machine learning to learn from historical records and anomalies to predict and assist user actions, automate certain operations or optimize user decisions.
• Prediction: Situation Handling launched by SAP can detect anomalies, notify corresponding users, and provide options from insight to action.
05.SAP S/4HANA Cloud and SAP BTP
As the core and backbone of digitalization, SAP S/4HANA Cloud has built-in intelligent technologies in the system, including situation processing, machine learning, and analysis. It also includes two parts, one is the pre-built use cases in the system. The other is an extension in S/4HANA Cloud. In addition, it can also be expanded in parallel through the SAP Business Technology Cloud Platform to provide more intelligent industry functions, including situation processing, machine learning, digital assistants and chat robots.
06. Situation handling
Situation handling is a framework in SAP S/4HANA that automatically detects abnormal situations and notifies specific user groups based on defined teams and responsibilities. SAP has a corresponding APP to notify relevant personnel.
In addition, there will be corresponding contextual messages in the corresponding business applications, and there will be an automatic notification in the SAP Fiori quick launch pad. Users can set the email address they receive in SAP Fiori to make corresponding settings.
Situation capture captures current business event conditions and outcomes, and it supports two scenarios:
① Object-based situation: You can specify the conditions under which the situation is created.
②Message-based situations: refers to situations where warning and error messages appear during system operation or reporting.
Object-based situations define conditions, and message-based situations select system messages to create situations.
07.Machine Learning
For embedded in SAP S/4HANA Cloud:
• Typically “simple” use cases such as trend analysis or forecasting
• Algorithms with low CPU-RAM-data requirements such as regression, clustering, etc.
• A large machine learning algorithm library that implements TensorFlow integration through embedded machine learning.
Machine learning and business logic actually reside in SAP S/4HANA Cloud.
08. Intelligent situational automation
Intelligent situation automation extends the situation processing in ERP on the BTP platform. It processes situations and uses business rules to automatically solve them. It can be based on rules and engines and SAP Intelligent RPA, and can define rules for automatically solving situations in a configurable way. And can use API calls to email alerts, or customer-created actions to build solutions to situations.
In addition, it can support the construction of intelligent business insights and action recommendations based on machine learning, allowing situation data to be monitored and analyzed to make corresponding situation improvements.
09.SAP Build process automation
SAP Build allows everyone to automate workflows and tasks without writing code. Users can create forms, manage decision logic, and build and adjust organizational processes through drag and drop, and use no-code, low-code features or the built-in automation recorder. Automate repetitive manual tasks.
All in all, the entire SAP Build simplifies process and task automation. The key is to allow business users to operate a variety of process aspects without writing code.
10.SAP AI technology product portfolio
The picture above shows the services currently covered by SAP AI products. Examples are as follows:
- Based on the SAP BTP platform, SAP provides SAP Conversational AI, that is, human-computer interaction, which can communicate with natural language and intelligent robots to obtain corresponding replies and suggestions.
- In SAP AI Business Services, you can see built services, such as document information extraction, invoice processing management system, etc.
- SAP AI Core can train and serve various AI scenarios. For example, based on the BTP platform to build corresponding AI scenarios, enterprises can use SAP AI Core to train corresponding data models. In addition to the pre-made services and tools provided based on the BTP platform, customers can also choose customized AI functions and AI scenario APPs using S/4HANA database, data intelligent utilization analysis cloud, and SAP partner products. .
11. Integrate and run AI/machine learning in SAP S/4HANA Cloud
The figure above shows the process of integrating and running AI/machine learning in SAP S/4HANA Cloud:
① Discover and set up scenes - specify an AI scene to be built
② Prepare data set, train and deploy - train the data model
③ Activation, testing and application - check the training results and activate them if they are correct
12. Two modes of applying AI/machine learning
In the SAP ERP public cloud, AI provides two modes:
• Embedded: pre-made and can be used directly in the SAP ERP public cloud.
• Parallel: Based on the SAP BTP platform to build more complex or intelligent scenarios expected by customers.
13. Two application modes of embedded AI/machine learning
For embedded mode, it is divided into two modes:
• Pre-configured: Embedded in the ERP public cloud. SAP has been pre-configured and users can directly train and activate it for use.
• Customization: Customers can choose which data sets to train and apply, and train and activate this data model.
14. Pre-configured AI/ML scenarios embedded in SAP ERP public cloud
In the SAP ERP public cloud, as shown in the figure above, AI technology is mainly used to provide purchase orders, contract management, sales planning, inventory management, goods movement, tax compliance and other solutions in the system.
15.ISLM (Intelligent Scenario Lifecycle Management)
ISLM (Intelligent Scene Lifecycle Management) provides a single entrance, which corresponds to the two APPs shown in the figure: one is intelligent scene and the other is intelligent scene management. Through these two APPs, all preconfigured intelligent scenarios can be uniformly trained, activated and other corresponding operations performed. In addition, ISLM itself does not charge additional fees.
16. Intelligent scene examples
The above is an example of a custom intelligent scene process:
① Define scene name
② Select scene type
③ Selection algorithm
④ Select training and application data sets
⑤ Specify target value
⑥ Training model
⑦ Check score
⑧Activate model
Enterprises are undergoing major changes unseen in a century and facing complex internal and external environments. Over the past seventeen years, Decision has always taken SAP as the cornerstone and is committed to helping more and more enterprises improve the quality of SAP implementation. Through a strong global Delivery capabilities, comprehensively help enterprises successfully achieve digital and intelligent transformation, cultivate elite teams, and build digital cores.
In the future, Decision will also bring more course sharing to people in the SAP industry. Follow the Decision official account to get the latest news on [Decision Micro Classroom] as soon as possible and get more event information!
【Service Guide】
For more information on SAP courses, project consultation and operation and maintenance, please call Decision's official consultation hotline: 400-600-8756
【About Decision】
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