- SAP Managed Tags
Level 1 – Easy ; 20 minute read
Audience: Project managers, business analysts, subject matter experts
Author: Mark Muir, SAP BTS, S/4HANA RIG Americas
Welcome! SAP’s strategy for industry brings 40+ years of know-how from classical ERP to the world of SAP S/4HANA and the Intelligent Enterprise. With SAP S/4HANA, we are building on the success of SAP Business Suite and SAP Simple Finance powered by SAP HANA with a new business suite called SAP S/4HANA.
Natively re-designed and built on SAP HANA for massive simplifications in the data model; indices, aggregates and data redundancies are eliminated for a simplified data model and co-existence of all 25 SAP industries. Customers have the benefit of having *multiple industry solutions activated in parallel and being able to select and operate single functions and processes from an industry solution opening the door to new and innovative business models i.e. re-architecting industry capabilities.
Key Innovations
SAP Industry Value Proposition
The Next Generation of Business Processes are already here, evolving SAP roadmaps along with the SAP Transformation Navigator help plan your journey to an intelligent enterprise (customer story link).
It’s very difficult to separate machine learning use case from industry, the table below offers an extensive industry portfolio and catalog of publications to help.
Machine Learning and Industry
As we learnt in the blog Solving unique challenges in your business the path to transformation employs numerous tools to search and filter machine learning use case scenarios e.g. Leonardo Kaleidoscope) to help optimize, extend and transform your business simply identify the use case and drill down to learn more (below).
Let’s not forget searching by industry doesn’t have to be by ‘industry’, your interests maybe discrete manufacturing and BYOM. Simply search the SAP Best Practices Explorer using terms “machine learning” or “predictive” to learn about available scope items by product e.g SAP S/4HANA Cloud, on-premise etc…. Last but not least If you are interested in SAP Partners, search the SAP AppCenter for more information.
SAP Roadmaps by Product Category
SAP Roadmaps by Industry
Thank you for your interest
Mark
Further reading in this Machine Learning blog series
Audience: Project managers, business analysts, subject matter experts
Author: Mark Muir, SAP BTS, S/4HANA RIG Americas
Welcome! SAP’s strategy for industry brings 40+ years of know-how from classical ERP to the world of SAP S/4HANA and the Intelligent Enterprise. With SAP S/4HANA, we are building on the success of SAP Business Suite and SAP Simple Finance powered by SAP HANA with a new business suite called SAP S/4HANA.
Natively re-designed and built on SAP HANA for massive simplifications in the data model; indices, aggregates and data redundancies are eliminated for a simplified data model and co-existence of all 25 SAP industries. Customers have the benefit of having *multiple industry solutions activated in parallel and being able to select and operate single functions and processes from an industry solution opening the door to new and innovative business models i.e. re-architecting industry capabilities.
Key Innovations
- *Simplified architecture and streamlined data models
- In the Moment Analytics
- New UX – Fiori – Any Device
- Business Suite Applications moved to Digital Core
- Simplified Business Processes & New Business Models
- **Industry Solutions all in one Digital Core
- ***Platform for Digital Innovation – Machine Learning, AI, IoT and Blockchain
- Cloud & on-premise deployment
- Natively integrated with LOB Cloud Edge Solutions
Note: More information related to S/4HANA Simplification categories please reference the latest update published on help.sap.com / Conversion & Upgrade Assets. **Restrictions do apply please always read the latest version of SAP S/4HANA restriction note and associated industry notes (SAP Support Portal). ***Refer SAP Roadmaps below.
SAP S/4HANA Journey Map: S/4HANA Enterprise Edition on-premise is 1809 (YY/Month)
SAP Industry Value Proposition
The Next Generation of Business Processes are already here, evolving SAP roadmaps along with the SAP Transformation Navigator help plan your journey to an intelligent enterprise (customer story link).
It’s very difficult to separate machine learning use case from industry, the table below offers an extensive industry portfolio and catalog of publications to help.
SAP Industry Posters and Papers: End-to-end industry vision to value story – September 2018
Intelligent Enterprise | Intelligent Suite | Intelligent Technologies | Digital Platform | ||
Industry | Digital White Papers | Intelligent Enterprise Posters | Intelligent ERP Value Papers | Innovation Point | SAP Cloud Platform Brochures |
| Aerospace & Defense | Paper | Value Paper | - | SCP Brochure | |
| Automotive | Paper HUB | Value Paper | Industry PoV PDF | SCP Brochure | |
| Banking | Paper HUB | - | Industry PoV PDF | SCP Brochure | |
| Chemicals | Paper HUB | Value Paper | Industry PoV PDF | - | |
| Consumer Products | Paper HUB | Value Paper | Industry PoV PDF | SCP Brochure | |
| Defense & Security | Paper | - | - | - | |
| EC&O - Construction | Paper HUB | Value Paper | - | - | |
| EC&O - Real Estate | Paper | - | - | - | - |
| Healthcare | Paper HUB | - | - | - | |
| High Tech | Paper HUB | Value Paper | Industry PoV PDF | SCP Brochure | |
| Higher Education | Paper HUB | - | - | ||
| IM&C | Paper HUB | Value Paper | Industry PoV PDF | SCP Brochure | |
| Insurance | Paper | 2018 Value Paper | Industry PoV PDF | SCP Brochure | |
| Life Sciences | Paper HUB | Value Paper | Industry PoV PDF | - | |
| Media | Paper | - | Industry PoV PDF | - | |
| Mill Products - Building Products | Paper | Value Paper | - | - | |
| Mill Products - Metals | Paper | Value Paper | - | - | |
| Mill Products - Paper & Packaging | Paper HUB | Value Paper | - | - | |
| Mining | Paper HUB | Value Paper | - | - | |
| Oil & Gas | Paper HUB | Value Paper | Industry PoV PDF | SCP Brochure | |
| Prof. Services | Paper HUB | 2018 Value Paper | Industry PoV PDF | SCP Brochure | |
| Public Sector | Paper HUB | Value Paper | Industry PoV PDF | SCP Brochure | |
| Public Security | Paper HUB | - | - | - | |
| Retail | Paper HUB | Value Paper | Industry PoV PDF | SCP Brochure | |
| Retail - Fashion | - | Value Paper | - | - | |
| *Smart Cities | Paper Smart City | - | - | - | |
| Sports | Paper | - | - | - | - |
| Entertainment | - | - | - | - | - |
| Telco | Paper | Value Paper | Industry PoV PDF | SCP Brochure | |
| T&T - Cargo | Paper | - | Industry PoV PDF | - | |
| T&T - Travel (Airlines) | Paper | - | - | - | |
| Utilities | Paper HUB | Value Paper | Industry PoV PDF | - | |
| Wholesale Distribution | Paper HUB | Value Paper | - | - | |
Machine Learning and Industry
As we learnt in the blog Solving unique challenges in your business the path to transformation employs numerous tools to search and filter machine learning use case scenarios e.g. Leonardo Kaleidoscope) to help optimize, extend and transform your business simply identify the use case and drill down to learn more (below).
Example: Cross Industry – Predictive Analytics and Machine Learning with SAP HANA
Let’s not forget searching by industry doesn’t have to be by ‘industry’, your interests maybe discrete manufacturing and BYOM. Simply search the SAP Best Practices Explorer using terms “machine learning” or “predictive” to learn about available scope items by product e.g SAP S/4HANA Cloud, on-premise etc…. Last but not least If you are interested in SAP Partners, search the SAP AppCenter for more information.
SAP Best Practices Explorer
SAP Roadmaps by Product Category
- SAP Leonardo
SAP Roadmaps by Industry
- Consumer Industries
- Discrete Manufacturing Industries
- Aerospace & Defense (A&D) ; Automotive ; High Tech ; Industrial Machinery & Components (IMC)
- Energy & Natural Resources Industries
- Chemicals ; Mill Products ; Oil & Gas ; Utilities ; Mining
- Financial Services Industries
- Public Services
- Services Industries
- ,Construction & Operations (EC&O) ; Professional Services ; Telecommunications ; Travel & Transportation ; Media
- Sports & Entertainment
Thank you for your interest
Mark
Further reading in this Machine Learning blog series
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