Simply put, the value of Artificial Intelligence Technologies in the Intelligent Enterprise is not really just about technology. It is also not about a particular tool or capability such as Machine Learning, Robotic Process Automation bots or anything else. The value of AI Technology lies in your ability to actually use this technology to create tangible innovative and time-saving solutions to solve complicated business problems.
You do this by taking an end-to-end business process view of the problem and then driving your solution to a defined business outcome. You can create a hundred cool bots, or algorithms or skills – but if they do not somehow or another converge upon a specific business process, and comprehensively address a true end-to-end business solution, they will all remain really cool solutions that sit on a shelf.
Let me illustrate this with an example.
Say that you are a Sales Manager for a mid-sized manufacturing firm. Your job is not just to create sales orders or to resolve delivery delays or to check on the status of individual orders. It’s all of the above – and more. The business outcome that you seek – a streamlined Order to Cash process that results in accurate forecasts, on-time deliveries, improved cashflows and happier customers is only possible by taking an end-to-end business process view of the system to clearly address the root causes of your business problems. You can use Machine Learning, RPA Bots, Situation Handling and Embedded Analytics in tasks to:
Consider the example below. By de-composing the Order-to-Cash process into its component parts and using AI technologies to a) automate routine tasks and b) identify opportunities for innovation, you can create synergy where one plus one now becomes equal to three!
Of course, you could easily automate individual simple tasks such as monitoring emails for orders with an RPA bot, but when you combine this with the automation of sales order confirmations and the creation of billing plans, business value is created. When you add the impact of machine learning to these processes to identify upsell opportunities or to accurately predict which quotes may turn into orders, a business outcome is born. When you are no longer focused on processing routine orders, but on handling the exceptional orders, your simple process becomes a value generating machine! The focus here is not really on the technology so to say, but rather on how the technology contributes to the Business Outcome. This is where the real value in AI Technology lies.
Measurable business outcomes are not often one dimensional. Similarly, using one tool on one process seldom creates a sustainable business win. They typically require a holistic, business process focus which may involve a combination of tools and technologies from machine learning to RPA to embedded analytics. The outcomes also rely on a rock-solid transaction processing engine (Like S/4HANA!) that is similarly focused on the complete end-to-end process. When you combine world class ERP, AI tools, Analytics and an outcome-based approach. Taking an end-to-end business process focus to your deployment of AI reflects your technology strategy as well as of your business strategy.
The Value of Pre-Configured Business Content
In SAP S/4HANA, all the AI technologies from SAP offer substantial pre-delivered content. The pre-delivered content gives you a foundation on which you can build your complete end-to-end solution without a bunch of complex code. The preconfigured bots, ML models, templates and reports offer valuable tools for quickly standing up proofs-of-concepts and prototypes. Taking this sort of horizontal approach to tackling your business problems enables you to look at the solution as a system and to focus on value added business outcomes. Too often, we see customers start down the road of creating complex one-dimensional custom solutions only to find out that they do not really address the problem and ultimately they do not add business value.
To help you make the most of your investment in SAP S/4HANA and in SAP AI Technologies, we have also created the SAP S/4HANA Co-innovation FrontRunner team. This is a team dedicated to helping you to accelerate your understanding of Machine Learning, Intelligent RPA, Conversational AI and Situation Handling. We can help you answer questions like “What use cases work with my release of S/4Hana?” or “How can I create an ‘Intelligent Roadmap’ to help me define a path for adoption of RPA in my company?” and many more. You can easily contact us via email at mailto:FrontRunner@SAP.com.
The team has actually recorded a number of examples that demonstrate end-to-end persona-based demonstration models to showcase a few of these full models that focus on business outcomes and even perhaps to show you a little of the “art of the possible”. Just drop us a line!
Follow us via @Sap and #S4HANA, or myself via @SDenecken
You do this by taking an end-to-end business process view of the problem and then driving your solution to a defined business outcome. You can create a hundred cool bots, or algorithms or skills – but if they do not somehow or another converge upon a specific business process, and comprehensively address a true end-to-end business solution, they will all remain really cool solutions that sit on a shelf.
Let me illustrate this with an example.
Say that you are a Sales Manager for a mid-sized manufacturing firm. Your job is not just to create sales orders or to resolve delivery delays or to check on the status of individual orders. It’s all of the above – and more. The business outcome that you seek – a streamlined Order to Cash process that results in accurate forecasts, on-time deliveries, improved cashflows and happier customers is only possible by taking an end-to-end business process view of the system to clearly address the root causes of your business problems. You can use Machine Learning, RPA Bots, Situation Handling and Embedded Analytics in tasks to:
- Create sales inquiries
- Predict sales performance
- Predict quotation to order conversion rate
- Alert to expiring quotation
- Create sales orders
- Create payment plans
- Predict delivery delays
Consider the example below. By de-composing the Order-to-Cash process into its component parts and using AI technologies to a) automate routine tasks and b) identify opportunities for innovation, you can create synergy where one plus one now becomes equal to three!
Of course, you could easily automate individual simple tasks such as monitoring emails for orders with an RPA bot, but when you combine this with the automation of sales order confirmations and the creation of billing plans, business value is created. When you add the impact of machine learning to these processes to identify upsell opportunities or to accurately predict which quotes may turn into orders, a business outcome is born. When you are no longer focused on processing routine orders, but on handling the exceptional orders, your simple process becomes a value generating machine! The focus here is not really on the technology so to say, but rather on how the technology contributes to the Business Outcome. This is where the real value in AI Technology lies.
Measurable business outcomes are not often one dimensional. Similarly, using one tool on one process seldom creates a sustainable business win. They typically require a holistic, business process focus which may involve a combination of tools and technologies from machine learning to RPA to embedded analytics. The outcomes also rely on a rock-solid transaction processing engine (Like S/4HANA!) that is similarly focused on the complete end-to-end process. When you combine world class ERP, AI tools, Analytics and an outcome-based approach. Taking an end-to-end business process focus to your deployment of AI reflects your technology strategy as well as of your business strategy.
The Value of Pre-Configured Business Content
In SAP S/4HANA, all the AI technologies from SAP offer substantial pre-delivered content. The pre-delivered content gives you a foundation on which you can build your complete end-to-end solution without a bunch of complex code. The preconfigured bots, ML models, templates and reports offer valuable tools for quickly standing up proofs-of-concepts and prototypes. Taking this sort of horizontal approach to tackling your business problems enables you to look at the solution as a system and to focus on value added business outcomes. Too often, we see customers start down the road of creating complex one-dimensional custom solutions only to find out that they do not really address the problem and ultimately they do not add business value.
To help you make the most of your investment in SAP S/4HANA and in SAP AI Technologies, we have also created the SAP S/4HANA Co-innovation FrontRunner team. This is a team dedicated to helping you to accelerate your understanding of Machine Learning, Intelligent RPA, Conversational AI and Situation Handling. We can help you answer questions like “What use cases work with my release of S/4Hana?” or “How can I create an ‘Intelligent Roadmap’ to help me define a path for adoption of RPA in my company?” and many more. You can easily contact us via email at mailto:FrontRunner@SAP.com.
The team has actually recorded a number of examples that demonstrate end-to-end persona-based demonstration models to showcase a few of these full models that focus on business outcomes and even perhaps to show you a little of the “art of the possible”. Just drop us a line!
Getting Started with a Trial Version of SAP Intelligent RPA here
For more information on SAP S/4HANA Cloud, check out the following links:
- SAP S/4HANA Cloud release info: http://www.sap.com/s4-cloudrelease
- SAP S/4HANA release info: com/s4hana
- Early Release Webinar Series here
- Best practices for SAP S/4HANA Cloud here
- SAP S/4HANA Cloud User Community: register here
- Feature Scope Description here
- What’s New here
- Help Portal Product Page here
- Implementation Portal here
Follow us via @Sap and #S4HANA, or myself via @SDenecken
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