AI can help us optimize pricing in real time, anticipate customer needs based on buying patterns, and even automate complex order management scenarios. It’s no longer just about automating tasks it’s about transforming how sales and distribution contribute to the business.

With AI, I see huge potential to reduce order errors, improve delivery commitments, and give sales teams the insights they need right when they need them. It’s the kind of evolution that brings together both efficiency and strategy. And honestly, after a decade and a half in this space, that’s the kind of shift that gets me genuinely excited.

Let’s talk about what is Artificial intelligence, Machine learning in simple term.

Artificial Intelligence (AI) is the computers or machines being made to think and decide like humans. It’s about putting machines in a position where they can do things that typically need to be done by human intelligence — like interpreting language, identifying pictures, solving mysteries, or making decisions.

Machine Learning (ML) is either a sub-domain (or subset) of AI. It’s the way that we’re teaching machines to get intelligent independently. We’re not writing each of the rules but giving them many data and that machine would observe patterns over this data. After that, whenever it could be able to independently make a choice or forecast.

Basic example:

If AI has to do something like instructing a robot about recognizing fruits

So ML is kind of like demonstrating the robot pictures of apples, bananas, and oranges — and letting it learn what each of them looks like, instead of explaining to it all the rules

Introduction of AI and ML in SAP

SAP S/4HANA, the cutting-edge ERP suite, is transforming the way businesses operate by incorporating advanced technologies like Artificial Intelligence (AI) and Machine Learning (ML). These innovations boost automation, refine decision-making, and maintain data integrity across a variety of industries. In this blog, we’ll dive into how AI and ML are woven into SAP S/4HANA and explore their practical applications in the real world.

Artificial Intelligence (AI) & Machine Learning (ML) in SAP S/4HANA

SAP S/4HANA leverages AI and ML to automate processes, reduce manual work, and provide predictive insights. Below are some key functionalities:

Sales & Customer Experience

1. Automated Sales Order Processing: AI-powered chatbots process customer inquiries and create sales orders automatically, improving response times.

2. Leverage Joule

Joule is capable of creating sales orders in both the SAP S/4HANA Cloud Private Edition and the Public Edition. It’s also a handy tool for managing various aspects of sales orders, including: –

• Creating sales orders based on other documents: Joule can generate new sales orders by referencing existing sales orders, quotes, or contracts.
  
• Generating sales order requests: It can assist users in crafting sales order requests by pulling information from unstructured data like PDFs or images.
  
• Modifying sales order fields: Users can easily update fields at both the header and item levels with Joule.
  
• Addressing sales order fulfilment issues: It’s equipped to help users tackle any problems related to fulfilling sales orders.
  
• Navigating to relevant apps: Joule can direct users to specific applications within SAP S/4HANA Cloud, such as the “Track Sales Orders” app.
  
• Retrieving sales order information: It can deliver summaries and detailed insights about sales orders, including document flow and pricing condition

3. AI-Based Sales Order Autocompletion:

Functionality: SAP S/4HANA Cloud Public Edition offers AI-driven autocompletion, which uses historical data and machine learning to provide intelligent recommendations for completing sales order data.

Example: The system can suggest the correct shipping address, payment terms, or material details based on past orders with similar characteristics.

SAP Fiori App: The “Monitor Recommendations for Sales Document Completion” app provides a central entry point to view incomplete sales orders and corresponding data field recommendations.

4. Importing Sales Orders from Excel Spreadsheets:

Functionality: You can use the SAP Fiori app “Import Sales Orders” to batch-create sales orders directly from Excel files.

Process:

• Upload the Excel file containing the sales order data.
  
• The system automatically creates sales order requests and populates the data.
  
• You can then simulate or create the sales order.

SAP BTP Use Case: SAP Business Technology Platform (BTP) can be used to automate sales order creation from Excel files, leveraging robotic process automation (RPA) to extract data from Excel and create sales order documents in SAP S/4HANA.

5. Automating Sales Order Creation from Unstructured Data:

Functionality: You can use SAP Build Process Automation to create an RPA bot to automate the processing of sales order requests received in the form of unstructured files like PDFs, images, etc

Process:

• The bot scans emails for keywords in the subject line.
  
• It extracts attachments from the emails and uploads them to the “Create Sales Orders – Automatic Extraction” app.
  
• The app creates sales order requests and uploads the email attachments to a document information extraction service.
  
• The service extracts relevant information from the email attachments.

6. SAP Sales Cloud Version 2, duplicate detection

Sales agents can leverage the feature that performs a check, comparing the configured fields with the list of existing accounts within the system. As an administrator, they can configure the duplicate check for accounts. Once configured, any new account that is created is checked against the configured fields and the result displays a list of the existing accounts with a confidence score, which enables sales agents to take a decision whether or not to proceed with the account creation.

Benefits

• Prevent from creating more duplicate records, improving data accuracy
  
• Ensure a cleaner database for operations and sales forecasts

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Backorder Processing (BOP) involves the bulk handling of orders in batch mode, wherein adjustments to order confirmations are made to align with business priorities and respond to shifts in the demand/supply dynamics within your order fulfillment process.

In the context of aATP BOP, a novel notion of requirement classification is introduced, enabling the confirmation of orders based on predefined criteria. This system comprises five classifications (win, gain, redistribute, fill, and lose), each equipped with a distinct rule governing the prioritization of order confirmations. For instance, the winner and the gainer hold the utmost priorities and retain their confirmed quantities without any reduction, while the loser consistently forfeits all confirmed quantities to any other classification.

Let’s go through the each BOP segment to get a thorough understanding.

Different BOP segments and behavior

Example Scenario:

Assumption: The “Scope of check” only considers the on hand stock. Not future stocks.

Organization ABC is receiving some purchase order from different customers and they raise sales orders in the below sequence.

Sales Order creation sequence in the model scenario

In accordance with the aforementioned illustration, organization ABC is generating multiple sales orders for its clientele. The first order pertains to a customer with a delivery priority of 3, who is not classified as one of the premier clients of organization ABC.

The second order is attributed to a customer of neutral standing, characterized as a regular and recurrent purchaser. At the point of initiating the sales order, the available on-hand stock is documented at 4000 pieces, considering that 8000 pieces have already been confirmed for the preceding order out of the total inventory of 12000 pieces. Additionally, the complete requisition cannot be confirmed due to the specified quantity for order 2 amounting to 6000 pieces.

Concluding the sequence, the third sales order is allocated to a premium customer. Upon commencement of the sales order, the on-hand stock will be depleted to zero. This is where the back-order processing functionality within aATP comes into play. Subsequently, an examination of how BOP navigates and manages the aforementioned situation shall be conducted.

BOP variant simulation result for the model scenario.

As depicted above, the BOP (Back Order Processing) variant initiates the process by revoking the entire confirmation attributed to customer 01. This action is prompted by the customer’s adherence to the LOSE strategy, allowing the unconfirmed quantity to become available for utilization by the WIN, GAIN, and REDISTRIBUTE strategies. In this specific business scenario, customer 03 aligns with the WIN strategy. Consequently, the unconfirmed quantity originally associated with customer 01 is reallocated to customer 03.

Nevertheless, achieving full confirmation for customer 03 remains unattainable, given their requirement of 9000 pieces. The deficit of 1000 pieces can be offset by sourcing from customer 02, characterized by a delivery priority of 02 and an inclination towards the REDISTRIBUTE strategy.

The critical aspect lies in discerning the disparity between LOSE and REDISTRIBUTE strategies within this context. Following the complete un-confirmation of the prior commitment to customer 01, a shortfall of 1000 pieces persists for the fulfillment of customer 03’s requirement. This shortfall is addressed through a partial confirmation extended to customer 02.

This elucidates how BOP adeptly manages and automates the resolution of issues arising from incongruities between requirements and demands, a process that traditionally necessitated human intervention.

In order to simplify the understanding process, i have simulated the same business scenario in my system environment and below is the BOP variant simulation result that could observe.

WIN

REDISTRIBUTE

LOSE

In SAP S/4HANA, the Enhanced Available-to-Promise (aATP) feature provides a range of SAP Fiori applications designed for the automated handling of backorders and the manual authorization of orders for delivery. These applications cater to various business document types, including sales orders and stock transport orders.

Each of the subsequent applications enables you to set up a particular step before initiating backorder processing or to oversee the outcomes of a concluded backorder processing operation:

Configure BOP Segment

This application allows you to establish a set of criteria for selecting priorities in distributing supplies when the demand for materials in sales and stock transport orders surpasses the existing inventory or capacity. Through the utilization of selection and exclusion conditions, along with prioritizes, you can automate the rescheduling and redistribution processes in alignment with your company’s strategy. Following this, the Configure BOP Variant application can be employed to create a variant, facilitating the direct execution of the corresponding backorder processing run within the app or through the Schedule BOP Run application. Access to this app is contingent upon the assignment of the Order Fulfillment Manager (R0226) business role to your user account.

Configure Bop Variant

Utilizing this application, you have the capability to establish a variant for backorder processing (BOP), incorporating optional filters and prioritizers. This allows for the automated rescheduling and redistribution of materials in restricted supply. The outcomes of successive backorder processing runs can be viewed in the Monitor BOP Run application.

Configure Custom BOP Sorting

Using this application, you have the capability to generate sequences for prioritizing requirements originating from sales and stock transport documents based on attributes that are not amenable to straightforward alphanumeric sorting, such as customer or sold-to party. In this process, you establish a logical framework for prioritizing requirements, which is subsequently applied in the Configure BOP Segment application and in subsequent backorder processing runs initiated from either the Configure BOP Variant or Schedule BOP Run applications.

Schedule BOP Run & Monitor BOP Run

Using these applications, you can set up and timetable tasks to execute backorder processing (BOP) runs. This involves specifying the technical parameters governing the selection criteria, operational characteristics of the run, and, if necessary, simulative and recurring runs, as well as subsequent update processes and logging. The outcomes of any scheduled run through this app can be monitored in the Monitor BOP Run application.

This concludes this article and the main object of writing this to give you all a high level understanding of Backorder Processing in aATP, SAP S4 HANA. Please do share all your insights.

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