Order Promising is a critical component of SAP's supply chain and order fulfilment processes. Also known as Available-to-Promise (ATP) or Advanced ATP (aATP), it ensures that customer orders are confirmed with delivery dates that are both feasible and aligned with real-time product availability, capacity, and business priorities. It is the process of evaluating material availability and making realistic delivery commitments during order entry. ATP/aATP checks material stock, incoming receipts, and constraints (e.g. production or transport capacity).It is tightly integrated with sales, production, procurement, and logistics.
This development includes demand and supply planning program where the orders raised in SAP are promised with quantity and delivery dates. The OP engines read allocated quantity from the planning system and promises orders against them. This solution integrates with the order management system (OMS) to process orders in real-time, sending them to the BY OP engine for availability and promise, with millisecond response times. It's SAP Integration is with Blue Yonder, OMS System.
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Plant -> CustomerPlant -> SPC
Plant -> Stockyard
Plant -> SPC Via Stockyard
SPC -> Customer
SPC -> Stockyard
6 Transaction codes developed as part of this development.
1st T-code focuses on feasibility, logging, and order confirmation.
2nd T-code handles direct release of sales orders. (Important & Urgent)
3rd T-code involves releasing sales orders with promising quantity and date, including a capacity check from 3rd party.
4th T-code allows bypassing sales order checks for smooth release. (Important but Not-urgent)
5th T-code automates the order promising confirmation process.
6th T-code automates the workflow for failed orders.
1. A sales order is created in the system and logged through custom T-code.
2. New T-code is developed to confirm the order along with capacity check.
3. The system triggers an ATP check to confirm whether the materials can be delivered on the requested date.
4. If available, the order is confirmed.
5. If not available, the system may : use other workflow to re-prioritize delivery, Apply Product Allocation rules to manage demand fairly, activate supply protection to safeguard inventory for high-priority demand & propose alternative delivery dates.
Study Of existing process. Earlier business was using similar type of sales orders for various scenarios but no specific order type can differentiate the scenarios, Business STD, UCW calculations is different as per their scenarios.
There is no valid zone check implemented at "Via Stockyard scenario", User can enter any value and log the order with wrong zone, which may lead to promising data to capture wrong supply w.r.t Sales order and promised delivery date as All these patterns use same order types across different scenarios.
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- The objective was to enhance the accuracy and efficiency of promising orders in SAP by simplifying management of supply plants particularly dual stock scenarios. This is a customised tool design for SAP SD order promising (OP) valuated ATP(Available-to-Promise) includes various T-codes development and modification.
- Proposed the idea & the importance of segregating the patterns based on order type, so tedious process could be simplified and have correct data-maintained w.r.t. order types.
- Identified the gap business team is facing while logging the orders and provided better insights on using this new idea and business users agreed to follow on the same approach for ease of order logging and maintaining the sales order data. Observed certain operational challenges, while not critical were contributing to the avoidable delays and inconsistencies.
- I explored how existing tools could be leveraged more effectively and implemented revised process flow of logging the orders process which is now very simple and free of inconsistency that end-user can do in daily activities. (Soln: With introducing new order type and SPC plant in variant configuration)
- I successfully involved in end-to-end development and deployment of a comprehensive Order Promising tool, ensuring seamless integration with both Blue Yonder (BY) and the existing Order Management System (OMS). The project began with a deep analysis of business requirements, followed by the design and configuration of the tool to align with real-time inventory visibility, ATP logic, and delivery promise accuracy. Rigorous testing phases were carried out in collaboration with cross-functional teams to validate all key interfaces between SAP, BY, and OMS, including data synchronization, exception handling, and latency tolerance. We meticulously tested the tool under various business scenarios, ensuring compatibility.
- After resolving critical dependencies and optimizing performance, the tool was deployed into production with zero disruption to live operations. Post-deployment monitoring confirmed seamless execution, with real-time order confirmation and delivery commitment functioning as intended. This initiative not only enhanced the reliability of order promising across systems but also improved customer satisfaction by ensuring accurate and timely delivery commitments.
- Leveraging a brute-force investigative approach, I was able to identify pain points and inefficiencies that were previously overlooked.
- I delivered measurable business impact, enhancing both data accuracy and governance across diverse sales order processes. This initiative significantly reduced the risk of manual errors and improved operational control, thereby strengthening trust and efficiency in the order management lifecycle.
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🟢 Availability Checks : Real-time evaluation of whether requested quantities are available for the requested delivery date.
📊 Considers current stock, planned receipts (like purchase or production orders), and customer orders.
📦 Product Allocation : Distributes limited inventory based on business-defined allocation rules (e.g. VIP customers, key markets).
🛡 Supply Protection : Reserves portions of available supply for strategic purposes (e.g., emergency stock or preferred channels).
🔁 Backorder Processing (BOP) : Automatically re-evaluates and reprioritizes open orders during shortages or delivery delays.
✅ Customer Satisfaction : Accurate commitments build trust and reduce delivery disputes.
🔄 Supply Chain Optimization : Reduces stockouts, minimizes excess inventory, and streamlines operations.
🎯 Business Priority Management : Enables rules-based prioritization (e.g. by region, channel, customer tier).
🔗 Multi-Level ATP : Checks across the supply chain (e.g. plants, warehouses, production orders) to confirm availability.
⚡ Real-time inventory visibility.
🚛 Order Fulfillment & Shipping.
🧠 Smart and dynamic order fulfilment.
🤝🏻 Positive user-feedback.
📉 Reduced order cancellations and backorders.
📈 Improved supply chain efficiency and planning.
🔄 Better use of inventory and production resources.
Order Promising in SAP is a strategic enabler. It ensures companies can commit to realistic, optimized delivery dates that align with both customer expectations and supply chain capabilities. Leveraging advanced features like aATP, businesses can build resilience, agility, and customer trust in today's dynamic fulfilment landscape.
