JD Edwards EnterpriseOne Order Promising: Save Time and Improve Accuracy. An Oracle White Paper January 2004

Transcription

1 JD Edwards EnterpriseOne Order Promising: Save Time and Improve Accuracy An Oracle White Paper January 2004

2 JD Edwards EnterpriseOne Order Promising: Save Time and Improve Accuracy EXECUTIVE OVERVIEW When can I have my order? Can you ship it tomorrow? Tell me now. Your customers simple questions often have complex answers. Whether they are speaking with you on the phone or placing an order on a web storefront, customers expect immediate gratification. The moment they place an order, they want to know when it will ship. How do you respond? How do you balance customer delivery requirements against your need to make a consistent profit? If you expedite the order, will your margin erode to the point that it will cost you instead of make you money? Considering all your other orders, do you have the ability to produce the order by the requested date? Is it more profitable to ship the order from a distribution center hundreds of miles away or to build and ship it directly from the factory? You could use standard lead times to answer these questions and hope for the best, but if the quoted lead-time is too long, your valued customer may go elsewhere. If your lead-time is too optimistic and you miss the delivery date, your customer may never come back. And if you incur additional expenses such as overtime and premium freight, your valued customers may become unprofitable. On the other hand, if you consistently deliver according to your commitments and quickly assess your capability to respond to urgent customer orders, your customers will become even more loyal and valuable. And if you fully understand the costs associated with these actions, you can ensure that the orders you accept are profitable. This whitepaper describes the common process for promising orders and explains how order promise software can save you significant time and improve accuracy. It also describes the added value of Oracle s JD Edwards EnterpriseOne Order Promising with its integrated, real-time order promising that can instantly provide answers to the following questions: When can I deliver the order? From where should I source it? How much will it cost? JD Edwards EnterpriseOne Order Promising Page 2

3 What will the profit margin be on the order? What Must an Order Promising Application Do? Recognizing that every customer is different, an order promising application must support multiple order entry points simultaneously promising accurate and profitable delivery dates via the internet, phone, fax, EDI transactions, customer relationship management (CRM) applications, or multiple disparate order entry systems. Understanding the Status Quo To really understand how an order promising application can impact your business, it is important to understand the process for promising orders that exists in most companies today (summarized in Figure 1 below). Figure 1: The order promising cycle time. The clock starts ticking when the customer calls in the order and asks a simple question, When can I have my order? The customer service representative attempts to contact the planning department, but the planner is in a meeting. Several hours may pass before the planner reacts to the request. If the order contains complex processes and multiple levels in bill-of-material structure, it may take the planner several days to evaluate the impact of inserting the order into the current schedule. Once planning has the answer, the customer service representative attempts to contact the customer. When the customer is finally reached, he may either accept the promise date or reject it. The order may even be revised. If the promise date is rejected or the order is modified, the process will have to be repeated, taking up more of your, and the customer s, valuable time. JD Edwards EnterpriseOne Order Promising Page 3

4 What Improvements Can You Expect from an Order Promising Application? An online order promising application supports a different process to solve this problem, as summarized in Figure 2. Figure 2: The application automates the order promising process. The application fully automates the process of providing accurate order commitments, which includes two steps. The work that the planning department did in the manual process is externalized into a one-time setup to precondition the enterprise for promising orders. Conceptually, this is very similar to externalizing the setup of a piece of machinery on the shop floor. The second step is to automatically promise accurate and optimized delivery dates in real time. The time to promise the orders is now analogous to the run time to produce parts on the machine. Step 1 The sales and planning departments agree on a process for promising orders. This might include roles and responsibilities, manufacturing facilities along with items produced, and inventory policies for different items. The departments establish customer rules regarding back orders, partial shipments, and product substitutions. Next, they determine business objectives for how to fulfill customer orders. Sample objectives would be maximization of customer service, minimization of cost, or profit maximization. These objectives govern the details of how the promise will be made. For example, the business objective for maximizing customer service might search through alternatives based on meeting the delivery date at the lowest cost by using existing inventory from multiple locations before incremental manufacturing JD Edwards EnterpriseOne Order Promising Page 4

5 is authorized. If delivery cannot be made on time, overtime can be authorized and material can be expedited as required. The minimizing cost objective might be based on satisfying the order at the lowest cost, within an acceptable delivery window, from available inventory in your closest distribution center. Manufacturing operations will not be disrupted within a specific timeframe and you will never plan on using overtime or expedited material. The order promising application then applies these business objectives to customers and items. Those with similar characteristics can be grouped together for simplicity. Step 2 Now you are ready to start taking orders. You can accomplish promising orders in two ways: auto-promise mode or scenario management mode. In auto-promise mode, the best delivery date based on your predefined business objective for the customer/item combination is automatically applied to the order. Auto-promise mode is used by customer service representatives who typically accept the highest-ranked promising scenario based on the customer s assigned business objective. Since the user never exits the business process of order entry, this mode supports rapid, high-volume order entry. If the date promised is not acceptable, the order can be easily transferred to a supervisor via a standard workflow process for further evaluation. The supervisor can evaluate other fulfillment alternatives by using a scenario manager. In scenario management mode, the user is presented with several alternatives for fulfilling the order. The delivery date, costs, margin percentage, and total profit are summarized at the order level and detailed line-item information also can be explored. For each alternative, the user can view all the constraints that impact the order across the multisite enterprise. How Does it Work? Figure 3 illustrates how an online order promising application evaluates the capabilities of the multisite enterprise to determine the potential methods available to fulfill the order. JD Edwards EnterpriseOne Order Promising Page 5

6 Figure 3: The online order promising application evaluates the capabilities of the multisite enterprise. First, the application performs an available-to-promise (ATP) check to see if the item exists in inventory anywhere in the network, or if there are any scheduled receipts currently planned. Then, if the results of this query do not satisfy the order, the business objective, and the customer rules, the order promising application proceeds to the next level where a capable-to-promise (CTP) check is performed to identify a feasible production method using unallocated capacity and materials. This query will evaluate material and capacity-constrained plans across multiple sites and will drill down through all levels of the manufacturing routing and bill of material. Purchased materials can be modeled by using standard supplier lead times or, the supplier s actual capacity can be modeled. The Importance of Real-Time Execution Information Integration between the live execution environment and the in-memory order promise model is the key to making accurate promises. What many people do not realize is that the order promising application must be tightly integrated to the back office as well as the front office to provide real-time visibility to sales orders and all inventory-related transactions. In fact, back office integration is the more important and harder of the two. True, real-time back office integration can only be delivered economically within a single software solution. Real-time execution integration is critically important because changes that occur in the supply chain, such as late purchase orders or scrapped work orders, need to be considered in your promises as soon as they occur. This real-time back office integration is a key differentiator for EnterpriseOne Order Promising. Delivering Value The value proposition for EnterpriseOne Order Promising real-time order promising is as simple as 1-2-3: JD Edwards EnterpriseOne Order Promising Page 6

7 By understanding your true capability to fulfill customer orders, you can reduce uncertainty across your supply chain, resulting in lower inventory levels and improved customer service. Because your promising methodology is precoordinated using the planning knowledge base, you can achieve a more profitable use of your intellectual capital and your supply chain assets. By understanding the costs and margins associated with different fulfillment options, you can reduce cost of goods sold and improve the profitability of customer orders. JD Edwards EnterpriseOne Order Promising Page 7

8 JD Edwards EnterpriseOne Order Promising: Save Time and Improve Accuracy January 2004 Oracle Corporation World Headquarters 500 Oracle Parkway Redwood Shores, CA U.S.A. Worldwide Inquiries: Phone: Fax: oracle.com Copyright 2004, 2005, Oracle. All rights reserved. This document is provided for information purposes only and the contents hereof are subject to change without notice. This document is not warranted to be error-free, nor subject to any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or fitness for a particular purpose. We specifically disclaim any liability with respect to this document and no contractual obligations are formed either directly or indirectly by this document. This document may not be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without our prior written permission. Oracle, JD Edwards, PeopleSoft, and Retek are registered trademarks of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners.