Advanced Planning in Supply Chains: Illustrating the Concepts Using an SAP® APO Case Study
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This book provides students with valuable insights into the capabilities of state-of-the-art APS and bridges the gap between theory model building and solution algorithms , software implementation, and adaptation to a specific business case.
Optimize visibility of final demand in the supply chain
Our business case - named Frutado - provides a unifying framework for illustrating the different planning tasks that arise in a company - from demand planning to the distribution of goods - that are addressed by APS. In addition, the book guides through interactive learning units which have been created and recorded for each module of SAP's APS.
Learning units can be downloaded free of charge ready to be displayed in a web browser. Together, the textbook and the learning units provide the required skills to better understand the concepts, models, and algorithms underlying today's APS. Chu 3, Z. He 4 and J. Li 5 1, 4, 5 School of Mechanical, Electronic and Control. All rights reserved.
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Size: px. Start display at page:. Wilfred Singleton 1 years ago Views:. Similar documents. Balaji Gaddam. More information. SAP Excellence. Series Editors: Professor Dr. Courses Listed. All rights reserved Copyright TeknOkret Services. All Rights Reserved. Available online at ScienceDirect. Summary This article provides useful insights More information. Planning and Scheduling Issues in Supply Chains.
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Hartmut Stadtler (Author of Supply Chain Management and Advanced Planning)
Oracle Production Scheduling. After manual review and approval, the forecast is released from liveCache. This disaggregation is controllable by users and can be performed based on equal measure, manual adjustment, or the averages of the level below the higher aggregation level.
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This is necessary for making the forecasting performed at a higher level usable for subsequent planning processes. This can prepare a company before an implementation for what areas on which to focus, as well as the common solutions, or what is often found to work for each of these issues.
Preparing for each of these allows a company to do a better job of forecasting modeling. Notice how the colors are correlated to one another, and that is the color coding of the relationship between the issue and the solution. Companies that implement DP are often in for a surprise. DP has a tough to master data workbench. It also has a statistical and causal forecasting front end that is complicated to troubleshoot or even to understand. The result of all these limitations is that companies do not end up with the forecasting capabilities they thought they would have.
What this means is that it is very common for SAP DP implementations around the world serve to enable the business to do the forecasting they want and should be able to do. In fact, after visiting eight clients with DP installed, we have yet to see a client use DP to adequately support their forecasting process. This article describes the issues on statistical forecasting and DP. Many clients can be at a loss when it this happens.
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They take this all as evidence that they must have personally done something wrong in the implementation or their users are simply resistant to change. While the consulting advice on DP implementations is in fact pretty poor, some these issues are related to the product itself. Companies need advice how to improve their DP implementation, but this information is not available from either the large consulting companies or from SAP.
In fact, we have found most of the information provided by SAP to our clients to not be genuine and to contain multiple errors. Interestingly, the client did not have a high SKU count. For years many companies have been hoping that problems with DP would be fixed with 7. After extensively analyzing 7. This usually comes as a disappointment because SAP uses the promise of future releases to defend against fundamental design limitations of their products.
SAP sells the vision of a future that never comes, and we are in the position of giving the news that the next release will not solve all of their problems. DP maximizes their income, ergo, DP is the best forecasting system in common usage. Most SAP consultants see their incentives being to get you to use and keep using DP and to only accept its limitations and adjust your business to DP rather than developing the best solution.
Most companies are using DP such a limited way, and lack the information to improve DP that we have yet to see a DP implementation that cannot be substantially improved. SAP DP uses a complex data infrastructure to support standard forecasting techniques. This infrastructure is controlled through the Data Warehouse Workbench. The software space is controlled by vendors, consulting firms and IT analysts who often provide self-serving and incorrect advice at the top rates.
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See by clicking the image below:. Click Link to Jump to Section. Interested in Accessing Our Forecasting Research? We have a better track record of being correct than any of the well-known brands. If this type of accuracy interests you, contact us and we will be in touch.