demand and supply planning with sap apo (sap press) | reading sample

Reading SampleStart with the basics! In this reading sample, we dive into the basic planning functionality found in SAP APO, in addition to the custo-mization and master data modeling steps for creating your supply chain plan.

Sandeep Pradhan

Demand and Supply Planning with SAP APO813 Pages, 2016, $79.95 ISBN 978-1-4932-1333-7

www.sap-press.com/4011

First-hand knowledge.

http://www.sap-press.com/4011#utm_source=readingsample&utm_campaign=SlideShare%20Social&utm_medium=social&utm_content=1333

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Contents

Introduction ..................................................................................................... 19

1 Introduction to Supply Chain Planning .................................... 25

1.1 Sales and Operations Planning ....................................................... 281.1.1 Goal of Sales and Operations Planning ............................. 291.1.2 Case Study: Manufacturing and Distribution ..................... 30

1.2 Supply Chain Operations Reference Model .................................... 331.2.1 Level 1: Process Types ...................................................... 351.2.2 Level 2: Process Categories ............................................... 361.2.3 Level 3: Process Elements ................................................. 38

1.3 Types of Supply Chains .................................................................. 441.3.1 Pipeline Structure ............................................................. 451.3.2 Late-Customization Structure ........................................... 451.3.3 Diverging Structure .......................................................... 451.3.4 Converging Structure ........................................................ 45

1.4 Case Study: A Supply Chain Dilemma ............................................ 461.4.1 Business Situation ............................................................ 461.4.2 Sourcing ........................................................................... 471.4.3 Manufacturing ................................................................. 471.4.4 Order Management .......................................................... 481.4.5 Distribution ...................................................................... 491.4.6 Modeling the Company with the SCOR Model ................. 491.4.7 Value Stream Mapping ..................................................... 52

1.5 Demand and Supply Planning Overview ........................................ 541.5.1 Demand Planning ............................................................. 551.5.2 Supply Planning ............................................................... 611.5.3 Supply Chain Maturity Model ........................................... 651.5.4 Supply Chain Performance Management .......................... 67

1.6 Summary ....................................................................................... 71

2 SAP APO as an Advanced Planning and Scheduling Tool ......... 73

2.1 Advanced Planning and Scheduling Concepts ................................ 742.1.1 Planning and Scheduling .................................................. 752.1.2 Concurrent Planning ......................................................... 762.1.3 Modeling ......................................................................... 772.1.4 Exception Management Using the Alert Monitor .............. 78

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Contents

2.1.5 Differences between ERP and APS .................................... 792.2 Introduction to SAP APO ............................................................... 80

2.2.1 Core Planning Modules .................................................... 812.2.2 Task Structure .................................................................. 832.2.3 Benefits of Using SAP APO ............................................... 85

2.3 Planning Functions ........................................................................ 902.3.1 Demand Planning and Forecasting ................................... 922.3.2 Inventory Management .................................................... 932.3.3 Supply Network Planning ................................................. 932.3.4 Distribution Planning ....................................................... 932.3.5 Supply Chain Monitoring .................................................. 932.3.6 Sales and Operations Planning ......................................... 932.3.7 Network Design and Optimization ................................... 94

2.4 Demand Planning Overview .......................................................... 942.4.1 Statistical Forecasting ....................................................... 952.4.2 Casual Forecasting ............................................................ 962.4.3 Composite Forecasting ..................................................... 962.4.4 Promotion Planning ......................................................... 972.4.5 Collaborative Demand Planning ....................................... 972.4.6 Data Management ........................................................... 972.4.7 Bill of Material Forecasting ............................................... 982.4.8 Characteristics-Based Forecasting ..................................... 982.4.9 Lifecycle Management ...................................................... 982.4.10 Transfer of Demand Plan .................................................. 99

2.5 Supply Network Planning Overview ............................................... 992.5.1 Safety Stock Planning ....................................................... 1002.5.2 Solvers ............................................................................. 1002.5.3 Subcontracting ................................................................. 1032.5.4 Scheduling Agreement ..................................................... 1042.5.5 Hierarchical Planning ........................................................ 1042.5.6 Distribution Planning ....................................................... 1042.5.7 Supply Chain Monitoring .................................................. 105

2.6 Technical Architecture ................................................................... 1052.7 SAP liveCache ............................................................................... 1072.8 Summary ....................................................................................... 109

3 Guidelines for Implementing SAP APO ..................................... 111

3.1 Transformation Initiatives and Prerequisites ................................... 1123.1.1 Transformation Process .................................................... 1133.1.2 Transformation Framework ............................................... 114

3.2 Implementation Methodology ....................................................... 117

Contents

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3.3 Template Rollout Approach ........................................................... 1203.3.1 Pre-Activities .................................................................... 1213.3.2 Baseline System Activities ................................................. 122

3.4 Change Management .................................................................... 1233.5 Implementing Performance Measures ............................................ 1253.6 Business Benefits Realization ......................................................... 128

3.6.1 Increased Sales ................................................................. 1303.6.2 Profit Optimization .......................................................... 1313.6.3 Finished Goods Inventory Reduction ................................ 1323.6.4 Raw Material Inventory Reduction ................................... 1333.6.5 Material Cost Reduction ................................................... 133

3.7 Case Study ..................................................................................... 1353.7.1 Supply Chain Transformation Planning ............................. 1353.7.2 Key Guiding Principles ..................................................... 1373.7.3 System Architecture ......................................................... 1383.7.4 Sales and Operations Planning Characteristics .................. 1393.7.5 Demand Planning Characteristics ...................................... 1413.7.6 Inventory and Deployment Planning Characteristics ......... 1423.7.7 Rough-Cut Production Planning Characteristics ................ 1433.7.8 Planning Organization ...................................................... 144

3.8 Summary ....................................................................................... 147

4 Preparing for Basic Planning Functionality .............................. 149

4.1 Basic Planning Tasks ...................................................................... 1504.1.1 Demand Planning ............................................................. 1514.1.2 Supply Network Planning ................................................. 153

4.2 Basic Customization in SAP APO-DP .............................................. 1554.2.1 InfoObjects ...................................................................... 1564.2.2 Planning Object Structure ................................................ 1614.2.3 Planning Area ................................................................... 1644.2.4 Planning Book .................................................................. 1704.2.5 Macros ............................................................................. 1754.2.6 Locking Key Figures ......................................................... 1804.2.7 Time Series Consistency Checks ........................................ 182

4.3 Data Staging for SAP APO-DP ....................................................... 1824.4 Data Management in SAP APO-DP ................................................ 190

4.4.1 Creating New Characteristic Value Combinations ............. 1914.4.2 Capturing History ............................................................. 1914.4.3 Transfer Planning Data ..................................................... 192

4.5 Setting up Forecast Methods ......................................................... 1934.5.1 Univariate Forecasting ...................................................... 194

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Contents

4.5.2 Forecast Definitions ......................................................... 1964.5.3 Univariate Forecasting Methods ....................................... 2004.5.4 Casual Forecasting Methods ............................................. 207

4.6 Basic Customization in SAP APO-SNP ............................................ 2084.6.1 InfoObjects ...................................................................... 2084.6.2 Category Group ................................................................ 2094.6.3 Planning Area ................................................................... 2124.6.4 Planning Book .................................................................. 2144.6.5 Key Figures and Macros ................................................... 216

4.7 Supply Chain Modeling for SAP APO-SNP ..................................... 2234.7.1 Model and Planning Versions ........................................... 2234.7.2 Location ........................................................................... 2244.7.3 Location Product .............................................................. 2264.7.4 Resources ......................................................................... 2324.7.5 Production Data Structure ................................................ 2354.7.6 Transportation Lanes ........................................................ 2374.7.7 Quota Arrangement ......................................................... 2384.7.8 Supply Chain Engineer ...................................................... 239

4.8 Summary ....................................................................................... 241

5 Basic Interactive Planning ......................................................... 243

5.1 Demand and Supply Planning Cycle ............................................... 2445.2 Interactive Demand Planning ......................................................... 248

5.2.1 SAP APO Planning Book Navigation ................................. 2485.2.2 Characteristic Value Combination Maintenance ................ 2555.2.3 Realignment ..................................................................... 2575.2.4 Notes Management .......................................................... 2585.2.5 Fixing Cell ........................................................................ 2595.2.6 Chart Engine .................................................................... 2605.2.7 Releasing the Demand Plan from SAP APO-DP to

SAP APO-SNP .................................................................. 2625.3 Interactive Statistical Forecasting ................................................... 2655.4 Interactive Supply Planning ........................................................... 2695.5 SNP Heuristics ............................................................................... 271

5.5.1 Heuristic Engine Run Process ............................................ 2745.5.2 Replenishment and Procurement Using SNP Heuristics ..... 2755.5.3 Master Production Schedule and Capacity Leveling

Using SNP Heuristics ........................................................ 2785.5.4 Distribution Planning Using SNP Deployment Heuristics ... 2815.5.5 Master Data Maintenance ................................................ 2825.5.6 Interactive SAP APO-SNP Deployment Planning ............... 286

Contents

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5.6 Load Planning Using the SAP APO-SNP Transport Load Builder ..... 2885.7 Demand and Supply Planning Alerts .............................................. 292

5.7.1 Types of Alerts ................................................................. 2935.7.2 Visualizing Alerts with the Alert Monitor .......................... 2935.7.3 Methodology: The Decision Tree ...................................... 296

5.8 Simulation via Version Management .............................................. 2975.9 Summary ....................................................................................... 299

6 Advanced Demand Planning ..................................................... 301

6.1 Promotion Planning ....................................................................... 3026.1.1 Promotion Planning with SAP APO .................................. 3036.1.2 Promotion Planning with SAP CRM .................................. 308

6.2 Lifecycle Planning .......................................................................... 3106.2.1 Phase-In/Phase-Out Modeling ......................................... 3116.2.2 Interchangeability ............................................................ 314

6.3 Seasonal Planning .......................................................................... 3156.4 Bill of Material Functionality .......................................................... 318

6.4.1 Creating a New Planning Object Structure ........................ 3196.4.2 Creating a New Planning Area .......................................... 3206.4.3 Defining a New Planning Book ......................................... 3216.4.4 Maintaining the Production Process Model and

Production Data Structure ................................................ 3226.4.5 Maintenance of Characteristic Value Combinations .......... 324

6.5 Customer and Product Segmentation ............................................. 3266.6 Customer Forecast Management ................................................... 3286.7 Alerts ............................................................................................ 3306.8 Microsoft Excel-Based UI ............................................................... 3316.9 SAP Duet Demand Planning .......................................................... 3356.10 Summary ....................................................................................... 336

7 Advanced Supply Planning ........................................................ 337

7.1 Safety Stock Planning .................................................................... 3387.1.1 Manual Static Safety Stock Planning ................................. 3407.1.2 Manual Time-Dependent Safety Stock Planning ............... 3427.1.3 Advanced Safety Stock Planning ....................................... 344

7.2 Aggregated Planning ..................................................................... 3497.2.1 Hierarchical Planning Scenarios ........................................ 3507.2.2 Setting up the Hierarchy Structure .................................... 3527.2.3 SAP APO-SNP Customization ........................................... 353

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Contents

7.2.4 Preparing Master Data ..................................................... 3557.2.5 Technical Design Flow ...................................................... 3577.2.6 Testing Business Scenario ................................................. 359

7.3 Shelf Life Planning ......................................................................... 3627.3.1 Shelf Life Master Data ...................................................... 3637.3.2 Shelf Life Transaction Data ............................................... 3647.3.3 SAP ERP Batch Integration ............................................... 3677.3.4 Shelf Life Key Figures ....................................................... 3697.3.5 Shelf Life Propagation ...................................................... 3727.3.6 Shelf Life Alerts ................................................................ 372

7.4 Planning Strategies and Forecast Consumption .............................. 3737.4.1 Planned Independent Requirement Segment

(Requirement Planning) .................................................... 3767.4.2 Assignment Mode (Forecast Consumption) ...................... 3767.4.3 Category Group (Forecast Consumption) .......................... 377

7.5 Subcontracting .............................................................................. 3797.5.1 Master Data Requirements ............................................... 3807.5.2 Planning Book .................................................................. 383

7.6 Warehouse Capacity Overview ...................................................... 3857.6.1 Master Data ..................................................................... 3857.6.2 Perform the SAP APO-SNP Planning Run ......................... 386

7.7 Direct Shipment Customers ........................................................... 3877.8 Product Interchangeability ............................................................. 390

7.8.1 Scenario 1: Consume Existing Inventory ........................... 3927.8.2 Scenario 2: Consuming Existing Inventory until a

Specific Date .................................................................... 3967.9 Transport Load Builder .................................................................. 399

7.9.1 TLB Profile ....................................................................... 3997.9.2 TLB Loading Method ........................................................ 4007.9.3 Shipping Strategies ........................................................... 4017.9.4 Pull-In Horizon ................................................................. 4047.9.5 Shipment Sizing ................................................................ 405

7.10 Stock Balancing ............................................................................. 4077.11 Supply Planning Alerts ................................................................... 410

7.11.1 Managing Favorites in the Alert Monitor .......................... 4117.11.2 Using the Alert Monitor ................................................... 4127.11.3 Alert Monitor Hierarchies ................................................. 4147.11.4 Alerts in the Interactive Planning Screen .......................... 416

7.12 Supply Chain Cockpit ..................................................................... 4187.13 Planner’s Home Page ..................................................................... 4197.14 Summary ....................................................................................... 424

Contents

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8 Collaborative Planning .............................................................. 425

8.1 Overview ....................................................................................... 4268.2 Collaborative Demand Planning ..................................................... 4298.3 Collaborative Supply Planning ....................................................... 4328.4 Workflow ...................................................................................... 4348.5 Configuration ................................................................................ 435

8.5.1 Activate ICF Services ........................................................ 4368.5.2 Maintain Entries in Table TWPURLSVR ............................. 4368.5.3 Maintain ICM Monitor ..................................................... 4378.5.4 Publish Internet Services .................................................. 4378.5.5 Collaboration Partner User ............................................... 438

8.6 Vendor-Managed Inventory ........................................................... 4428.6.1 VMI Model and Technical Messaging Flow ...................... 4448.6.2 Configuring VMI Scenario in SAP APO-SNP ...................... 446

8.7 Integrating SAP Supply Network Collaboration with SAP APO ....... 4498.8 Inter-Market Demand and Supply Planning in a Single SAP APO

Application .................................................................................... 4528.9 Summary ....................................................................................... 457

9 Reporting ................................................................................... 459

9.1 SAP Supply Chain Performance Management ................................ 4609.2 SAP APO and SAP BW Integration ................................................. 463

9.2.1 Data Dimensions in SAP APO ........................................... 4639.2.2 SAP Business Warehouse Layers ....................................... 4659.2.3 Integration Scenarios ........................................................ 467

9.3 Extraction Process from SAP liveCache to SAP BW ......................... 4729.3.1 Generate DataSource Export ............................................ 4729.3.2 Create a Query ................................................................. 478

9.4 SAP APO-DP Data Model .............................................................. 4809.4.1 Flow 1: Historical Data Load (Inbound Flow) .................... 4809.4.2 Flow 2: Data Extraction (Outbound Flow) ........................ 482

9.5 SAP APO-SNP Data Model ............................................................ 4839.6 SAP BW Business Content ............................................................. 484

9.6.1 Access Standard Business Content .................................... 4859.6.2 Install Standard Business Content ..................................... 4859.6.3 Supply Chain SCOR Metrics .............................................. 4879.6.4 Level 1: High-Level Strategic Metrics ................................ 4899.6.5 Level 2: Diagnostic Metrics .............................................. 4919.6.6 Level 3: Configuration Metrics .......................................... 492

9.7 Summary ....................................................................................... 493

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Contents

10 SNP Optimizer ........................................................................... 495

10.1 SNP Optimization Concept ............................................................ 49610.1.1 SNP Optimization Steps ................................................... 49810.1.2 Differences between Heuristics and Optimizers ................ 49910.1.3 Constraints ....................................................................... 500

10.2 Costs ............................................................................................. 50110.2.1 Unsatisfied Demand or Delay ........................................... 50310.2.2 Storage Costs ................................................................... 50510.2.3 Safety Stock Penalty ......................................................... 50510.2.4 Production ...................................................................... 50610.2.5 Transportation .................................................................. 50710.2.6 Resource Expansion .......................................................... 50810.2.7 Procurement .................................................................... 509

10.3 Profiles .......................................................................................... 51010.4 Case Study: Network Model .......................................................... 513

10.4.1 Identifying Variables for a Graphical Representation ......... 51410.4.2 Running the SNP Optimizer with Constraints ................... 515

10.5 Automatic Cost Model .................................................................. 52510.5.1 Priorities and Preferences ................................................. 52510.5.2 Business Rules .................................................................. 527

10.6 SNP Optimization Explanation Log ................................................ 52810.7 Case Study: Supply Allocations ...................................................... 529

10.7.1 Optimization Model Input ................................................ 53010.7.2 Optimization Constraints .................................................. 53010.7.3 Optimization Cost Factors ................................................ 53110.7.4 Production Capacity Maintenance .................................... 53210.7.5 Maintain Storage Inventory Costs ..................................... 53410.7.6 Testing ............................................................................. 53510.7.7 Planning Run .................................................................... 535

10.8 SNP Deployment Optimizer ........................................................... 53810.9 The APO Performance Monitor ..................................................... 54010.10 Integrating External Optimizers ..................................................... 54110.11 Summary ....................................................................................... 543

11 Demand and Supply Matching with Capable-To-Match .......... 545

11.1 Capable-to-Match Concept ........................................................... 54611.1.1 Planning Characteristics .................................................... 54611.1.2 Planning Scenario ............................................................. 546

Contents

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11.1.3 Planning Modes ............................................................... 54811.1.4 Demand Prioritization ...................................................... 54911.1.5 Supply Categorization ...................................................... 55011.1.6 Search Strategy ................................................................ 551

11.2 Customization via the CTM Profile ................................................. 55111.2.1 Planning Scope ................................................................. 55211.2.2 Strategies ......................................................................... 55511.2.3 CTM Integration with Global ATP ..................................... 55611.2.4 CTM Early/Late Demand Fulfilment .................................. 56011.2.5 Aggregation ..................................................................... 56111.2.6 Demand ........................................................................... 56211.2.7 Supplies ........................................................................... 56311.2.8 Settings ............................................................................ 56411.2.9 Supply Distribution .......................................................... 566

11.3 Master Data .................................................................................. 56611.4 Planning Run ................................................................................. 56811.5 Case Study ..................................................................................... 56911.6 Summary ....................................................................................... 571

12 Inventory Planning and Optimization with SAP APO and SAP ERP .............................................................................. 573

12.1 Inventory Optimization ................................................................. 57512.1.1 Dynamics ......................................................................... 57612.1.2 Supply Chain Applications ................................................ 57812.1.3 Techniques ....................................................................... 580

12.2 Inventory Analysis Methodology ................................................... 58112.2.1 Product Portfolio Classification (ABC Analysis) .................. 58212.2.2 Inventory Stocking Policies Quadrant ............................... 58512.2.3 Inventory Historical Analysis ............................................. 58712.2.4 Inventory Un-Bundling ..................................................... 59112.2.5 Inventory Modeling .......................................................... 59412.2.6 Inventory Cost-Benefit Analysis ........................................ 598

12.3 Designing an Inventory Control System ......................................... 60012.3.1 Economic Order Quantity ................................................. 60012.3.2 Lot Sizing ......................................................................... 60212.3.3 Target Stock Level ............................................................ 608

12.4 Multi-Echelon Inventory Planning ................................................. 61112.5 Summary ....................................................................................... 614

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Contents

13 Characteristics-Based Planning ................................................ 617

13.1 Process Overview .......................................................................... 61813.2 Technical Steps .............................................................................. 620

13.2.1 Case Study ....................................................................... 62113.2.2 Variant Configuration ....................................................... 62213.2.3 Material Master ............................................................... 62413.2.4 Characteristics .................................................................. 62613.2.5 Variant Class .................................................................... 62813.2.6 Super BOM ...................................................................... 62913.2.7 Super Routing .................................................................. 63013.2.8 Configuration Profile ........................................................ 63113.2.9 Object Dependencies ....................................................... 63213.2.10 Customizing Sales Orders ................................................. 633

13.3 Forecasting .................................................................................... 63513.3.1 Activate Characteristics-Based Planning ............................ 63613.3.2 Master Data ..................................................................... 63613.3.3 Planning Book Design ...................................................... 63913.3.4 Descriptive Characteristics ................................................ 64213.3.5 Demand Planning Release ................................................ 643

13.4 Supply Planning Integration ........................................................... 64513.4.1 Business Scenario and Technical Steps .............................. 64513.4.2 Block Planning Integration ............................................... 648

13.5 Summary ....................................................................................... 650

14 SAP Industry Solution Example with SAP APO ........................ 651

14.1 SAP Apparel and Footwear Industry Solution ................................. 65214.2 SAP ERP (AFS Extension): Integrated Solution Overview ................ 654

14.2.1 Process Steps ................................................................... 65514.2.2 AFS Planning .................................................................... 658

14.3 Master and Transactional Data Integration .................................... 65914.3.1 Maintain Master Data ...................................................... 66014.3.2 Data Transfer from SAP ERP to SAP APO .......................... 66014.3.3 Bill of Materials Construct in SAP ERP (AFS Extension) ..... 66114.3.4 Transactional Data Integration .......................................... 663

14.4 SAP APO Solution for AFS Using Aggregated Functionality ............ 66714.4.1 Demand Planning: Seasonal Functionality ........................ 66814.4.2 Supply Network Planning: Aggregated Functionality ......... 668

14.5 SAP Business Function ................................................................... 67314.6 Summary ....................................................................................... 674

Contents

17

15 Technical Architecture ............................................................... 675

15.1 Core Interface ................................................................................ 67615.1.1 Configuration Steps .......................................................... 67715.1.2 Integration Models ........................................................... 67915.1.3 Incremental Data Transfer ................................................ 68415.1.4 Administration ................................................................. 68815.1.5 Troubleshooting ............................................................... 70015.1.6 Customer Exits ................................................................. 70315.1.7 Publication of Planning Results ......................................... 70415.1.8 Regular CIF Monitoring Transactions ................................ 705

15.2 Technical Upgrade Functional Activities ......................................... 71015.2.1 Plan Phase ....................................................................... 71315.2.2 Prepare Phase .................................................................. 71315.2.3 Upgrade Phase ................................................................. 71415.2.4 Post-Upgrade Phase ......................................................... 714

15.3 SAP APO on SAP HANA ................................................................ 71615.3.1 Deployment Options ........................................................ 71715.3.2 Benefits ............................................................................ 71815.3.3 SAP S/4HANA .................................................................. 720

15.4 SAP Supply Chain Info Center ........................................................ 72115.4.1 Dashboards ...................................................................... 72215.4.2 Deployment Options ........................................................ 72715.4.3 Data Replication .............................................................. 727

15.5 Rapid Deployment Solutions for SAP APO ..................................... 73715.6 SAP APO as an Add-on to SAP ERP ............................................... 74115.7 SAP Fiori Apps for SAP APO .......................................................... 74415.8 Hardware Sizing using Quick Sizer ................................................. 74615.9 Technical Integration with Non-SAP Applications .......................... 750

15.9.1 SAP APO Business Warehouse ......................................... 75115.9.2 Enterprise Service Bus ...................................................... 752

15.10 Summary ....................................................................................... 753

16 Technical Enhancements ........................................................... 755

16.1 Data Conversion Strategy .............................................................. 75616.1.1 Data Conversion Process .................................................. 75716.1.2 Data Mapping and Cleansing ............................................ 758

16.2 Legacy System Migration Workbench ............................................ 76016.3 Converting Data Using LSMW ....................................................... 761

16.3.1 Loading Master Data ........................................................ 763

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Contents

16.3.2 Converting Transactional Data .......................................... 76816.3.3 Importing Data with IDocs ............................................... 772

16.4 Technical Modifications in SAP APO .............................................. 77216.4.1 Business Scenario 1: Material Master CIF .......................... 77316.4.2 Business Scenario 2: Product Master Creation .................. 77516.4.3 Business Scenario 3: Transaction Data Mapping ............... 77716.4.4 Business Scenario 4: SAP APO-SNP PDS Modification ...... 78016.4.5 Business Scenario 5: SAP APO-SNP Planning Book

Modifications ................................................................... 78116.4.6 Business Scenario 6: User Exit Macro ................................ 78216.4.7 Business Scenario 7: SNP Heuristics Lot Sizing .................. 78516.4.8 Business Scenario 8: CTM Demand Prioritization .............. 78516.4.9 Business Scenario 9: Demand Planning with SAP BW ....... 78616.4.10 Business Scenario 10: Demand Planning to

Supply Planning Release ................................................... 78716.4.11 Business Scenario 11: Alert Monitor ................................. 78816.4.12 Business Scenario 12: TLB Interactive Display ................... 788

16.5 Authorization Concept ................................................................... 78816.5.1 Master-Derived Role Concept .......................................... 78916.5.2 Defining Roles .................................................................. 790

16.6 Process Chain ................................................................................ 79116.6.1 Main Components ............................................................ 79216.6.2 Create the Process Chain .................................................. 79316.6.3 Process Chain Monitoring ................................................ 79616.6.4 Parallel Processing ............................................................ 797

16.7 Summary ....................................................................................... 798

17 Conclusions and Outlook .......................................................... 799

Appendices ....................................................................................... 803

A Resources ................................................................................................ 805B List of Acronyms ...................................................................................... 807C The Author .............................................................................................. 811

Index ................................................................................................................ 813

Reading SampleStart with the basics! In this reading sample, we dive into the basic planning functionality found in SAP APO, in addition to the custo-mization and master data modeling steps for creating your supply chain plan.

Sandeep Pradhan




“Preparing for Basic Planning

Functionality”

Contents

Index

The Authors


149

Chapter 4

In this chapter, you’ll learn the basic planning functions that are performed in SAP APO, as well as the basic customization and master data modeling steps needed to start creating your supply chain plan.

4 Preparing for Basic Planning Functionality

In this chapter, you’ll learn the basic customization steps for APO-DP and APO-SNP in SAP APO. While this task is usually performed by a solutions designer inthe SAP APO project, this chapter also aims to help business users understand thefoundation on which the SAP APO standard configurations are performed.

This chapter will help you to better understand the calculations that the SAP APOsystem performs during the planning run. We’ll also explain the APO-DP fore-casting models and APO-SNP modeling objects that prepare the system for thebasic task structure performed during the weekly planning cycle. Understandingthis basic foundation will also enable you to help enhance a company’s SAP APOfunctionality for any change in future business models.

As shown in the mind map for this chapter (see Figure 4.1), we will be discussinghow to set up basic planning functionality in SAP APO. Besides highlighting thecustomization steps in APO-DP and APO-SNP, we’ll also discuss how to set upforecasting models and a supply chain model as part of SAP APO functionality.

We’ll delve further into using our business case study, ABC Technology, as anexample. While ABC Technology is focused on both manufacturing and distribu-tion, the company’s primary focus is on inventory control and goods distribution.We’ll get started with understanding the basic planning tasks that a supply chainplanner must go through with SAP APO, and see how these tasks fit into ABCTechnology’s methods.

Preparing for Basic Planning Functionality4

150

Figure 4.1 Learning Points for the Chapter (Mind Map)

4.1 Basic Planning Tasks

The goal of the supply chain planner role is to balance the demand and supplyplan for their group of products. The planner performs these planning tasks on aweekly or monthly cycle.

SCP is an iterative process that consists of creating an unconstraint demand planusing the forecasting process, and then optimizing various supply plans in theform of procurement, production, replenishment, and distribution plans. SAPAPO is the best tool to help with these tasks, as it’s a decision-support tool thatoutputs planning results for the supply chain planner to evaluate analysis andmake any necessary changes.

Example

ABC Technology wants to use SAP APO to plan its laptop, desktop, and monitorproducts. Since it manufactures and distributes these products in North America, thecompany plans to use APO-DP for forecasting and APO-SNP for replenishment anddistribution supply plans. The company is challenged with providing custom products

Basic PlanningFunctionality in SAP APO

Basic Planning TasksDemand Planning

Supply Planning

Basic Customization in APO-DP

InfoObjects

CharacteristicsNav. Attribute

Aggregates

Key figure

Planning Area

Planning Books

Macros

Aggregation andDisaggregation

Proportional Factor

Time-Based Disaggregation

Time series Consistency Checks

Data Staging in APO-DP

InboundHistorical

Delta

Outbound

Data Handling

Setting up ForecastMethods

Forecast Methods

Forecast Profiles

Background Processing

Forecast Errors

Basic Customization in APO-SNP

InfoObjects

Planning Area

Planning Book

Macro

Category Group

BW Extraction

Supply Chain Modeling in APO

Model/Version

Location

Calendar

Product Location

Transportation Lane

Transport Method

TLB Profile

Lot Size Profile

Quota Arrangement

Resource

Production Data Structure

Consistency Check

Supply Chain Engineer

BW Extraction

Fixed kf

Realignment

Characteristics ValueCombination

Basic Planning Tasks 4.1

151

to its customer base on the shortest possible lead-time, in order to keep its next-daydelivery value proposition.

In the following sections, we’ll review the planning tasks performed by thedemand planner and supply planner in the SAP APO landscape and identify thebusiness planner’s interactions with SAP APO. Understanding the planner’s rou-tine business activities is important for the SAP solution designer when it comesto designing the system per business requirements.

4.1.1 Demand Planning

The planning tasks in SAP APO are always based on algorithm programs, whichthe business planner can validate and adjust, if necessary. Figure 4.2 shows theschematic activity flow for APO-DP.

Figure 4.2 Demand Planning Tasks

Historical sales orders are required for the statistical forecasting process 1. Thehistory is primarily staged from SAP Business Warehouse (SAP BW). SAP BWextracts the sales orders from SAP ERP using Logistics Information System (LIS)structures in SAP ERP. As shown in the architecture in the figure, there will betwo data loads: the initial historical data for the last two or three years, and thepost–go-live weekly delta loads on actual sales orders recorded in the past week.

SAP ERP

SAP BWAnalyzeAlerts

StatisticalForecast

APO-SNPand

PP/DS

SAP APO

Delta

History

Delta

History

APO-DPPlanning

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APO-DPPlanning

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Some companies might include a custom filter in SAP BW to segregate salesorders based on order types for business reasons. This task is primarily per-formed by the company IT group; no user involvement takes place.

SAP APO has a small, built-in SAP BW component that can be used to stage thedata coming from SAP BW. The data flows from SAP APO’s SAP BW componentto the SAP liveCache time series planning books 2. The planner validates histor-ical data, and might make manual adjustments to the history. Once the history isadjusted, it becomes the baseline for statistical forecast calculation 3.

Next, the baseline history serves as input for the forecasting run, which either canbe set to run a model automatically, or based on user definitions. In the case ofthe automatic forecasting model, the system selects the model that gives the low-est forecast error (for example, MAPE). Alternatively, the user may select definedforecast models for his or her product or product groups based on pre-analysis.The result of the forecasting run is analyzed by a demand planner in the APO-DPplanning book 4.

The demand planner can analyze the forecasting run by looking at the forecasterrors, which are identified by the forecast model that’s selected by a system orbusiness user. Also, an alert can be set up to compare the forecast with the aver-age sales from the last three months and provide an alert if the proposed forecastis more than, say, 25% of that value. The planner again has the ability to overridethe system’s proposal with some judgmental adjustments. Also, in this activity,the sales and marketing team enters the promotions to close the gap on thedemand plan and yearly operational plan (i.e., budget).

The final demand plan then undergoes discussion in the monthly forecast reviewmeetings before the monthly sales and operations plan. Once the supply chainand sales, marketing, and finance teams reach a consensus on the final demandplan during the business meeting, an SAP BW snapshot is taken of the plan andreleased to supply planning to check on supply feasibility 5. The release of thedemand plan to supply planning can be either to one of the SAP APO functional-ities (APO-SNP or PP/DS) or the SAP ERP-MRP system directly, based on procure-ment planning design selection.

Example

ABC Technology distributes its products from three distribution centers where customerorders are captured. SAP APO will perform forecasting at the location product level for

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the next twelve months, in monthly buckets. ABC Technology uses the combination ofdefined forecasting (exponential, seasonal, and linear) and automatic forecasting mod-els, the latter being used for products for which the individual forecasting is difficult toidentify.

ABC Technology’s demand planner reviews the forecast and makes any adjustments inSAP APO planning books for the short horizon to better reflect market demand situa-tions.

4.1.2 Supply Network Planning

Once the final demand plan is released to supply planning (APO-SNP, in our busi-ness case), the supply planner starts his or her planning activities. The role of thesupply planner is not only to check the supply feasibility of the unconstraintdemand plan, but also to formulate a feasible procurement, distribution, and pro-duction plan. The supply planner communicates with sourcing units (e.g., facto-ries and vendors) to check the feasibility of proposed plans. He or she is furtherdiscussed in the monthly sales and operations meeting. The supply planner alsoneeds to check both the material availability and capacity to supply the demand.

Figure 4.3 shows the schematic activity flow for APO-SNP in SAP APO. The majoractivity for the business in these processes would be analyzing the SAP APO resultand fine-tuning the master data for any parameter corrections. The figure illus-trates the following system flow:

1 The supply chain activities require supply chain modeling before planningbegins. Using transportation lanes and other SAP APO master data elements,the business user models their supply chain in SAP APO. The modeling processincludes setting up the supply network and relevant master data settings for theSAP APO solvers to calculate an accurate supply plan. The core master data istransferred from SAP ERP using SAP APO’s Core Interface (CIF) technology.The supply chain data objects are further discussed in Section 4.7. Also definedwithin the supply chain model is the target inventory for each location in thesupply network.

2 Besides the master data, transaction code data is also activated via CIF betweenSAP ERP and SAP APO. All SAP APO-relevant receipts, demands, and stocks areexchanged between the two systems in real time. There is a standard CIFcompare/reconcile consistency report that the IT support group needs to run


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periodically in order to ensure that all transactional data is consistent betweenthe SAP ERP and SAP APO systems.

Figure 4.3 Supply Network Planning Tasks

3 The unconstrained demand plan is released from APO-DP at the location prod-uct level. The planner analyzes the supply situation before the nightly run andmakes any required adjustments (for example, increasing capacity).

4 The nightly planning run touches the complete supply network and plans thesafety stock, replenishment, distribution, and production plans. Depending onthe business requirements, the first planning run can consider infinite or finitecapacities.

5 The supply planner analyzes the supply situation again and reacts based on sup-ply alerts (for example, stockouts) to focus on items that require criticalaction. The planner may accept the system proposals, or may override thoseproposals with his or her own feasible plan for the sales and operations plan-ning meeting.

6 A second planning run is performed to re-balance demand and supply acrossthe network. Any excess inventory will trigger alerts for stock balancing. Thisplanning run may run on finite capacity and constraint environment. Amonthly snapshot may be taken at this stage by SAP BW.

APO DP

AnalyzeAlerts

PlanningRun

PlanningRunSupply Chain

Model

SAP ERP SAP APO

Master Data

Transaction Data

SupplyChain

Execution

ManufacturingPlanning

SNPPlanning

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SNPPlanning

Books

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7 The final supply plan is published to the manufacturing, distribution, and pro-curement teams for supply chain execution. The planner may use the TransportLoad Builder (TLB) in APO-SNP to ensure that the proposed stock transportorder and purchase order meet the load capacity and vendor minimums.

Example

ABC Technology’s network consists of manufacturing and distribution facilities. Thesupply planner uses the APO-SNP planning book to review the demand and supply sit-uations across the network following the nightly planning run. Though the supply plan-ning is done at the weekly bucket level, the planner closely monitors the inventory lev-els across the network to ensure that customer orders are being fulfilled, and that prod-ucts are produced and replenished on time.

Having studied the planner’s basic tasks, we’ll now discuss the steps you need tofollow to configure the SAP APO functionality for both APO-DP and APO-SNP.

4.2 Basic Customization in SAP APO-DP

This section explains the basic customization steps for APO-DP, as well as thebackground information and basic definitions you’ll need to get started. The cus-tomization steps consist of setting up a planning object structure for planningbased on the product, customer, and time characteristics; identifying the key fig-ures (e.g., forecast, sales orders, promotions); and setting up the planning bookand macro (used for mathematical calculation) for both background and interac-tive planning.

Example

ABC Technology would like to design an SAP APO planning book with different prod-uct, customer, and time characteristics. Some examples of these characteristics areproduct, product family, brand, customer, customer group, and calendar month. Thekey figures display the planning data for the identified characteristics. Some examples ofthe key figures are historical sales orders, forecast, and sales and marketing promotions.

Customizing APO-DP starts with a data modeling exercise in identifying InfoOb-jects (characteristics and key figures), which is explained in the following sub-sec-tions. The solution designer performs the customization, taking into accountbusiness requirements from demand planner users.


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4.2.1 InfoObjects

InfoObjects represent the smallest selling unit in SAP BW. They define the busi-ness process and information we are seeking. An example of an InfoObject is cus-tomer, product, or historical sales order quantity. Before we start customizingInfoObjects, you need to understand some background information about them.First of all, there are five different types of InfoObjects:

� Characteristics Some examples of characteristics are customer, product, material group, cus-tomer group, and location. These represent the planning levels and consist ofcustomer and product attributes. One or more characteristics make up the keyto the data record for demand planning. Characteristics are definitions fordescribing the business object, not the data.

� Key figures Key figures represent the numeric information for the business object. Thereare different types of key figures: quantity, amount, date, time, number, andinteger. Some examples of key figures are selling price and actual sales orderquantity.

� Time characteristics Time characteristics describe time reference for the business event. Some of thestandard SAP time characteristics are calendar day (0CALDAY), calendar week(0CALWEEK), calendar month (0CALMONTH), calendar quarter (0CALQUARTER), calen-dar year (0CALYEAR), fiscal year (0FISCYEAR), and fiscal period (0FISCPER).

� Unit characteristics Unit characteristics are used for providing a unit of measure for the defined keyfigure.

� Technical characteristics Technical characteristics are used for technical purposes. An example is arequest ID for storing the data load information.

These InfoObjects are translated with the data modeling, which identifies theproduct, customer hierarchy, and time dimensions to be used in the SAP APOplanning object structure. Before you start customizing, you should alwaysunderstand the dimensions of the characteristics to be used in the SAP APO data-base model for which you’d like to perform demand planning. As such, we’ll startwith a data modeling exercise.


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Data Modeling Exercise

The data model defines the customer, product, or time characteristics on whichwe want to divide the planning data in the SAP APO planning book. As Figure 4.4shows, we start by drawing a three-dimensional axis with product, customer, andtime dimensions.

Example

For ABC Technology, we need to identify the product, geography, and customer hierar-chies relevant to planning and promotions. Though the hierarchy master data may haveseveral levels, we only need to identify the aggregation level against which we forecastand distribute the products for SAP APO planning. For each product, customer, andtime dimension, we list all of the hierarchical objects that would be relevant for APO-DP.

Figure 4.4 InfoObject Data Modeling

Figure 4.4 shows how an ABC Technology business planner would separate his orher data for planning and reporting purposes in SAP APO. Examples of productcharacteristics are product category, brand, range, and product, while customercharacteristics are sales organization, sales region, location, channel, and cus-tomer. The time dimensions are calendar week and month. The planner can also

Product

Customer/Geography

Time

ProductCategory

Range

Brand

DemandPlanner

Product

CustomerGroup

CalendarMonth

Customer

Location

Sales Region

SalesOrganization

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CalendarWeek


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identify characteristics to be used for selection and navigation, but not for plan-ning. This type of characteristic is called a navigational attribute. An example of anavigational attribute is the demand planner code as part of product characteris-tics, and the customer group for customer characteristics.

Customization Steps

Now you’re ready to start creating InfoObjects.

First, create the InfoObject in the Administrator Workbench in SAP APO via themenu path SPRO � SAP Reference Img � Advanced Planning and Optimization �

Supply Chain Planning � Demand Planning � Basic Settings � Data Warehous-

ing Workbench.

In the left part of the Data Warehousing Workbench, in the Modeling section,click on InfoObjects. Right-click the node InfoObjects and choose Create Info-

Area. An InfoArea is used for storing the characteristics and key figure catalogsrelevant to the data model.

Tips & Tricks

The BW Administrator Workbench can also be accessed via Transaction RSA1.

Once you’ve created the InfoArea, right-click on the InfoArea node to Create

InfoObject Catalog. The InfoObject Catalog is used to catalog the InfoObjects,which have been created as characteristics, time characteristics, or key figures. AsFigure 4.5 shows, we want to create two separate catalogs for characteristics andkey figures. The catalog is used for storing project-specific APO-DP InfoObjectsfor both characteristics and key figures. Per our case study, you need to input theproduct, customer, and time characteristics into the characteristics catalog, andthe key figures into a separate catalog. You can maintain SAP standard character-istics and key figures starting with a 9A prefix in the catalogs by directly inputtingthe technical field. The standard 9A prefix denotes characteristics (for example,9AMATNR and 9ALOCNO) and key figures (for example, 9ADFCST) that are provided bySAP.

Create new InfoObjects for the required characteristics and key figures by right-clicking the catalog, selecting Create InfoObject, and maintaining a technicalname and description. Always select BW InfoObject to be used for data stagingand extraction. Some examples of characteristics are product group, customer


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group, product, customer, sales organization, location, and material group, whichall help to separate planning data into different dimensions. As Figure 4.5 shows,we can either directly input the InfoObject, or create a new one. You can accessthe InfoObjects via Transaction RSD1 for any further maintenance.

Figure 4.5 Steps for Creating Characteristics and Key Figures InfoObjects

APO-DP offers functionality in the form of a navigational attribute, which can beused as a characteristic in the planning book for navigation, analysis, and report-ing purposes. The ABC Technology business planner can use the characteristicDemand Planner to segregate products for planning and the customer group, asanother characteristic, for the purpose of customer segmentation. You willneed to set up the navigational attribute, which helps define the selection and

Direct inputor create new keyfigure InfoObject

Create InfoArea

Create char. catalog

Create keyfigure catalog

Direct Inputor create new char.

InfoObject


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navigation criteria without defining them as characteristics in the demand plan-ning structure. The first three steps (as shown in Figure 4.6) are:

1 Assign an attribute to the characteristics. The characteristics can be accessed viaTransaction RSD1 or in the BW Administrator Workbench (Transaction RSA1)InfoObject folder. Double-click on the characteristics name to display the detailsfor maintenance.

2 Next, input the characteristic that needs to serve as the navigational attribute. Asshown in the figure, the navigational attribute for the customer is the customergroup. Once maintained, click the Navigational Attribute icon to switch onthe navigational attribute.

Figure 4.6 Setting up a Navigational Attribute to the Characteristics

3 The last step is to maintain the master data of the valid combination value in thetable, as shown in Figure 4.7.

Input the attribute

Maintain theattribute values

Switch on thenavigational attribute


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Note

You can refer to SAP OSS Note 413526 for the list of comparisons between navigationalattributes and characteristics.

Figure 4.7 Navigational Master Data Maintenance with Valid Combinations

4.2.2 Planning Object Structure

Now that we have created the InfoObjects in APO-DP, the next step is to createthe planning object structure, which will define the characteristics we want tomodel in the planning books. The planning object structure contains the charac-teristics required for planning and stored in SAP liveCache. The characteristicsdetermine the planning level and how the data can be stored. In our case study,ABC Technology has elected to use the most commonly used characteristics fromthe product and customer hierarchies.

The key here is to select all off the characteristics that will be used for planningpurposes. The activation of a planning object structure results in the creation of


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an internally generated InfoCube in which the characteristic combinations for theplanning object structure are stored. Follow these steps to create the structure:

1. Create a planning object structure via SPRO � SAP Reference Img � Advanced

Planning and Optimization � Supply Chain Planning � Demand Planning �

Basic Settings � S&DP Administration.

2. Click the Planning Areas tree structure, and then choose Plng Object Struc-

tures to change the path from Planning Area to Planning Object Structure.

3. Transfer all the relevant characteristics defined earlier in InfoObject from theright side to the left, as shown in Figure 4.8. Clicking Navigation Attributes

displays all the attributes associated with the planning characteristics.

Figure 4.8 Setting up Planning Object Structure for Demand Planning

Create Aggregates

Within the Planning Object Structure, we can also define aggregates. The pri-mary purpose of the aggregate is to improve system performance while accessingthe planning data. This configuration will help the business planner access datafaster in the planning books with large selection.


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Example

ABC Technology will want to define aggregates, so the demand planner has to access anumber of stock-keeping units (SKUs) for planning. The use of aggregates serves as anindexing of the demand planning data.

In addition to the detailed level, the planning data is also stored in the aggregatelevels. Although the use of aggregates consumes little more SAP liveCache spacein-memory, the planning data load access is faster with the aggregate mechanism.This is because there is no aggregation happening after you load your selection.The system knows an aggregate exists and hence loads it directly.

To create an aggregate, right-click the planning object structure and select Create

Aggregate. Figure 4.9 shows an example of an activated aggregate. With thisfunctionality, the ABC Technology planner can now use the aggregate character-istics as a selection profile when accessing large volumes of data in the SAP APOplanning book.

Figure 4.9 Aggregate for Planning Object Structure


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Note

Refer to SAP OSS Note 503363 for more information on the use of aggregates in plan-ning object structures.

4.2.3 Planning Area

A planning area is the central data structure in APO-DP. It lists all the characteris-tics (i.e., the planning object structure) and contains a collection of key figures tobe used in the planning process. You can connect the planning area with an SAPBW data mart to send the historical data to APO-DP. Key figures for planning andtheir disaggregation types are defined for a planning area.

Before we begin configuring the planning area, we need to define the fiscal yearvariant and the storage bucket profile, which will later be assigned to the plan-ning area. Once users start using the SAP APO system, more characteristics andkey figures might be needed in the planning area to offer more flexibility in theplanning process. These additions require deactivating the current planning areaand the possible loss of planning data. For this reason, a backup of APO-DP iskept in either SAP APO’s internal SAP BW system, or in the SAP BW system. Thiscontingency is also built during the system upgrade, when the planning areas aredeactivated and the SAP liveCache system is brought down. As a best practice, theplanning data backup is routinely scheduled every month.

Define the Fiscal Year Variant

Many companies use the fiscal year variant for financial reporting purposes. Toalign finance estimates with planning volume, it would be ideal to use the fiscalyear variant for the calculation. The fiscal year variant is used to determine the fis-cal year, how many posting periods are available in a year, and which dates con-stitute the end of each period. It is recommended that the fiscal year be definedfor a longer period of time than the horizon defined in the planning books.

Example

ABC Technology would like to plan for the next rolling twenty-four months, using thelast two years’ historical data. For this reason, if planning is done one year back and oneyear ahead in the planning book, it is recommended that the fiscal variant be definedtwo years in the past and two years into the future.


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The fiscal year variant needs to be updated annually, at the end of each fiscal year,in order to reflect the periods of the succeeding years. To do this, follow the menupath SPRO � SAP Reference Img � Advanced Planning and Optimization � Sup-

ply Chain Planning � Demand Planning � Basic Settings � Maintain Fiscal

Year Variant.

Next, create a storage bucket profile, which defines how the system stores the datacreated by APO-DP or APO-SNP. You define the storage bucket profile for a specificnumber of periods; thus, it is recommended that the periods be updated periodi-cally. The fiscal variant is attached within the storage bucket profile. The custom-ization path is SPRO � SAP Reference Img � Advanced Planning and Optimiza-

tion � Supply Chain Planning � Demand Planning � Basic Settings � Define

Storage Bucket Profile. Figure 4.10 shows an example of a storage bucket profile.

Figure 4.10 Storage Bucket Profile

Once we have defined the fiscal year variant and the storage bucket profile, wecan input them into the planning area, as described in the next subsection.

Configure the Planning Area

The planning area combines the characteristics (from the planning object struc-ture) and various key figures to further configure the planning. The planning


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book is where the business users perform planning analysis and adjustments toformulate a demand plan. To set up the planning area, follow these steps:

1. To customize the planning area, follow the menu path SPRO � SAP Reference

Img � Advanced Planning and Optimization � Supply Chain Planning �

Demand Planning � Basic Settings � S&DP Administration.

2. Right-click the planning area node and select Create Planning Area. In theplanning area, specify the following in various tabs:

� The list of the key figures (created earlier as InfoObjects) to be used for plan-ning, as shown in Figure 4.11 (Key Figure tab).

Figure 4.11 Demand Planning Area


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� Currency to be used for planning (Info tab).

� Unit of measure for planning (Info tab).

� Aggregate level on which to data can be stored beside the lowest level toimprove performance (Aggregate tab).

� Aggregation and disaggregation rules for the key figures (Key Figure Aggre-

gation tab).

In the Planning Area � Key Figure Aggregation tab, we can define the aggrega-tion and disaggregation of each key figure by its calculation type and its time-based disaggregation type. In the Calculation type field, we can mention if thekey figures needs to be marked pro-rata (type S), average (type A), or a referenceto a different key figure (type P).

Proportional Factors

As Figure 4.12 shows, while the majority of key figures are marked with calcula-tion type S, the average price key figure is average A, and the manual adjustmentis marked P to be based on historical key figure pro rata.

Figure 4.12 Aggregation and Disaggregation Logic for Key Figures


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Similarly to the calculation type, we maintain time-based disaggregation fordefining rules for planning data disaggregation. Some examples of time-based dis-aggregation are either proportional allocation (type P) or no time-based disaggre-gation (type N). The time-based disaggregation is of particular interest in businessscenarios when the majority of the sales occur during the last week or days of themonth. Figure 4.12 shows different calculation and time-based disaggregationtypes. The main concept here is proportional factors. SAP APO uses proportionalfactors to enable the disaggregation of data down to the lowest level.

Example

ABC Technology plans to calculate the proportional factors and use the calculation as areference for the statistical forecast key figure. This will ensure that the forecast is placedat the correct location based on the historical pattern. ABC Technology has two loca-tions where the historical sales were split at 40% and 60% for a specific month of theyear. When the forecast is calculated for the same future month, the system takes thesame percentage and disaggregates the forecast figures based on those values.

For some of the other product groups, the ABC Technology planner would like to havethe ability to override the system-generated proportional factors and just use the time-based disaggregation to reflect the stocking policy across various tree locations in SAPAPO. In this business scenario, the business planner would maintain the location-pro-portional factors offline and manually upload them to the planning book. The propor-tional factors can be generated based on actual sales history as well as manuallyadjusted by the demand planner.

Tips & Tricks

It is recommended that the automatic generation of proportional factors be done everybook month to take into account any changes in the proportional factors based on theprevious book month’s actual sales.

APO-DP’s method of aggregation and disaggregation is called a “consistent” plan-ning model (Figure 4.13). Using the lowest level of actual data (usually the prod-uct-location level), it generates proportional values throughout its planning net-work (characteristic value combinations).

The system uses proportional factors to distribute its products nationally. Theproportional factor can be overridden by the demand planner based on theirexperience with the product. ABC Technology would want to change its propor-tional factors based on the distribution centers (DC) stocking policy. These changesmight be initiated due to strategic reasons or slow-moving inventory in one part


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of the supply network. Changing a key figure value anywhere within this plan-ning network automatically triggers a proportional re-propagation throughoutthe network, which was calculated earlier. You can drill down or drill up throughone or more levels. There are two main calculation types here for proportionalfactor calculation:

� Pro rata of planning data The data is disaggregated according to the distribution ratio that the systemderives dynamically from the existing planned data. The proportional factorsare not used with this disaggregation type.

� Proportional factors The proportional factors are percentage based and held in the key figure APOD-PDANT. Figure 4.12 shows an example for forecasting a key figure, which usesthe key figure APODPDANT to disaggregate. ABC Technology would like to use themost recent year’s historical proportional factor for the same bucket as thisyear’s forecast key figure.

Figure 4.13 SAP APO Consistent Planning

Time-Based Disaggregation

Besides the calculation type, we also maintain time-based disaggregation. A sce-nario for time-based disaggregation may occur when ABC Technology has prod-ucts that always peak at month-end sales during the last week of the month. Inthis situation, we can define the time-based disaggregation key figure (type K) inthe planning area configuration, as shown previously in Figure 4.12, in the Key

Figure Aggregation tab, which defines the percentage split of the monthly fore-cast into weekly buckets. The business planner maintains the percentage, and the

Proportionalvalues

generated

Pro Rata orProportional

Factors

LowestLevel

Planning

Aggr

egat

ion

Disaggregation

PlanningLevel


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system uses this key figure percentage during the disaggregation of the forecastfrom monthly to weekly buckets. The ABC Technology planner can maintain theproportional factors and time-based disaggregation factor offline in MicrosoftExcel and use the “upload” function to load it into the demand planning book.

Planning Area Key Figure Settings

In a production environment, it might be necessary to change the key figure settingsto support new business requirements. An example would be if ABC Technologywould like to integrate new proportional factor logic with the planning solution. FromSAP SCM 7.0 onwards, the planning area offers the flexibility to change the key figuresetting without de-initializing the planning area using report /SAPAPO/TS_LCM_PAREA_CHANGE2. However, note that de-initializing the planning area leads to a potential lossof all time series data for the planning area.

Once the planning area is configured, we next need to design a planning book. Theplanning book is where most of the calculation occurs and provides informationto business users. There are usually two sets of planning books—one for businessplanners and the other for performing background calculations.

4.2.4 Planning Book

Your next step is to customize the planning book for your business requirementsin order to define the planning information content and layout of the interactiveplanning screen. The planning book serves as the frontend interface to the ABCTechnology demand planner users. The business planners would use the plan-ning book for different purposes. While the primary goal would be analyzing theforecast result based on history, the planner can also remove historical outliersand perform interactive forecasting directly in the planning book. The key figurein the planning book may also provide demand planning accuracy calculations forthe planner to analyze.

Planning books are highly customizable, and the screen can be designed to suitindividual planning tasks. Besides having different time bucket views, the plan-ning book can be designed to have multiple data views based on the informa-tion requirements. Each planning book can have multiple data views, giving theuser flexibility to view and analyze planning information in different angles.Some examples of data views are views for historical data, key figures, and fore-casting-related key figures. A typical planning book looks like what is shown in


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Figure 4.14, with the selection variant on the left section and the planning viewsection in middle. There are additional setting toolbars for downloading anduploading planning books, pivot sorting, and more.

Figure 4.14 SAP APO Planning Book View

Create the Time Bucket Profile

Before creating a planning book, you need to create the time bucket profile to beused for the planning book. A time bucket profiles defines the historical or futuretime horizon for APO-DP and helps businesses to visualize their planning data inthe planning book. With this step, you define which time buckets can be used forplanning, how many periods of each time bucket are used, and the sequence inwhich the time buckets appear in the planning table.

Example

Since the ABC Technology planner would like to visualize planning data monthly, quar-terly, and yearly, we can define time bucket profiles and switch them accordingly in theplanning book. As the default for the planning book, we will assign twenty-four monthsof time bucket profiles in monthly buckets.

The first and second planning bucket profiles determine how the data (historyand future) is viewed. Using the time bucket profile, the business can determine

SelectedObject

Standard Selections

User SpecificPlanning Books

Macros

SelectedKey Figures

Graphical Represent

HeaderInformation

Additional Settingstoolbar

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the historical period it would like to view and the future period for viewing fore-casts. It is not determining the forecast horizon. The third planning bucket’s pro-file is used to determine the number of forecast value periods released from APO-DP to APO-SNP. To customize the time bucket profile, follow the path SPRO � SAP

Reference Img � Advanced Planning and Optimization � Supply Chain Plan-

ning � Demand Planning � Basic Settings � Define Planning Bucket Profile, oruse Transaction /SAPAPO/TR30.

An example of a planning time bucket profile is shown in Figure 4.15, in whichthe planning bucket is split between weekly and monthly buckets. This allows thebusiness users to view some portion of the data on the weekly buckets for opera-tional planning and the rest of the data on monthly buckets for tactical and oper-ational planning.

Figure 4.15 Planning Time Bucket Profile

Custom Planning Books

The interactive Planning Book Wizard (Transaction /SAPAPO/SDP8B) is availableif you need to create custom planning books. We’ll walk through the planningbook creation process in the following steps:

1. Type in the new planning book name and click Create.

2. Input a text description of the planning book, assign a planning area, and selectthe forecasting method and proportional maintenance (Figure 4.16, 1). ClickContinue to move to the next tab.

3. Select the key figures required in the planning book for both viewing and calcu-lations purposes. Drag and drop from the Planning Area section to the Plan-

ning Book section (Figure 4.16, 2). Click Continue to move to the next tab.


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Figure 4.16 Demand Planning Book Wizard (1/2)

4. Select the planning book characteristics (used for slice and dice) required in theplanning book by dragging and dropping them from the right section to the leftsection (see Figure 4.16, 3). Click Continue to move to the next tab.

5. Change the key figure description to make it more easily understandable forbusiness users. Create auxiliary key figures directly, if required for calculations(see Figure 4.17). Click Continue to move to the next tab.

6. Input the time bucket profile(s) for both the past and future horizon visibilityin the planning book. Select Table 2 if you need to design a two-tabular sectionin the planning book for business users (for example, if they need to view twosections to compare the volume and dollar values; see Figure 4.17, 4 and 5).Click Continue to move to the next tab. In this case, the planner can have twosplit planning book tables. While the top table shows the planning data in vol-ume, the bottom table might give the planning data in dollar values.


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Figure 4.17 Demand Planning Book Wizard (2/2)

7. In the final step, arrange the key figure sequence you want the business usersto visualize in the planning book (see Figure 4.17, 6). In this step, the solutiondesigner needs to consult with business users to identify the layout of the keyfigures in the planning book. Click Complete to finalize the planning book cre-ation.

Our next step is to look at macros, which are embedded in the planning book foreither mathematical calculation or alert generations.


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4.2.5 Macros

A macro is an important component for facilitating planning tasks in a planningbook. Both simple and complex macros can be designed. Some examples of sim-ple macros are a calculation based on key figures, changing the cell color in aplanning book, and copying a key figure value from one row to the next. Anexample of a complex macro is the generation of alerts or pop-up messages whena cell falls below a certain threshold. The macros can be triggered either interac-tively (i.e., manually in a planning book) or via background batch processing.

SAP APO provides a tool called the Macro Builder, which allows you to create yourown custom macros to perform a variety of functions, such as mathematical, sta-tistical, logical, and planning calculations. Macros are a prerequisite to performsome of the simple and complex mathematical calculation in APO-DP. There areno standard APO-DP macros that you can use out of the box, as the majority of plan-ning books are custom. SAP provides some examples of macro functions, whichcan be used as templates for building macros. To access the Macro Builder, followthe menu path SPRO � SAP Reference Img � Advanced Planning and Optimiza-

tion � Supply Chain Planning � Demand Planning � Basic Settings � Define Mac-

ros, or use Transaction /SAPAPO/ADVM. As shown in Figure 4.18, the MacroBuilder has different screen areas, which we’ll discuss in the following subsections.

Figure 4.18 Macro Builder Screen

Elements

Depot

Planning TableData View layout

Events

Clipboard

MacroDevelopment

Area


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Elements

Elements are the building blocks of macros. You can use the following elementoptions when building your own custom macro:

� Macro Used for macro description and determining the period to be analyzed andwhether interactive or mass processing is mentioned. If selected interactively,it allows business users to execute macros from the planning book.

� User exit macro Used for implementing custom macros in routine code and for building com-plex logic in ABAP language.

� Step

Consists of one or more macro calculations with the number of iterations foreach step. The steps need to be structured enough to follow the logic insequence. Various business calculations can be created in logical sequence withthe use of steps.

� Control Statement Used with a condition statement to define macro steps and calculations. Con-ditional statements like IF and ENDIF are embedded in the macro to draw thebusiness decision tree.

� Condition

Defines logical conditions together with control statements to be used in macrosteps and calculations. Used in macros in conjunction with control statementsto draw the business decision tree.

� Planning table Consists of many sub-items for which the result of the macro calculation isassigned either in cells, rows, or columns. Used in macros to assign the calcu-lated value to a particular cell in the planning book.

� Operator/Functions Arithmetic, statistical, or mathematical calculation to be performed for a spe-cific row. Macros include operators and/or functions to calculate a specific keyfigure. An example would be using COVER_CALC to calculate the projected days’supply for demand based on the receipt elements.

� Alert/Status Writes alerts in the Alert Monitor and displays the status after the execution ofa macro. The macro can execute dynamic and database alerts and write theresult in the Alert Monitor.


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� Process message

Defines the message text and has the system issue a message in response to thealert situation.

� Action box Allows you to trigger an action that contains a function.

� Documents

Can be used to trigger email notifications to the user.

Macro Development Area

The Macro Development Area serves as a work area for the solution designer tocreate macros. Figure 4.19 shows an example of two macros created in the workarea by dragging and dropping various elements.

Figure 4.19 Macro Builder Work Area

Mathematicalcalculation

macro

Alertmacro

Controlstatement

Checkmacro

Activatemacro

Deactivatemacro/step

Level 1Level 2

Level 3Level 4

Condition

Alert update


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The first macro creates forecast bias by subtracting the forecast from the actualvalue, while the second macro creates alerts for the deviation based on a percent-age factor. Macros are highly customizable and can easily represent some of thebusiness exception rules. As seen in the first macro example, there are four levelsdefined within a macro:

� Level 1 is the macro description.

� Level 2 is a step mentioning the time horizon the macro needs to iterate.

� Level 3 is a result of the specific key figure from the planning table.

� Level 4 is the argument that is often a function or logic for the macro.

Also seen in the example are the use of the control statement, condition state-ment, alert update, and simple mathematical calculations. Besides the Activate

macro icon, the other two icons (Check and Deactivate) are helpful to trouble-shoot the macro syntax errors during macro writing.

User Exit Macros

User exit macros can be used to code complex business requirements not supported bystandard macro functions. Use function module EXIT_/SAPAPO/SAPMMCP6_005, whichincludes program ZXMUSERU0 where the user exit routine can be written.

Depot

The macros get parked in the Depot. Once the macros are activated and saved,they can be parked in the depot by simple drag and drop. Different statuses canbe identified with macro status colors:

� Green Indicates that the macro has no syntax or logic errors and that the macro iscompiled and activated.

� Yellow Indicates that the macro has been checked and does not have error but is notactivated.

� Red The macro is not complete.


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Events

Once the macro is developed, it can be executed interactively or in a batch job.Alternatively, the macro can be triggered automatically if assigned as Events inone of four types:

� Default Macros are executed when the planner opens the planning book and selects hisor her products. The macro is also regenerated once the planner performs someaction and saves the result interactively.

� Level Change Macros are executed when the planner drills up and down in the interactiveplanning book.

� Start Macros are executed when the planner opens the planning book and selects hisselection ID.

� Exit Macros are executed when the planner saves the plan and exits the planningbook.

Process Steps for Creating a Simple SAP APO Macro

The following provides some simple steps for creating a macro in the MacroWorkbench, which is accessed via Transaction /SAPAPO/ADVM:

1. Navigate to the macro development area. Right-click Macros in the Macro

Book and then click Create New Macro � Add Macro.

2. Give a text description of the macro. If the macro can be interactively executedin the planning book, choose any appropriate icon design in the Assigned

pushbutton. Click Continue once done.

3. Right-click the macro name and then choose Add Macro Element � Step. Givesome description of the step. Click Continue once done.

4. Now drag and drop Row from the Planning Table in the Element section tothe macro development area. Identify the key figure to be used for the calcula-tion. Click Adopt once done. If any more key figures are dragged and droppedfor calculation (let‘s say A = B + C), select Create in Next Level for key figuresB and C.


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5. Drag and drop the Operator/Function to the key figure calculation. ChooseInsert when inserting the mathematical operation + between two key figures Band C. Click Continue once done.

6. Click the Consistency Check before activating the macro. Any syntax errorswill be identified in this step. If there are no errors, the macro name icon willturn yellow, and we can activate the macro.

7. If the macro needs to be executed every time we open the planning book or exitor change the planning level, drag and drop the macro under the Default, Level

Change, Start, and Exit options on the Events section on the Macro Builder.

8. Save the macro by clicking the Save icon.

4.2.6 Locking Key Figures

Sometimes a business may need to lock a key figure after planning. There can bevarious business reasons for locking a key figure to avoid any system calculationoverride. For example, the ABC Technology demand planner locks the currentmonth plan after it is released in sales and operations. This snapshot helps thecompany to calculate the forecast accuracy based on the snapshot.

Another business scenario when the locking function can be used is in allocation.This is often used when remaining material quantities need to be redistributed toother products (for example, promotional items) in a product group after the baseproduct volume is fixed. The fixed value should not change if you change othervalues of key figures at different planning levels. To customize fixing within a keyfigure, follow these steps (see Figure 4.20):

1. Access the BW Administrator Workbench in SAP APO using Transaction RSA1.Define two key figures—one for the value of the key figure and one to store thefixing information.

Note

Note that the second key figure type needs to be an SAP APO key figure (not SAP BW).During the key figure creation, we get two options: an SAP APO key figure or SAP BWkey figure type. The SAP BW key figure type is used primarily for data staging andextraction process, while the SAP APO key figure type is used only for planning purposes.


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2. During the key figure definition, assign the second fixing key figure informa-tion on the first key figure info object within the Fixed Key Figure field.

3. Access the planning area administration using Transaction /SAPAPO/MSDP_ADMIN. In the planning area, the first key figure will have Fixed key figure

type. This is just a validation step to ensure correct assignment of the key figure.

As a result of these steps, when a user is in the planning book and right-clicks theFix Cell option, a padlock icon and a pink font indicate that this value is nowfixed. If you want to automate the functionality, you can fix the key figure with amacro by making a change in the key figure scope of the change to level fixing inthe Macro Workbench, as shown in Figure 4.20.

Figure 4.20 Fixing Key Figures

Fixing via Macro

Planning Area

InfoObject


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Note

Refer to SAP Notes 643517 and 687074 for more information on how to fix key figureswith macros.

4.2.7 Time Series Consistency Checks

Once any new master data is maintained in APO-DP, we need to execute the con-sistency check and delta sync programs routinely. For data consistency, it ishighly recommend that you check the SAP liveCache consistency on a regularbasis. Table 4.1 lists all transaction codes you can use to check the time series con-sistency check in APO-DP.

Once you‘ve performed the basic configuration, it’s time to load the historicaldata via data staging. We’ll discuss this in the following section.

4.3 Data Staging for SAP APO-DP

Data staging in APO-DP involves both inbound and outbound flows to SAP APO.The inbound flow is the historical sales order data, which is interfaced from SAPERP via SAP BW. The outbound flow is the data extraction of demand planningdata for reporting purposes. The core activities performed during the inboundand outbound staging are as follows:

Transaction Description

/SAPAPO/TS_LCM_CONS_CHECK Time series consistency check

/SAPAPO/TS_PSTRU_CONS_CHECK Planning object structure consistency check

/SAPAPO/TS_LCM_PLOB_DELTA_SYNC Adjust time series object in planning object structure

/SAPAPO/TS_LCM_REORG Delete time series and time bucket profiles having no SAP liveCache anchors

/SAPAPO/OM17 Consistency check between SAP liveCache and time series

/SAPAPO/TS_PAREA_INITIALIZE Initialize time series in planning area

Table 4.1 SAP liveCache Consistency Check Transaction Codes

Data Staging for SAP APO-DP 4.3

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� Inbound staging Involved in loading the historical sales orders data and delta sales orders aftersystem cutover.

� Outbound staging Involved in the extraction of planning data from SAP liveCache for reportingand archiving purposes in SAP BW.

Figure 4.21 shows the schematic flow diagram for the inbound and outboundflows in SAP APO. The inbound flow starts from SAP ERP Logistics InformationSystem (LIS) extractors for sales orders and deliveries that will load the actualsales orders into the historical InfoCube in SAP BW.

Figure 4.21 Demand Planning Data Staging Involving SAP ERP, SAP BW, and SAP APO

There are two InfoCubes: one for historical sales orders and the other for the deltaload after the system has gone live. The material and customer master data are alsointerfaced with SAP BW to be enriched with additional material and customer

SD Delivery2LIS_12_VASCL

SD Order2LIS_11_VASCL

Customer

Material

Customer

Material

SalesHistoryCube

SalesHistoryCube

APO-DP Planning Area

SalesDeltaCube

SalesDeltaCube

SalesReporting

SalesArchiving

SAP liveCache

SAP ERP SAP BW SAP APO

Exportdatasource

Export datasource

SalesODS


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attributes (for example, MRP controller or transportation zone), which are usedfor demand planning. The historical load usually consists of two to three years ofsales order history, while the delta load consists of the last week’s sales orders.Once the data is available in APO-DP’s internal SAP BW component, it can betransferred to the APO-DP area. The subsequent process creates forecasting for thematerials.

The outbound data staging begins once the planning is finalized and can be pub-lished to SAP BW for the reporting and archiving processes. The data is extractedfrom time series SAP liveCache and passed into SAP BW objects. The main reasonsto route the data staging via SAP BW are the scalability, archiving, and reportingcapabilities. The business uses the report for its monthly forecast review meetingand also for sales and operations planning meetings.

Let’s see the customization steps for modeling the SAP APO inbound process forloading historical data into an SAP APO InfoCube. All the customization steps aredone in the BW Administrator Workbench (Transaction RSA1):

1. Create a source system. A source system indicates the system from which the transactional data andmaster data originated. Besides the flat file system, there are multiple othersource systems available to connect with SAP BW in SAP APO. Examples areSAP BW, DBConnect, and web services. ABC Technology would like to uploadthe historical sales orders from both the flat file and the SAP BW system. To cre-ate a source system, right-click the source system type (file, BW) and select Cre-

ate. Figure 4.22 1 shows the source system created from the BW Administra-tor Workbench.

2. Create a DataSource. After the source system, we create a DataSource. Here we specify the format ofthe file, which will be uploaded into the InfoCube, so this needs to be in accor-dance with the file format that has been decided for data upload. The ABCTechnology planner has decided to load the historical sales from the flat file.Select the DataSource option from the Modeling section and right-click theunassigned node to select the Create DataSource option. Provide the sourcesystem name to be linked with the DataSource. Figure 4.22 2 shows Data-Source creation for transactional data (historical sales).


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Figure 4.22 Steps for Creating a Source System and DataSource

Custom DataSource

Companies often build custom tables in their systems to support business requirements.Use Transaction SBIW (Generic DatasSource - Maintain Generic DataSource) for customtable extraction. Input the transactional data table name in the Transaction Data fieldto create the DataSource.


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3. Create InfoCube. The InfoCube serves as a data container for the planning data wherein weassign the characteristics and key figures (see Figure 4.22, 3). The InfoCube canreceive data from multiple InfoSources. Follow these steps (see Figure 4.23):

� Access Transaction RSA1. Right-click InfoProvider in the Modeling area tofirst create an InfoArea 1.

� Once the InfoArea is created, right-click the created InfoArea again to createyour InfoCube by choosing option Create InfoCube 2.

� Nominate the InfoCube to be the BW type in the Choice of BW Application

pop-up screen 3 and 4.

� In the InfoCube, directly input the dimensions (characteristics) and key fig-ures by clicking on Dimensions � Create New Dimensions.

Note

If you have any navigational attributes attached with the characteristics, they will pop-ulate automatically in the InfoCube (step 5).

Figure 4.23 Steps for Creating an InfoCube in SAP APO’s Internal SAP BW Component


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The final InfoCube, once activated, will look like what’s shown in Figure 4.24.The InfoCube will store the data to be transferred to the planning area as timeseries objects in SAP liveCache for demand planning.

Figure 4.24 InfoCube with Various Dimensions (Characteristics) and Key Figures

4. Create transformation. Once the InfoCube is created, we need to define the transformation and datatransfer process (DTP) for mapping the source (file) with the destination (Info-Cube). Follow these steps:

� Access Transaction RSA1 (Figure 4.25), right-click your InfoCube name, andselect Create Transformation 1.

� In the Create Transformation screen, input the DataSource to be con-nected with the InfoProvider (InfoCube) 2 and 3.


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� An automatic proposal of the field mapping between the DataSource andInfoCube will be shown in the next screen. Take note of the rule type bywhich we can define the data transformation method 4. The rule type isused for any transformation (for example, changing the unit of measurefrom an alternative to a base unit of measure). In the rule type, we definewhether any data conversion is required from the DataSource file beforeloading historical data into the InfoCube.

� Assign a constant value to a characteristic, change the calendar day to calen-dar month or input routine to change the unit of measure.

Figure 4.25 Steps for Creating Transformation

5. Create data transfer process (DTP). This process will be used to upload the file into SAP APO and schedule it as aprocess chain job:


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� In Transaction RSA1, locate your InfoCube under the InfoProvider. Underthe InfoCube structure, click the DTP to input the file loading path, per theexample in Figure 4.26 (1 and 2). The DTP can be either scheduled in a pro-cess chain (Transaction RSPC or run directly via Transaction RSA1.

Figure 4.26 Steps for Creating the DTP

� Once the DTP process runs successfully, view the data content of the requestby right-clicking the InfoCube (see Figure 4.27) and selecting Manage 1.Highlight the InfoCube and select the icon on top, Contents. This will dis-play the InfoCube contents. Figure 4.27 also shows the data model for theInfoCube 2. We can also view the data model by clicking the Display Data


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Model option 3. A graphical tree structure shows how the data from thesource system (flat file) moves to DataSource, and then via DTP to the Info-Cube.

Figure 4.27 InfoCube Content and Data Model

ABC Technology uses the InfoCube not only for loading the historical files, foronline reporting purposes via a virtual InfoCube with SAP APO’s internal SAP BWcomponent.

4.4 Data Management in SAP APO-DP

APO-DP needs characteristic value combinations (CVC) to exist for every possiblecombination that needs to be planned. This means that every time a new product

Data Management in SAP APO-DP 4.4

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is launched or a customer/customer group starts buying a product they did notbuy in the past, a new CVC needs to be created in APO-DP. In the following sec-tions, we’ll show you how to create a CVC and how to work with it.

4.4.1 Creating New Characteristic Value Combinations

For new products, the new characteristic combinations will have to be createdmanually since the planning needs to forecast before the first actual salesoccur. In our business case example, ABC Technology has implemented a newproduct introduction (NPI) workflow, which tracks the completion of all themaster data maintenance activities in a timely manner. For situations when acustomer buys an existing product for the first time, the new characteristiccombinations can be generated automatically using the history of these sales.The CVC can be created either manually or automatically via Transaction/SAPAPO/MC62. For manual creation, the demand planner clicks Create sin-

gle characteristics combination for the specific master planning object struc-ture. In the next screen, the demand planner maintains all the required charac-teristics and presses Execute (F8).

Note

You can find additional information on how to maintain CVCs in Chapter 5, Section5.2.2.

4.4.2 Capturing History

The sales order history is captured in SAP APO’s internal SAP BW InfoProvider(InfoCube), where we can generate the characteristics combinations automati-cally. This process can also be scheduled as a background batch job. To enable thisprocess, the user needs to validate that the sales order history is available in theInfoCube using Transaction LISTCUBE and access Transaction /SAPAPO/MC62,which is used for CVC generation using the InfoCube (see Figure 4.28). For large-volume CVC creation, it is always recommended to split the job to avoid anyperformance issues. You should run the time series consistency programs (see Sec-tion 4.2.7) after the CVC creation to avoid any SAP liveCache inconsistency anchorissues.


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Figure 4.28 CVC Creation

4.4.3 Transfer Planning Data

Once the CVC is created as APO-DP master data, we can transfer the planningdata from SAP APO’s internal SAP BW InfoCube to the APO-DP planning area. Todo this, access Transaction /SAPAPO/TSCUBE (see Figure 4.29). Enter the Info-Cube (source) and APO-DP planning area (destination) in their respective fields,as well as the planning version (active version 000).

Map the InfoObject of the InfoCube with the key figure in the planning area. Thetransfer of the planning data can be validated in the planning book (Transaction/SAPAPO/SDP94). During the transfer, the business planner needs to exit theplanning book to avoid any data locking issues.

Once the history is loaded in the planning book, the planner needs to identify thebest forecast model to run the product for determining future forecasts. Settingup the forecast method is discussed in the next section.

Setting up Forecast Methods 4.5

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Figure 4.29 Loading Planning Data from InfoCube to Planning Area/Book

4.5 Setting up Forecast Methods

Before performing the forecast modeling in the system, the business plannerneeds to make some of the following decisions to start the process.

Example

ABC Technology needs to decide on the level of the product hierarchy at which to runthe statistical forecast. It also needs to decide on the time bucket used for statisticalforecasting, the length of history and future horizons, forecasting method, parameterswithin the method, and frequency of update for the forecasts.

There are two different methods of forecasting available in APO-DP: univariateforecasting and casual forecasting. The former purely studies the historical pattern


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and proposes the best fit model based on the lowest forecast error. The lattercombines the external market factors (economic condition, price, weather, etc.)while determining the forecast.

Next, we will look at both univariate and casual forecasting methods. First, let uslook at the univariate forecast methods. In our business case example, dependingon product family, ABC Technology can use either of the forecasting models.While the univariate is easy to formulate, the casual requires more effort on thecollection of external environment data.

4.5.1 Univariate Forecasting

This section presents the overview on forecasting model framework using univar-iate forecasting as example. Further explanation on the univariate forecasting isprovided in Section 4.5.3.

Within the univariate forecasting method, there are more than 20 different statis-tical models available in SAP APO, but we can broadly classify them into two:exponential smoothing and linear regression. Exponential smoothing uses inherentproperties of time series, while linear regression extrapolates a model fitted to thedata. Table 4.2 provides the list of six commonly used forecast methods across theexponential and linear regression.

Figure 4.30 illustrates the forecasting model framework with steps toward iden-tifying the best fit forecasting model:

1. Collect the raw historical sales data from the source system.

2. Analyze the data and perform possible manual outlier corrections on knownevents.

Forecast Method Profile Interactive

Single Exponential Smoothing M11 Constant Models

Holt’s Method M21 Trend Models

Seasonal, No Trend M31 Seasonal Models

Holt-Winters’ Method M41 Seasonal Trend Models

Linear Regression M94 Linear Regression

Seasonal Linear Regression M35 Seasonal and Linear Regression

Table 4.2 Commonly Used Forecast Methods in SAP APO


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Figure 4.30 Forecasting Model Framework

3. Load the planning data into SAP APO to study the historical pattern.

4. Perform the decision tree on demand pattern seasonality and linear trends.

5. Select the decision tree model and run an interactive forecast.

Historicalsales raw

data

Dataanalysis

complete

Plot the data inplanning book and

analyze pattern

Is thedemand pattern

seaonal?

Does thepattern havelinear trend?

YES NO

Seasonallinear

regression orHolt-Winters

Seasonal,no trend

Holt orlinear

Regression

Singleexponentialsmoothing

NOYESNOYES

Perform automaticforecasting model

comparision

Manual vs. auto forecast error

acceptable

Forecast modelidentified

YES

NODoes the

pattern havelinear trend?


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6. Run the automatic forecast selection model.

7. Compare the manually selected and automatic forecast model with forecasterror analysis.

8. Reiterate the result with a similar forecast model by fine-tuning , , and parameter values.

9. Alternatively, identify new forecast models until the result is satisfactory, perbusiness requirements.

4.5.2 Forecast Definitions

Before we look at various forecast methods in more detail (later on in this sec-tion), let’s look at some common definitions used in the forecasting process.

Model Parameters

The model parameters—alpha (), beta (), and gamma ()—control the weightingof each historical value. Alpha is used in basic value calculation, beta in trendvalue calculation, and gamma in the seasonal index calculation. Values for theparameters range from 0 to 1. Values closer to 0 will use the whole history, whilevalues closer to 1 use only the more recent historical data. The parameters alsocontrol how reactive the forecast is to changes in the historical pattern.

Figure 4.31 graphically depicts the three parameters. ABC Technology presentsthe lowest value of 0.1 across all three parameters in the auto-model and lets thesystem perform in increments until it finds the lowest forecast error.

Figure 4.31 Forecasting Model Parameters

Basic value (α)

Trendvalue (β)

Seasonal value (γ)

Past Future


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Ex-Post Forecast

An ex-post forecast is a forecast run in the past against historical values. The ex-post forecast is used to measure model fit. Figure 4.32 shows the ex-post forecastcalculated during the forecast run. The comparison of the ex-post forecast andhistory gives the forecast error used for identifying best-fit model. Some of theforecast models (i.e., moving average, weighted moving average, history adopted,and manual forecast) do not generate the ex-post forecast. This analysis allows theABC Technology demand planner to look at the outliers identified during the ex-post moving average calculation.

Figure 4.32 Ex-Post Forecast and Initialization During the Forecast Run

Model Initialization

As most of the model uses the recursive method to look at the history pattern,depending on the model, one or more period is required for initialization. Table4.3 gives the list of minimum periods required by the system and ideal history forproper statistical calculation.

Forecast Method System Statistical

Single exponential smoothing 3 6

Holt’s method 4 6

Seasonal, no trend 12 24

Holt-Winters’ method 15 24

Linear regression 1 6

Seasonal linear regression 12 24

Table 4.3 Minimum Number of Periods Required by the System

Initialization

Dat

a V

alues

Ex-post Forecast

History Future

Forecast

History Values

Forecast Values


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Forecast Error

A forecast error is defined as deviation between the actual history and the calculatedex-post forecast. The lower deviation (forecast error) means the forecast has usedmore of the historical pattern while estimating the future forecast. The demandplanner needs to closely monitor the forecast error while picking the best fit fore-casting model for their products. SAP APO provides alerts in form of diagnosisgroup where the % forecast error tolerances can be defined for monitoring the fore-casting result. Table 4.4 lists all the forecast errors. Industry best practice recom-mends using forecast errors MAPE and MAD for forecasting model identification.

Forecast Error Name

Definition Comment

Mean absolute deviation (MAD)

The mean absolute deviation is calcu-lated by the absolute difference between the ex-post forecast and the actual value.

The mean absolute deviation is the error calculation used to determine the best fit in the Auto Model 2 Forecast-ing Model. MAD is an exam-ple of absolute error.

Error total (ET) The error total is the sum of the dif-ference between the actual and the ex-post forecast.

Mean absolute percentage error (MAPE)

The mean square error is the average of the sum of the square of each dif-ference between the ex-post forecast and the actual value.

The mean absolute percent-age error is the most com-monly used in the industry, along with MAD. MAPE is an example of relative error.

Mean square error (MSE)

The mean square error is the average of the sum of the square of each dif-ference between the ex-post forecast and the actual value.

Square root of mean square error (RMSE)

The root mean square error is the square root of the average of the sum of the squared difference between the actual and ex-post forecast value.

Mean percentage error (MPE)

The mean percentage error is the average percentage error of the differ-ence between the ex-post forecast and the actual values.

Mean percentage error is the simplest of all the errors, with high chances of being skewed due to outlier record.

Table 4.4 Forecast Error Used for Analysis


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Forecast Profile

In APO-DP, the logic of how a forecast is carried out is stored in the forecast pro-file. Since different models can be used for different products, various forecastprofiles can be set up in the system. The forecast model to forecast seasonal prod-ucts may be different than stable products. The maintenance of the forecast pro-file is done primarily by the business users. The ABC Technology demand planneruses his or her product experience to set some of the products on the auto-fore-casting model and separate others to run on a pre-defined forecasting model.

Best Practice

As an industry best practice, the forecasting model is reviewed by the business onceevery quarter by analyzing the forecast accuracy performance. The same forecast profilecan be used for both interactive and background batch jobs.

A forecast profile is created in Transaction /SAPAPO/MC96B, as shown in Figure4.33. Besides defining the forecast and history key figures, we also define thehorizons and the forecasting model.

Figure 4.33 Forecast Profile


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Assignment of Forecast Key Figures

Key figures can be assigned to store the calculations of forecast, corrected history,corrected forecast, ex-post forecast, and ex-post forecast MLR. This assignment isdone in Transaction /SAPAPO/MSDP_ADMIN with the path Extras � Forecast

Settings. Figure 4.34 shows the forecast key figure assignment.

Figure 4.34 Forecast Key Assignment in Planning Area

Corrected History

The outlier from the history can be corrected either manually or automatically bydefining in the forecast profile—outlier correction, as shown in Figure 4.33. Thecorrection is done for the outlier lying outside the tolerance level calculated withreference to standard deviation. The ABC Technology demand planner reviewsthe automatic cleansing of the outliers to ensure that the historical pattern is nottouched during the correction.

Corrected Forecast

The corrected forecast takes into account the workday correction for the respec-tive bucket. This can be achieved by maintaining the Days in Period field in theunivariate forecast profile (Figure 4.33). An alternative would be to use a macrobased on the time stream planning calendar defined in the location master.

4.5.3 Univariate Forecasting Methods

Let’s study some of the commonly used univariate (statistical) models in this sec-tion.


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Single Exponential Smoothing (Method 11)

This method is best suited for products with a historical pattern that does notinclude any seasonality or trend. Some of the ABC Technology products, such asdesktops, have stable sales and will use the single exponential smoothing method.This method forecasts the next period (monthly bucket), and this value isrepeated for next 12-18 months. The forecast method yields a flat line. The forecastis a weighted average of the baseline history, and the recent history is weightedmore than the past periods.

A parameter value of closer to 0 will result in a slower decline, while one closerto 1 will result in a fast decline. A recommended parameter value is between 0.2and 0.5. An example of a single exponential smoothing model from ABC Technol-ogy is shown in Figure 4.35.

Figure 4.35 Single Exponential Smoothing Model


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Holt’s Method (Method 21)

ABC Technology markets some products that have specific lifecycles (for example,laptops) and need to model the upward/downward trend pattern to ensure thatthey do not have excess inventory when the product is being replaced withanother product line. Holt’s method is suitable for products with a historical pat-tern that does not include any seasonality but does have a consistent linear trend,upward or downward.

The forecast is a straight line, with a positive or negative slope. Two parametersare needed to estimate the forecast: and . As for single exponential smoothing, controls how much weight is given to the most recent periods and controlshow strongly the trend is smoothed. A trend dampening profile can be defined inthe forecast profile to smooth out the trend. A recommended parameter value for and is between 0.3 and 0.5. Higher values favor more recent data. An exampleof the Holt's method modeled from ABC Technology is shown in Figure 4.36.

Figure 4.36 Holt’s Trend Model


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Seasonal, No Trend Model (Method 31)

ABC Technology also markets some products (monitors) that demonstrate someseasonal patterns during school holiday and holiday seasons. For these groups ofproducts, the company plans to model the seasonal forecasting model. Thismethod is suitable for products with a historical pattern that includes seasonalitybut no consistent trend. The forecast will copy the seasonal pattern into thefuture, but there will be no trend adjustment.

Two parameters are needed to estimate the forecast: and . As for single expo-nential smoothing, a controls how much weight is given to the recent periods,while parameter controls the seasonal pattern used to forecast. A recommendedparameter value is between 0.3 and 0.5, and for , between 0.1 and 0.3. Thelower value of favors two seasonal patterns. An example of a seasonal modelfrom ABC Technology is shown in Figure 4.37.

Figure 4.37 Seasonal Model

Holt-Winters’ Model (Method 41)

This method is suitable for ABC Technology products with a historical patternthat includes seasonality and a linear trend. (For example, the company is selling


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some computer accessories, but they’re outdated and sell worse from year toyear.) The forecast will copy the seasonal pattern into the future and adjust a lin-ear trend, upwards or downwards. Three parameters are needed for this methodbe set: , , and . These three parameters need to be fine-tuned with the iterativeforecasting process to achieve a low forecast error values (MAD and MAPE).

Linear Regression (Method 94)

This method is an alternative to method 21, but based on a different approach. Noparameters need to be set. This method uses a classic linear regression based onthe least-squares principle. This regression is extrapolated. It is the same methodas the linear trend line option in Excel.

Seasonal Linear Regression (Method 35)

This method is an alternative to method 41, but based on a different approach.No parameters need to be set. This method first estimates seasonal indexes,which are used to de-seasonalize the baseline history. Then, a linear regression isapplied. This regression is extrapolated, and the forecast is seasonalized back.This method weights the values in the past equally. Note also that the trend com-ponent cannot be eliminated within this method.

Croston Model (Method 80)

The Croston Model (80) is used when demand is sporadic or intermittent. Thereturn is a constant model to meet the possible sporadic demand. This model isused by ABC Technology for some of its product line that doesn’t have a stablehistory.

Automatic Forecasting Models

SAP APO also offers an automatic forecasting model that the business can opt touse for initial forecasting model identification or comparison purposes. The mostcommonly used is Auto Model Selection Procedure (Method 56). This methodtests for constant, seasonal, and/or trend models while attempting to minimizeerror by adjusting , , and parameters. This model adjusts , , and betweenthe values of 0.1 and 0.5 in increments of 0.1, while calculating the MAD for eachiteration. The iteration with the lowest MAD is the model chosen, with the appro-


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priate smoothing factors. Setting up the auto model allows the ABC Technologydemand planner to review the system-proposed model and makes any changes asrequired.

Forecast Error Result Analysis

Implement BAdI /SAPAPO/SDP_FCST4 to record the background processing results offorecasting models in tables /SAPAPO/FCSTHEAD and /SAPAPO/FCSTACCU. Set the EV_FLAG_ACTIVE = ‘X.

Mathematical Formulas1

Let’s see some of the standard formulas used in the forecasting calculation. Table4.5 outlines the constant, trend, and seasonal trend models and the basic formu-las.

1 help.sap.com

Model Model Parameters

Constant model Basic value = Hist(1) where Hist(i) is the ith historical value

Trend value = 0

Seasonal indices = 1

Mean absolute deviation (MAD) = 0

Trend modelsTrend value =

Basic value = + Trend

Seasonal indices = 1

Mean absolute deviation (MAD) =

Seasonal models Basic value = Mean of the historical values of the first historical season

Trend value = 0

Seasonal index for a period = Historical value for that period divided by the basic value

Mean absolute deviation (MAD) = 0

Table 4.5 Constant, Trend, and Seasonal Trend Model Formulas

Hist(3) – Hist(1)

2

Hist(3) + Hist(2) + Hist(1)

3

3

Σ |Basic value – Hist(i)|i=1————————————————3


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Table 4.6 outlines the seasonal and trend basic formulas.

Seasonal trend models

Trend value =

where Hist(i) is the ith historical value and SL is the length of a season.

Basic value =

Seasonal index for a period =

Where S(i) is the ith seasonal index.

Mean absolute deviation (MAD) =


Seasonal and trend models

Forecast value for the period (t+i)

P(t+i) = [G(t)+i * T(t)] * S(t–L+i)

Where:

Basic value: G(t) = G(t–1) + T(t–1) +

Trend value: T(t) = T(t–1) + [G(t) – [G(t–1) + T(t–1)]

Seasonal index: S(t) = S(t–L) +

For the constant model

T(t) = 0, = 0, S(t) = 1.0, = Gamma = 0

For the trend model

S(t) = 1.0, = Gamma = 0

Table 4.6 Seasonal and Trend Model Formulas


Table 4.5 Constant, Trend, and Seasonal Trend Model Formulas (Cont.)

Hist(1+SL) + Hist(2+SL) + Hist(3+SL) – Hist(1) – Hist(2) – Hist(3)

(3* SL)

SL+3

Σ Hist(i)i=4

———————— + SL

Trend * (SL –i) ——————————

2

S(i+3) = Hist(i+3)

—————————————————— Basic value – Trend* (SL-i)

SL

Σ |[Basic value – (SL–i) * Trend] * S(i) – Hist(i+3)|i=1

————————————————————————————————————— SL

[ V(t) – G(t–1) – T(t–1) ]S(t–L)

[ V(t) – S(t–L)]G(t)


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4.5.4 Casual Forecasting Methods

Casual forecasting is based on the relationship between the variable to be fore-casted and an independent variable. The SAP APO casual forecasting method isbased on multiple linear regression (MLR) using the ordinary least squaresmethod. The equation for the method is simple: y = a + bx. This is a simple alge-braic formula. It simply defines the shape of a line.

When used with regression analysis, the y, or dependent variable, represents thedemand. This is the number we are trying to forecast. The x, or independent vari-able, represents the item that directly influences the shape of the line. a is theintercept, while b is the slope of the line. Correlation measures the strength of therelationship between the dependent and independent variables.

Example

For example, ABC Technology uses the price as one of the casual variables in the calcu-lation, while the other business scenario uses weather as one of the drivers for the MLRcalculation.

For the seasonal model

T(t) = 0, = 0

P(t+i) = The forecast calculated for the period (t+i) in the current period (t)

i = Forecasted horizon

G(t) = The current basic value for the current period (t)

G(t-1) = The previous basic value from the previous period

L = Period length (often 12)

V(t) = Actual demand (history) for the current period (t)

T(t) = The current trend value calculated for the current period

T(t-1) = The previous trend value from the previous period

S(t) = The seasonal index for the period (t)

S(t-L) = The previous seasonal index for the period (t)

= Smoothing factor for the basic value ‘G’, 0 < < 1

= Smoothing factor for the trend value ‘T’, 0 < < 1

= Smoothing factor for the seasonal indices ‘S’, 0 < < 1


Table 4.6 Seasonal and Trend Model Formulas


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Now that we’ve completed the basic customization of APO-DP, we’ll move on tocustomizing the other important SAP APO module: Supply Network Planning.

4.6 Basic Customization in SAP APO-SNP

This section focuses on explaining the basic customization steps for APO-SNP.Unlike what you saw with APO-DP, where we had to create many different ele-ments, APO-SNP uses the majority of the standard InfoObjects, characteristics,key figures, and planning books from SAP. There are multiple standard APO-SNPplanning books that ABC Technology can use as a template to design its supplyplanning books. The flexibility of macros on these planning books allows thecompany to change some of the demand and supply calculations.

In the following sections, we’ll show you where to find APO-SNP InfoObjects andplanning materials, and how to use them.

4.6.1 InfoObjects

Standard characteristics and key figures are used in SAP-provided planning areasand planning books. The planning data in APO-SNP can be stored either in time-series based SAP liveCache or order-based SAP liveCache. The key figure informa-tion to be stored as order or time series SAP liveCache is defined in the planningarea configuration. The order SAP liveCache key figures are the ones that areinterfaced with CIF to SAP ERP.

The standard characteristics provided are listed in the master planning object struc-ture 9ASNPBAS, while the key figures are displayed in standard planning areas9ASNP01, 9ASNP02, 9ASNP03, 9ASNP04, and 9ASNP05. The master planningobject structure and planning area can be accessed using Transaction /SAPAPO/MSDP_ADMIN. If you don’t see the characteristics and key figures, run report/SAPAPO/TS_D_OBJECTS_COPY from Transaction SE38 (ABAP Editor).

Additional key figures can be created to support business requirements either bynavigating to the BW Administrator Workbench (Transaction RSA1) and follow-ing the path RSA1 � Edit � Objects � InfoObject, or by directly typing TransactionRSD1. Here, maintain the SAP APO key figure of quantity (QUAN) and base unitof measure 0BASE_UOM.

Basic Customization in SAP APO-SNP 4.6

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4.6.2 Category Group

Every key figure in APO-SNP is linked with categories. The categories are descrip-tions of different stock types, receipt types, or requirement types in SAP APO. Agroup of categories (also known as ATP elements) can be classed as a categorygroup representing various elements. This way, the aggregation of all the catego-ries is shown in the key figure for the specific bucket. Another important use ofthe category group is the ability to specify the quantity type for each of thedefined categories. With this functionality, different key figures can be config-ured to specify the requested sales orders, confirmed sales orders, or backordersin the planning book. The flexibility of defining the category per key figure pro-vides flexibility to businesses to distinguish the use of each demand and supplyplanning key figure for calculation.

Example

An example from ABC Technology is the inventory type taken into account for thedemand and supply calculation. The company wants to take only unrestricted inventoryinto account and not count blocked or restricted inventory into stock calculations.Another use is separating two key figures for sales orders and deliveries.

To customize a category (see Figure 4.38), follow menu path SPRO � SAP Refer-

ence IMG � Advanced Planning and Optimization � Global Available to

Promise � Maintain Category. Here you’ll see all the available categories in SAPAPO; these can be transferred from SAP ERP by the CIF integration model for theATP customizing object. The activity can be performed in SAP ERP via generatingand activating the CIF integration model using Transactions CFM1 and CFM2.

Similarly, you customize a category group via menu path SPRO � SAP Reference

IMG � Advanced Planning and Optimization � Supply Chain Planning � Supply

Network Planning � Basic Settings � Maintain Category Groups. As Figure4.38 shows, the quantity type can capture the requested, original, and confirmedquantity. From the defined list of the categories, we define a new category group.Under this new category group, we input all the categories we want to display inthe key figure. For some specific key figure, we can define whether the categoryquantity type is requested, original, or confirmed.


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Figure 4.38 Categories Assignment to Category Group

The category and category group can be maintained in either of the followingfour function areas in both configurations and also during the planning datarelease from APO-DP to APO-SNP:

� Planning area Assignment of category and category group to individual key figures in Trans-action /SAPAPO/MSDP_ADMIN, as shown in Figure 4.39.

� Demand Planning release to Supply Network Planning Assignment of category when releasing the demand plan, from the time seriesto order SAP liveCache. Figure 4.39 shows the Transaction /SAPAPO/MC90demand plan release to supply planning. As shown in the figure, we maintainthe Time Series LiveCache for APO-DP to be released as Order LiveCache inAPO-SNP. The forecast order category is maintained as FA.

Category Group

Categories

Category Group


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Figure 4.39 Category Group Assignment in APO-SNP Planning Area, APO-DP Release

� Location master Default stock category, available to deploy and available to issue fields specificto a location can also be specified in the location master data (Transaction/SAPAPO/LOC3), as shown in Figure 4.40.

� Location product master In situations where a business would like to prioritize the local forecast overinternal replenishment transfers request, you need to maintain the locationproduct master, as shown in Figure 4.40. In the SNP2 tab, maintain the cate-gory group in fields ATD/ATI to be taken into account for the APO-SNP distri-bution planning process. The values maintained in the location product takeprecedence over the location master data category group. This allows the busi-ness to define the parameters per location product combination.

SNP Planning Area

DP to SNP Release


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Figure 4.40 Master Data Maintenance of Category Groups

4.6.3 Planning Area

As with the demand planning area, we need to maintain planning areas for theAPO-SNP business process. The planning area is where we maintain the base plan-ning unit of measure, time bucket, and key figures. APO-SNP comes with two pre-delivered planning objects: structure 9ASNPBAS (supply planning) and 9ASNPSA(scheduling agreement). It is recommended that we use these two planning objectstructures during the APO-SNP planning area creation. The APO-SNP Planning

indicator in the planning object structure automatically assigns all the APO-SNPcharacteristics.

Similar to what we discussed in Section 4.2.3 regarding APO-DP, we need to cre-ate a storage bucket profile. A storage bucket profile defines how the systemstores the data created in SAP liveCache and how it is used for calculation pur-poses. Use Transaction /SAPAPO/TR32 to create the storage bucket profile. Unlikewith APO-DP, SAP offers pre-defined APO-SNP planning areas that are recom-mended to be copied and used per business requirements (see Table 4.7).

Location Master

Product Location


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To create your own APO-SNP planning area, copy the planning areas listed inTable 4.7 by going to Transaction /SAPAPO/MSDP_ADMIN, selecting the plan-ning area, and right-clicking Copy. Additional custom key figures can be added ifrequired to support the business process. Other parameters, such as defining thestorage bucket profile or unit of measure, can be done in the planning area. Sincethe ABC Technology planner uses a different unit of measure for planning, we canspecify a common planning unit of measure in the planning area.

You need to initialize the planning area by right-clicking Initialize Planning Ver-

sion for usage.

APO-SNP Planning Area(s)

Description

9ASNP01 � Time series based.

� Used for supply and demand propagation for simulating changes caused by supply chain constraints to fulfill market demands.

� All results stored as time series for quantity and time restrictions.

9ASNP02 � Order based.

� Central planning area used for supply planning.

� Encompasses many basic (replenishment, distribution, and capac-ity) and advanced (aggregated, subcontracting, shelf life, and product substitution) functionalities in supply planning.

9ASNP03 � Scheduling agreement processing using SNP heuristics planning.

9ASNP04 � Optimization-based planning with time-dependent restrictions.

� APO-SNP optimizer profile lists all the constraints to be factored during the optimization run. However, there may be situations when the constraints need to be defined that are time-based.

� Upper limits of production, supplier capacity, transportation, or stock on hand can be defined as constraints.

9ASNP05 � Safety stock planning.

� Both basic and advanced safety stock planning can be performed in this planning area.

9AVMI03 � Used for deployment heuristics with consideration for demands in the source location.

� Used primarily for VMI scenario.

Table 4.7 List of Standard APO-SNP Planning Areas


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4.6.4 Planning Book

As explained in Section 4.2.4, the planning book serves as both the frontenduser interface for the business users to plan and for batch background process-ing for planning cycles and alert generations. The ABC Technology businessusers plan to use the supply planning book to visualize the demand, supply, andinventory information on a real-time basis to make key decisions. SAP deliversstandard APO-SNP planning books and recommends its customers to use theseplanning books as templates while building their own custom planning books(see Table 4.8).

APO-SNP Planning Book(s) Description

9ASNP94 Interactive planning book for executing supply planning and Transport Load Builder (TLB) features. Using this planning book, the planner can create external procure-ment, replenishment, production, distribution, and load plans.

There are two data views in 9ASNP94. The first data view, SNP94(1), is for supply planning, while the second data view SNP94(2) is for capacity planning. The TLB screen is accessed by using the icon.

9ASOP This planning book is used to run the APO-SNP planning method based on supply and demand propagation.

There are four data views in 9ASOP: Location product, transportation, PPM, and resource.

9ADRP This planning book is similar to the 9ASNP94, with the difference being the addition of the table view, showing the distribution receipts and issues. There is only one data view on this planning book.

9AVMI This planning book is for the VMI scenario. In addition to APO-SNP data, we can display VMI receipts and demand key figures in this planning book. There are two data views for this planning: one for planning and the other for capturing external partner forecast.

9ASA This planning book is used for the APO-SNP scheduling agreement process. There is only one data view for this planning book.

Table 4.8 List of Standard APO-SNP Planning Books Delivered by SAP


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The custom planning book can be easily created using one of the SAP standardplanning books from the table as a template. The planning book can be created inTransaction /SAPAPO/SDP8B in four steps, as shown in Figure 4.41:

1 Define your new planning book and data view using a reference with standarddata view. In our scenario, we are copying the standard 9ASNP94(1) planningbook. Once you click the Create icon, a message will pop-up mentioning that“macros were copied and are inactive.”

2 Assign your own planning area to the planning book from transaction menupath Edit � Assign Planning Area.

9ASNPAGGR This planning book supports APO-SNP hierarchical plan-ning. The book has two data views to perform aggre-gated planning and planning with aggregated resources.

9ASNP_PS This planning book is used for product interchangeabil-ity when planning. The book has one data view, with additional key figures to support the product substitu-tion features.

9ATSOPT This planning book is used to maintain the time-based constraints for the APO-SNP optimizer. The planning book has two data views.

9ASNP_SSP This planning book is used for basic and advanced safety stock calculations.

9ADRP_FSS This planning book is used for the deployment heuristics to also consider the customer demand in the source location and not deploy the entire inventory for internal replenishment transfers.

9ASNP_SHLF This planning book is used for shelf life planning. There are four additional key figures with shelf life functions to support the planning process.

9ASNP94_INTERACT This planning book is for displaying aggregated supply planning and aggregated resource planning information.

9ASNP94_BATCH This planning book is for running the supply planning processes in the background.

APO-SNP Planning Book(s) Description

Table 4.8 List of Standard APO-SNP Planning Books Delivered by SAP (Cont.)


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3 Select your planning area and click Continue. An application log will be gen-erated mentioning that the new planning area is assigned. While exiting, if thismessage appears again for resetting the original value, select No.

4 Generate all the macros for the planning book in Transaction /SAPAPO/ADVM.

Figure 4.41 Steps for Creating a Custom APO-SNP Planning Book

4.6.5 Key Figures and Macros

The standard APO-SNP planning book provides all the vital information requiredfor supply chain planning. Per business definitions, we can change the namingabbreviation of the key figure to make it easier for the business to understand.For example, for the SNP Distribution Demand key figure, we can change thename to Purchase Orders key figure.

Let’s look at the definition of standard key figures and macro calculations pro-vided in the standard planning book 9ASNP94. As shown in Figure 4.42, the keyfigures are grouped into three categories: demand, supply, and inventory.


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Figure 4.42 Standard Planning Book Key Figures

The business needs to clearly understand the definition of the standard key fig-ures, as some are transactional while others are macro function calculated. Let’slook at the standard APO-SNP key figure definitions in tabular form in Table 4.9.

Key Figure Definition Macro Calculation Category

Forecast This key figure initially represents the gross forecast, but once the sales orders come, it represents the net forecast (unconsumed forecast).

A consumption (forecast/sales orders) based on the requirement strat-egy of the product performs the fore-cast consumption function.

FC req: Forecast require-ment

Table 4.9 Standard APO-SNP Key Figure and Macro Definitions

Demand

Supply

Inventory


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Sales order Requested sales orders and open deliveries. Additional custom key figures can be defined to identify the con-firmed sales orders based on quantity type maintenance in the cat-egory group.

Distribution demand (planned)

This key figure rep-resents the stock trans-fer requisitions from the supply network. This replenishment will include unconstraint requirements to fulfill both possible customer backorders and addi-tional stock build in other distribution cen-ters.

BC: Stock transfer reservation

BH: Stock transport requisition

BJ: Supplier scheduling agreement requirement

EB: SNP release for stock transport requisition

ED: SNP VMI sales order

HJ: SNP suppliers sched-ule agreement release

Distribution demand (confirmed)

This key figure rep-resents the outgoing constraint supply plan after the APO-SNP deployment run.

EG: Deployment: Purchase requisition

EH: Deployment VMI sales order

Distribution demand (TLB confirmed)

This key figure rep-resents the stock trans-port order (outgoing load plan) build after the APO-SNP TLB inter-active or batch run.

BI: Stock transport order

Dependent demand

This key figure represents demand in the form of a BOM explosion.

AY: Dependent demand

EL: SNP dependent demand

AU: Order reservation without withdrawal

AV: Order reservation with withdrawal


Table 4.9 Standard APO-SNP Key Figure and Macro Definitions (Cont.)


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Total demand

This key figure adds all the demand elements highlighted in the above rows.

Sub-macro of stock balance. Adds all the demand ele-ments.

Forecast + Sales Order + Distri-bution Demand (Planned) + Dis-tribution Demand (Confirmed) + Distribution Demand (TLB Con-firmed)+ Depen-dent Demand

Distribution receipt (planned)

This key figure rep-resents the proposed purchase requisitions to the source location.

AG: Purchase requisition

BD: Stock transfer reservation

BE: Scheduling agree-ment schedule line

EA: SNP purchase requisition

HG: SNP scheduling agreement schedule line

Distribution receipt (confirmed)

This key figure rep-resents the confirmed purchase requisitions to the source location.

EF: Deployment pur-chase requisition

Distribution receipt (TLB confirmed)

This key figure rep-resents the purchase order to the source location.

BF: Purchase order item schedule line

In transit This key figure rep-resents the goods in transit to the destina-tion location.

AH: Advanced shipment notification

EI: In transit




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Production (planned)

This key figure rep-resents the APO-SNP planned production.

EE: SNP planned order

Production (confirmed)

This key figure rep-resents the production plan created by the manufacturing module.

AC: Production order (created)

AD: Production order (released)

AI: Planned order (firmed, unconfirmed)

BU: Inspection lot

AJ: Planned order (not firmed, confirmed)

Manufacture of co-products

This key figure represents the receipt elements for the co-product.

EM: Receipt from manu-facture of co-products

Total receipts This key figure adds all the supply elements highlighted in the above rows.

Sub-macro of stock balance. Adds all the supply elements.

Distribution Receipt (Planned) + Distribution Receipt (Confirmed) + Distribution Receipt (TLB Confirmed) + In Transit + Production (Planned) + Production (Confirmed) + Manufacture of co-products




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Stock on hand

This key figure represents stock on hand at different periods.

Sub-macro of stock balance. Calculated as:

Unrestricted inventory + receipts - demand or projected stock on hand + incoming receipts - outgoing demand

Supply shortage

This key figure rep-resents how short on inventory the company is versus demand.

The supply shortage value is dependent upon the stock on hand projected key figure. The macro equations reads as follows:

IF the Stock on Hand Projected Key Figure > = 0,

THEN

Stock on Hand Initial = Stock on Hand Pro-jected

AND Supply Shortage = 0

ELSE IF

Stock on Hand = 0

THEN Absolute Value (Stock on Hand Projected)

END




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Safety stock This key figure is used for safety stock calcula-tion by the function SAFETY_CALC.

The advanced safety stock method takes into account demand, supply variability, and service level.

Calculated by a sub-macro to the Safety Stk/Reor-der Point/Targt Stock Lvl macro.

Days’ supply This key figure represents the days of supply the company is holding inventory against future demand.

Macro calculation (Stock on Hand / Total Demand) * Days in the Period.

The number of days in the period is another macro: workdays.

Reorder point

This key figure rep-resents the reorder point and returns the function REORDER_CALC.

The standard macro adds the safety stock during the reorder point calculation.

Target days of supply

This key figure is calcu-lated through use of the TARGET_DAYS function.

Target stock level

This key figure is calcu-lated through use of the function TARGET_CALC.

The standard macro adds the safety stock during the tar-get stock level cal-culation.

ATD receipts This key figure is used in the deployment plan-ning and calculates the available-to-deploy quantity from the source location.

Populates per the loca-tion or location product master data mainte-nance.



Supply Chain Modeling for SAP APO-SNP 4.7

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4.7 Supply Chain Modeling for SAP APO-SNP

The APO-SNP process starts with the business deciding how it wants to model itssupply chain in the SAP APO system. The modeling not only reflects mapping thedistribution network in SAP APO, but also defines parameters based on supplychain constraints. Supply chain modeling is one of the key activities that requirebusiness involvement and validation. In the modeling, ABC Technology definesnot only the network structure for its distribution, but also master data parame-ters to reflect the business requirements. While the ABC Technology desktop andmonitor businesses may have structured network models, the laptop business dis-tribution might look more like a web network.

In this section, we’ll highlight the data elements that make up the supply chainmodel in APO-SNP. These elements are primarily master data settings needed tosupport APO-SNP planning business processes. Before we get started, however, aclear understanding of master data modeling is required before we begin theplanning process in APO-SNP.

4.7.1 Model and Planning Versions

The model in SAP APO stores all the master data (i.e., location, product, transpor-tation lanes, and production data structures) and can have multiple linked ver-sions. The version primarily stores the transaction data for the model master datadefinitions. All the data versions are stored in SAP liveCache for the business toaccess and analyze the planning data. However, there will be only one active ver-sion 000, which synchronizes the transactions between SAP ERP and SAP APO.The other simulation versions created will be snapshots of the active version andcan be used for what-if analysis.

ATD issue This key figure is used in the deployment planning and calculates the avail-able-to-issue quantity from the source location.

Populates per the location or location product master data maintenance.




224

The model and version are created via the menu path Advanced Planning and

Optimization � Master Data � Planning Version Management � Model and

Version Management (Transaction /SAPAPO/MVM). Figure 4.43 shows themodel and version creation with some version options for APO-SNP:

� Change Planning Active Used by SNP heuristics for net change planning.

� No Planned Order without Supply Source The SNP optimizer looks for valid production data structure (PDS) or produc-tion process model (PPM) and if checked, will not create planned orders unlessreferenced to PDS or PPM.

� Consider Stock Transfer Horizon of Source Location Affects the SNP heuristics and CTM planning process by defining a time fencefor the distribution receipt where the new requirements can only be fulfilledafter the stock transfer horizon.

� Local Time Zone Enter a check mark to consider a local time zone instead of UTC.

Figure 4.43 Model and Planning Version Management in SAP APO

4.7.2 Location

Locations in SAP APO represent both internal and external physical entities in thesupply chain model. The physical entity can also represent external business part-

Model and PlanningVersion create


225

ners, such as vendors and customers. Only locations that the business wants toinclude in the supply chain model need to be transferred to SAP APO. The loca-tion master is transferred from SAP ERP via CIF.

Maintain Location Master Data

The menu path for the location master data maintenance is Advanced Planning

and Optimization � Master Data � Location � Maintain Location (Transac-

tion /SAPAPO/loc3). The Location tabs that are relevant for APO-SNP are Cal-

endars, Resources, SNP, and Extra Attributes.

In the location master, the following tabs are used for populating data fields rele-vant to APO-SNP:

� Calendar In the Calendar tab, we maintain the shipping, receiving, and production cal-endars (time stream). The time stream calendar is maintained via Transaction/SAPAPO/CALENDAR. This offers the business the flexibility to specify the cal-endar per location. The shipping calendar refers to the weekdays when thegoods can be outbound from the warehouse, and similarly, the receiving calen-dar specifies the weekdays the goods can be received inbound to the ware-house. The production calendar specifies the manufacturing plant calendar forproduction schedule.

� Resource In the Resource tab, we can maintain storage and handling resources. Whilethe storage calendar can be used for measuring the warehouse capacity for thespecific location, the handling resource can be used to take into account thegoods receipt processing time in SAP APO in the business scenario in which theproduction needs additional time for quality.

� SNP In the SNP tab, we represent the stock, available to deploy, and available to issuecategory groups for APO-SNP calculations. The business can model which re-ceipts it wants to distribute per its business rule.

� Addt. In the Addt. tab, we can maintain five additional, freely definable attributes forthe location used for selection, planning, or reporting purposes. The attributescan be defined in the configuration path SPRO � SAP Reference IMG � Advanced


226

Planning and Optimization � Master Data � Maintain Freely Definable Attri-

butes. The attributes are stored in table /SAPAPO/LOC.

Figure 4.44 shows the various location master tabs and the calendar maintenance.

Figure 4.44 Location Master in SAP APO

4.7.3 Location Product

The location product represents the material master from the SAP ERP system. TheSAP APO location product is transferred via CIF from SAP ERP. The product mas-ter has global and location-specific properties maintained similarly to the SAPERP material master. SAP APO uses SAP ERP as the source system for the masterdata creation. The business can identify whether it would like the real-timechanges to reflect from SAP ERP to SAP APO or in batches.

Maintain Location Product Master Data

These settings of master data transfer in SAP ERP are maintained in TransactionCFC9. The menu path for the location product master data maintenance isAdvanced Planning and Optimization � Master Data � Product � Maintain

Product (Transaction /SAPAPO/MAT1). Let’s look at various product masterfields relevant to the APO-SNP planning process in Table 4.10. The SAP APO


227

master data fields in the table are maintained in different ways. For example,while the majority of the master data is transferred via CIF from SAP ERP, someof the master data is directly maintained in SAP APO. The maintenance in SAPAPO can be done either with mass maintenance Transaction MASSD or other datamaintenance (e.g., LSMW) techniques. Let’s look at the fields that are transferredvia CIF or SAP APO-specific techniques in Table 4.10.

Master Data Tabs (Views)

Master Data Field (CIF/APO)

Definition

Administration (location)

SNP planner (CIF) Planner code assigned for planning book, background processing, and alerts selections.

Properties (global) Material group (CIF)

Used planning book, background processing, and alerts selections.

Product hierarchy (CIF)

Used for planning books, background pro-cessing, and alerts selections.

Transportation group (CIF)

Grouping of products while building trans-port loads.

SDP relevance (APO-specific)

Indicator for excluding products planning in APO-DP and APO-SNP.

Weight (CIF) Product attribute used in APO-SNP TLB.

Volume (CIF) Product attribute used in the APO-SNP TLB.

Stacking factor (CIF)

Product attribute used in the APO-SNP TLB, which indicates how many pallets can be stacked over each other.

Shelf life (CIF) Indicates how many shelf life days the prod-uct has before expiring and includes matura-tion time.

Planning with shelf life (CIF)

Indicator for considering shelf life for APO-SNP planning processes.

Maturity time (CIF) The incubation period after the production receipt before the product can be shipped to customers for sales.

Required mini-mum shelf life (CIF)

Used in shelf life planning and indicates the minimum shelf life required on batches for sales.

Table 4.10 SAP APO Location Product Master Data Fields


228

Required maxi-mum shelf life (CIF)

Used in shelf life planning and indicates the maximum shelf life required on batches for sales

Additional data (APO-specific)

Additional attributes specific to the product to be used in the planning process (for exam-ple, price). Up to three freely definable attri-butes can be defined specific to the location product to support the planning process.

The attributes can be defined in configura-tion path SPRO � SAP Reference IMG � Advanced Planning and Optimization � Master Data � Maintain Freely Definable

Attributes. The attributes are stored in table /SAPAPO/MATKEY.

Unit of measure (global)

Unit of measure (CIF)

Defines all the available alternative units of measure for planning. A scenario may consist of different products being planned in differ-ent purchasing units of measure. To get plan-ning consistency, a common planning unit of measure may be defined for the SAP APO planning book.

SNP1 (location) Penalty costs (APO-specific)

Location-dependent penalty cost to be used by the SNP optimizer can be defined here. Penalty costs can be defined for no delivery, delay, and maximum delay across various demand types (e.g., forecast, customers, and sales orders).

SNP2 (location) Demand profile (APO-specific)

The profile helps to determine how demand is calculated during the SNP heuristics and deployment planning runs. We can define the Forecast Horizon field, where the fore-cast is not taken into account; Pull Deploy-

ment Horizon, where planned distribution demands are considered for deployment; and Period Split for disaggregating the demand release to supply plan.



Definition

Table 4.10 SAP APO Location Product Master Data Fields (Cont.)


229

Supply profile (APO-specific)

The profile helps to determine how supply is calculated in the SNP heuristics and deploy-ment planning runs. We can define in APO-SNP production horizon, where SNP produc-tion plans are not created, and similarly in APO-SNP stock transfer horizon, where stock transfers are not created. We can also define the push deployment horizon, where planned distribution receipts are considered for deployment. If the indicators for Fix Produc-

tion and Fix Stock Transfers are checked, the earlier planning results are fixed for the APO-SNP production horizon and APO-SNP stock transfer horizon during the SNP heuris-tics and optimizer runs.

Deployment pro-file (APO-specific)

The profile helps to determine the distribu-tion rules for deployment heuristics during the planning run. Push distribution covers various scenarios when the available-to-deploy (ATD) is enough to cover the demand. The fair share rule is defined for sce-narios when demand is greater than supply (see Chapter 5).

Demand at source location (APO-spe-cific)

The two fields—Consider Sales Orders and Consider Forecast—can be checked if we want deployment heuristics to take into account the source location sales orders and forecast during the real-time deployment run.

SNP interactive order creation (APO-specific)

The No Fixing indicator can be checked to undo any fixing for any APO-SNP orders cre-ated by the planner in the planning book.

CTM settings (APO-specific)

Time based priority and Demand select hori-

zon can be defined for product-location spe-cific during the CTM planning run.



Definition



230

Other data (CIF- and APO-specific)

Defines the product priority, ATD receipts, and ATD issues for the location product. The product priority is used in CTM and SNP optimizer runs. The ATD defined in the loca-tion product is taken into account in the APO-SNP deployment and TLB runs.

Demand (location) Proposed strategy (CIF)

Primarily transferred from SAP ERP material master strategy group. The proposed strategy helps in determining how the forecasted demand is produced and consumed with sales orders. The Consumption mode directs on the forward or backward consumption direction, as well.

Pegging (APO-specific)

Considers fixed or dynamic pegging strategy.

Available stock (APO-specific)

Settings for additional stock category to be considered in the APO-SNP CTM run.

Lot size (location) Procedure (CIF) Defines various lot size procedures to be used during the APO-SNP planning run. The lot size procedures available are Lot-to-lot,

Periodic, Fixed, and Reorder point.

Quantity deter-mination (CIF)

Defines the maximum lot size, minimum lot size, rounding value, target stock level method, and target days of supply. The lot size param-eters and target stock level methods are used during the APO-SNP planning run.

Scheduling (APO-specific)

Defines the safety days of supply and period factor. The safety days’ supply used in APO-SNP and CTM (safety time) identifies the number of workdays over which the system has to take into account future demand when calculating safety stock. The period factor sig-nifies when the availability date/time needs to be scheduled in the bucket, on the range of 0 to 1. The value of 1 signifies a date toward the end of the bucket And is only used if the period factor is not defined in the transportation lane.



Definition



231

Stock data (APO-specific)

Defines the safety stock, reorder point, and max stock level. Also defines the basic and advanced safety stock method to be used. For the advanced safety stock method, addi-tional fields like Service Level, Demand Fore-

cast Error %, and Replenishment Lead Time

Forecast Error % are maintained.

Procurement (loca-tion)

Procurement type (CIF)

This field defines whether the product is pro-duced in house, externally procured, or a combination of both.

Procurement costs (APO-specific)

Used in the SNP optimizer for cost calcula-tions.

Stock cost (APO-specific)

Production storage cost and safety stock cost are used for the SNP optimizer calculation.

ABC indicator (CIF) Defines whether the product is fast moving or slow moving based on the ABC indicator.

GR/GI (location) Processing times, in days (CIF)

Defines the goods receipt processing time and goods issue processing time to take into account additional time for handling and quality checks. Added on top of transporta-tion lead times during the availability date calculation.

Capacity consump-tion (APO-specific)

The Storage Consumption per Base UOM field can be used for the storage capacity. Handling resource capacity consumption can also be defined.

Shipping (CIF) Loading group can be used for APO-SNP TLB during the load building.

Extra (location) Freely definable attributes (APO-specific)

Up to five freely definable attributes can be defined specifically to the location product to support the planning process. The attributes can be defined in configuration path SPRO � SAP Reference IMG � Advanced Planning

and Optimization � Master Data � Maintain

Freely Definable Attributes. The attributes are stored in table /SAPAPO/MATLOC.



Definition



232

Example

ABC Technology would like to change some of the parameter values during the standardtransfer using CIF. These changes are done via CIF user exit enhancement, which will beexplained in detail in Chapter 15.

4.7.4 Resources

Resources in the form of production, transportation, and storage represent a poolof capacity for checking supply plan feasibility. As APO-SNP uses bucket-orientedplanning, the planning time buckets are represented by day denominations. Theresource to be used for APO-SNP production plan creation is either a bucket, sin-gle-mixed, or multi-mixed resource. The bucket resource shows the capacity con-sumption once the production orders are planned. The single-mixed and multi-mixed resources can be used for the APO-SNP and PP/DS planning processes.While the single-mixed resource has a single capacity (100%) the multi-mixedmay have more than a single capacity (> 100%).

Example

Depending on the solvers used by ABC Technology, different resources might be used.For product families using the SNP heuristics as a planning engine, we only need a pro-duction resource for manufacturing and a handling resource for modeling goods receiptlead time. For another set of product families, various resources in the form of produc-tion and transportation can be used for cost optimization.

The SAP APO resource master data is primarily maintained in SAP ERP. The busi-ness user maintains the SAP ERP master data using Transaction CR02. The SAPAPO resource master is transferred from the SAP ERP work center and capacitymaster data. As shown in Figure 4.45, within the capacity maintenance, we canmaintain the parameters for the SAP APO resource. Also via Transaction CFC9 inSAP ERP, we can direct the CIF to create a single-mixed or multi-mixed resourcein SAP APO.


233

Figure 4.45 Resource Settings in SAP ERP

Once transferred from SAP ERP (see Figure 4.46), various planning parameterscan be maintained in SAP APO. The menu path for the resource master data main-tenance is Advanced Planning and Optimization � Master Data � Resource �

Maintain Resource (Transaction /SAPAPO/RES01). One such important parame-ter is the definition of APO-SNP bucket capacity for us to analyze the bucket con-sumption. The purpose of the resource in APO-SNP is to provide a rough-cutcapacity plan, which is managed by capacity variant settings. Here, we can definethe normal, maximum, and minimum capacities (defined by quantity/rates). Fol-low these steps (see Figure 4.46):

1. Create a definition of the quantity/rate per bucket. Define the bucket capacityfor normal, minimum, and maximum for the period type (single day).

2. Create capacity variants. Assign the three capacity definitions to three capacityvariants in the SAP APO resource master data.

Work Center—CR03

Transaction CFC9


234

Figure 4.46 Maintenance of Capacity Variants in the SAP APO Resource Master

3. Once the variants are maintained, we can see all three capacities in the APO-SNP planning book. The business planner gets the visibility of the maximum,minimum, and normal capacities for the modeled resource (see Figure 4.47).

Figure 4.47 APO-SNP Capacity Planning Book


235

Resource in SAP liveCache

Run report /SAPAPO/CRES_CREATE_LC_RES periodically to correct any inconsistenciesin the resource master creation in SAP liveCache.

4.7.5 Production Data Structure

The PDS/PPM functionality represents the combination of the work center andBOM in SAP APO. The master data is transferred via CIF from production ver-sion. The SAP ERP production version combines both routing and BOM masterdata. The APO-SNP PDS is generated directly from SAP ERP, while the APO-SNPPPM is converted from PP/DS PPM in SAP APO via a generation report.

The PDS is used to calculate production time, production cost, material flow, andresource loads in the plant. The menu path for the PDS master data maintenanceis Advanced Planning and Optimization � Master Data � Production Data

Structure � Display Production Data Structure (Transaction /SAPAPO/CUR-

TO_SIMU). The PDS (see Figure 4.48) has an operation category to define the pro-duction activities. For each activity, there can be modes (resources) and com-ponents (product) assigned. The mode contains the throughput rate to producethe base quantity. The components represent the input and output componentsof the operation.

Figure 4.48 Production Data Structure in SAP APO

The following information summarizes the PDS shown in the figure:

� Each PDS includes one or more operations, which are steps in the productionprocess.


236

� Each operation includes one or more activities, the components consumed bythe activity, and their sequence within the operation.

� The PDS has validity parameters by lot size and time intervals.

� The variable costs defined for a PDS include the costs of input material as wellas the cost of production.

Since PDS is bucket oriented, the production lead time is calculated based on thecritical path operations, in days, and with the use of the resource factory calendar(Figure 4.49).

Figure 4.49 Production Lead Time Calculation in APO-SNP PDS

APO-SNP PDS

The APO-SNP PDS generated from SAP ERP can be influenced by using one of the fol-lowing BAdIs:

Oper. 10

Oper. 30

Oper. 20

Oper. 50

Oper. 40

Oper. 60

Operation

Activity

Components ModeFinish-Start

Finish-Start

Finish-Start

Production Lead time (critical path)


237

� /SAPAPO/CURTO_SNP Calculate bucket consumption of resources with the CALC_BUCKET_CONSUMPTIONmethod of this BAdI. This method, which executes standard calculation of bucketconsumption, is active automatically. However, you can change the calculation.

� /SAPAPO/CULLRTOSNP Carry out optimization-based APO-SNP planning. You can use the FILL_COST_FIELDS method of this BAdI to fill the SNP PDS cost fields.

SAP also provides Transaction /SAPAPO/CURTO_EDIT to change the APO-SNP PDSheader data in SAP APO locally.

4.7.6 Transportation Lanes

Transportation lanes represent the material flow between two physical locationsin SAP APO. A means of transport is also defined within the transportation lanewith appropriate truck capacity and transportation duration, as shown in Figure4.50.

Figure 4.50 Transportation Lane in SAP APO

The menu path for the transportation lane master data maintenance is Advanced

Planning and Optimization � Master Data � Transportation Lane � Maintain

Transportation Lane (Transaction /SAPAPO/SCC_TL1). The transportation lanehas three views: Product, Means of Transport, and Product Specific Means of

Transport, as shown in Figure 4.51.

In the Product view, the product validity date, minimum/maximum lot size, costfunction, block indicator, and form of procurement (e.g., subcontracting, con-signment, and standard) are maintained.

DistributionCenter 1

DistributionCenter 2

Means of Transport—TruckTransportation Duration—2 days

Truck Capacity—40 cube ft

Transportation Lane


238

Figure 4.51 SAP APO Transportation Lane: Three Views

In the Means of Transport view, one or more mean of transport is assigned tothe transportation lane, transportation duration, transport calendar, and cost oftransport method. Also defined is the TLB with the loading method (i.e., straightloading or load balancing). If the straight loading method is used, the deploymentorders are sorted per the product loading group, while the load balancingattempts to distribute multiple products in the same truck.

In the Product-specific Means of Transport, we define the transport resourcecapacity consumption, lot size profile, and specific costs.

The TLB profile is maintained via Transaction /SAPAPO/TLBPRF and defines thecapacity constraints to meet vendor minimums while cutting purchase orders totruck loads and building stock transport orders for internal replenishments. TheTLB constraint parameters are defined in Transaction /SAPAPO/TLBPARAM.

4.7.7 Quota Arrangement

For multi-sourcing business scenarios, we can set up quota arrangement so thatthe demands are based on pre-defined quota. For example, two manufacturinglocations are sourcing the same product to the distribution center. We candefine the percentage each sourcing should receive of the net requirements


239

from the distribution centers. The menu path for the quota arrangement masterdata maintenance is Advanced Planning and Optimization � Master Data �

Quota Arrangement � Maintain Quota Arrangement (Transaction /SAPAPO/SCC_TQ1).

Figure 4.52 shows a business example in which ABC Technology has two suppli-ers sourcing raw materials to the manufacturing facility. Once the goods are pro-duced, they are distributed to three distribution centers based on quota alloca-tion. We have maintained quota arrangement for both inbound and outboundmaterial flow to the manufacturing plant.

Figure 4.52 Quota Arrangement in APO-SNP

4.7.8 Supply Chain Engineer

Supply Chain Engineer is an SAP APO functionality that can be used to create andmaintain supply chain models in pictorial form. There is no configurationrequired; you just need to have master data maintained on the supply network.The supply chain model consists of the specific planner work area in scope and allSAP APO data objects to be planned.

Incoming Quota Arrangement

Outgoing Quota Arrangement

70% 30%

30% 20%

50%


240

Supply Chain Engineer is also used for mass maintenance of master data. Themodel consists of a node and links among the physical locations, with materialflow direction represented by transportation lanes. The menu path for the supplychain engineer master data maintenance is Advanced Planning and Optimiza-

tion � Master Data � Supply Chain Engineer � Maintain Model (Transaction/SAPAPO/SCC07). Figure 4.53 shows the supply chain engineer with a graphicalrepresentation of the model on the top of the screen and master data elements(work area) on the bottom. Add objects to the supply chain engineer by right-clicking and selecting the Add Objects to Work Area option. The users inputtheir respective master data objects (i.e., location, location products, and PDS).Based on the location product combination, the transportation lanes are automat-ically generated in Supply Chain Engineer.

Figure 4.53 SAP APO Supply Chain Engineer

Summary 4.8

241

Another important use of the Supply Chain Engineer is for master data modelconsistency check. The model consistency checks not only for all the master dataconsistency, but also how the model will behave when running various APO-SNPengines. Business users can routinely run the consistency check by using Transac-tion /SAPAPO/CONSCHK.

4.8 Summary

In this chapter we explained the basic configuration tasks for APO-DP and APO-SNP. While the configuration for APO-DP is flexible, the configuration for APO-SNP is more structured and standard. The main reason for the latter is its integra-tion with SAP ERP.

The chapter also explained how to set up the forecast model in APO-DP andframework for identifying the best forecast method. The chapter ends by explain-ing the supply chain modeling using APO-SNP and prepares the planner for per-forming basic planning.

The next chapter introduces the basic navigations and demand and supply plansthat can be formulated in SAP APO. The chapter uses a weekly planning cycle toexplain different functions within APO-DP and APO-SNP.

813

Index

A

ABCanalysis, 582classification, 137, 584inventory analysis, 584segmentation, 142

Active variant, 508Actual costs, 532Additional demand (shelf life), 370Administrator Workbench, 158, 180Advanced safety stock planning, 344

setting up, 346Advanced supply planning, 337AFS, 652, 654, 658

allocation run, 656APO-SNP aggregated planning, 658batch characteristics, 665bill of materials, 661business benefits, 652characteristics, 660data transfer, 660data transfer reports, 660execution process, 657hierarchies, 663hierarchy master data, 669highlights, 653industry solution, 652inventory management, 657manufacturing process, 656master data, 658, 660material, 668, 670material grid, 660order group, 663orders transfer, 664planning, 658procurement process, 656product costing, 657production version, 662safety stock, 670seasonal demand planning, 658supply chain planning, 655technical flow, 655third-party processing, 656

AFS (Cont.)transactional data, 663transactional order integration, 664

Aggregated and disaggregated, 94Aggregated planning, 349, 561Aggregated supply network planning, 104Aggregates, 162, 476Airline strategy, 560Alert, 296, 330, 373

decision tree, 296threshold values, 410

Alert Monitor, 78–79, 105, 293, 330, 372, 410, 413, 788/SAPAPO/AMON1, 372favorites, 411hierarchies, 414

Allocationmanagement, 259proposals, 537

Alternative resource balancing, 359APO-DP, 94, 191, 304

alerts, 330APO-SNP release, 787basic customization, 155BOM, 318Book Wizard, 173characteristics, 787forecasting, 718interactive planning book, 318planning book, 304, 786planning book customization, 172

APO-SNPaggregated planning, 668aggregated planning technical flow, 358aggregates, 477alert types, 411allocation optimizer, 529alternative planning method, 546basic customization, 208bucket capacity, 233cost profile, 518deployment, 359deployment heuristics, 281deployment optimizer, 538

814

Index

APO-SNP (Cont.)disaggregation program, 672heuristics, 271, 718, 785interchangeability field attributes, 393key figure definitions, 217lot size profile, 511optimization bound profile, 511optimization planning, 535optimization result, 516optimization steps, 498optimizer, 214–215, 780orders, 564penalty cost group profile, 511planning area, 212–213planning book, 214, 569, 594, 781planning engine, 670planning profile, 512planning tasks, 271priority profile, 511solvers, 270subcontracting scenarios, 379supply chain modeling, 223

APO-SNP planning books9ASNP_PS, 3929ASNP_SHLF, 3699ASNP_SSP, 3439ASNPAGGR, 3539ASNPSBC, 383alert profile, 414

Apparel and footwear (AFS), 316, 651Application

errors, 688log, 693usage and performance, 540

Application link enabling (ALE), 677Architecture, 105As-is analysis, 115Assembly

component, 621forecast, 640planning, 619

Asset management, 87Assignment mode (forecast consumption),

376Assortment BOM, 661Asynchronous communication, 676Attach rate, 621, 640

Auto Model Selection Procedure, 204Automatic cost

generation, 527model, 525

Automatic forecasting models, 204Auxiliary key figures, 173Available-to-deploy (ATD), 282Available-to-promise (ATP), 282

category, 562elements, 209

B

Background jobs, 792Backorder processing (BOP) sort profile, 562Backward consumption, 378BAdIs, 236, 308Balancing transportation lanes, 410Baseline system, 122Basic functions toolbar, 254Basic interactive planning, 243Batch

characteristics, 368input session, 767inventory, 364status, 366

Bill of material (BOM), 318costs, 506explosion, 321

Blockbasis definition, 649planning, 648reference cycle, 650stock, 366

BOM, 98, 546, 553Bottom-up and top-down, 141Bucket

consistency, 264consumption, 780

Building process chain, 794Bullwhip effect, 64, 427Business

case, 112function, 673, 710goals, 125partner, 438

Index

815

Business (Cont.)performance, 464process owner, 127readiness, 116rules, 521, 527situation, 46specific logic, 562transaction event (BTE), 680

Business Application Programming Interface (BAPI), 308, 541, 760, 776

Business benefits, 123, 128Business Explorer (BEx), 477

C

C++ mathematical, 499Calculation type, 167Cannibalization, 304Capable-to-Match (CTM), 100Capacity

KPI, 725leveling, 100, 247, 278, 358–359, 387management, 279variants, 233, 508

Capital investment, 129Casual forecasting, 96, 193, 207Categorization profile, 564Category

group, 209, 377management, 426

Cause-effect analysis, 115CBF

profile, 637table, 637

Changemanagement, 113, 123–124pointer, 686recordings, 685

Characteristic value combination (CVC), 190, 255, 318, 637

Characteristics, 626, 651Characteristics and class, 367Characteristics for optimization run, 540Characteristics-based forecasting, 98, 618, 635

APO-DP release, 643CVC, 638

Characteristics-based forecasting (Cont.)descriptive characteristics, 642flow, 635master data, 636planning books, 639planning object structure, 636profile, 637table, 637

Characteristics-dependent planning (CDP), 617, 619–621, 645

Chartdesigner, 260elements, 261engine, 260

CIF, 80, 227, 323, 363, 503, 627, 660administration, 688compare/reconcile function, 691configuration, 677customer exits, 703delta inconsistency report, 700delta report, 688, 780distribution definitions, 687enhancement, 703, 773incremental data transfer, 684master data, 681model activation, 680model generation, 680monitoring transactions, 688post-processing, 690queue names, 693queue statuses, 695regular monitoring transactions, 705SAP APO transaction codes, 678SAP ERP transaction codes, 677structure, 774transaction codes, 680transaction data, 682troubleshooting, 700user exits, 703

CIF Cockpit, 688–689Class type 300, 628Clear old logs, 565Client level, 624COGS, 657Coherent, 745Collaboration partner user, 438–439Collaborative planning, 97, 429, 434

816

Index

Collaborative planning, forecasting, and replenishment (CPFR), 426, 430

Collaborative supply planning, 432–433COM routine, 108–109Common component planning, 578Communication, 124

errors, 688Composite forecasting, 96Concurrent planning, 76Conditional statement, 795Configurable

finished product, 621material, 624profile, 631

Consensus-based forecasting, 429Consistency check, 182, 241Consistent planning model, 168Constant model, 95Constraint, 102, 244, 498

management, 77plan, 273supply plan, 281

Constraint-based heuristics, 547Consumption

group, 643master data, 377planning, 608strategies, 373

Control cost, 502Conversion rules, 765Convex polyhedron, 497Corrective

actions, 461decisions, 463history, 200

Costfactors, 501–502function, 506, 509maintenance, 501modeling, 524parameters, 503penalties, 503profile, 511reduction, 128savings and reduction, 128

CPFR process flow, 430CPLEX engine, 497

Critical component, 276Cross dock, 401, 403Croston model, 204CTM, 785

aggregated planning, 567early/late demand fulfillment, 560engine, 547global settings, 560integration with global ATP, 556master data, 566planning characteristics, 546planning method, 548planning parameters, 568planning run, 568planning scenario, 546solver run, 568sort profile, 785supply categories, 564supply distribution, 566time stream calendar, 554

CTM profile, 551, 670aggregation, 561demand, 562planning scope, 552settings, 564strategies, 555supplies, 563

Customercharacteristics, 157hierarchy, 255segmentation, 159, 326service levels, 136

Customer Forecast Management (CFM), 328CVC

maintenance, 324master data, 323

Cycle stock, 339, 592

D

Daily bucket profile, 264Data

cleansing, 758consolidation, 465conversion, 757conversion strategy, 756dimensions, 463

Index

817

Data (Cont.)management, 97mapping, 758model, 77, 155sources, 473staging, 182, 465

Data conversionsautomated, 757manual, 757

Data Warehousing Workbench, 158Database alerts, 293DataSource, 184

custom, 185Days’ supply, 370, 723Dead stock, 591Debugging CIF, 777Decision basis for shipment sizing, 405Decision support tool, 116, 123, 243Decision variables, 102, 498, 514Decision-making, 113Decomposition, 522Delay

costs, 502penalty, 503

Delta replication, 727Demand

characteristics, 141class priority, 527data model, 480forecast error percentage, 346forecasting, 92management accuracy, 69, 491objectives, 55planner, 83planning, 54, 81, 92, 151priorities, 503–504, 526–527, 549, 562process decomposition, 55profile, 512release, 643signal, 90stability, 597tasks, 151under coverage, 723variability, 338, 345

Demand and supply planningalerts, 292cycle, 244

Demand and supply planning (Cont.)overview, 54reporting, 459

Demand Waterfall Analysis app, 745Deployment

heuristics, 286master data, 282optimizer profile, 538strategies, 282–283

Descriptive characteristics, 642Deterministic inventory model, 595Diagnosis group, 266Differences heuristics and optimizers, 499Differentiated planning, 141Direct

delivery, 390shipment, 389–390shipment customers, 387

Disaggregated, 561, 671Discrete

capacities, 522lot sizes, 521mode, 508optimization, 521solver, 510

Distribution, 49plan, 538planning, 93, 104, 247, 281rules, 538

Distribution resource planning (DRP), 612Domino strategy, 560Dual simplex method, 518Dynamic

pegging function, 370relationship, 370

E

Economic order quantity (EOQ), 600curve, 601versus safety stock, 609

Economics equilibrium, 54EDI

DESADV, 445ORDCHG, 445ORDRSP, 445

818

Index

EDI (Cont.)PROACT, 444STPOD, 446

Empowering for success, 124Engineer-to-order product, 37Enhanced product planning functionality

(EPP), 718tasks, 719

Enhancement packages, 673, 703, 710Enterprise service bus (ESB), 752

services, 752Error total (ET), 198ETL (extract transform load), 481, 759Exception driven, 141Exception Management, 78, 292, 330Excess

inventory push, 407supplies, 566

Executive support, 116Expiry quantity, 370Explore Days of Supply app, 745Explore Projected Service Level app, 745Explore Projected Stock Value app, 745Explore Stock Deficits app, 745Explore Stock Overages app, 746Explore Supply Network app, 746Explore Supply Shortages app, 746Explore Uncovered Sales Order app, 746Exponential smoothing, 194Extension workbench (APX), 541External optimizers, 541Extract

APO-DP data, 482APO-SNP data, 484structure, 473

F

Factory distribution network, 513Fair share rule, 284Field mapping, 765FIFO, 370, 656Financial

costs, 461reconciliation, 140

Finite iterative planning, 546

Fiscal year variant, 164Fit/gap analysis, 121Fixed

cell, 259lot size, 604pegging, 548

Forecast, 196accuracy, 722assignment of forecast key figures, 200bias, 723comparison, 268consumption, 373error, 198ex-post forecast, 197extrinsic, 59forecast accuracy KPI, 725interactive, 312intrinsic, 58method, 193–194model framework, 194model parameters, 196netting, 669profile, 199, 266, 312qualitative, 58quantitative, 58result analysis, 205statistical, 193, 738

Form fit function (FFF) class, 391Forward consumption, 379Freshness date, 362Full replication, 727

settings, 728Function module

/SAPAPO/MSDP_MD_SOS_GET, 563EXIT_/SAPAPO/SAPLBOP_SORT_020, 563

Functional specification, 774

G

Generated hierarchy, 352Geographical dispersion, 428Global

asset utilization, 136available-to-promise, 82, 618composition, 120system, 121

Index

819

Global (Cont.)template, 112visibility, 135

Graphical display, 266Groff procedure, 608

H

Hard constraints, 500Hardware sizing, 746Heterogeneous data, 462Heuristics, 100, 499

calculation, 273engine, 274location, 271multi-level, 272network, 272

Hierarchical planning, 104, 349–350APO-SNP customization, 353location hierarchy, 351location product hierarchy, 351master data, 355planning product, 351technical design, 357testing business scenario, 359

Hierarchymaster data, 352structure, 352

High costs, 532Holt's Method, 202Holt-Winters' Model, 203 Horizontal aggregated planning, 523

I

ICF services, 436ICM monitor, 437IDoc, 760

inbound processing, 768ILOG components, 542Implementation

deliverables, 117roadmap, 115, 137

Inboundand outbound exchanges, 751logistics, 26

Inbound (Cont.)staging, 183

Independent forecasting, 621Individual demands, 546Industry benchmark benefits, 128InfoArea, 158InfoCube

create, 186InfoObject, 155, 251

catalog, 158characteristics, 156create, 158key figures, 156technical characteristics, 156time characteristics, 156unit characteristics, 156

Information exchange, 427Initial data transfer, 686Integer variables, 497Integration models, 676Interactive APO-SNP deployment planning,

286Interactive demand planning, 248, 291Interactive optimizer planning, 516Interactive planning alerts, 416Interactive statistical forecasting, 265Interactive supply planning, 269Interchangeability, 314

consume inventory, 392consume inventory until specific date, 396master data, 392, 397planning run, 395

Interior point method, 518Inter-market demand and supply planning,

452Intermittent, 95Internet Communication Manager (ICM), 106,

436Inventory

analysis, 581build, 593control system, 600cost benefit analysis, 582, 598historical analysis, 587holding costs, 532level, 505, 573management, 87, 93

820

Index

Inventory (Cont.)methodology, 575, 581modeling, 594obsolescence, 136overall reduction, 598planning and optimization, 573policy, 143, 579reduction, 575reduction carrying cost, 599stock policies, 584stocking policies quadrant, 585strategies, 581turns, 69, 491un-bundling, 591

Inventory optimization, 575dynamics, 576supply chain application, 578

Inventory turnover, 589Item category, 633, 645

J

J-curve effect, 124Judgmental costs, 532

K

Key figure, 200, 320lock, 180

Kit, 319KMAT

material, 626material type, 621

KPI, 719

L

Labor expenses, 599Lead time, 597Legacy System Migration Workbench

(LSMW), 755, 760, 763advantage, 760loading methods, 760loading process, 761

Level 1 SCOR metrics, 490

Level loading, 144Lifecycle

management, 98planning, 310

Like modeling, 310Linear

optimization, 518programming, 496programming equation, 514regression, 194, 204

LO (logistics) cockpit, 480Load

balancing, 290, 400consolidation, 389data into planning book, 252method, 289planning, 288

Locationaggregation, 670app, 746disaggregation, 671hierarchy, 349master, 211, 225product, 226, 553product master, 211split, 263

Location Product app, 746Logical system, 677Logistics costs, 86Logistics Information System (LIS), 151, 183Lot sizing, 290, 602

optimization, 578optimum prodecures, 606periodic procedures, 605rules, 275static procedures, 602

Lot-for-lot, 603Low-level coding, 274

M

Macro, 175, 216create, 179depot, 178elements, 176events, 179workbench, 355, 392

Index

821

Macro Builder, 175Macro Development Area, 177MAD, 96, 204Maintenance cycle, 710Make-to-order product, 37Make-to-stock production, 374Manual static safety stock planning, 340

SB (quantity-based), 340setting up, 341SM (both quantity- and demand-based), 341SZ (demand-based), 340

Manual time-dependent safety stock planning, 342MB (quantity-based), 343MM (both quantity- and demand-based), 343MZ (demand-based), 343setting up, 343

Manufacturing, 47, 269, 579MAPE, 96, 204Mapping table, 263Master data, 553, 756Master production schedule (MPS), 247, 278Master-derived role concept, 789Material

flow, 121grids, 660master, 624

Material requirements planning (MRP), 608, 718

Mathematicalformulas, 205linear programming, 495

Maturation time, 364, 373Maximum delay, 502Mean absolute deviation (MAD), 198Mean absolute percentage error (MAPE), 198,

722Mean percentage error (MPE), 198Mean square error (MSE), 198Microsoft Excel, 331, 335

add-in, 478Minimum

remaining shelf life, 363Mixed-integer linear programming (MIP), 497Model, 77

initialization, 197parameters, 196

MRP procedures, 608MRPII/DRP, 79Multi-echelon inventory

optimization, 581planning, 611

Multilevel ATP, 619Multi-pickup, 401Multiple linear regression, 96Multi-sourcing business scenarios, 238Multi-stop, 401

N

Navigational attribute, 159Net forecast, 374Network

aggregation, 670design and optimization, 94disaggregation, 358, 671

New product introduction (NPI), 141, 310Nightly planning run, 154Non-delivery penalty, 502Notes management, 258

O

Object dependencies, 630, 632Objective function, 102, 498, 515, 532Object-oriented database, 107Obsolescence, 311ODS, 471OMS objects, 108One number, 32On-time delivery, 136Operational

improvements, 128weekly meeting, 247

Operational data store (ODS), 471, 751Optimal solution, 515Optimization, 495

concept, 496constraints, 530cost factors, 531explanation log, 528–529goals, 498, 530

822

Index

Optimization (Cont.)model input, 530problems, 102scope, 517server, 499

Optimizer, 101Order management, 26, 48

cycle time, 69, 490Order selection option, 554Organization areas, 369Out of the box, 337Outbound

logistics, 26staging, 183

Outlier correction, 267

P

Pallet floor, 291Parallel processing, 797Parameter, 203

/sapapo/clp_drilldown, 441/sapapo/clp_rephead, 440/sapapo/clp_row_wi, 441/sapapo/clp_webbhead, 440/sapapo/clp_webdown, 440/sapapo/clp_webgraph, 439/sapapo/clp_webnote, 439/sapapo/clp_webpivot, 440value, 201

Pareto Principle, 326Pegging, 371, 555, 647Penalty

costs, 502for non-delivery, 503

Percentage remaining shelf life, 364Perfect order fulfillment, 68, 489Performance measures, 125Period

lot sizing, 605review policy, 597split factor, 264

Persistent staging area (PSA), 471Petrochemical supply chain, 569Phase-in profile, 314Phase-in/phase-out modeling, 311Pipeline stock, 339, 592

PIR segment, 376Planned independent requirements, 374Planner’s Home Page, 718Planning, 75–76

book, 170, 214, 733hierarchies, 141horizon, 28, 245horizon and granularity, 83object structure, 161, 319run, 246, 535sales and operations, 93strategies, 373system architecture, 747task structure, 83weekly activities, 84with final assembly, 374with planning product, 375with shelf life, 363without final assembly, 375

Planning area, 164configure, 165new, 320

Planning bookauthorization, 791creation, 309graphs, 260header, 253layout, 248new, 321toolbar, 251

Planning organization, 144options, 146structures, 145

POS forecasting, 426Post-implementation, 119Postponement, 578PP/DS

block planning, 648Preferences, 525Primal simplex method, 518Priorities, 501, 525, 566Pro rata, 169Process chain, 796Procurement

costs, 509planning, 275type, 275

Index

823

Productcharacteristics, 157, 428, 617decomposition, 522discontinuation, 390group hierarchy, 356hierarchy, 255, 662interchangeability, 390segmentation, 327split, 264

Product forecast notification (PFN), 451Production

capacity, 532costs, 86, 503, 506priority, 525version, 380, 630

Production data structure (PDS), 235, 322, 631, 645, 662

Production Planning and Detailed Scheduling (PP/DS), 642orders, 564

Production process model (PPM), 101, 383, 552

Profitability, 128Project phase activities, 117Projected

financial benefits, 129service level, 723wastage quantity, 370

Promotionattribute types, 303characteristics level, 304key figures, 303reports, 308status, 306

Promotion planning, 97, 302interactive book, 306views, 307

Proportional factor, 168, 639Protocol HTTP, HTTPS, and SMTP, 436Prototypes, 117Pull distribution, 284Pull scenario, 282Pull/push

by demands, 284deployment horizon, 538distribution, 283scenario, 282–283

Pull-driven concept, 617

Pull-in horizon, 289, 404Purchasing

costs, 86document shelf life, 367info record, 380

Q

qRFCalert, 692monitor, 693

Qualityinspection stock, 366rate definition, 508usage decision, 366

Query builder, 478Queued remote function call (qRFC), 676Quick Sizer, 746

questionnaire, 747Quick-win

initiatives, 112projects, 136

Quota arrangement, 100, 238, 409

R

Range of coverage, 587Rapid deployment solutions (RDS), 737Recording function, 763Reference

model, 123system, 121

Regional systems, 121Remote function call (RFC), 676Reorder

cycle policy, 347lot size, 596point policy, 347

Re-plan, 79Replenishment

lead time, 346planning, 275procurement, 276

Reports/SAPAPO/CIF_DELTAREPORT3, 691/SAPAPO/CTMDISAGGR, 567

824

Index

Reports (Cont.)/SAPAPO/DP_BOM_LIST, 324/SAPAPO/OM_REORG_DAILY, 565/SAPAPO/RDMCPPROCESS, 705/SAPAPO/RMSNPOPT, 501/SAPAPO/RSDP_CALC_SAFETY_STOCK, 347/SAPAPO/RSNP_SHLF_PROP, 372/SAPAPO/RTSINPUT_CUBE, 481/SAPAPO/TS_LCM_CONS_CHECK, 257, 324/SAPAPO/TS_LCM_PLOB_DELTA_SYNC, 257/SAPAPO/TS_NOTES_DOWNLOAD, 259/SAPAPO/TS_PAREA_INITIALIZE, 321/SAPDMC/SAP_LSMW_INTERFACE, 772RAPOKZFX, 682RCPTRAN4, 685RIMODAC2, 684RIMODDEL, 684RIMODGEN, 683RIMODOUT, 684RIMODSRH, 684RLOADVMI, 447SAPAPO/RCIFQUEUECHECK, 692

Required maximum shelf life, 364Required minimum shelf life, 364Requirement

class, 624types, 374, 624

Resourceallocation, 501capacity, 387, 508disaggregation, 671expansion, 508hierarchy, 356master, 649master data, 532mix balance, 116utilization, 359

Responsiveness, 462Restricted stock, 366Return on working capital, 70, 491RFC communication user (CPIC), 678RICEFW, 756Risk pooling, 579RLT forecast error percentage, 346Rollout preparation, 121Rough-cut production planning characteris-

tics, 143

Routing, 76, 380Rule condition table, 558Rule-based planning, 558

S

Safety stock, 339, 342, 550, 591advanced, 580basic, 580, 595calculation methods, 340penalty, 505planning, 338violation cost, 526

Sales and operations planning, 93, 244capability matrix, 31case study, 30characteristics, 139definition, 28framework, 32goal, 29meeting, 140

Sales ordercustomization, 634history, 191type, 633

SAP APO, 452, 454aggregated planning, 667application layer, 106authorization, 788benefits, 85Core Interface (CIF), 153core planning modules, 81create process chain, 793data conversion using LSMW, 761data extraction process, 474database, 106database model, 156finished goods inventory reduction, 132increased sales, 130macros, 371, 773material cost reduction, 133methodology, 117model, 223phases, 117planning book, 248, 304, 312planning functions, 90

Index

825

SAP APO (Cont.)prerequisite, 116profit optimization, 131promotions, 303quota arrangement, 409rapid deployment solutions (RDS), 737raw material inventory reduction, 133requirement strategy customization, 375resource master, 387roles, 790same-box model, 453SAP ERP add-on, 741–742SAP Fiori apps, 744SAP SCM server, 742solution for AFS, 667technical architecture, 105technical concepts, 675technical landscape architecture, 106TLB, 788transaction data, 687user exits, 776–777

SAP APO Collaborative Planning, 425, 428–429configuration, 435

SAP APO on SAP HANA, 716, 727APO-DP, 718APO-SNP, 718benefits, 717core planning processes, 718decision support, 720deployment, 717SAP Supply Chain Info Center, 721system operations, 720UI and interaction, 718

SAP APO Performance Monitor, 540SAP APO process chain, 791

process type, 792process variants, 792

SAP APO technical upgradeplan phase, 711, 713post, 712post-upgrade phase, 714prepare phase, 711, 713upgrade phase, 712, 714

SAP Basis, 106SAP Business Suite on SAP HANA, 744

SAP BW, 151, 182business content, 484component, 152data mart, 164data staging, 184extraction process, 472extractor, 475layers, 465metrics, 464objects collection, 486open hub service, 751presentation, 465reporting, 465SAP APO, 751staging, 465transactional data, 464transformation, 465upload logic, 481

SAP BW integration scenarios, 467operational data store (ODS), 471planned and actual data, 470planned and actual data SAP APO, 469SAP APO ad hoc reporting, 467SAP BW ad hoc reporting, 468

SAP Duet Demand Planning, 335SAP ERP, 719, 738

AFS integrated solution, 654batch integration, 367plug-in, 676SAP APO add-on, 741user exits, 778

SAP Fiori, 744SAP HANA Studio, 729SAP industry solution, 651SAP Integrated Business Planning (IBP), 612,

802SAP liveCache, 97, 152, 161, 235, 447, 499,

569, 728anchor inconsistency, 324consistency, 182database consistency, 688inspector program, 748object memory system, 109object-oriented database, 107order, 210, 263order data, 107SAP APO on SAP HANA, 717

826

Index

SAP Notes1057389 - interchangeability, 3921358057—TLB, 292373756 - BW data implementation, 475391018 - Batch integration, 366514947—TLB, 292526835 - ITS installation, 436710198—TLB, 292720121- Collaborative Planning, 436751392 - Batch integration, 366816973 - Internet Services, 437932917 - Collaborative Planning, 438

SAP Process Integration (PI), 451, 752SAP Quality Management (QM), 365SAP SCM Queue Manager, 688, 702SAP Supply Chain Info Center, 717, 720–721

dashboards, 722data replication, 727deployment, 727general settings, 733views, 726

SAP Supply Chain Management (SCM), 799SAP Supply Chain Performance Management

(SCPM), 67, 460capabilities, 462

SAP Supply Network Collaboration (APO-SNC), 449

Scheduling, 75–76, 104Scope activities, 738SCOR

Level 1 to Level 2, 492Level 2 to Level 3, 493performance attributes, 488scorecard metrics, 489

Search strategy, 551Seasonal

linear regression, 204model, 95No Trend Model, 203pattern, 317, 668planning, 75, 315, 667trend, 95trend basic formulas, 206

Segregation of duties (SOD), 789Selection profile, 249Serialization, 676

Servicefactor, 346level percentage, 346parts planning, 600

Setup duration, 648Shelf life, 362–363

alerts, 372business scenario, 371class, 368expiration date (SLED), 365key figures, 369master data, 363Planning, 362propagation, 372transaction data, 364

Shipment sizing, 405Shipping strategies, 401Short-term wins, 125Simulation

mode, 297plan, 128, 297run, 559

Single exponential smoothing, 201Sizing framework, 746SKU level, 567Slack, 593SLT, 727SNP optimizer, 495, 499, 515–516, 520

constraints, 500costs, 501–502, 532input log, 509, 524output logs, 524profiles, 510screen, 517solution log, 520solution method, 523

Soft constraints, 498, 500Solution method, 518Solvers, 78, 100

Capable-to-Match, 103optimization, 101

Source system, 184Sourcing, 47

policies, 579Square root of mean square error (RMSE), 198Stacking factor, 290Standard business content, 485

Index

827

Statistical forecasting, 95Stochastic inventory model, 595Stock

balance macro, 274balancing, 247, 407build, 593coverage, 723KPI, 725on hand (shelf life), 370product, 37requirement list, 665type, 366

Stockout, 578situations, 407

Storagebucket profile, 164–165costs, 502, 505inventory costs, 534

Straight loading, 290, 400Strategic

group, 624metrics, 489planning, 28

Strong user involvement, 116Subcontracting, 103, 379

master data, 380planning book, 383SAP APO master data, 381transactions, 384

Substitution key figures, 392Success metrics, 113Super bill of materials (BOM), 629Super routing, 623, 630Supersession chain, 390Supply

alerts, 154, 410allocations, 529categorization, 550characteristics, 142limits, 550network planning, 82, 93, 99objectives, 61plan feasibility, 232process decomposition, 62profile, 512projection, 723shortage (shelf life), 370

Supply (Cont.)signal, 90variability, 338, 345workflow, 269

Supply allocations, 529Supply chain

agility, 488assessment, 114asset management, 488configuration, 428constraints, 90, 538context, 90costs, 488, 538definition, 26, 99end-to-end business processes, 26Engineer, 239execution, 27flexibility, 462maturity model, 65metrics, 68, 114modeling, 77, 153, 223monitoring, 93, 105network, 79–80objectives, 26Operation Reference (SCOR), 460, 487pull, 64push, 64reliability, 488responsiveness, 488scope, 113transformation, 244transformation approach, 136transformation planning, 135transformation program, 135types, 44viewer, 569vision, 116

Supply Chain Cockpit (SCC), 82, 105, 294, 418–419, 421–424

Supply Chain Operations Reference (SCOR)balancing supply chain, 42business models, 37communication, 43gathering requirements, 40gathering resources, 41modeling, 49overview, 33performance metrics, 36

828

Index

Supply Chain Operations Reference (SCOR) (Cont.)process categories, 36process elements, 38process levels, 34process types, 35scorecard metrics, 68supply chain, 38

Supply chain typesconverging structure, 45diverging structure, 45late customization structure, 45pipeline structure, 45

Switch Framework, 673Synchronized supply, 428Synchronous communication, 676System architecture, 138System Landscape Transformation (SLT), 727

T

Tactical planning, 28Target stock level, 342, 608Task structure, 83Technical enhancements, 755, 772

Alert Monitor, 788APO-DP to APO-SNP release, 787APO-SNP PDS, 780APO-SNP planning book, 781APO-SNP TLB interactive, 788CIF enhancement, 773CTM demand prioritization, 785product master, 775SAP APO user exits, 782SAP BW, 786SNP heuristics, 785transactional data, 777

Technical integration with non-SAP applica-tions, 750

Technology strategy, 114Template rollout, 120Time bucket, 32

profile, 171Time decomposition, 522Time series data management (TSDM), 451Time-based disaggregation, 169

type, 167

Totalcost curve, 601shelf life, 363supply chain management cost, 491

Traditional supply chain, 427Transaction

/INCMD/UI, 314, 392, 397/SAPAPO/ADVM, 175, 216, 355, 392, 608,

782/SAPAPO/AMON_SETTING, 294/SAPAPO/AMON1, 294, 331, 410/SAPAPO/ATYPES_SDP, 293/SAPAPO/C2, 691/SAPAPO/C5, 292, 705/SAPAPO/CC, 689/SAPAPO/CCR, 780/SAPAPO/CFM_ANALYSIS, 330/SAPAPO/CFM_FC_REL, 330/SAPAPO/CFM_POWL, 330/SAPAPO/CFM_WFALL, 330/SAPAPO/CLPISDP, 441/SAPAPO/CONSCHK, 241/SAPAPO/CP1, 687/SAPAPO/CP2, 687/SAPAPO/CQ, 702/SAPAPO/CSNP, 509/SAPAPO/CTM, 552, 670/SAPAPO/CTM10, 566/SAPAPO/CTMAPLOG, 569/SAPAPO/CTMCUST, 555/SAPAPO/CTMMSEL, 553/SAPAPO/CTMORDSEL, 554/SAPAPO/CTMSCPR, 564/SAPAPO/CTMTSTR, 554, 567/SAPAPO/CURTO_EDIT, 237, 506/SAPAPO/CURTO_SIMU, 645/SAPAPO/IPM01, 637/SAPAPO/LLC, 274/SAPAPO/LOC3, 381, 566/SAPAPO/MAT1, 226, 363, 382, 505, 566,

643/SAPAPO/MC01_BBD, 649/SAPAPO/MC62, 191, 323–324, 638/SAPAPO/MC7A, 264/SAPAPO/MC7B, 264/SAPAPO/MC8S, 263/SAPAPO/MC90, 210, 263, 644/SAPAPO/MC96B, 199, 312

Index

829

Transaction (Cont.)/SAPAPO/MP31, 303/SAPAPO/MP32, 304/SAPAPO/MP33, 303/SAPAPO/MP39, 308/SAPAPO/MP40, 303/SAPAPO/MP41A, 308/SAPAPO/MP41B, 308/SAPAPO/MSDP_ADMIN, 181, 200, 208,

210, 213, 317, 319–320, 451, 477, 636/SAPAPO/MSDP_FCST1, 311/SAPAPO/MVM, 224/SAPAPO/OM_LC_UPGRADE_70, 712/SAPAPO/OM_LVC_OBJECTS, 748/SAPAPO/OPTEXPLAIN, 523, 528/SAPAPO/PBSTDOBJ, 503/SAPAPO/PERMON, 540/SAPAPO/PPM_CONV, 323/SAPAPO/QUAN, 532/SAPAPO/RBA04, 558/SAPAPO/REL_TO_OLTP, 687/SAPAPO/RELHSHOW, 403, 670, 672/SAPAPO/REPL, 730/SAPAPO/REPL_DELTA, 730/SAPAPO/REPL_MODEL, 728/SAPAPO/RES01, 233, 280, 382, 508, 532/SAPAPO/RLGCOPY, 257/SAPAPO/RRP3, 365, 644, 646/SAPAPO/SCC_TL1, 237, 382, 389, 404, 516/SAPAPO/SCC02, 294, 419/SAPAPO/SCC03, 323, 383/SAPAPO/SCC07, 240/SAPAPO/SDP_ADMIN, 473/SAPAPO/SDP_EXTR, 476, 478/SAPAPO/SDP_PAR, 797/SAPAPO/SDP_SEASON, 316–317, 668/SAPAPO/SDP110, 292/SAPAPO/SDP8B, 172, 215, 309, 321–322,

355, 384, 641, 782/SAPAPO/SDP94, 192, 248, 306, 314/SAPAPO/SNP04, 290/SAPAPO/SNP05, 279/SAPAPO/SNP06, 672/SAPAPO/SNP08, 669/SAPAPO/SNP09, 671/SAPAPO/SNP10, 372/SAPAPO/SNPCOSF, 507/SAPAPO/SNPOPLOG, 499, 523

Transaction (Cont.)/SAPAPO/SNPTLB, 290, 403/SAPAPO/SUPCAT, 564/SAPAPO/TL1, 566/SAPAPO/TLBPARAM, 238/SAPAPO/TLBPRF, 238, 288, 388, 399/SAPAPO/TR30, 264/SAPAPO/TR32, 212/SAPAPO/TSCUBE, 192/SAPAPO/VERCOP, 298/SAPAPO/VERMER, 298/SAPCND/AO11, 558/SCA/FCST_OUT, 4511435310, 262388260, 268BAPI, 752BD50, 686BD52, 686BDCP, 686BMBC, 365C223, 380, 630, 662CA01, 380, 630CFC9, 226, 232CFM1, 366CFM2, 366CL02, 369CMOD, 778CR02, 232CRC1, 380CS01, 629, 661CT04, 369, 626, 660CU50, 629data, 756data CIF enhancement, 779J3AH, 660LSMW, 761, 768MASSD, 227MC40, 583MC41, 583MC44, 590ME11, 380ME2O, 384ME52N, 665MIGO, 365MM02, 363, 627MMBE, 665O1CL, 369PDS_MAINT, 506, 780

830

Index

Transaction (Cont.)RSA1, 180, 184, 485, 787RSD1, 159RSPC, 189, 794RSPCM, 796SBIW, 185SE11, 563SE38, 208SE80, 437SFW5, 710, 743SICF, 330, 436SM35, 767SMICM, 437ST14, 540SWDD, 434VA01, 631

Transformationframework, 114goals, 126process, 113

Transport Load Builder (TLB), 155, 214, 288, 290, 399constraint parameters, 238load optimization, 400loading method, 400objectives, 399planning book, 403profile, 388, 399selection profile, 290shipment sizing configuration, 406shipments, 291, 404

Transportation, 507–508, 516lane block indicator, 409lane priority, 525lanes, 237matrix, 514network, 578network model, 501relevant hierarchy, 403zone, 401

Transportation Lane app, 746Tree diagram shareholder ROA, 128Trend model, 95

U

Univariate forecasting, 193–194, 200Un-pegged supplies, 566

Unrestricted stock, 366Upgrade process, 711Upside supply chain flexibility, 69, 491Upsizing and downsizing, 399Urgency for change, 124User exits, 773

macro, 178, 782User settings, 254

V

Value stream mapping, 52Variant class, 628Variant configuration, 620, 622

characteristics, 626configuration profile, 631CU43, 631customizing sales orders, 633object dependencies, 632super BOM, 629super routing, 630variant class, 628

Variant selection, 249Vendor capacities, 379Vendor management replenishment, 428Version management, 297Vertical aggregated planning, 522Virtual

cubes, 469location, 349

Visibility, 462Vision, 126Visualizing alerts, 293VMI, 214

benefits, 443concepts, 443process flow, 444scenario, 445–446

W

Warehouse capacity, 385Weekly

cycle, 246planning activities, 246

Weighing factor, 519

Index

831

Weighted average cost of capital (WACC), 130Work area, 240Work center master, 380Workflow

builder, 434CLP_ALERTS, 434CLP_PLANNING, 434customizing, 769

X

XML PROACT message mapping, 448


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Sandeep Pradhan is an SAP solution architect in the supply chain management field and has more than 17 years of professional experience. He specializes in sup-ply chain application advisory services and has achie-ved results by helping clients understand, architect, select, and implement the SAP supply chain solutions required to run their businesses. In his various roles

(project manager, solution architect, functional consultant, supply chain manager), he has been responsible for providing thought leadership in supply chain strategy, business processes transformation, technology architecture, and business integration. He has worked on numerous full lifecycle SAP APO-Demand Planning and Supply Network Planning implementations from the discovery phase through the implementation phase.

He specializes in SAP supply chain execution (SAP TM, EWM, EM) as well as SAP supply chain planning modules (SAP IBP, SAP APO) in SAP HANA enviroments. Sandeep holds an MBA from Monash University, Australia, and is also author of the book Implementing and Configuring SAP Event Management (SAP PRESS, 2010) and co-author of Global Available-to-Promise with SAP: Functionality and Configuration (SAP PRESS, 2011). You can contact Sandeep Pradhan at [email protected].

Sandeep Pradhan




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