1. High-Level OP Planning and Demand Management EGN 5622 Enterprise Systems Integration Spring, 2015

2. Production Planning & Execution
Version 1.0
Production Planning & Execution
January 2007
Demand Management
Forecasting
Sales & Operations Planning
Sales Inf. System
CO/PA
MPS
MRP/CRP
Manufacturing Execution/SFC
Order Settlement
Procurement Process
Tactical Planning
Detailed Planning
Manufacturing Execution
The Rushmore Group, LLC

3. High-Level OP Planning
ECC 6.0
January 2008
High-Level OP Planning
Planning activities:
CO/PA
Forecasting
Sales and Operations Planning
Planning strategy for a product
Demand Management
Demand management feeds to MPS and in turn MRP/CRP
© SAP AG and The Rushmore Group, LLC 2008

4. Operations Planning & Execution
Version 1.0
January 2007
Operations Planning & Execution
Major Players:
Tactical Planning (at corporate level)
COO, CFO, Controller, Sales & Marketing, Product Line mangers, Production Planner
Detailed Planning (at plant level)
Production Planner/Scheduler, MRP Controller, Capacity Planners
Execution (at shop floor level)
Production Line Workers, Shop Floor Supervisors
Sales Info
Forecasting
CO/PA
Sales OP Planning
Tactical Planning
Demand Management
Detailed Planning
MPS
MRP/CRP
Manufacturing Execution/SFC
Procurement Process
Order Settlement
Execution
The Rushmore Group, LLC

5. Costing-Based CO-PA
CM: profit margin

6. Costing-Based CO-PA
CO-PA is profitability analysis, based on cost- of-sales accounting.
CO-PA can be viewed as a cube of 3 dimensions (representing product, country, and customer)
CO-PA data are collected from various areas, such as
sales orders or billing data from SD,
production costs and variance from PP, and
values of overhead cost controlling from controlling.

7. Pricing and Costing for mfg. goods
Cost components
Materials Costs
Labor costs
Equipment costs
Strategies to reduce costs
Lean manufacturing
Systems approach

8. Sales and Operations Planning (SOP)
Version 1.0
January 2007
Sales and Operations Planning (SOP)
Information Origination
Sales
Marketing
Manufacturing
Accounting
Human Resources
Purchasing
Intra-firm Collaboration
Institutional Common Sense
A more recent proposal to fix forecast errors is to use collaboration. The idea is that if different parts of the supply chain collaborate on a common forecast and everyone plans based on that single forecast; then there is little need for one part of the chain to hedge based on the uncertainty of what is done in other parts of the chain. Intra-firm collaboration, you would think, would be common place – seems that a little common sense would dictate that everyone in a firm come together with a common set of forecast figures. But this is rarely the case. Marketing has a set of forecasts, so too does operations. Sales has their forecast and it’s possible that for budgeting purposes Finance uses still another. The advancement of enterprise resource planning (ERP) systems is helping ensure that there is only one forecast, based upon the principles of a single data repository used by all areas of the enterprise.
Forecasts affect most functional areas of the firm and are the starting point for resource allocation decisions. For example, manufacturing must plan production on a day to day basis to meet customer orders, while purchasing needs to know how to align supplier deliveries with the production schedules. Finance needs to understand the forecasts so that the proper levels of investment can be made in plant, equipment, and inventory and so that budgets can be constructed to better manage the business. The marketing function needs to know how to allocate resources for various product groups and marketing campaigns. Forecasts also determine the labor requirements required by the firm so that the human resources function can make proper hiring and training decisions when demand is expected to grow.
The Rushmore Group, LLC

9. Master Data - Product Groups
Version 1.0
January 2007
Master Data - Product Groups
Aggregate planning that group together materials or other product groups (Product Families)
Multi- or Single- Level Product Groups
the lowest level must always consist of materials
Bikes
Touring
Mountain
24 Speed
18 Speed
Red 24T
Blue 24T
Red 24M
Blue 24M
Aggregate forecasts of a group of similar products are generally more accurate than individual forecasts of the individual products that make up the group.
The Rushmore Group, LLC

10. Planning Levels Bikes Touring 24 Speed 18 Speed Red 24T Blue 24T
Version 1.0
Planning Levels
January 2007
Bikes
55%
Touring
45% Mountain
70%
24 Speed
30%
18 Speed
40%
60%
50%
Red 24T
Blue 24T
Red 24M
Blue 24M
Planning at Product Group Level
Planning at Material Level
The Rushmore Group, LLC

11. Version 1.0
Demand Management
January 2007
Link between Strategic Planning (SOP) & Detailed Planning (MPS/MRP)
The results of Demand Mgmt is called the Demand Program, it is generated from our independent requirements – PIR (Planned IR) and CIR (Customer IR)
Product Groups
Bikes
45% Mountain
55%
Touring
Disaggregation
Aggregating forecasts across multiple items reduces forecasting errors. A clothing store, for instance, might be able to estimate within a pretty narrow range what the demand will be for men’s dress shirts. But when that store tries to estimate the demand for individual styles, colors, and sizes of shirts, the accuracy of their forecasts will be considerably worse. Firms handle this kind of forecasting problem usually in one of three ways; they either forecast from the bottom up, from the top down, or they start in the middle and work both up and down. The “top down” forecast essentially estimates total sales demand and then divides those sales dollars level by level until the stock keeping unit (SKU) is reached. The “bottom up” method, as one might expect, starts with forecasts at the SKU level and then aggregates those demand estimates level by level to reach a company–level forecast. Another method, one might call the “in-between” method, starts forecasts at the category level (like men’s dress shirts), and then works up to determine store sales and works down to divide up the forecast into styles, colors and SKUs.
30%
18 Speed
70%
24 Speed
40%
18 Speed
60%
24 Speed
40%
Red 24M
60%
Blue 24M
50%
Red 24T
50%
Blue 24T
Material
The Rushmore Group, LLC

12. Demand Management Forecast Sales Planned Independent Requirements
Version 1.0
Demand Management
January 2007
Forecast
Sales
Planned
Independent
Requirements
Customer
Independent
Requirements
Demand
Program
MPS / MRP
The Rushmore Group, LLC

13. Transfer from High Level to Detailed Planning
Version 1.0
January 2007
Transfer from High Level to Detailed Planning
Bikes
55%
Touring
45% Mountain
70%
24 Speed
30%
18 Speed
40%
60%
50%
Red 24T
Blue 24T
Red 24M
Blue 24M
Demand Planning Data
Planning at Material Level
Disaggregation
Planned Independent Requirements
At Material and Plant Level
Transfer
Operative Planning
Data
Planning at Group Level
The Rushmore Group, LLC

14. Creation of The Demand Program Production Plan
ECC 6.0
January 2008
Creation of The Demand Program Production Plan
The result of Demand Management is the demand program
Data Elements of the Production Plan
Time Buckets
Sales
Production
Stock levels
Days supply
January 2008
© SAP AG - University Alliances and The Rushmore Group, LLC All rights reserved.
© SAP AG and The Rushmore Group, LLC 2008

15. Enterprise Strategic Planning SAP Implementation

16. Version 1.0
Planning Strategies
January 2007
Planning strategies represent the business procedures for
Planning of production quantities, and
Dates
SAP offers a range of PP strategies
From those for MTS (Make-to-stock)
To those for MTO (Make-to-order)
Planning strategies represent the business procedures for the planning of production quantities and dates. A wide range of production planning strategies are available in the SAP R/3 System, offering a large number of different options ranging from pure make-to-order production to make-to-stock production. Depending on the strategy you choose, you can:
Use sales orders and/or sales forecast values to create the demand program
Move the stocking level down to the assembly level so that final assembly is triggered by the incoming sales order
Carry out Demand Management specifically for the assembly
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

17. Version 1.0
Planning Strategies
January 2007
Multiple types of planning strategies based upon environment
Make-To-Stock
Make-To-order
Driven by sales orders
Configurable materials
Mass customization of one
Assembly orders
Planning strategies represent the business procedures for the planning of production quantities and dates. A wide range of production planning strategies are available in the SAP R/3 System, offering a large number of different options ranging from pure make-to-order production to make-to-stock production. Depending on the strategy you choose, you can:
Use sales orders and/or sales forecast values to create the demand program
Move the stocking level down to the assembly level so that final assembly is triggered by the incoming sales order
Carry out Demand Management specifically for the assembly
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

18. Planning Strategy for Make-to-Stock
Version 1.0
January 2007
Planning Strategy for Make-to-Stock
Planning takes place using Independent Requirements
Sales are covered by make-to-stock inventory
MTS Strategy Types in SAP
10 – Net Requirements Planning
11 – Gross Requirements Planning
30 – Production by Lot Size
40 – Planning with Final Assembly
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

19. Planning Strategy for Make-to-Order
Version 1.0
January 2007
Planning Strategy for Make-to-Order
Planning takes place using Customer Orders
Sales are covered by make-to-order production
MTO Strategy Types in SAP
20 – Make to Order Production
50 – Planning without Final Assembly
60 – Planning with Planning Material
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

20. Forecasting set up in SAP
Version 1.0
Forecasting set up in SAP
January 2007
Forecasting Models
Trend
Seasonal
Trend and Seasonal
Constant
Selecting a Model
Automatically
Manually
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

21. Trend-Seasonal Forecast based on Historical Data
Version 1.0
January 2007
Trend-Seasonal Forecast based on Historical Data
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

22. Sales and Operations Planning (SOP)
Version 1.0
January 2007
Sales and Operations Planning (SOP)
Flexible forecasting and planning tool
Usually consists of three steps:
Sales Plan
Production Plan
Rough Cut Capacity Plan
Planned at an aggregate level in time buckets
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

23. Transfer SOP to Demand Management
Version 1.0
January 2007
Transfer SOP to Demand Management
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

24. Demand Management Version 1.0 January 2007 The Rushmore Group, LLC
January 2007 (v1.0)
© 2007 by SAP AG. All rights reserved. SAP University Alliance. The Rushmore Group, LLC
The Rushmore Group, LLC

25. Lab 1: (Due date: 1/30/2015) Display Product group
Review work center and assigned capacity
Create consumption values (forecast) for finished products
Create sales and operations plan (SOP)
Check stock/requirements list
Transfer SOP to demand management
Review demand management
Run MPS with MRP
Review stock/requirement list