GitaCloud SAP IBP for Inventory Webinar May 25th 2018

1© 2018 GitaCloud, Inc. All Rights Reserved.
SAP IBP for Inventory Webinar
GitaCloud Webinar Series 2018

Moderator Introduction
• Welcome to this webinar focused on IBP for Inventory 1805 release
• This webinar is brought to you jointly by GitaCloud, SAP, and Demand Driven Institute
• All attendee microphones will stay muted
Webinar Moderator: Guenter Schmidt – Principal, GitaCloud
• 25+ years implementing and supporting SAP Supply Chain solutions in Europe, North America and Asia
• Expertise in Semiconductor / High-Tech, Aerospace, innovative and non-mainstream use-cases
• ex-Broadcom Sr. Director Business Transformation and Sr. Director IT, responsible for SAP ecosystem
• ex-TriQuint Semiconductor IT Applications Director, IT owner of Response Planning Processes

Before we begin

Our Speakers
Chad Smith – Partner, Demand Driven Institute
• Co-Founder and Partner at the Demand Driven Institute. Fully involved in operations, marketing and product
development as well as speaking engagements throughout the world.
• Co-author of Demand Driven Material Requirements Planning and several other books
• Nearly 20 years of implementation experience with organizations including Unilever, Siemens, Intel and Boeing.
• Began career working for and then with Dr. Eli Goldratt, author of The Goal.
Beatrice Hulde – SCM Solution Management, SAP America
• Solution Owner for SAP IBP for inventory
• Digital Supply Chain specialist with a focus on Integrated Business Planning
• Several years of expertise in SAP IBP, especially also S&OP and Supply Chain Control Tower
• Working with customers from across the Globe and all industries
Ashutosh Bansal – President & CEO, GitaCloud
• Leading GitaCloud across General Management, Sales, Marketing, and Strategy functions.
• SCM/IBP SME. With SAP IBP solution since its inception. Ashutosh has led sales & delivery for multiple SCM/IBP
engagements globally.
• 25 years of SAP Implementation Experience. Leadership roles at PwC, IBM, and SAP.
• Ashutosh blogs actively on SCM/IBP topics at LinkedIn (12K+ followers)

Agenda
IBP for
Inventory
Overview
IBP for Inventory Showcase Wrap-up,
Q&A
Kick-off
5 min 15 min 35 min
Guenter
Schmidt
Beatrice
Hulde
Ashutosh Bansal All
Demand Driven
MRP Overview
20 min
Chad Smith
15 min

CUSTOMER
Beatrice Hulde, IBP SolutionManagement
May 2018
SAP Integrated Business Planning
for inventory

Legal Disclaimer
The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of
SAP. This presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP
has no obligations to pursue any course of business outlined in this document or any related presentation, or do develop or
release any functionality mentioned therein. This document, or any related presentation and SAP´s strategy and future
developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at
anytime for any reason without notice. The information in this document is not a commitment, promise or legal obligation to
deliver any material, code or functionality. This document is provided without a warranty of any kind, either express or implied,
including but not limited to, the implied warranties of merchantability, fitness for particular purpose, or non-ínfringement.This
document is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or
omissions in this document, except if such damages were caused by SAP´s willful misconduct or negligence.
All forward-looking statements are subject to various risks and uncertainties that could actual result to differ materially form
expectations. Readers are cautioned no to place undue reliance on these forward-looking statements, which speak only as of
their dates, and they should not be relied upon in making purchasing decisions.

What Problems Are We Solving?
Business Volatility
Today, companies are facing increased supply chain risk due to economic uncertainty, escalating
customer expectations, demand volatility, and supply variability. To remain competitive, they must
improve their ability to plan, analyze, and collaborate to help ensure long-term growth and profitability.
Consequence
▪ Too much inventory
▪ Not enough inventory
▪ Right inventory, wrong place
Finance
Customers
Planners

But, this is not easy!
Deploy inventory targets across the supply chain,
meeting service level objectives at the lowest cost
Customer challenge:
Eliminate excess inventory and at the same time improve service

SUPPLY
CHAIN
How much inventory do I need
at my Distribution Center?
How much inventory do I need
at my Manufacturing location?
Service level targets
Forecast
Forecast error
Consistently over/under forecasting (bias)
Intermittent demand
Outlier sales or forecasts
Multiple service levels and inventory thresholds
Seasonality/promotions
Internal and external demand
DEMAND
Lead times
Lead-time uncertainty
Internal service levels
Schedule attainment variability
Production/distribution batch sizes
Supply reliability
Capacity restrictions
Frozen production/planning periods
Multiple supply sources
SUPPLY
What makes this difficult to do

With increasing supply chain complexity…
 Supplier
s
 Customer
s
…these factors multiply

What does IBP for inventory accomplish for the end-to-end supply chain?
90% 100%
Inventory($)
92% 94% 96% 98%
Customer Service Level (%)
Optimal inventory Company current performance
Achieve the Right Balance Between Service
Levels and Inventory Investment
60%
40%
20%
0%
-20%
-40%
-60%
DecreaseIncrease
Fix the Mix of Inventory!

SAP Integrated Business Planning for inventory prescribes inventory activity
to maximize profit while buffering uncertainty
How about here?
How much
inventory here?
Here?

Unified Platform & Integrated Processes
SAP HANA
Supply Chain Control Tower
Exception Handling and Business Network Collaboration
Sales & Operations
Strategic and Tactical Decision Processes
Demand
Demand Sensing,
Statistical
Forecasting &
Consensus Planning
Inventory
Multi-Stage
Inventory
Optimization
Response & Supply
Allocations &
Deployment
Planning,
Order Rescheduling
Unconstrained &
Constrained
Supply Planning

New Generation of Supply Chain Planning from SAP
State-of-the-Art Architecture based on SAP HANA
One Integrated Planning Model
Real-time
planning and
what-if scenario
simulation
Embedded social
collaboration
platform
SAP JAM
Integrated
business planning
SCP processes
Real-time insight,
monitoring &
alerting
Smart algorithms
incl. machine
learning
Simplified User
Experience with
SAP Fiori and
Microsoft Excel
Sales & Operations Planning
Supply Chain Control Tower
Demand Inventory
Planning Optimization
Response,
Deployment &
Supply Planning

Integrated Business Planning, powered by HANA
A single data model to swiftly drive collaboration and action in your business
• Inventory: Master Uncertainty, drive S&OP decisions to the Planners
- Efficiently position inventory to best absorb forecast error, demand variability and supply
uncertainty
- Multi-echelon (multi-stage) inventory optimization to solve the science of postponement
- Drive S&OP decisions to inventory target recommendations forPlanners
 Sales and Operations: Monthly and Weekly Planning
- Balance demand and supply while providing organizational visibility and alignment
- What-if scenarios, using “real time” information
- JAM embedded communication, and analytics
• Supply Chain Control Tower: Visibility
- Achieve end-to-end visibility in the extended supply chain
- ŸIntegrate Data from various Systems
- ŸDrive visibility and action with configurable Analytics & Alerts and Case Management
• Demand: Demand analytics, demand sensing. Forecast Better
- Demand Sensing (predict and reforecast, pattern recognition)
- Forecasting statistical techniques
- Collaborative Demand Planning
• Supply and Response: Master supply planning and response intelligence
- Plan production, procurement, and distribution
- Respond to daily disruptions through what-if analysis to change supply plans and reschedule demand
- Manage allocations where supply is scarce

What are the 3 key differentiators for
SAP Integrated Business Planning for inventory?
Multi Stage Inventory
Optimization
Maximum working-
capital efficiency to
meet service level
targets
Complete Scalable
Model
Demand, supply
chain, and financial
model at aggregate &
detailed levels
Supply
FinanceDemand
S S S
C C C
S S S
C C C
Executive
Review &Real-
Time Analytics
Sales and
Marketing
Forecasting
Consensus
Demand
Planning
Revenue &
Profit Impact
Inventory
TargetSetting
& Projections
Material &
Capacity-
Constrained
Planning
Real-Time What-if
Scenario Planning
Real-time scenarios
and simulation on
entire model

Inventory positioning in network Inventory optimization
‘What if’ analysis on inventoryDrivers of inventory
SAP Integrated Business Planning for inventory
Sample Use Cases

SAP IBP for inventory – sample process flow
Model
Assumptions
• Products
• Demand
Forecast
• Service Targets
• Supply Chain
Network
• Inventory
Policies
• Planning
Horizon
• Owner:
Business
Function
Master Data
Input
• Cleansing
• Review
• Integration
• Frequency:
Monthly
• Owner:
IT/Business
Function
IBP for
inventory
• Run Forecast
Error Operator
• Run Multi-
Stage
Optimization
Operator
• Run Inventory
Components
Operator
• Frequency:
Daily, Weekly,
or Monthly
• Owner: IT
Finalize
Inventory
Plan
• Approve and
communicate
final inventory
plan
• Integrate
output results
to ERP system
• Frequency:
Daily, Weekly,
or Monthly
• Owner:
Business
Function
 Objective: Calculate safety stock proposals for all SKU/Location combinations in the network.

Agenda
IBP for
Inventory
Overview
Q&A
Kick-off
5 min 15 min 35 min
Guenter
Schmidt
Beatrice
Hulde
Ashutosh Bansal All
Demand Driven
MRP Overview
20 min
Chad Smith
15 min

An Introduction
All contents © copyright 2018 Demand Driven Institute, all rights reserved.

Material Requirements Planning
“As this book goes into print, there are some 700 manufacturing
companies or plants that have implemented, or are committed to
implementing, MRP systems. Material requirements planning has
become a new way of life in production and inventory management,
displacing older methods in general and statistical inventory control in
particular. I, for one, have no doubt whatever that it will be the way of life
in the future.” Orlicky 1975
Joe Orlicky
Features:
• Time Phased Planning
• Level by level BOM explosion
• Dependent demand planning
Benefits:
• Component synchronization
• Reduction in inventory
• Improved priorities
• MRP did become THE way of life for planning.
• It was conceived in the 1950s with the
prevalence of computers.
• It was codified in the 1960s by a small group of
practitioners.
• It was commercialized in the 1970s
• By 1990 most manufacturers of even modest
scale had an MRP system
.

Supply Chain Characteristics 1965 Today
Supply Chain Complexity Low High
Product Life Cycles Long Short
Customer Tolerance Times Long Short
Product Complexity Low High
Product Customization Low High
Product Variety Low High
Long Lead Time Parts Few Many
Forecast Accuracy High Low
Pressure for Leaner Inventories Low High
Transactional Friction High Low
Complex and Volatile is the “New Normal”
Conventional planning rules have not
appreciably changed since the 1960s.
MRP still plans today the way it did 50
years ago!
Today’s supply chains look VERY different
from 1960’s supply chains when
conventional planning rules were
formulated but…
.

The New Normal and Inventory Implications
Supply chains have elongated
and fragmented while customer
tolerance times have dropped
dramatically.
This disparity means holding
stock at some strategic point is a
must to keep and/or grow sales.
Also, there are more products
with shorter life spans to
manage - many use common
components and resources.
This means managing stock
positions effectively is a must for
effective capital and resource
management.
This also means that planning
horizons are more remote from
actual demand realization
(longer range forecast).
This also means that detailed
item level forecasting is much
more difficult.
How is the conventional approach faring with all of this?
The three rules of forecasts:
1. They start out wrong
2. The longer the range, the
more wrong they are
3. The more detailed, the
more wrong they are
.

Conventional Inventory Management Effects
We know there are two universal
points with regard to inventory.
Between these points there is an
optimal range to maintain.
Too MuchToo Little
A B
0
Optimal RangeWarning Warning
.

Conventional Inventory Management Effects
Most companies exhibit a “bi-modal
distribution” – most of the inventory
is either too low or too high
90% of companies report this issue!
Too MuchToo Little
#ofpartsorSKU
0
With every MRP run an oscillation
effect often occurs in which
inventory quickly moves from one
distribution to the other.
Optimal RangeWarning Warning
A B
.

Three Bottom Line Effects to Companies:
1. Chronic Shortages
2. Excessive Inventory
3. High Expedite Expenses & Waste
But the real problem
is at a higher level!
.

The Collective SCM Problem
Bull-Whip Effect: “An extreme change in the supply position upstream in
a supply chain generated by a small change in demand downstream in
the supply chain. Inventory can quickly move from being backordered to
being excess. This is caused by the serial nature of communicating
orders up the chain with the inherent transportation delays of moving
product down the chain.” (APICS Dictionary, 14th Edition)
End Item
AssemblerFoundry Component
Sub-
Assembler
Demand Signal Distortion
Supply Continuity Variability
Transference AND
amplification of variability in
BOTH directions.
A true solution must deal with
demand AND supply distortion
together.
The more parts to the supply
chain – the worse the effect!
.

Demand Driven MRP
A method to model, plan and manage supply chains to protect and
promote the flow of relevant information and materials. DDMRP uses
strategic decoupling points to drive supply order generation and
management throughout a supply chain.
Position, Protect and Pull
Material
Requirements
Planning
(MRP)
Distribution
Requirements
Planning
(DRP)
Lean
Theory of
Constraints
InnovationSix Sigma
First articulated in 2011 by the
Demand Driven Institute after
15 years of research and
extensive application.
Through innovation critical
planning needs are fused with
mainstream improvement
disciplines based on FLOW.
.

The Five Components of DDMRP
Strategic Decoupling
Buffer Profiles and
Levels
Demand Driven
Planning
Position
1
Protect
2 3
Pull
4 5
Dynamic
Adjustments
Visible and
Collaborative
Execution
.

Position – Strategic Decoupling
Strategically places decoupling points of inventory
within the product structure and supply chain.
1
This stops the transfer and
amplification of variability in
BOTH directions where it
matters most.
End Item
AssemblerFoundry Component
Sub-
Assembler
Demand Signal Distortion
Supply Continuity Variability
Planning horizons shorten AND
lead times compress.
.

Decoupling Placement Criteria 1
.
Decoupling Point Placement Considerations
Customer Tolerance Time The time the typical customer is willing to wait before seeking an alternative source.
Market Potential Lead Time
This lead time will allow an increase of price or the capture of additional business
either through existing or new customer channels.
Sales Order Visibility Horizon
The time frame in which we typically become aware of sales orders or actual
dependent demand.
External Variability
Demand Variability: The potential for swings and spikes in demand that could
overwhelm resources (capacity, stock, cash, etc.).
Supply Variability: The potential for and severity of disruptions in sources of supply
and/or specific suppliers.
Inventory Leverage and Flexibility
The places in the integrated bill of material (BOM) structure (matrix bill of material) or
the distribution network that enables a company with the most available options as
well as the best lead time compression to meet the business needs.
Critical Operation Protection
These types of operations include areas that have limited capacity or where quality
can be compromised by disruptions or where variability tends to be accumulated
and/or amplified.

Position – MRP versus DDMRP
MRP (Everything Coupled) DDMRP (Strategically Decoupled)
1
MRP was never designed to decouple! It
makes everything dependent forcing longer
planning horizons and variability accumulation.
Critical Difference:
.

Protect – Buffer Profiles and Levels 2
.
=
Order frequency and size
Safety
Primary coverage
Group Settings
(Buffer Profiles) x Individual Part Properties =
Zone and Buffer Levels
for Each Part
Item Type PURCHASED
Lead Time Category LONG (.25)
Variability Category HIGH (.65)
Lead Time 21
Minimum Order Quantity (MOQ) 300
Location
(Distributed parts only)
N/A
Average Daily Usage (ADU) 17
233
357
300

Critical Differences 2
MRP was NOT designed to manage
stock positions – it was designed to be
the perfect make to order calculator.
MRP nets to zero.
DDMRP NEVER nets
to zero!
Safety
Stock
.

Protect – Dynamic Buffer Adjustment 3
Most conventional safety stock and reorder
point positions are static NOT dynamic.Critical Difference:
Buffer levels flex as Average Daily Usage
(ADU) is updated.
0
20
40
60
80
0
200
400
600
800
1000
1200
Recalculated Adjustments
Buffers are intentionally flexed up or
down in anticipation of planned events or
seasons.
0
20
40
60
80
100
0
200
400
600
800
1000
Demand Adjustment Factors
.

Pull – Demand Driven Planning
Planned orders create supply orders in
anticipation of need over a longer planning
horizon
Conventional MPS-MRP Planning
?
Plant
Planning
Suppliers
Logistics
Forecast
4
A sales order is HIGHLY ACCURATE.
A planned order is HIGHLY INACCURATE
Sales
Order
Plant
Planning
Suppliers
Logistics
Only qualified sales orders within a short
range horizon qualify as demand allocations
DDMRP Supply Order Generation
Versus
.
It Starts With a More Relevant Demand Signal
It Continues With a More Relevant Supply Order
Generation Equation…

4The Net Flow Equation
.
Questions every planner cares about each day.
What do I have?What is coming
to me?
What demand do I
need to fulfill
immediately?
What future demand
is relevant?
Buffer Status and Supply Order Generation occurs through a DAILY
application of the “Net Flow Equation”.
Supply order issued
for up to the top of
the buffer
Net Flow Position
Qualified Sales Order DemandOn-Hand + Open Supply -

Dependence Within Independence with
“Decoupled Explosion”
.
MRP Explosion DDMRP Decoupled Explosion
• In DDMRP parent demand passes through non-buffered components just the same as
with MRP
• That demand will stop at stocked points no matter what

Pull – DDMRP Execution
Easy to Interpret Signals on Open
Supply Priorities
Order # On-Hand Status Order Type Due Date Customer
MO 12379 MTO May - 12 Super Tech
MO 12401 12% RED MTS May - 14 Internal
MO 12465 27% RED MTS May - 12 Internal
MO 12367 53% YELLOW MTS May - 12 Internal
MO 12411 61% YELLOW MTS May - 16 Internal
Order # Order Type Due Date Customer
MO 12367 MTS May - 12 Internal
MO 12379 MTO May - 12 Super Tech
Order # On-Hand Buffer Status
PO 819-87 27% (RED)
WO 832-41 42% (RED)
WO 211-72 88% (YELLOW)
5
MRP = Priority by due date
DDMRP = Priority by buffer status
vs.
.

Say Goodbye to the Bi-Modal Distribution
DDMRP is proven to allow companies
to plan and execute in the optimal
range at strategically chosen points!
Too MuchToo Little Optimal Range
#ofpartsorSKU
Warning Warning
0
A B
.

DDMRP’s Proven Benefits
Benefit Typical improvements
Improved Customer Service Users consistently achieve 97-100% on time fill rate performance
Lead Time Compression Lead time reductions in excess of 80% have been achieved in several
industry segments
Right-sizes Inventory Typical inventory reductions of 30-45% are achieved while improving
customer service
Lowest total supply chain cost Costs related to expedite activity and false signals are largely eliminated
(fast freight, partial ships, cross-ships, schedule break-ins)
Easy and Intuitive Planners see priorities instead of constantly fighting the conflicting
messages of MRP
.
Case Studies Available at: https://www.demanddriveninstitute.com/case-studies

THE authoritative book on
Demand Driven Material
Requirements Planning
THE authoritative education
on Demand Driven Material
Requirements Planning
www.demanddriveninstitute.com
.

Agenda
IBP for
Inventory
Overview
Q&A
Kick-off
5 min 15 min 35 min
Guenter
Schmidt
Beatrice
Hulde
Ashutosh Bansal All
Demand Driven
MRP Overview
20 min
Chad Smith
15 min

IBP for Inventory Showcase
Inventory Optimization in Action…

1. Supply Network, Master Data Review
2. Forecast Error App
3. Multi-Echelon Inventory Optimization (MEIO) Run
4. Inventory Plan Analysis Dashboards
5. Exception Management, What-if simulations, Publish Plan
6. Demand Driven MRP (DDMRP)
Inventory Optimization Showcase Flow

Customer Map by Sales Volume

Supply Network Map

Supply Network Model

Input Quality Dashboard

Calculate Forecast Error

Lagged Forecast vs. Sales Analysis

Forecast Bias: App Settings

Forecast Bias: Calculated vs. Used

Global (Multi-Stage) Inventory Optimization

Calculate Target Inventory Components

Expected Lost Demand

Inventory Plan Analysis

Safety Stock Drivers

Safety Stock Days

Reorder Point

Safety Stock (Days) Alert
Max: 60 Days
Min: 10 Days

Decomposed (Single-Stage) Inventory Optimization

What-if Simulation: Transportation Lead Time Error CV

Recommend Decoupling Points

Calculate DDMRP Buffer Levels

DDMRP: Red, Yellow, Green Zone Calculations
Type Key Figure Calculation Value
Input Period Between Replenishment
(Weeks)
1
Decoupled Lead Time (Weeks) 2
Lead Time Factor Per Buffer Profile Master Data for Medium Lead Time .6
Variability Factor Per Buffer Profile Master Data for Medium Variability .6
Propagated Average Daily Usage 4485
Output Minimum Order Quantity Per Production, Transportation Min Lot Size 0
Red Zone Base PROPAGATEDADU × DECOUPLEDLEADTIME × 7 × LEADTIMEFACTOR 4485 x 2 x 7 x .6 = 37674
Red Zone Safety PROPAGATEDADU × DECOUPLEDLEADTIME × 7
× LEADTIMEFACTOR × VARIABILITYFACTOR
4485 x 2 x 7 x .6 x .6 =
22604
Yellow Zone PROPAGATEDADU × DECOUPLEDLEADTIME × 7 4485 x 2 x 7 = 62790
Green Zone MAX (MOQ, PROPAGATEDADU × PBR ×
7,PROPOGATEDADU × LEADTIMEFACTOR ×DECOUPLEDLEADTIME × 7)
Max (0, 4485 x 1 x 7, 4485 x
.6 x 2 x 7) = Max (0, 31395,
37674) = 37674
Top of Red Red Zone Base + Red Zone Safety 37674 + 22604 = 60278
Top of Yellow Top of Red + Yellow Zone 60278 +62790 = 123068
Top of Green Top of Yellow + Green Zone 123068 +37674 = 160742

DDMRP: Top of Red, Yellow, Green

MEIO vs. DDMRP: Results Comparison

Agenda
IBP for
Inventory
Overview
Q&A
Kick-off
5 min 15 min 35 min
Guenter
Schmidt
Beatrice
Hulde
Ashutosh Bansal All
Demand Driven
MRP Overview
20 min
Chad Smith
15 min

Release 1805
1. Potential data protection and privacy features include simplified deletion of personal data, reporting of personal data to an identified data subject, restricted access to personal data, masking of personal data, read access logging to special
categories of personal data, change logging of personal data, and consent management mechanisms. 2. This is the current state of planning and may be changed by SAP at any time without notice.
SAP Integrated Business Planning for inventory
Product road map overview - key themes andcapabilities
Inventory Optimization
▪ Network trees exposed in Inventory
Operators
▪ Distribution attribute for consumption:
Normal or Gamma distribution of forecast
error in Multi-Stage IO Operator
Demand-driven MRP Planning
▪ DDMRP operators output Critical Path
Indicators and Decoupling Point Reasons
▪ DDMRP SAP Fiori app shows percentage
change bar chart for scenarios
Supply Chain Network Fiori app
▪ Symbol legend
▪ Order-based planning networks
▪ Rolling time period filters
▪ UI error logging
▪ Time-varying cyclical sourcing in algorithms
(loops)
▪ Inventory Components Operator accounts for
impact of lot size at upstream flow-through
nodes
▪ Non-stocking nodes enhanced with lead time
variability
▪ Forecast Error app outputs outlier periods
and additional forecast error demand types
(frequent & intermittent)
▪ DDMRP SAP Fiori app creates, edits and
runs scenarios
▪ Forecast Error App calculates ADU based on
blended horizon (historical & future)
▪ Version-specific master data
V1805 – Recent innovations(1) V1808 – Planned Q3/2018(1,2) V1811 – Planned Q4/2018(2) V1902 – Planned Q1/2019(2)
▪ Fractional-week lead times and PBRs used
in calculation of backlog and propagated
demand
▪ Inventory optimization using maximum
constraints (storage tanks)
▪ “I” push calculation for downstream
▪ Improved scalability of concurrent inventory
runs
▪ Inbound integration of Master Data
▪ DDMRP SAP Fiori app saves scenario
results to baseline
▪ Filter by Location
▪ Navigate to Analytics and Dashboard SAP
Fiori apps
▪ Improved performance through adoption of
normalization framework
▪ Inbound integration of Key Figures
▪ Outbound integration of safety stock and
other inventory targets
▪ Outbound integration of decoupling point
indicators and buffer profiles to S/4 HANA
▪ Update time period filter
▪ Network layout enhancements

Wrap Up - Integrated Business Planning for inventory
• Achieve the Right Balance Between Inventory
and Service Levels with Multi Stage optimization
• Fix the Mix of inventory by item and location
• Use inventory more efficiently to buffer risk
and uncertainty – at least total cost
Business Benefits
▪ Improve customer service levels 5-10%, with better order lead time variability
▪ Reduce working capital 15-30%, with corresponding reductions in obsolescence
and inventory carrying cost
▪ Improve planner productivity with 20-40% less time spend expediting, and more
effective supply plans

IBP Inventory Functionalities
• Inventory Reference Planning Areas: SAP3 (MEIO), SAP3B (DDMRP)
• Planning Levels, Master Data, Attributes as Key Figures, Key Figures
• Configuration:
• Technical Weeks, Subnetworks, Multiple Modes of Transport, Safety Stock Policy Indicator
• Functionality:
• Supply Chain Network App, Manage ABC / XYZ Segmentation Rules App
• Manage Forecast Error Calculations App: Lagged Error Measures, Intermittency Check, Bias Cap
• Inventory Optimization Operators: Global Inventory Optimization, Calculate Inventory Components,
Expected Lost Demand Calculation
• Custom Alerts, Analytics, Dashboards
• What-if Scenarios / Simulations: Single-Stage Inventory Optimization, Version specific Master Data
• Demand Driven MRP Operators: Recommend Decoupling Points, Calculate Buffer Levels
• DDMRP Buffer Analysis App
• 1805 Recent Features: Network ID, DDMRP Critical Path Indicators, Decoupling Reasons, Buffer Simulations

GitaCloud Digital Learning Platform
Visit learning.gitacloud.com

• Evaluate SAP IBP with GitaCloud Bootcamps:
• SAP IBP 2-day Platform & Applications Bootcamp in Mumbai, India: July 9th – 10th, 2018
• SAP IBP 2-day Platform & Applications Bootcamp in Gurgaon, NCR, India: July 12th – 13th, 2018
• SAP IBP 4-day Platform & Configuration Bootcamp in San Francisco Bay Area, USA: Aug 27th – Aug 30th, 2018
• SAP IBP 4-day Response & Supply Bootcamp in San Francisco Bay Area, USA: Oct 1st – Oct 4th, 2018
• Visit www.gitacloud.com/events for full events calendar
• Ramp-up on SAP IBP on your own schedule:
• GitaCloud Digital Learning Platform: learning.gitacloud.com
• GitaCloud YouTube Channel
• Connect with GitaCloud for an SAP IBP Demo / Workshop at your premises:
• Email: connect@gitacloud.com
• Phone: +1-925-519-5965
• Address: 6200 Stoneridge Mall Road, 3rd Floor, Pleasanton, CA 94588, USA
• Website: www.gitacloud.com
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GitaCloud SAP IBP for Inventory Webinar May 25th 2018

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