These slides were delivered to SCM Executives as part of keynote address from Ashutosh Bansal, founder & CEO of GitaCloud. The event took place in Mumbai, India on 12th April, 2017 and was jointly hosted by GitaCloud and SAP.

1. © 2017 GitaCloud, Inc. All Rights Reserved.
Digital Business Planning powered by GitaCloud and SAP IBP Platform
12th April 2017

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Digital Business Planning - Agenda
2
9:00
9:15 Demand Driven / Outside-in: The next frontier in Value Network Planning capabilities
Ashutosh Bansal, GitaCloud
10:00 SAP’s strategy and visions within Integrated Business Planning and Supply Chain Management
Neeraj Athalye, SAP
10:45 Break: Light Refreshments
11:00 Deep Dive: SAP IBP Showcase
•Integrated Scenario Planning with IBP for S&OP
•Demand Sensing with IBP for Demand
•Inventory Optimization with IBP for Inventory
Akhilesh Pandey, GitaCloud
12:30 Panel Discussion: SAP IBP - Lessons learned & Implementation Best Practices
Ashutosh Bansal, Vasan VS, Neeraj Athalye, Moderated by Akhilesh Pandey
1:15 Wrap-up, networking and lunch
Kick-off & Welcome
Vasan VS, GitaCloud, Neeraj Athalye, SAP

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Which type of supply chain are you running?

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• FMCG Company:
• Seasonal products. High volume. High demand variability driven by weather, promotions, etc.
• Low forecast Accuracy across the large SKU portfolio.
• High service levels lead to high inventory of perishable product. Bullwhip effect on suppliers.
• Constrained Raw Materials. RM buy needs to be timed.
• Supply chain constraints (e.g., RM/PM) not modeled in current excel based production planning system
• Short term market demand quite different from forecast.
• Planner burnout with reactive management of supply chain. Looking for stress free supply chain.
Challenges we have observed...

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• Pharmaceutical Company:
• Measuring forecast accuracy at Country level despite high number of Distribution Centers.
• Measuring forecast accuracy with 1 month lag despite pharma supply chain lead-time being 3-4 months
• High service level requirement. Low forecast accuracy at lead time at SKU/DC level. High inventory levels.
• Low forecast accuracy for NPI, emerging markets, samples.
• Ineffective process to model long term demand and capacity requirements.
Challenges we have observed...

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• Automotive Company:
• Spare parts forecast accuracy very low for exports markets.
• Long tail in Spares SKU portfolio. Manual forecasting approaches not scaling.
• Response is to increase order lead time. Customer service issues.
• Inventory optimization challenge with old SKUs. MOQ constraints.
• Inventory visibility challenges.
Challenges we have observed...

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What drives your supply chain?
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Manufacturing Driven
Deliver a Feasible Plan for Operations
Match Demand with Supply
Sales Driven
Match Demand
with Supply
Business-
planning Driven
Maximize
Profitability
Demand Driven
Maximize Opportunity
Sense and Shape Demand
Market Driven
Maximize Opportunity and
Mitigate Risk. Orchestrate
Demand Market to Market
Greater Benefit
• Growth
• Resilience
• Efficiency

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Stage5
Value Creation
Network
MINDSET
Inside-Out
Outside-In
Stage1
Silo’ed Goals
Stage 2
Scaling SC
Functions
TARGETCost Service
Stage 3
Integrated
Supply Chain
Stage 4
Demand Driven
Value Networks
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Gartner Five Stage Maturity Model

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SAP APO (Stage 3) vs. SAP IBP (Stage 4)
Demand Sensing
Inventory
Optimization
Sales & Operations
Planning
Control Tower
Demand Planning
Detailed Scheduling
Distribution
Planning
Stage 3
Integrated
Supply Chain
Stage 4
Demand Driven
Value Networks
System of
Differentiation SOD
System of Record SOR
9
Supply Planning

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Digital Business Processes run differently
10
Adapt &
Respond
Act &
Monitor
Shape (to
resolve
gaps)
Plan (to
understand
gaps)
Sense

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IBP is much more than S&OP
Sense /
Predict
Demand
Enrich with
Sales &
Marketing
Input
Demand
Shaping /
Consensus
Generation
Plan Demand
Unconstrained
Consensus
Demand Plan
Scenarios
Compare
Current vs.
Target
Inventory
Sales Input
on Service
Levels
Inventory&
Service Level
Optimization
Plan Inventory
Target
Inventory
Levels by
Demand
Scenario
Review
Critical
Resource
Capacity
Flow
Demand
through
Network
Supply Shaping
/ Cost
Optimization
Plan Supply
Constrained
Supply
Response
Scenarios
Develop end to end
Scenarios (Demand,
Inventory, Supply)
Sales & Operations Planning S&OP
Balance Plans, Resolve Issues, Make Decisions
Assess Forecasted
Financials, Options for
Trade-offs
Balancing (Pre S&OP)
Meeting
Executive Decision
Meeting
S&OP Plans
Release S&OP Plans
for detailing &
execution
Sales & Operations Execution S&OE
Publish Plans, Monitor Execution, Respond
Monitor Short Term
Demand-Supply
Imbalances
Monitor Execution
Performance
Respond to
Variations from
Plan
Operational
Response
Functional Planning Processes
Generate Plans aimed at Functional Excellence
11

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Business environment for the Demand Planner
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Evolving Consumer
Volatile Demand
Demand Driven Value Network
to sense & react near-real-time
SKU Proliferation
Omnichannel Fulfillment
NPI Forecast Bias Promotion Modeling
What is needed
Impact
Forecast accuracy ceiling
High error & bias
Planner burnout

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The Fallacy of High Forecast Accuracy
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Product Family / Monthly
SKU / Location / Monthly
SKU / Location / Customer / Weekly or Daily
70-85%
55-70%
35-55%
1
2
3
Executive View
SCM Manager
View
Demand Planner
View
Forecast Accuracy Iceberg

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SAP Integrated Business Planning Platform
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Supply Chain Control Tower
“End-to-End Visibility, Monitoring and Alerting”
IBP for Sales & Operations
“Strategic and Tactical Decision Processes“
IBP for Demand
“Demand Sensing and
Statistical Forecasting”
IBP for Inventory
“Multi-Stage Inventory
Optimization”
Supply
“Constrained and
Unconstrained Supply
Planning”
IBP for Response
“Allocations Planning
and Order Rescheduling”
Unified SAP HANA Platform for Cloud Deployment
&

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SAP IBP Webinar from GitaCloud
SAP IBP Platform: Key Differentiators
Scalable & Flexible Model
Sales
FinanceOperations
Model any detail across time or
function, Insights like never before
Social, Connected
Collaborate internally / externally
Record full context of decisions
Risk
Profitability
Real Time Scenario Planning
Model risk and profitability in your
plans. Simulate on the fly
Real Time Insights
Track Supply Chain KPIs Real-Time
with Control Tower
Modern Intuitive UX
Millennial grade UX. Business
Planner Adoption Enabler
Data Integration
Out of the box, simple, secure
integration with SAP ERP and APO
Rich Functionality
Demand Sensing, Control Tower,
Optimization, MEIO in One Solution
HANA in Cloud
HANA in-memory. Cloud based.
Elastic compute with reduced TCO
15

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Demand Planning vs. Demand Sensing
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time
Forecast
wk1 wk2 wk3 wk4 wk52…
Demand Planning: E.g., executed monthly in weekly buckets
Demand Sensing: Generally done daily in daily buckets
Difference between short-term forecast and consensus mid/long-term
forecast
Demand Planning = Time series methods – based on history - trend and seasonal patterns
Demand Sensing = Adjust the demand plan – data from present and recent past - pattern recognition algorithms

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What planning processes does Demand Sensing impact?
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Deployment and
transportation
decisions
Production and
packaging sequences
Material
purchasing
Short Term Planning Horizon
Inventory Optimization
Today

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Case Study: Weekly forecast accuracy improvement
Global health and beauty care consumer products
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Lag
Demand
planning
wMAPE
Demand
sensing
wMAPE
Absolute
difference
%
Change
Week 1 61% 31% 30 49%
Week 2 62% 46% 16 26%
Week 4 65% 52% 13 20%
Week 6 68% 56% 12 18%
Compelling results seen in the PoC for internal signals
18%–49% reduction in forecast error across 6 weeks
6%–8% reduction in forecast bias across 6 weeks
Driven by significant over-forecasting bias, 7–8 day average order lead times, and complexity from large
number of SKU location combinations
wMAPE = Weighted mean absolute percentage error

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Single Stage Calculations:
• Isolated planning results in
over-buffering of inventory
across the supply chain
• Determining postponement
strategy is challenging (To stock
at upstream or downstream
warehouse)
Multistage Optimization:
• Coordinated planning
eliminates over-buffering
of inventory and ensures
services objectives are
met
2
Stage
S S S
C C C
1
3
S S S
C C C
Inventory Optimization simultaneously optimizes inventory across the entire supply chain
based on meeting customer service requirements with the lowest amount of inventory dollars
Global (Multi-Stage) Inventory Optimization

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SAP Inventory Optimization: What is Being Calculated?
Increase
Achieve the Right Balance Between
Inventory and Service Levels
Fix the Mix of Inventory!
90% 92% 94% 96% 98% 100%
Inventory($)
Customer Service Level (%)
Optimal inventory Company current performance
-60%
-40%
-20%
0%
20%
40%
60%
DecreaseIncrease
20

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SAP Integrated Business Planning for Inventory
Improve customer service levels
Maximize the efficiency of inventory and
working capital
Standardize the inventory target-setting
process at each tier within the supply chain to
feed operational plans
Inventory
Demand Response and Supply
Sales & Operations
Supply Chain Control Tower
Customer service levels
lifted from 93.7% to
99.1
Improved service levels with a
20% reduction in days of
inventory

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Origins
• Started in Mar 2015
• Incorporated in Delaware, USA
• Founded by Ashutosh Bansal (ex-
SAP; Industry Leader / Sales
Executive at SAP America)
Footprint
• Headquartered in Pleasanton, CA
• Regional office in Gurgaon, India
• Website: www.GitaCloud.com
Partnerships
• SAP PE Services Partner
• River Logic (Enterprise Optimization)
Reseller
• Snaplogic (Integration Platform)
Reseller
Mission
Help enterprises and people
make better decisions
GitaCloud Overview

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Expertise
• Enterprise License / Services Sales
• Supply Chain Transformation Advisory
• SAP Implementation Services
• SAP Optimization Services
• Business Process as a Service:
• Demand Sensing
• Inventory Optimization
GitaCloud Overview
Domains & SAP Solutions
• Integrated Business Planning with SAP IBP
• Demand Sensing
• Inventory Optimization
• Control Tower
• Supply & Response Planning
• ERP with SAP S/4 HANA:
• MRP Live, Advanced ATP
• Supply Chain Solutions: SAP APO, SNC, EM
• Digital Transformation with SAP IOT, PDMS
• Enterprise Performance Mgt with SAP BPC, C4A
• Collaborative Procurement with SAP Ariba
Industries
• CPG (FMCG)
• Pharmaceutical
• Automotive
• Mining & Metals
• Chemicals
• Oil & Gas

24. © 2017 GitaCloud, Inc. All Rights Reserved.
SAP IBP is a key focus are for GitaCloud
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SAP IBP S&OP Webinar
Jan 18th, 2017
SAP IBP Webinar focused on
Revenue Forecasting in S&OP
• Jointly with SAP: Kris
Gorrepati (SAP IBP Solution
Mgt) as Guest Speaker
• Replay: SAP-GitaCloud IBP
S&OP Webinar Recording
SAP IBP S&OP Workshop
Jan 28th - Feb 5th, 2017
SAP IBP hands-on 4 day Workshop
• Sold out workshop.
• 10 learners across NA and APJ
Scope:
• SAP IBP Overview
• SAP IBP Configuration
• SAP IBP Mock Implementation
SAP IBP Inventory Webinar
Feb 24th, 2017
SAP IBP Demand Webinar
Mar 23rd, 2017
SAP IBP Webinar focused on Demand
Sensing
• Jointly with SAP: Tod Stenger (SAP
IBP Demand Solution Owner)
• Replay: SAP-GitaCloud IBP Demand
Webinar Recording
SAP IBP Webinar focused on Multi-
Stage Inventory Optimization
• Jointly with SAP: Jeff Majestic
(SAP APJ Business Development)
• Replay: SAP-GitaCloud IBP
Inventory Webinar Recording

25. © 2017 GitaCloud, Inc. All Rights Reserved.
SAP IBP is a key focus are for GitaCloud
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SAP IBP Customer Event in APJ
Apr 12th, 2017
Half a day Face-to-Face Customer Event
• Location: Mumbai, India
• Hosted jointly with SAP
• Top customer brands in CPG, Pharma, Auto,
Chemicals confirmed (25+ companies)
• 40+ C-level, VP SCM or higher LOB executives
• SAP India S/4 Initiative Head as Keynote Speaker
• Expect to start 5 or more SAP IBP POCs
SAP IBP S&OP Workshop
Mar 25th – Apr 2nd, 2017
SAP IBP S&OP hands-on 4 day
Workshop
• Link to Register
Scope:
• SAP IBP Overview
• SAP IBP Configuration
• SAP IBP Mock Implementation
SAP IBP Demand & Inventory Workshop
April 29th – May 7th, 2017
SAP IBP Demand & Inventory focused hands-on 4
day Workshop for customers interested in Demand
Sensing or Inventory Optimization
• Link to Register
Scope:
• SAP IBP Demand Overview
• Demand Planning, Demand Sensing in detail
• SAP IBP Inventory Overview
• Multi-Stage Inventory Optimization in detail

26. © 2017 GitaCloud, Inc. All Rights Reserved.
GitaCloud Digital Transformation Methodology
Rapid Supply Chain Assessment & SAP IBP POC
Current State
Assessment
Best Practices
Fit-Gap
Target State
Design
Transformation
Roadmap
Review Current State
• Current Organization
(Roles, Responsibilities,
Incentives)
• Current Processes
(Formal, Shadow)
• Current Systems
• Current Data Quality
• Current Reports &
Metrics
Assess Gap vs. best in class
• Peer Benchmarking
• Maturity Assessment
• Gap Analysis (Define &
Prioritize Gaps)
Envision Target State
• Tied to current maturity
• Define high-level
processes
• Define Solution
Architecture, Data
requirements
• Define target state Org
• Define target state
policies & metrics
Develop Transformation
Game Plan
• Recommended
Business Releases
• Solution Architecture
Impact of in-transit
states
• High level timeline and
dependencies
• Value Roadmap
(Business case)
SAP IBP POC / Pilot
Run a Pilot
• Controlled data-set
• Choose a process area
with high level of
Sponsorship or value
• Show value quickly
• Leverage Industry
Reference Models
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• Leading electrical car manufacturer
• Customer challenged to come up with an accurate demand forecast for Remanufacturing Operations
• Rapidly evolving platform; dynamic failure mix
• Regional differences
• Excel based complex solution (hundreds of tabs)
• GitaCloud brought in Demand Sensing and Capacity Forecasting best practices
• Showcased the solution with a rapid POC – convinced customer on solution value
• Implemented and successfully went live in record time
• Customer team completely satisfied with the solution and its benefits
GitaCloud Client Engagements
Case Study: Remanufacturing Planning at a leading Automotive Brand

28. © 2017 GitaCloud, Inc. All Rights Reserved.
As a department manager supporting Remanufacturing department in a growing organization, forecasting
and planning has high importance in driving results.
We are impressed with GitaCloud. GitaCloud combines deep supply chain skills with the ability to develop
targeted solutions to hard business problems.
Alla Anashenkova, Department Manager, Remanufacturing Planning, Leading
Automotive Manufacturer
GitaCloud Client Engagements
Case Study: Remanufacturing Planning at a leading Automotive Brand
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29. © 2017 GitaCloud, Inc. All Rights Reserved.
Ashutosh Bansal
Founder & CEO, GitaCloud
+91-8130654555, +1-925-519-5965
LEVEL 9, SPAZE I-TECH PARK, A1 TOWER, SECTOR 49, SOHNA ROAD, GURGAON, HARYANA, 122018, INDIA
ashutosh@gitacloud.com
www.GitaCloud.com