Re-architecting Your Supply Chain

for High Velocity Growth

Anthony Noguera & Padman Ramankutty

Agenda

� NVIDIA Company Overview

� Intrigo Overview

� State Of Industry

� Business Problem

� CODE Solution Overview

From Super Phones to Super Cars

GeForce®

, Quadro®

, TeslaTM

VISUAL & PARALLEL COMPUTING

GPU

Tegra®

MOBILE COMPUTING

Mobile

Processor

GEFORCE® | Helping Gamers Enjoy Games

BEST VISUAL EFFECTSQuadro GPUs were behind allof the “Best Visual Effects” Oscar nominees for the past three years.

Image courtesy of GK Films

WORLD-CLASS SUPERCOMPUTINGIn October 2011, Oak Ridge National Labs announced that it will use 18,000 NVIDIA Tesla GPUs to develop the world’s fastest supercomputer, called “Titan.”

MARKET LEADERSHIPTegra has taken the market by storm. Today, more than 30 tablets and 65 phone SKUs are powered by the super chip.

NVIDIA FACTS

Founded in 1993

Jen-Hsun Huang is co-founder, president and CEO

Listed with NASDAQ under the symbol NVDA in 1999

Invented the GPU in 1999 and has shipped more than 1 billion to date

FY12: $4 billion in revenue

7,000 employees worldwide

2,300 patents worldwide

Ranked #10 “greenest” company in America by Newsweek in 2011

Headquartered in Santa Clara, Calif.

About Intrigo

We are a Premier Enterprise Consultancy, focused on orchestrating Customer

Value Networks at the confluence of Demand, Supply and Innovation.

OUR SERVICES

Advisory

Re-architect the planning processes

Usability / workflow re-model

Enterprise Architecture and Software components

Implementation

Complete turnkey implementation

Assemble to deliver

Support

Offshore project/engineering delivery

Planning Analytics

Supply Respond Sense

Innovate

Source: AMR

Create

Demand

Intrigo Systems’ Clients

“The ability of Intrigo’s leadership team to execute in a

complex, multi-party environment directly contributed to the

success of our project."

-- John Hanna,

Director - iPlan Project, Clorox

“Intrigo's deep industry domain knowledge and their

expertise in SAP made for an effective implementation of

our Business Systems. Their commitment and focus to

making us successful make Intrigo a key partner for

Aptina.”

-- Joe Passarello, CFO, Aptina Imaging

State of Supply Chain Planning in

the Semiconductor Industry

• Discrete vs. attribute-based part numbers

• Multiple postponement points

• Optimization planning models

• Long lead time materials (wafers)

• Capacity-constrained, high value materials

• Test equipment, allocation to multiple subcons, cost

• Heuristic planning models

• Order-based planning (customer centric Models)

• Lead time assumptions are vague in fabless model

Business Problem

NVIDIA's business has grown more complex

Our ability to project, manage and optimize our wafer supply

has entered the critical path of our growth

Existing spreadsheet-driven processes cannot scale to the

growth of our business (market segments, number of SKUs,

product complexity)

Focus today is simply aligning supply to marketing demand

by product family

Tomorrow, we want to employ production plans optimized for

cost, capacity and flexibility

Desired Maturity of Supply Chain

Planning

Excel Planning

Complete Planning

Scenario planning

Optimized planning

Integrated planning

CODE

program

CODE – COMPLETE, OPTIMIZED DATA ENGINE

Active links with

Sales, BU, & Finance

tools; i.e., mutual

plans re-align

regularly

NVIDIA's Supply Chain Planning

Evolution

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Demand

Planning (SAP APO)

Unconstrained

Supply planning

(SAP APO – PPDS

heuristics)

GATP with product

Allocation (SAP APO)

VMI deployment (SAP

Deployment)CODE

• Constrained planning

• Optimized planning

• Scenario Planning

Inventory Forecasting and

Supply-Demand Alignment

(SAP APO+BO Dashboards) Postponement

Planning

FCD improvements /

12-month Supply

Commit

Vendor Evaluations

We evaluated several vendors with the final two

being SAP/Intrigo vs i2 (JDA)

Most of our business sponsors preferred i2 over

SAP given i2’s perceived richness of

semiconductor-specific functionalities and more

experience in the space

But IT and Intrigo convinced the business about the

much better TCO of SAP and the feasibility of this

path

Planning & Execution Landscape

SAP SD

Customer Demand

Orders

Promise

Dates

Planning

Wafer & BE Planning

Supply

Statement

Demand

Sourcing

Available

To promise

Order Management

Inventory

Management

Build Optimization

� Inventory Levels are calculated by the system using service targets, demand history, and supply chain models

� Safety Stock can also be defined in days of coverage

Collaborative Supply Planner

Requested

Committed

Unmet

Unmet %

Requested

Committed

Unmet

Unmet %

Requested

Committed

Unmet

Unmet %

Requested

Committed

Unmet

Unmet %

All Vendors All Business

SAP MM

APO ATP

APO

SAP

(ABR)

PDMT

O.R. tools

Excel

SAP

(SPNR)

Windchill

Serus

Production

Execution

HUB

Demand

and

supply

BOM interface

to SAP

Sub cons

No changes

Changes in the

system

Planning data management

� I n v e n t o r y L e v e l s a r e c a l c u l a t e d b y t h e s y s t e m u s i n g s e r v i c e t a r g e t s , d e m a n d h i s t o r y , a n d s u p p l y c h a i n m o d e l s

�

C o l l a b o r a t i v e S u p p l y P l a n n e r

R e q u e s t e d

C o m m i t t e d

U n m e t

U n m e t %

R e q u e s t e d

C o m m i t t e d

U n m e t

U n m e t %

R e q u e s t e d

C o m m i t t e d

U n m e t

U n m e t %

R e q u e s t e d

C o m m i t t e d

U n m e t

U n m e t %

A l l V e n d o r s A l l B u s i n e s s

New System

S

A

P

B

W

+

B

O

Box color legend

Execution

APO

Steelwedge

Demand

Planning

Guiding Principles

• Flexible planning models

• Postponement

• Buffer stock

• Usability and maintainability of the planning master data

• Planning rules maintained in Business language

• Ease of maintenance

• Explainability of the planning results

• Scenario and bridge Analysis

Planning Solution Overview

Optimization

for Wafer

Planning

Wafer Allocation by

Wafer Family:

Constraint for

Backend planning

Backend planning

to determine Assy

starts, PFG starts

for Forecast

PFG Supply:

Constraint for SLT

Planning

SLT Planning to

determine PFG

starts for demand

signal

Projected

Finished goods

for Order

Commitments

Wafer Planning by SAP APO OptimizerWafer Planning by SAP APO Optimizer

Backend planning by SAP APO OptimizerBackend planning by SAP APO Optimizer

Backend SLT planning by

SAP CTM

Backend SLT planning by

SAP CTM

Custom UI for Data ManagementCustom UI for Data Management

Direct Sort Flow (Wafer

Buy)

Direct Sorted Wafer Buy

PFG Postponement Flow

Direct Flow

PFG to FG Flow

Assembly Flow Test Flow PFG to FG Flow

Sort

Back Grind

Assy Test SLT

Tape and Reel

FG

Bump

PFG/FG*Assembly

Back Grinded

Die

DieSorted WaferBumped WaferUnbumped

Wafer

Fab

Supply Plans generated for:

Fab - Sort

Die inv to FG

SLT/T&R adhoc runs

Focus on data, priorities, rules and system generates supply plans* Test out part numbers

for Direct Flow only.

Required for capacity

planning in SLT

Reference Model – Material Flow

Planning Scenarios Overview

POR Version

Backend material and capacity-constrained version

Wafer capacity-constrained version

Wafer capacity-unconstrained version

Backend material-constrained, capacity-unconstrained version

Backend constrained, push production

SLT material and capacity-constrained version

SLT material-constrained, capacity-unconstrained version

Scenario solves as per the requirement

Wafer Plan

Backend Plan

SLT Plan

Planning Systems Overview

APO Planning Engine

Core InterfaceStandard SAP component to transfer Planning

Input Data (Master and Transaction Data) and Output Data (Planning results)

APO Planning Engine

Transaction Data

Data

Warehouse

APO Master Data transfer

Data

Repository

Input Screens Planning data management tool

Publish to output

ECC

ECC Master Data transfer

Execution instructions to subcon

Confirmations from subcon

APO Master Data transfer

Build Rules

Build Strategies

Time Phased Data

Planning results

Implementation Overview

• End-to-end Blueprint Design completed as of 2/15

• Phased project approach but design was end-to-end

• Expected go-live in 2012 and 2013

• Q&A