MSC- Who We Are and What We Do - Chief Executive...Supply Chain Mgmt./ New Product Introduction Global Supply Chain Transformation, Technology and Analytics Integrated Business Planning

MSC- Who We Are and What We Do

107Countries Served

>390Number of Suppliers(includes component suppliers)

~$8B Total Amount of Annual Spend

30KShip To Locations

1TBTotal Daily SC Data Generation

1.7M+ Est. FY17 Number of Retail and Commercial Sales Orders

33Number of Mfg & Distribution Operations

>42,000Number of Active SKU’s

2.0M+Est. FY17 SAP Deliveries

>77M Units Manufactured & Shipped

Strategic

SourcingCare

Manufacturing

Supply Chain Mgmt./

New Product Introduction

Global

Supply

Chain

Transformation,

Technology

and Analytics

Integrated

Business

Planning

Safety,

Compliance

& Sustainability

Our Products

PC Hardware

Surface Hub HoloLens

Software

Xbox

Surface

Surface Studio

MSC Global Presence

Argentina

Colombia

Canada

Australia

Austria

France

Japan

Singapore

Malaysia

UK

UAE

Germany

Russia

Brazil

Hong Kong SAR

Czech Republic

Netherlands

TaiwanMexico India

Finland

Microsoft Supply Chain Challenges

Pricing and Margin Pressure

Increasing Customer Service Expectations

1 Digitized Supply Chain

MSC’s 1DSC Transformation Journey

The Azure Platform Enables our Connected Digital Supply Chain Foundation

Supply Chain Partner Systems

Warehouse

ManagementShop Floor Control System Transportation

ManagementBOM Management

Corporate systems

CommerceDevice Telemetry CRM

SubscriptionsProduct

Catalog

Sales

Point of Sales Freight

Management Enterprise

Services

Supplier ERP

Data & Advanced Analytics Platform

HD Insight Event

HubsAzure Data LakeAzure Data

Factory

Supply Chain Cloud

Supply Chain Services

Azure API

Management

Microservices Azure Application

Insights

Microsoft Supply Chain Core Transactional Systems

Make

(MDS)Deliver Care

Dev/NPIFinance

Source Plan

Drive world class Customer Care, Product Quality & Compliance

Enable Scale and Complexity

Effectively Deliver Products & Services to Market

Aggressively Manage Costs

Connected: MSC Purpose is reflected in what we measure via Power BI

Microsoft Manufacturing Digital Transformation: Leading

the Industry with Microsoft Tools/Technologies

Factory Video

Speed

Scale Capture - 1B data points/day, Analyzed < 1%

Accessibility to data measured in hours/days

Predictive Factory’s with MDS, a Azure-based system for real-time factory floor & product lifecycle analytics

Before: Static, siloed data (TCS, Shop Floor…) After: Enables proactive alerting, predictive analytics

MTE TCS

T2T1

JDM1

Shop Floor

Any T1 or Critical T2

Returns

JDM1 Shop

Floor

TCS TCS

Share

Point

SQL

EIP

Other T1Critical T2T2

JDM1

Reduced Returns, Higher Yields, Better Productivity

Returns

System enables Power BI, machine learning, advanced analytics & decision making capability

E2E Visibility from Incoming to Customer Proactive Alerting, Real time Insights

Incoming Part

Quality & Availability

CTF/CTQ

IoT Process Monitoring

Product

Yield

Outgoing

Quality

Field

Quality

Returns

Repair &

Refurb

T2

Quality

Output & Shipment

Progress

Incoming Manufacturing Customer

Proactive

Alerting

Predictive

AnalyticsBig Data

Mining

Real time

Insights

• Creating Clarity via Personalized Dashboards

• Increasing Collaboration, Connected Data Streams

enable Teamwork

• Improving Factory Productivity/Optimization

• Big Data insight and Machine Learning

• Proactive Alerting

• Predictive Analytics

Implementation is changing the way we (Microsoft & partners) manage the day to day factory operations

Personalized dashboards align to Factory Manager’s purpose

Example: Factory Manager Product Dashboard Example: Proactive Alerting

Surface

Pro 4

Alerts identify one tester drifting out of control.

Tester taken off line, and issue corrected before yield impacted

Alerts identify significantly different battery placement measurements on one line vs others

Fixture alignment issue corrected before quality impact

Proactive alerting monitoring critical IoT enabled measurement data

Analytics engine evaluated multiple attribute

variables to predict top patterns across

Wafers, Chips

Model predicted optimal patterns and

optimized manufacturing parameters for

improved yield

Results

Predictive

insights

Factory

Data

Azure ML

Targeted patterns/combinations

demonstrated ~30% yield improvements

and $2M in scrap reduction

Assembly component, Genealogy, MES,

Environmental

Training Machine Learning models to

identify drivers/patterns of SP4 returns

attributed to critical HW genealogy,

software telemetry & CSS data

Current model predicts ~80% recall rate for

a returned device.

Improving precision with additional Factory

and Customer/Retailer data

Expected

Results

Current

insights

Azure ML

Targeting to achieve:• Improved CSS/Customer interaction

• 1st Returns reductions, better quality

• Improved returns forecasting

Product

Big DataProduct Experience• SW release/updates

• App/accy Incompatibility

• Windows telemetry

Product Design & Mfg• Mfg/Test process

• Components/supplier

• Hardware/device design

As a result of the foundation, we are now starting to use predictive analytics & machine learning in the factory

Example: Predictive Yield Improvement Example: Predictive Return Insights

Digital Transformation increases Pace

Data is the new Currency