analytics in high tech electronics supply chain

© 2010 Supply Chain Council. ALL RIGHTS RESERVED. | < filename > | Slide 0 | 21 April 2014

SCC Global Member Meeting and

Supply Chain World North America

Nashville, Tennessee, USA

April 14-15, 2014

Trends in High Tech Supply Chain

Partha Bose - IBM

© 2014 IBM Corporation 1

THIS PRESENTATION COVERS 3 TOPICS

2 Role of Analytics in

Supply Chain

3 The Software-Defined

Supply Chain

1 Today’s High Tech

Supply Chain


3 CHARACTERISTICS

OF HIGH TECH SUPPLY CHAINS

Economies of Scale BIG

Multi-Tier Supply

Chains COMPLEX

Low Cost Supply

Chains GLOBAL


See what others don’t

Exploit global efficiencies

Know the customer as well

as yourself

Source: IBM Institute for Business Value

Volatility

Value

Visibility

NEW VISION AND NEW RULES ARE NEEDED


#1: KNOW THE CUSTOMER AS WELL AS YOURSELF

Predict demand and be in a position to react to demand variability and market volatility with rapid response and allocation of all global resources

Implementation of Smarter Supply Chain Capabilities


CONSUMER ELECTRONICS MAJOR

S&OP as a globally integrated process

manages the Supply Chain globally on

a weekly basis

Global visibility of inventory levels and

replenishment needs

Model of Global SCM

Customer 1

Customer 2

Customer 3

Region Sales

Region Sales

Region Sales

Plant1

Plant2

Plant3

Unit of Planning

$XB

$YB

2003 2012

Over 3X

Achieved over 3X growth

for last 10 years

through pure organic growth

In major divisions, Global Operation

Center & HQ supply chain management

teams have maintained the same size,

supporting a business that has grown 3

times


STRATEGIC INITIATIVES HAVE ENABLED THE COMPANY’S GLOBAL SCM ENVIRONMENT

Global Competition

Risk of Supply Chain Disruption

Lower Margin

Key Challenges Strategic Initiatives

Globally Integrated Supply Chain

Optimize global operation

Global Concurrent Launching

Get high profit in early market

Advanced Customer Collaboration

CPFR & Retail Channel Mgmt

Extended Supply Chain Flexible supply with less risk

Increased Market Uncertainty


STRATEGIC MIX OF BUY & MAKE OF KEY COMPONENTS

Make

Buy

Buy Vs.

flexible

flexible

Strategy of Component

Supply

Strategy for key

components

In short term, there’s a

constraint to change

the Buy strategy

Mix Buy & Make for key components

to mitigate the risk of supply chain

disruption

In order to make key decisions for

new internal investment of component

plants, clear visibility on the

component demand-supply balance is

needed


IBM’S GIVIEW PLANNER FUNCTIONALITY MET 4 KEY REQUIREMENTS

9

Plant A (Internal)

Purchase (External)

Warehouse

Purchase

Purchase

Purchase

Manufactur

e

Manufactur

e

Dummy

Transport 10%

90%

Transport

60%

40%

Transport

Demand

Demand

Demand

Warehouse

for Domestic/Export

Demand from

Final Assembly

Component Manufacturing

Or Purchasing

Proportional

Sourcing

Auto Build ahead (1

week)

No carryover @ Plant:

Push out all inventory to W/H

Consume Capacity by cycle time

1

2

3

4


Collaborate with insight and visibility to events, with suppliers, service providers and customers in an open, action-oriented, environment.


#2: SEE WHAT OTHERS DON’T

© 2014 IBM Corporation 11 11

What if you could accurately predict

which characteristics tend to lead to

a higher frequency of failures?

What if, when an asset is

scheduled for maintenance,

you could predict what

parts are likely to fail in the

near future?

What if you could identify the characteristics

that tend to increase ownership cost and

downtime over the life of a system?

What if you could replace

those parts that have not yet

failed and avoid further

unscheduled downtime?

What if you could quickly mine the

thousands of logs that describe the

maintenance performed on a system and

determine what important observations are

being logged by the maintenance team?


Group cases that exhibit

similar characteristics.

Which parts tend to fail most

often? At what rate do they

fail?

Predict or Classify

behavior & characteristics.

What are the

characteristics of parts that

perform well versus parts

that fail often?

What events occur

together?

Given a series of part

failures, which parts are

likely to fail in the future?

Associate Classify

Cluster

DATA

MINING

Data Mining &

Predictive Modeling

unearths insights

PREDICTIVE ASSET OPTIMIZATION


2. Predictive Maintenance

(Service Optimization)

1. Manufacturing Quality

3. Warranty Analytics

4. Remote Diagnostics

(Connected Equipment)

5. Business Model

Transformation

Predictive maintenance for plant equipment

Equipment repair and maintenance optimization

Optimization of service parts and engineers’ schedules

Production quality management

(PLC/MES/Quality inspection data)

Warranty monitoring and analysis

Field quality early warning using warranty claim data

Warranty accruals management

Equipment data analysis and early warning

Remote monitoring and diagnosis

Maintenance optimization

Business model transformation with extended warranty,

performance assurance, and operational excellence.

Transformation to analytics-driven organization

APPLIES TO 5 BUSINESS DOMAINS IN EQUIPMENT MONITORING.


• Virtuous Cycle: Inflection point to

rapid change: at 15 percent of the

market, a sudden takeoff in the

proportion of spending is shifting

to managed print services

• Huge Value Proposition:

Compelling 30+ percent cost

reductions for customers, higher

margins for winning vendors

• Service Extension: Branching

beyond copying into printers,

processes, and other IT

infrastructure services

• Winner Takes All: Transformation

driving consolidation toward larger

vendors

THE MARKET FOR PRINTING SERVICES TRANSFORMED ITSELF IN 3 YEARS BETWEEN 2008 AND 2011

Source: Photizo Group, MPS Advisory Service, MarketWatch™

Huge Growth for Managed Print Services,

Represented by the Number of MPS Programs Announced 75%

50%

25%

0%

= Number of new MPS programs

= MPS program growth

1 1 1 1

10

31

11

2

1% 2% 3% 4%

14%

45%

56% 58%

2004 2005 2006 2007 2008 2009 2010 2011


PAO ARCHITECTURE

Industrial Enterprise Services Bus

(Message Broker)

End User Reports, Dashboards, Drill Downs

High volume streaming data

(InfoSphere Streams)

Telematics, Manufacturing Execution Systems,

Legacy Databases, Distributed Control Systems

EAM System

(Tivoli Maximo Tririga or other)

Analytic Datastore

(Pre-built data schema for storing quality, machine and prod data, configuration)

DB2

Statistical Analytics

(SPSS Modeler)

Decision Management

(SPSS DM)

Business Analytics

(COGNOS BI)


UK Utility Company

In Production Line

• Pro-active detection rate

increased by 90-100%

• Sustained 41% reduction

in production incidents

and unscheduled

downtime

• Reduced liability damage

by 30% in 2 years

Japanese Manufacturer

In Field Services

• Saved $1 million in repair

costs in under 2 weeks

• 12-14 times return on

investment in just 4

months

German Auto Manufacturer

In Warranty Services

• Proactive identification of

systematic error patterns

and their dependencies

• Reduced warranty cases

from 1.1 to 0.85 per

vehicle

• 5% reduction in warranty

cases

• Annual savings of €30m

CASE EXAMPLES


Optimize pipeline inventory, the global network, and cost structures. Create cost-efficient, sustainable practices while hedging risks.


#3: EXPLOIT GLOBAL EFFICIENCIES


Globally Integrated Enterprise

Multinational Era

Homegrown IT

Multiple, separate supply

chains

Few common processes

ERP

Enterprise efficiencies

Streamlined global

processes

Information sharing

Analytics

Enterprise and multi-

enterprise optimization

Transparent SC

Predictive, Cognitive

Smarter Supply Chain

CASE EXAMPLE: IBM


R&D

Marketing

Finance

TO FROM

Supply Chain

• 3 global procurement centers • 300 local procurement centers

• Outsourced non-core processes reduced costs 25-35%

• Integrated decision-support

• Multiple local organizations

• Non-integrated decision support

• 13 global standardized marketing programs leveraged locally

• Product- and geo-specific marketing

IT

• 1 global CIO

• 5 global data centers

• 4,790 applications

• 128 Local CIOs

• 155 local data centers

• 16,000 applications

• Fully integrated R&D

• Collaboration with 50 organizations to build IP marketplace

• Multiple international R&D centers

• Local specialization with duplication

HR

• Global HR planning

• Standardization

• Local systems and management

• Local resource skill-set definition

GLOBAL INTEGRATION


IBM’S SUPPLY CHAIN TRANSFORMATION

Pain Points Transformation Approach

IBM’s supply chain was a fragmented cost center and not

critical to overall revenue.

Challenges included:

Pockets of integration in functional silos but no enterprise-

wide common process

Distributed and hard-wired to business units

‒ Non-electronic invoicing

Lack of shared measurements and end-to-end visibility

Non-consolidated transaction processing

Integrated supply chain together with shared measurements

to support end-to-end operation

Focused on client satisfaction along with operational results

Leveraged global scale by connecting suppliers online with

IBM’s international workforce

‒ Consolidated transaction processing in global delivery

centers

Introduced supply-chain business transformation outsourcing

capability

Integration Benefits

Business Operations Benefits Financial Benefits

Averaging $3.0 - 6.5B in procurement savings

every year for the last six years

Manages over $35B+ of spend for IBM across plus

over $20B spend on behalf of clients

Quality early Warning System saves $40M per year

Transformed from 36 plants and 300 Operations Centers to 9 plants and 5 Consolidated Global Operations Centers

35,000 suppliers connected online in 45 countries; 98% of invoices are electronic

Improved sales force productivity: now spending 38% more time with clients

100,000 Business Partners, 90+% of orders “touch-less”

Clients in 100 countries have self-service access to contract, order and inventory information


SOFTWARE DEFINED

SUPPLY CHAIN


3 NEW TECHNOLOGIES

3D PRINTING OPEN SOURCE INTELLIGENT

ROBOTICS


HARDWARE CONSTRAINED

BUILD A

MOLD OR

CAST

HARDWIRE

PRODUCTIO

N LINE

DEVELOP

EMBEDDED

CHIP

SOFTWARE DEFINED

PRINT PARTS

DIRECTLY BY

SOFTWARE

RECONFIGURE

ASSEMBLY

THROUGH

SOFTWARE

DIGITAL

CONTROLS USING

SOFTWARE


4 DIFFERENT PRODUCTS

COST

VOLUME

SIZE

COMPLEXITY

PERSONALIZATION

WASHING

MACHINE

INDUSTRIAL

DISPLAY

MOBILE

PHONE

HEARING

AID


3 AMAZING RESULTS

COST

SCALE

CO2 IMPACT


LOWER COST

23

% CHEAPER

AGGREGATE NORMALIZED UNIT COST


LOWER SCALE

90

% LESS

VOLUME

REQUIRED

AGGREGATE NORMALIZED

MINIMUM ECONOMIC SCALE


NOT NECESSARILY GREENER

100

89

33

100 9992

100 100 101100

120

109

0

20

40

60

80

100

120

140

2012 Traditional 2017 Digital 2022 Digital

AGGREGATE NORMALIZED

CO2 ANALYSIS

9% HIGHER

67

% LOWER


BIG

COMPLEX

GLOBAL

SMALL

SIMPLE

LOCAL


RECOMMENDATIONS FOR INDUSTRY


ibm.com/electronics

analytics in high tech electronics supply chain

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