Global Technology Outlook 2006guideitalia.org/files/6_G_Lanfranchi_IBM Global... · Analytics Characteristics of On Demand Embedded Software PervasivePervasive ... Dynamic Performance/Power

1

© 2002 IBM Corporation

IBM Research

Global Technology Outlook 2006 Do Not Distribute

Global Technology Outlook 2006

IBM Software Group | Tivoli software

2

Research and Development Laboratories

? Austin

Fujisawa

Yasu

? Beijing

? Delhi

Boeblingen

? ZurichLa Gaude ? Tokio

Yamato

? HaifaTucson

San Jose? Almaden

Santa Teresa

? ResearchHardware DevelopmentSoftware DevelopmentHardware and Software Development

Bangalore

Dublin

Hursley

Greenock

Rome

Endicott

East Fishkill

Burlington

Poughkeepsie

? Yorktown HeightsToronto

Rochester

Boulder

Raleigh

?Krakow

IBM Research

Global Technology Outlook 2006 Do Not Distribute © 2006 IBM Corporation 3

History of Innovations

IBM Research


U.S. Patent Leadership

800

1300

1800

2300

2800

3300

3800

1993 1995 1997 1999 2001 2003 2005

IBM Research


Global Technology Outlook

“I think there is a world marketfor maybe five computers.”

Thomas Watson, chairman of IBM, 1943

“Computers in the future may weigh no more than 1.5 tons. ”

Popular Mechanics, 1949

“There is no reason anyone would want a computer in their home. ”

Ken Olsen, founder of DEC, 1977

“640K ought to be enough for anybody. ”

Bill Gates, 1981

IBM Research


GTO Genetic Map

TechnologyTechnology

SW Dependability

SW Dependability Post 9/11Post 9/11 SW Quality/

SecuritySW Quality/

Security

StorageStorageModular SystemsModular Systems

Virtual IdentityVirtual Identity

Technology & Systems


Continual Optimization

Continual Optimization

Optimize to Survive

Optimize to Survive

Data & AnalyticsData &

Analytics

Characteristics of On DemandCharacteristics of On Demand

Embedded Software

Embedded SoftwarePervasivePervasivePervasivePervasive

Intelligent Infrastructure

Intelligent Infrastructure UtilitiesUtilities AutonomicAutonomic

Dynamic e-Business

Dynamic e-Business

Next Gen Web

Next Gen Web

On-Demand FrameworkOn-Demand FrameworkSW LayersSW Layers

Speak to ITSpeak to IT

Innovation in Services

Innovation in Services

Enterprise SW

Enterprise SW



MetadataMetadata

TechnologyTechnology TechnologyTechnology TechnologyTechnology

Legislation & Data

Legislation & Data

Stochastic Analysis &

Optimization

Stochastic Analysis &

Optimization

Pervasive Connectivity

Pervasive Connectivity

Architecture of BusinessArchitecture of Business

Intelligent InformationIntelligent

Information

People ProxiesPeople Proxies

TechnologyTechnology

Optimized Systems

Optimized Systems

Services 2.0Services 2.0

SW Evolution

SW Evolution

Event-Driven World

Event-Driven World

7


IBM Research


Technology Update

IBM Research


Passive Power Continues to Explode

?Power components:? Active power

? Passive power

• Sub-threshold leakage (source-drain leakage)

? Gate leakage

Po

wer

Den

sity

(W

/cm

2 )

0.010.110.001

0.01

0.1

1

10

100

1000

Gate Length (microns)

Active Power

Passive Power

1994 2005

Gate Length (microns)

Gate Leakage

IBM Research


Approaches to Overcome the Limits

LithographyCooling

Layout

Immersion Lithography

Innovation

Ultra-thin SOI

High K – Metal Gate Strained Silicon

Hitachi: Water cooled notebookJuly 2002

12-22 nm

Heavily doped, ultra-thin body

Micro-channel cooler

Contacts further from junction

Stress liner overlap increased

Speed optimized

29.5 nm Resolution

Materials& Structures

Silicon Germanium

IBM Research


Improving Performance

0.18um 0.13um 90nm 65nm

Technology Generation

0

20

40

60

80

100

Rel

ativ

e G

ain

in P

erfo

rman

ce

Innovation Scaling

? No longer possible by scaling alone? New Device Structures

? New Device Design point

? New Materials

Before 90’s1hydrogen

H

5

boron

B

8

oxygen

O

15

phosphorus

P14

silicon

Si

33

arsenic

As

13

aluminum

Al

IBM Research


Improving Performance

0.18um 0.13um 90nm 65nm

Technology Generation

0

20

40

60

80

100

Rel

ativ

e G

ain

in P

erfo

rman

ce

Innovation Scaling

? No longer possible by scaling alone? New Device Structures

? New Device Design point

? New Materials

Before 90’s1hydrogen

H

5

boron

B

8

oxygen

O

15

phosphorus

P14

silicon

Si

33

arsenic

As

13

aluminum

Al

Since the 90’s 7

nitrogen

N

9

fluorine

F

32germanium

Ge

22Ti22titanium

Ti

73Ta73tantalum

Ta

29

copper

Cu

29tungsten

W

17

chlorine

Cl

39yttrium

Y40

zirconium

Zr

72hafnium

Hf

23vanadium

V

41niobium

Nb

24chromium

Cr

42molybdenum

Mo

21scandium

Sc

75Rhenium

Re

43ruthenium

Ru

77iridium

Ir

45rhodium

Rh

27cobalt

Co

78platinum

Pt

45palladium

Pd

28nickel

Ni

57lanthanium

La

58cerium

Ce59

Praeseodymium

Pr

60neodymium

Nd62

samarium

Sm

63europlum

Eu

64gadollinium

Gd65

terbium

Tb66

dysprosium

Dy67

holmium

Ho

68erbium

Er69

thullium

Tm70

ytterbium

Yb

20calcium

Ca

38strontium

Sr

56barium

Ba

12magnesium

Mg

Beyond 2006

35Br35Bromine

Br30zinc

Zn

83bismuth

Bi

6carbon

C

2

helium

He

54

xenon

Xe

IBM Research


Moving to an Ultra-Low Voltage Operating Point

~10x

~3x

~10x

~3x

1E+12 1E+13 1E+14 1E+15 1E+16

Total Logic Transitions / sec

0.1

1

10

Load

ed S

witc

hing

Ene

rgy

(fJ)

Energy vs Performance

10X power reduction for only 3X performance penaltyOperating point of today's

high perf. MPUs @ ~ 1V

Optimal power / performancepoint @ ~ 0.5V

IBM Research


Transition to 3D CMOS

Year of Announcement1950 1960 1970 1980 1990 2000 2010

Mod

ule

Hea

t Flu

x(w

atts

/cm

2 )

0

2

4

6

8

10

12

14

Bipolar

CMOS

? Op

po

rtu

nit

yfo

r 3D

Si

IBM Research


Random Local Variability is Becoming Increasingly Significant

Lot 1 Lot n

?Lot/wafer non-uniformity

?Tool/process variation

? In-line monitoring and process control

?Across chip variation (e.g., ACLV)

?Density effects

?Process and design compensation

?Convolution of multiple sources

?Design for robustness to variation

SystematicLocal

Global

RandomLocal

RandomRandom

Node

Variability ofMature Technology

120 nm 90 nm 65 nm 45 nm

Systematic

SystematicGlobalGlobal

IBM Research


AutonomicInfrastructure

Active Approach to Design for Variability: Autonomic Infrastructure

High-level Inputs

Workloadsimulation of

bandwidthdynamics

Analysis ofprocess

variability andnoise sources

SYSTEM IMPACT:

Monitor / Analyze / Plan / Execute (MAPE)

?Dynamic Performance/Power Optimization?Reliability Improvement?Yield Enhancement

Circuit/Macro Level

Chip/Module/Card/Rack Level

Simple Protocol

FirmwareCalls

CircuitBuildingBlocks

Hierarchical Control Data Exchange Layer

Fast loop

Intermediate loop

Slow loop

System Performance Request

Circuit

System Monitoring

Controller

Actuator Library(e.g. Vdd, Frequency,

Back gate biasing, Functional unit control)Sensor Library

(e.g. supply noise, Vth)

IBM Research


Industry Implications

?Power and variability continue to be the two principal concerns facing semiconductor industry

?CMOS performance gains will continue for the next ten years through the incorporation of new materials, innovative process integration, and tailored layouts

?Ultra-low voltage devices and circuits will emerge enabling 3D silicon integration with attendant density scaling

?Packaging technology will continue to grow in importance as devices structures increase in complexity

?Increasingly on-chip sensing and monitoring for improved variability control and yield will be the norm

17


IBM Research


The Event-Driven World

IBM Research


The Event-Driven World

• Billing• Security• Fraud alerts• Retrospective

processing

Location Based Service (Traffic)

RFID-enabled Checkout

Intelligent Oil Field

ENRON Chairman

indicted……

..

Fraud/Compliance

Surveillance RFID-enabled Scanning

VoIP, VoD, IMS, etc.

IPv6 Map

IBM Research


Surveillance

Financial

Market Data

RFID Data

Rich Media

TDDB

DBMSDB

Data Warehouse

General Framework for Time-Dependent Event Handling

Event ActionEvent Analysis

Event Notification

Event-based Engine

An event-based engine routes, sequences, and filters event data in a time-dependent fashion

TD: Time-dependent

Continuously Analyze Event

Streams

Identify Patterns of Interest

Selectively Notify Systems

& Personnel

IBM Research


Sensor Analytics Sensor Analytics

Person entering restricted tunnel

Abandoned bag on platform

Stamford, CT Newark Airport, NJ

Alert: Potentially Coordinated Attack

Surveillance Example

Pub/Sub Client

Pub/Sub Client

Messaging Hub

Messaging Hub

Event AnomalyDetection

Event AnomalyDetection

DBMS

Suspicious Activity Detection ~ 1 sec

Correlation of Suspicious

Activity ~ 20 sec Distributed Event Miner

IBM Research


Defense, Intelligence, and Homeland Security

Straight Through

OLTP

OLAP

Data Mining

Data Fusion

Message Transformation

Filtering

Emergence of Intelligent Event-Driven Applications

Fra

ud

Man

agem

ent

?s ms sec min hr

Sec

uri

ties

Tra

din

g S

yste

m

Inte

llig

ent

Oil

Fiel

d

Business Intelligence

(OLAP)


(Data Mining)

E-c

om

mer

ce

tran

sact

ion

s

Lo

cati

on

Bas

ed S

ervi

ce,

Pre

sen

ce, S

IPR

FID

Har

d R

eal-

Tim

e

Sof

t R

eal-

Tim

e

Nea

r R

eal-

Tim

e

Processing Complexity

Processing Latency

IBM Research


Defense, Intelligence, and Homeland Security

Fra

ud

Man

agem

ent

?s ms sec min

Sec

uri

ties

Tra

din

g S

yste

m

Inte

llig

ent

Oil

Fiel

d


(OLAP)


(Data Mining)

E-c

om

mer

ce

tran

sact

ion

s

Lo

cati

on

Bas

ed S

ervi

ce,

Pre

sen

ce, S

IPR

FID

OLAP (Teradata, DB2, Oracle)

Mes

sag

ing

ES

B

OLTP (DB2, Oracle, SQL Server)

Time-Dependent

Event-Driven Middleware

Straight Through

OLTP

OLAP

Data Mining

Data Fusion

Message Transformation

Filtering

Emergence of Intelligent Event-Driven Applications

Processing Complexity

Processing Latency

hr

IBM Research


Current and Emerging Players

Event Engine

Accelerator

Real-time Database

Real-time JVM

Informix RTLReal-time JVM

IBM Research


Data Source N

Data Warehouse

ETL

Data Source 1

Reference Architecture for Event-Driven Middleware

DBMS

App 1 App N

Short-term storage

Long-term storage

…Intelligent, Time-

dependent, Pub/Sub, and Routing Hub

…

DB Tradeoffs for Event-Handling

1. Latency for Consistency

2. Throughput for Persistence

ESB responsible for:

?High-throughput data handling

?Low-latency messaging and routing

IBM Research



?The real world is being captured (through sensors) and modeled at increasing spatiotemporal resolution

?On demand businesses will need to evolve to deal with (monitor, process, store, and respond) the increasingly event-driven world

?New middleware, programming models, and tools will emerge to deal with the increasing volume and time-dependent requirements of event-driven data

?SOA will be augmented with event orientation and processing, resulting in a hybrid between a web service and an event programming model

26


IBM Research


Application-Optimized Systems

IBM Research


Application-Optimized Systems

GTO 2006Application-Optimized

Systems

?Customizable? Flexible?Easy to program? Low TCO?Manageable ?Standards based?Multi-threaded?Accelerator enabled?Power frugal

Virtual Middleware

Virtual OSVirtual Engine

New Apps

We are entering a new era of “application-optimized computing” with 10-100X in performance advantages enabling a whole new class of applications

Data source: Competitive Analysis Technical Team (CATT)

Dense Server Chip

GTO 2001Modularity

ext cachecontroller

memctrl

PPC core

PPC core

PPC core

PPC core

64bPPCCore

Transaction Server Chip

Game Chip

cmp / recover

ext cachecontroller

Growable L2 Slice

jtag / SP Fast I/O

memctrl

PPC core

PPC core

PPC core

Game Chip

special arithmetic

processorsHigh BW graphics interface

High BW memoryinterface

I/O

PPC core

GTO 2003Scale-OutBladeCenter

GTO 2003Virtual Computer

1998 2000 2002 2004 2006 2008

Production Date

20

200

FPG

IBMIBM-SF

IntelTSMC

100

RecentHistorical

Trend

GTO 2004 Device Performance Roadmap

IBMIBM-SF

IntelTSMC

IBM Research


Modularity At All Levels is Enabling a New Era of Application-Optimized Systems

A A A A

A A A A

C

CC

CC

CC

C C

C

C

C

L2 Cache

C

C

L2Cache

L2 Cache

Multi-threads, Multi-cores, Specialty cores, Accelerators,

Busses, I/O

Chip Level

SoC design, Compilers, Libraries

Operating systems, Middleware,

Management tools

Subsystem LevelMemory,

I/O subsystem,Specialty blades

ManageCustomers

Strategy

Tactics

Execution

Merchandising Store/Channel Operations

Supply Chain &Distribution

FinanceAdministration

BusinessAdministration

Business Perf. Mgmt.

External Market Assessment

Legal and Regulatory

Indirect Procurement

Real Estate, Facilities and

Equipment

HR Administration

Corporate Finance and

Controls

Customer Insights

Vendor and Product

Performance Execution and Management

Distribution Center

Transportation Resources

Product Directory

Accounting and GL

Outbound

Logistic s

Store/Off -site Services Execution

Inventory Planning

Channel, Category Strategy and Planning

Assortment and Space Planning Management and Execution

Supply Chain

Strategy and Planning

Financial Management and Planning

Organization and Process Design

Corp. Planning

Alliance Management

Line of Business Planning

Develop and Operate IT Systems

Distribution Oversight

Market Risk Management

Customer Relationship Planning and

Strategies

Product Planning,

Development & Pricing

Strategies

Customer Insights

Vendor Relationship

Strategies

Assessing Customer

Satisfaction

Matching Supply and

Demand

Order Management

Customer Account Servicing

Item Management

Treasury

Store Operations

Management


Event, Promotion


Customer Directory

Inventory, Product Tracking and Tracing

Operations Back Office

Financial

Outbound Logistics

Store/Channel Design and

Layout

Store/Channel Labor

Strategy

Store/Channel Objectives &

Strategy Planning

ManageCustomers

Strategy

Tactics

Execution

Merchandising Store/Channel Operations

Supply Chain &Distribution

FinanceAdministration

BusinessAdministration

Business Perf. Mgmt.

External Market Assessment

Legal and Regulatory

Indirect Procurement

Real Estate, Facilities and

Equipment

HR Administration

Corporate Finance and

Controls

Customer Insights

Vendor and Product

Performance Execution and Management

Distribution Center


Product Directory

Accounting and GL

Outbound

Logistic s

Store/Off -site Services Execution

Inventory Planning

Channel, Category Strategy and Planning

Assortment and Space Planning Management and Execution

Supply Chain


Financial Management and Planning

Organization and Process Design

Corp. Planning

Alliance Management

Line of Business Planning

Develop and Operate IT Systems

Distribution Oversight

Market Risk Management

Customer Relationship Planning and

Strategies

Product Planning,

Development & Pricing

Strategies

Customer Insights

Vendor Relationship

Strategies

Assessing Customer

Satisfaction

Matching Supply and

Demand

Order Management

Customer Account Servicing

Item Management

Treasury

Store Operations

Management


Event, Promotion


Customer Directory

Inventory, Product Tracking and Tracing

Operations Back Office

Financial

Outbound Logistics

Store/Channel Design and

Layout

Store/Channel Labor

Strategy

Store/Channel Objectives &

Strategy Planning

5.6 GF/s, 4 MB

2 processors

2 chips, 1x2x14 processors

11.2 GF/s1.0 GB

16 compute cards(16 compute, 0-2 IO

cards)64 processors

180 GF/s16 GB

32 Node Cards2048 processors

5.6 TF/s512 GB

20 KWatts1 m2 footprint

64 Racks, 64x32x32131,072 processors

360 TF/s32 TB

1.3M Watts

SystemRack

Mode Card

Compute Card

Chip

Business processesSystem LevelBusiness Level

Web Services, SOAEnterprise Service Bus

System level design,Protocols

Processor blades/drawers/racks

IBM Research


Examples of Application-Optimized Systems At All Levels

BlueGeneCell Applications?Protein folding?DOE applications?Modeling of

neocortex

Applications?Gaming ?3D rendering

BladeCenterApplications?Networking blades?Search blades?XML blades?Cell blades

IBM Research


Example: Computed Tomography (CT)

Image whole heart in 1 rotation

4D CT –includes time

2 slices 4 slices 8 slices 16 slices32

slices

64

slices

128

slices

256

slices

Current CT Products Future CT Products

1. Faster rotation speeds = more data, faster

2. More slices per rotation = more data, faster(# of images per study increased 10X in last 24 months)

3. Will lead to more computer aided detection and/or diagnosis

ALL 3 drive demand for compute power and for medical imaging, real time imaging, and functional imaging

Opportunity for integration of hardware accelerators with CT devices and software systems

IBM Research


Simplified Systems Management Remains Key Challenge for Scale-Out

Server Spending

Management and Server Spending Outlook

ManagementSpending

20406080

100120140160

‘96 ’98 ‘00 ’02 ’04 ’06 ’08Source: IDC, 2004

Spending($B)

?Hardware costs have been decreasing due to? Moore’s Law? Scale-out

? Scale-out adds increased complexity? More operating systems to manage? Heterogeneous systems? Incremental resource additions? Version control ? Multiple policy levels

IBM Research


Virtualization Will Significantly Simplify Management

1970 1980 1985 19901975 1995 2000 2010

Integrated Virtual machine

S/ 360

DistributedClient / Server Model

2005

*PDS- IBM Research Project

Pervasive virtualization will be used to re-aggregate distributed systems into

virtual systems

Z-LPARS

Operating System

Server Clusters

Network

Storage

Middleware

Softricity

IBM PDS*

Xen

VMotion

Virtual Iron

VPN

IBM SVC

SAN.FS

VMware

IBM Meiosys

Processor / Memory

IBM PHYP

MS Virtual Partitions

VFrame

Applications

IBM EWLM

IBM Research


Spectrum of Virtualization

Resource virtualization and application virtualization are complementary and can co-exist

Complete isolation between OSsRun different OSsSmaller trusted computing base

Isolation only between AppsRunning 1 version of OSTrust depends on entire OS

Apps share common OS servicesSmaller containerLess context switching overhead

Only HW resources are sharedLarger containerMore context switching overhead

ServerVirtualization

Application EnvironmentVirtualization

PHYP,Xen,VMware

PDS, Softricity,Meiosys, Veritas Appscale

Hardware

OS 1

App App

OS 2

App App

Hypervisor

Runtime Environment

Runtime Environment

Hardware

OS

App App

Mediator

Runtime Environment

Runtime Environment

ShallowDeep

SharingLess More

Isolation

ResourcePartitions

Java VirtualMachines

CICS Regions

LPARS,PPARS

IBM Research


Pervasive Virtualization Drives IT Management Simplification

?Redistributing workloads to optimize performance/QoS, improved resource utilization

?Security and isolation through partitioning

?Provisioning new systems using pre-built images (freeze-dried stacks)

?Concurrently supporting incompatible environments

?Robust retention compliance through archive of entire system image (data, application, middleware, OS, etc.)

35


IBM Research


The Accelerating Evolution of Software

The Web

As

“The Platform”

IBM Research


Evolution of Enterprise ApplicationsE

nte

rpri

se A

pp

licat

ion

Evo

luti

on

60’s-80’s 90’s-00 00-10’s Time

Mainframe World

Client-Server World

Web Services Enabled World

Enterprise applications built by IT departments

Applications initially prototyped by LOBs, then rebuilt by IT departments

Applications built by LOBs and end-users, customizing and aggregating services as needed

IBM Research


Situational Application Example – Scipionus.com

Application built by one person in one day, leveraging Google maps web service

Legend:

– events

– changes

– 50 latest

IBM Research


Rapid Growth of Domain-Specific ServicesExamples of companies offering services on the web today, and growing …

Terrafirma

SForce

NDFD XML

Google Maps API

FedEx Tracking

Online Tracking

DHL Web Services

Search, Maps

USPS Web Tools

E-Commerce

Repository for boutique services

PayPal

IBM Research


Web 2.0 Meme (Web Culture)

The Web as

“The Platform”

Tools: RSS, AJAX, PHP,

Ruby

Services, not packaged software

Architectural participation

Small pieces loosely joined, or

“re-mixed”

Harnessing collective

intelligence

Software that gets better as more people use it

Standards: REST, XHTML

Techniques: Mash-up, wiki,

tagging, blogging

Rich user experiences

Light-weight programming

models

Zeitgeist of the current internet generation

IBM Research


Mash-up

List of stores

Google Map web service

NOAA Weather web service

Mash-up definition: from Wikipedia

Bastard pop is a musical genre which, in its purest form, consists of the combination (usually by digital means) of the music from one song with the a cappella from another. Typically, the music and vocals belong to completely different genres. At their best, bastard pop songs strive for musical epiphanies that add up to considerably more than the sum of their parts.

SAP order fulfillment

RSS feed of top-selling items

Wiki commands to compose application

IBM Research


Traditional and Situational Application Environments

Traditional (Transactional)

?Careful, formal change management?Slowly evolving

applications?Changes are major

?Handful of large applications on 100s of machines?Often dedicated – several

machines per application

?Structured design and programming?Code Review?Function test?Quality test?Performance test

Situational (Collaborative)

?Change management is a huge challenge?Rapidly changing

applications?Changes generally minor

?Thousands of small applications on handful of machines?Each machine has

hundreds of applications

?Unstructured programming?Little discipline?No formal test process –

using the application is test

Development, deployment, and management of situational applications contrast those processes used in traditional enterprise application development

ModelModel

AssembleAssemble

ManageManage

DeployDeploy

IBM Research



? Situational application development will become a dominant methodology for software development, initially in the web community and at the periphery of the enterprise – and ultimately across the extended enterprise

? Composite situational applications will represent the next generation of enterprise portal metaphors – from on-the-glass content integration (portlets) to on-the-glass application integration (mash-ups)

?While composite situational applications are each simple, the enterprise IT environment will continue to grow in heterogeneity and complexity due to the diversity of applications and their development paradigms

? The movement towards situational applications will accelerate the componentization of software – enterprise software, ISV applications, middleware, business services

? Enterprises will be pressured by LOB users to expose the functional interfaces of enterprise applications and refactor them into bite-size chunks in order to utilize new functionality provided by situational applications

? New end-user programming tools are emerging to enable the rapid discovery, customization, and integration of situational applications

43


IBM Research


Services 2.0

Service1

Service2

Service4

Service3

IBM Research


Broad Acceptance of Business ComponentizationExample: Auto Industry CBM

?CBM maps for all industries including 70 industry sub-segments

?225+ engagements across all industries?Over 1500 IBM services practitioners trained globally

Business Administration

Corporate/LOB Strategy & Planning

Organization & Process Policies

Alliance Strategies

Human CapitalManagement

Legal & RegulatoryBusiness

PerformanceIntellectual

Property

Building/Facilities

& Equipment

IT Systems& Operations

Knowledge & Learning

Financial Management

Capital Appropriation

Planning

FinancialPlanning &Forecasting

Risk Manage-ment & Internal

Audit

Treasury

TaxManagement

Accounting & General Ledger

CostManagement

Product/Process

Portfolio Strategy &Planning

Research &Development

Design Rules& Policies

ProgramManagementConfigurationManagement

DesignValidation

ChangeManagement

MechanicalDesign

In-vehicleSystem Design

Process Design

Tool Design& Build

SupplyChain

Supply ChainStrategy & Planning

DemandPlanning

SupplierRelationship

Planning

Supply ChainPerformanceMonitoring

SupplierManagement

LogisticsManagement

InventoryManagement

TransportationManagement

Procurement

Marketing& Sales

CustomerRelationship

Strategy

Sales & PromotionPlanning

BrandManagement

RelationshipMonitoring

Demand Forecast

& Analysis

DealerManagement

CustomerRelationshipManagement

OrderManagement

LeaseManagement

Direct

Control

Execute

Production

ProductionStrategy

ProductionRules & Policies

Master ProductionPlanning

ProductionScheduling

QualityManagement

PlantOperations

MaintenanceManagement

ProductionMonitoring

Service &Aftersales

Post Vehicle Sale

Strategy

WarrantyManagement

QualityManagement

End-of-LifeVehicle

VehicleService

PartsManagement

Strategic Differentiation

Competitive ParityBasic

Strategic

IBM Research


Linking CBM to SOA

?Build CBM enterprise model

?Trace component links

?Identify “hot” component

?Isolate for analysis

?Disaggregate into services elements

?Model the service elements

?Implement on SOA platform

Controlling

Executing

Directing Business Planning

Business Unit Tracking Sales Mgt

Credit Assessment

Reconciliation

Compliance

Staff Appraisal

Relationship Mgt

Sector Mgt

Product Mgt

Production Admin

Product Fulfillment

Marketing Campaigns

Product Directory

Credit Admin

Customer Accounts

GeneralLedger

DocumentManagement

Customer Dialogue

Contact Routing

StaffAdmin

BusinessAdmin

New Business Development

Relationship Mgt

Servicing & Sales

Product Fulfillment

Financial Control &

Accounting

Sector Planning

Portfolio Planning

Account Planning

Sales Planning Fulfillment Planning

FulfillmentManagement

SalesSalesSales

SOA Platform (ESB)

SWService

SWService

SWService

SWService

SalesService

1

Service2

Service4

Service3

Model the key service elements

IBM Research


Granularity of Business Services ElementsV

alu

e to

clie

nt

Granularity of offering

Many small componentsHigh cost of integration

A few large components Less flexibility

OptimizedFlexibility-cost balance

Cost affected by standards, availability,

legacy, skills, tools, quality,

technical factors

Large GrainSmall Grain

IBM Research


Services “Mash-Up”: Classic Disruptive TechnologyM

arket Need

s

Capability & Functionality

Time

Composable simple services

Small

Large

Medium

Traditional Enterprise Services

SMB market spawns the technologies that will ultimately disrupt the traditional enterprise market

IBM Research


Tools are Emerging for Efficiently Composing Complex Business Services

Client Interview Template ToolStructured and guided approach to collection of client

needs at business level

Solution ComposerBuilds composite service from service elements

? Application Configuration Tool? Creates a new customer instance with selected service

elements

? Interface Matching Tool? Automates creation of translation to client systems

? Cost Estimator? Provides cost estimate for contract

Social Network Analysis Tools Surfaces informal relationship assets

IBM Research


Social Network Analysis (SNA) Tool Example

Source: Rob Cross, McIntyre School of Commerce, University of Virginia, http://www.robcross.org/

? Insights from SNA

? Organizational charts may not show how work really gets done

? Senior executives not always central

? SNA can reveal problems:

? Central person could be overworked

? Risk to organization if central person goes away

? Peripheral people can represent untapped knowledge

Social network analysis reveals hidden connections providing an “organizational X-ray”

IBM Research


Composing Services: From Art to EngineeringMoving from a customized approach to a standard configured approach

Informal processes hidden

Manual integration of service elements

Personnel dependent asset reuse

Expertise driven costs and resources estimation

Isolated service assets

Ad hoc requirements gathering

Customization for each service implementation

“Art” “Engineered”

Relationships assets managed

Assisted mapping of service elements

Systematic and consistent asset reuse

Model-based cost and resource estimation

Composable service assets

Structured and guided requirements gathering

Configuration of service offerings

IBM Research


Extending the Reach of Business Terms

IT Platform

“Codify business rules in IT terms”

Business Processes

If (..)Then (..)Else (…)

“IT” terms

“Business Terms”Web 2.0Business Services Mash-up

Web 2.0 and business services mash-ups will codify application logic in business terms and accelerate the move to SOA

Existing ISV Applications

Open, Modular Business Services

Web Services Platform

Standards

52


IBM Research


GTO & the Rome Lab

IBM Research


Rome Lab focus on GTO?Tivoli Dynamic Workload Broker

?New generation of event based scheduling?Virtualization of resources for the scheduled job execution?Service based scheduling (adapters based on web services) The Web

As“The Platform”

?Tivoli License Compliance Manager?End-user notification of non compliance to entitled licenses ?Discovery of virtualized resources -Handling of licensing models in virtualized environments ?Componentization and exposure of reusable functions through Web Services

The WebAs

“The Platform”

?Progressive Deployment System?Pre-installation of OS, applications and prereq middleware in a virtual sand-box

?Tivoli Provisioning Manager?Orchestration – Event driven provisioning of Software, OS, Storage, Network (US OPEN Web Site Orchestration)?Provisioning of Software Stacks (Applications, Middleware) - Bare metal OS Provisioning ?Web services interface - OPAL publishing of Out-of-the-Box Automation Packages

The WebAs

“The Platform”

?Network Interactive Content Access?e-Commerce solution to publish and sell on the Web

?Rome Solution Lab?Designing an ESB based architecture for Energy & Utilities companies?Modular services approach to meet customer business needs Service

1

Service2

Service4Service

3

?Rome Services Lab?Adoption of Component Infrastructure Roadmap tool to design modular solutions for customer business requirements -Product-oriented service packaging for a modular offering

Service1

Service2

Service4Service

3

Global Technology Outlook 2006guideitalia.org/files/6_G_Lanfranchi_IBM Global... · Analytics Characteristics of On Demand Embedded Software PervasivePervasive ... Dynamic Performance/Power

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