Multi-channel Retail

Retail 2.0 “Perfect Store”

Business Model

Multi-channel Retail

Retail 2.0 – Perfect Store

RETAIL MERCHANDISING

Sales Analysis – Retail Data Warehouse

Retail Proposition – Store Tier / Clustering

Product Catalogue – Master Data Management

In-store Systems – EPOS (Tills) and SEL (Label Printing)

Planning and Forecasting – Provisioning and Replenishment

Multi-channel Retail Architecture – In-store, Catalogue, On-line, Mobile

Category Management - Product Assortment and Mix, Shelf / Space Planning.

Retail Marketing – Customer Profiling and Segmentation – Offers, Promotions and Campaigns

Customer Centric Retailing - “Customer First” – Customer Loyalty, Offer, Experience & Journey

Si nous faisons la même vieille chose, de la même vieille manière, nous obtiendrons toujours les mêmes vieux résultats…..

Retail 2.0 “Perfect Store” Domains

RETAIL 2.0

DOMAINS

BUY MOVE SELL Planning and

Forecasting

Procure Provision

and

Replenish

Logistics Customer

Management

Channels Marketing Retail

Operations

Head Office

Future

Management

Strategic

Foresight and

Future Studies

Sustainability

Renewable

Resources

Future Logistics

Landscape

Social Anthropology

Ethno-graphics

Demographics

Future PDA Hand

Held Device and

Smart Device

Propositions

Future Retail

Markets and

Opportunities,

Future Retail

Landscape

Future Retail

Policy and

Legislation

Strategy and

Planning

Store Tiers /

Clustering

Product

Assortment and

Mix

Vendor

Management

Strategy

Category

Management

Strategy

RFID

Wireless

GPRS / UMTS

/ WAP

Hand Held Device

and PDA

Customer Insight

and Loyalty Strategy

Mass Customisation

Micro-marketing

Channels Strategy

MVNO / MVPN

Propositions

Smart Devices -

Planning and

Transition

Retail

Proposition and

Customer Offer,

Customer

Experience and

Journey,

Governance,

Reporting and

Controls

IFRS

SOX

Business

Operations

Planning and

Demand

Forecasting

Contracts and

Framework

Agreements

Purchasing

Schedules and

Call-off

Inventory and

Provisioning

Logistics

Operations

Value Chain

Management

Customer

Management

Business Operating

Model (BOM)

Channels Business

Operating Model

(BOM)

Offers and

Promotions

Management

Product /

Category

Management

Retail Operations

Business

Operating Model

(BOM

Value Chain

Management

Retail

Performance

Reporting, and

Management

DWH

BI

Analytics

Architecture Planning and

Forecasting

Architecture

Vendor

Management

and

Procurement

Architecture

Inventory,

Provisioning

and

Replenishment

Architecture

Supply Chain,

Architecture

Customer Domain

Architecture

Channel

Architecture

PLCM / CRM

Architecture

EPOS / Retail

Merchandising

Architecture

Financials,

Reporting and

Analytics

Architecture

Solution

Architecture

Planning and

Forecasting

Solutions Design

Procurement

Solution Design

Inventory,

Provisioning

and

Replenishment

Solution Design

Supply Chain,

Solution Design

CRM Systems

Call Centre and

Contact Centre

Solution Design

Channel; Access

Solution Design

PIMS and

Campaign

Management

Architectures

EPOS / Retail

Merchandising

Solution Design

Performance

Management

DWH and BI

Systems

Management

Planning and

Forecasting

Systems

Manugistics,

Quantum

Procure-to-Pay

Systems

JDA Retail

Oracle Retail

SAP IS / Retail

Provisioning

Systems

JDA Retail

Oracle Retail

SAP IS / Retail

GIS Mapping and

Network Gazetteer

Supply Chain

Systems

CRM Systems

Call Centre and

Contact Centre

Systems

Content

Management

e-commerce

Systems

PIMS / CRM

and Campaign

Systems

JDA Retail

Oracle Retail

SAP IS / Retail

EPOS / Retail

Salas Systems

and CRM

Systems

Record-to-Report

Systems

JDA Retail

Oracle Retail

SAP IS / Retail

IBM FileNet, EDM

Infrastructure

Management

Retail

Infrastructure

Monitoring and

Control

Warehouse and

Distribution

Automation

Multi-media Channel

Access and

Fulfilment

Multi-media Channel

Access and

Fulfilment

Business Continuity

On-demand

Computing and

Shared

Services

EPOS Network

Infrastructure

Monitoring and

Control

Desktop Services

Client Inventory,

Provisioning, Help

Desk and Support

Key Basic Industry Sector Familiarity /

Understanding

Good Segment Understanding / Previous Experience Current Segment / Business Unit Knowledge

Fast Fashion Retailing and Digital Brand Management

FAST FASHION RETAILING and BRAND MANAGEMENT

In Europe, consumer spending through the recession has been re-focussed on either Value Brands or Luxury Goods

Marques - squeezing revenue and profit out of Retailers with mid-market Retail Propositions and traditional middle-of-the-road

Branding Strategies. Traditional Fashion Retailers have two seasons – Spring / Summer and Autumn / Winter - where popular

lines are retained year-on-year. Fast Fashion Retailers (New Look, Primark, Next - where Fast Fashion lines are only

available in-store for a few days or weeks, and Fast Fashion items are not subsequently repeated – unless they are popular

enough to become Standard Lines) are growing fast – mostly at the expense of those conventional retailers with traditional

Spring / Summer and Autumn / Winter Seasons which often feature “signature” popular repeatable standard core lines -

always available in-store, season on season, year on year.....

Fast Fashion and Luxury Goods Retailers are now under intense competitive pressure to drive down costs by adopting a

more Lean / Agile Supply Chain Model (a la mode de Wal-Mart), and by improving Supplier Relationships and Strategic

Vendor Management. Fast Fashion Retailers are also required to be better at exploiting On-line and Mobile Sales Channels -

which are growing much faster than traditional In-store and Catalogue Channels. Customers still like to mix-and-match Sales

Channels - unwanted items purchased On-line are often exchanged In-store for replacement or refunds.

Consumers are becoming increasingly better educated. Across many urban conurbations in the Southern part of the UK,

young people purchase cheap fashion items frequently and in large numbers - these items are worn for a single season (or

until they fall apart.....) and are viewed by consumers almost as disposable items. Young consumers with similar disposable

incomes in major Cities in Scotland and Northern Italy, for example - will spend the same amount of money in a season on

just a few items chosen very carefully from Luxury Goods Brands – and then keep them in their wardrobe for many years.....

The sudden proliferation of pervasive Smart Devices communicating via the Smart Grid with the Cloud indicates that we may

have just witnessed the beginning of a startling new episode in technology driven consumer behaviour – the advent of the

always-on digital connected society – Smart individuals living in Smart households within the Smart Cities of the future. Smart

Phones such as the Apple iPhone, HTC Desire, Google Nexus One, Windows Phones – are enabling innovative and engaging

Customer Experience and Journey Stories, both in-store and mobile, including Social Media Conversations..

Luxury Goods Retailing and Digital Brand Management

LUXURY GOODS RETAILING and BRAND MANAGEMENT

Luxury Goods companies have traditionally targeted two primary “old money” customer segments – affluent

fashion-conscious socialites (age range 25-35) who follow the skiing, sailing and social seasons in major cities and

exclusive resorts in either Europe or America - and retired or semi-retired individuals (age range 55-65) who have

created and accumulated significant wealth during their Business and Professional careers – and who now have

significant time and money available to devote towards their interests and leisure pursuits. Families are raised in

the Gap Years (age range 35-55).

Many familiar Luxury Goods brands now belong to just a few Luxury Brand Aggregators such as French PPR, and

Louis Vuiton Moet Hennessy (LVMH) – along with the Swiss luxury goods conglomerate Richemont. In any

economic downturn, these Brand Aggregators are no longer able to drive increased growth sufficient to meet their

Shareholder expectations or maintain volume targets from Business Partner / Stakeholders, in traditional Markets

and Customer Segments – and so are forced to expand their Market Coverage, Product Ranges and Brand

Footprints (and at the same time risk suffering the dual unforeseen consequences of erosion of Product

positioning, desirability and cache – along with the dilution of core Brand recognition, perception and value).

Today, the new Luxury Goods marketing focus has turned towards two “new money” customer segments - newly

wealthy individuals in the emerging economies of the BRICS;s (Brazil, Russia, India and China) – and young

Media and Entertainment Professionals and Elite Team Sports Athletes (age range 20-30) in the West. Goldman

Sachs forecast that China will be buying one 3rd of the world's luxury goods in under a decade,,,,,

• Young Media and Entertainment Professionals and Elite Team Sports Athletes (age range 20-30)

• New, Emerging and Developing Markets for Luxury Goods– Brazil, Russia, India China (the BRICs) •

Multi-channel Retail - Strategy

Multi-channel Retail

Strategy Development

Strategy Development and Business Transformation

1. Business Strategy 1.1. Business Innovation

- Manufacturing, Procurement, Logistics

- Products and Services

- Partners and Channels-to-market

- Retail Proposition and Customer Offer

- Customer Experience and Journey

- Service Delivery Channels

- Service Management

1.2. Strategy Discovery - Business Drivers, Mission, Strategy

- Outcomes, Goals, Objectives

1.2. Strategy Development - CSF’s, KPI’s, Business Metrics

- Strategy Packs

2. Business Transition 2.1. Business Transition Planning

2.2. Business Process Design

2.3. Business Programme Planning

2.4. Business Change Management

3. Organization Management

4. Human Resource Management

5. Business Operating Model 5.1 Operational - Process Execution, Integration and

Orchestration

5.2 Tactical - Analysis, Reporting and Communication

5.3 Strategic - Command, Control and Co-ordination

6. Business Process Outsource 6.1. Business Process Outsource Planning

6.2. Business Process Outsource Transition

7. Business Process Management 7.1. Business Process Re-engineering

7.2. Continuous Process Improvement

8. Enterprise Performance Management

9. Business Programme Management 9.1. Benefits Realisation

9.2. Communications

9.3. Stakeholder Management

10. Project Portfolio Management 10.1. Resource Management

- Programmes, Projects, Work Streams

- Deliverables, Milestones

- Activities, Tasks, Resources

11. Enterprise Portfolio Management 11.1. Function Library

11.2. Service Catalogue

11.3. Application Inventory

11.4. Infrastructure Portfolio

12. Technology Planning & Strategic Investment 12.1. IS / IT Strategy

- Strategic Architectures & Technologies

- Strategic Vendors & Products

12.2. IS / IT Architecture - Blueprints, Roadmaps, Transition Planning

12.3. Technology Planning - Platform Replacement

- Technology Refreshment

12.4. Strategic Investment - Key Technology Enablers & “Quick Wins”

EA-envision: The Enterprise Framework for Business Transformation

Strategy Development Topics Business Transformation Topics

Retail 2.0 “Perfect Store”

Strategy Development

Retail Proposition

Customer Profiling

Customer Segmentation

Customer Offer

Customer Experience

Customer Journey

“Take hold of your future - or your future will take hold of you…..” (Patrick Dixon - Futurewise. 2005)

CRM Strategy

Social Media Strategy

Customer Loyalty

Customer Insights

Offers and Promotions

Customer Campaigns and influencer Programmes

Delivering the Customer Relationship Strategy & Vision

• Enhancing the Customer Experience and Journey via innovative Product and Service Differentiation: -

– Customer Profiling and Segmentation – profiling and allocating every individual Customer to a specific Segment and Stream – and planning appropriately to service those Segments and Streams.

– Micro-marketing – understanding the unique needs of every individual Customer (e.g. product / feature / function / option) – and responding appropriately to service those needs.

– Mass-customisation – packaging attractive product / service offerings (e.g. appliance / consumables / extended warranty) - to meet the unique requirements of specific Customer Streams and Segments.

– Contact Centre Management - capturing every inbound/outbound contacts from every direct/indirect source

– Information Discovery – identifying trends, patterns and hidden relationships in the Enterprise Data Warehouse

– Customer Insight – Using Customer Profiling and Segmentation, Social Media, geo-demographic and other behavioural data for Propensity Modelling, defection/churn detection, and up/cross-sell

– Campaign Management – responding to Customers according to their needs – customisation / personalisation

The Retail Cycle

Source /

Purchase

‘Buy’

Provision /

Replenish

‘Move’

Merchandising

/ Multi-channel

Retail / POS ‘Sell’

Analysis /

Insight

‘Report’

Planning /

Forecasting

‘Plan’

Shared

Services

‘Support’

Head Office Functions Retail Operations

Buy – Move – Sell Plan – Support – Report

Procurement Logistics Merchandising Planning Support Analytics

Retail Cycle v. Retail Primitives

Product

Customer

Basket

Where?

Who?

What?

Store

Why? How?

When?

Motivation Sale

Time

Planning /

Forecast

‘Plan’

Source /

Procure

‘Buy’

Analysis /

Insight

‘Reporting’

Marketing /

Advertising/

‘Promote’

Supplier Location

What / Why? Where / How?

Provision /

Replenish

‘Move’

Merchandising

/ Retail / POS

‘Sell’

Category Tier

Head Office Functions Retail Operations

Customer

Channel Campaign

Promotion

Offer

Sourcing Site

Formulating the Retail Proposition & Customer Offer

• Formulating the Retail Proposition / Customer Offer.

– Retail Proposition – transforming the Retail Strategy into the Retail Proposition - Store Tier/Location cluster and Product Assortment & Mix

– Customer Centric Retailing – “Customer First” - using Social Media and Customer Insights to maximise customer satisfaction and revenue

– Customer Offer – offering customer segments the widest possible range of products and services of interest to them via a choice of multi-media contact channels, intermediaries and service access methods

– Brand Management – planning the customer loyalty strategy and publicising the Customer offer through Digital Brand Management

– Customer Loyalty – maintaining detailed Customer Information and discovering Insights through customer loyalty and brand management

– Customer Journey – planning the customer experience and journey through Customer Loyalty / Insight and Up-sell / Cross-sell Campaigns

– Customer Experience - ensuring consistency, quality and an attractive Customer Experience across every contact channel and social media site for a high quality, compelling and rewarding Customer Journey

The Eight Primitives

The Eight Primitives…..

Who – Customer

What – Product

Where – Location

Why – Campaign

When – Time

How – Payment Method

Which – Store Tier / Cluster`

Via – Sales Channel

What ?

Who ?

Basket

Location

Customer

Category / Product

Where ?

Motivation Payment Method

Time

Why ? How ?

When ?

Retail Fact Table

Retail Dimension Tables

Via ? Which ? Sales Channel Store / Tier

Campaign

Offer / Promotion

The Eight Primitives v. Retail Dimensions

Product

Customer

Basket

Where?

Who?

What?

Location

Why? How?

When?

Motivation Sale

Time

Retail Fact Table

Retail Dimension Tables

Retail Dimensions

Customer – Who

Product – What

Location – Where

Campaign – Why

Time – When

Payment Method – How

Store / Tier Cluster – Which

Sales Channel – Via Channel Store Via ? Which ?

Retail Data Discovery

Product

Customer

Basket

Where?

Who?

What?

Store

Why? How?

When?

Motivation Sale

Time

Supplier Location

Category Tier

Channel Campaign

Promotion

Offer

Retail Entities Expanded…..

Product

Customer

Basket

Where?

Who?

What?

Store

Why? How?

When?

Motivation Sale

Time

Category

Supplier

Tier

Clustering

Classification

Sourcing

Location Site

Product

Assortment & Mix

Category Selection v. Store Tier

Region Type

Channel Campaign

Promotion

Offer

The Customer Domain

Customer

Basket

Stream

Segment

Streaming

Segmentation

Card

Issuer

Payment

Bank Cash

Finance

In-Store Internet

Channel

Sale

Call Centre

Geographic Demographic

Lifestyle Behaviour

Profiling

Retail Strategy Development

Product

Customer

Basket

Category

Supplier

Stream

Segment

Where?

Who?

What?

Store

Tier

Clustering

Streaming

Segmentation

Customer

Insight

Classification

Why? How?

Time

When?

Retail Proposition Customer Offer

Sourcing

Location Site

Product

Assortment & Mix

Motivation

Campaign

Selection Response

Contact

Promotion Offer

Advertising

Marketing

Contribution

Card

Issuer

Payment

Bank Cash

Finance

In-Store Internet

POS

Sale

Call Centre

Customer Experience Customer Journey

Visit Selection

Geographic Demographic

Lifestyle Behaviour

Category Selection v. Store Tier

• Awareness

• Interest

• Need

• Desire

Profiling

What

/ Why?

Where

/ How?

Customer

Service

Product

Support

CRM CEM

Big Data BI

PIMS

Analytics EPM

E-Retail Card

Services

Media

Services

DW/H ERP

Digital Transformation

Multi-channel Retail

Retail 2.0 Digital Transformation

Throughout eternity, all that is of like form comes around again –

everything that is the same must return again in its own

everlasting cycle.....

• Marcus Aurelius – Emperor of Rome •

Retail 2.0 Digital Transformation

Part 2

Part 4

Part 3

Part 1

Strategic Enterprise

Management Framework

Enterprise Target Operating

Model (eTOM)

Future Management

and Innovation Plans

Solution Architecture

Enterprise Architecture

Model and Roadmap

Enterprise Architecture

Business Programme

Plan / Project Plans

Infrastructure

Architecture

Business Operating

Model (BOM)

Business Architecture

Strategic Outcomes,

Goals & Objectives

Innovation, Research

and Development

Business Programme

Management

IS / IT Strategy

Technology Strategy

Systems Planning

Enterprise Governance,

Reporting and Controls

Infrastructure Planning

Business Planning

Organisation Structure

Retail 1.0 Strategic Foresight

Strategy Development

Organisational

Change

Enterprise Architecture

Framework

NGE – Next-

Generation

Enterprises

Collaborative

Business

Models

Service

Convergence I

Business

Transformation

Technology Change

NGA- Next-

Generation

Architectures

Enterprise

Application

Integration

Technology

Convergence I

Buy Move Sell

Smart

Devices

Mobile

Platform

Cloud

Services Retail 2.0

I

Transition - Retail 1.0 to Retail 2.0 “Perfect Store” Business Operating Model = Innovation I

Retail 2.0 “Perfect Store” – Architecture Landscape

Hybris / IBM WebSphere

SAP NetWeaver Pi and/ or IBM MQSI

SAP IS/Retail

SAP CRM

Stebo or IBM Product Centre

Internet

Contact

Centre

Mobile 3rd Party

E-commerce Platform

Integration Platform

Retail Platform

CRM Platform

Catalogue Platform

Internet

Contact

Centre

Mobile

3rd Party

ATG Dynamo Oracle Fusion Oracle Retail

Oracle CRM

Stebo or Kalido

Internet

Contact

Centre

Mobile 3rd Party

SAP Solution Architecture

Oracle Solution Architecture

Customer Loyalty

In-store Systems

Customer Loyalty

EPOS / SEL

Customer Loyalty

EPOS

Sales Channels

Fulfilment Channels

Sales Channels Fulfilment Channels

Sales Channels Fulfilment Channels

In-store

Home

Delivery

In-store

Home

Delivery

In-store

Home

Delivery

Retail 2.0 “Perfect Store” Multi-channel Enterprise Architecture

Data Warehouse

Head Office Shared Services

BI / BO / BW HANA

SAP ECC7, ERP

Oracle OBIE

Oracle e-Business

Suite

Social Media Real-time Analytics

Mobile Platforms

Cloud Digital Channels Social Media

Conversations

PS0004

Shelf / Space

Allocation

PS0001 Customer Offer

PS0002 Retail

Proposition

PS0003

Pricing

PS0019 Marketing

Communications (Advertise)

PS0012 Customer

Segmentation

PS0009 Global CRM

PS0011 Marketing Services -

(Analysis and Research)

PS0010 Customer

Experience and Journey

PS0006 Product

Assortment and Mix

PS0008 Forecasting and Replenishment

PS0007 Global Category

& Supplier

PS0021 Sales Analysis

and Value Chain Reporting

PS0022 Global Product

Sourcing

PS0023 Global Supply

Chain

PS0014 BUY

(Procurement)

PS0016 SELL Retail

Merchandising

PS0015 MOVE

(Logistics)

PS0017 Public Relations

PS0024 Global Shared

Services

PS0005

Business

Planning

PS00029

Analytics

PS0027

Social

Intelligence

PS0028

Digital Platforms

& Multi-channel

Retail

Digital Channels & Analytics

Retail Merchandising & Logistics Head Office

Customer Relationship Management

PS0018 Customer

Information & Services

PS0013 Customer

Loyalty

Customer

Services

PS0025

Global Product

Catalogue

PS0020,

Offers and

Promotions

PS0026

Local Product

Catalogue

Multi-channel Retail - Process Groups

Retail Architecture Roadmap

b

ERP Roll-out

Product Management

Customer Management

Prepare Blueprint Realisation

Current State Enterprise Application Integration

Implement

Requirements

Blueprint

Design

ERP PoC

Build

Rehearsals

Cut-Over

QUICK WIN – Product Information Management / Master Data Management

Validate PoC

Process Fitness Programme –Strategy Roadmap

PoC

Strategy

Plan

Mobilisation

Requirements

Blueprint MDM PoC

Plan

Design

Build

Implement

Requirements

Blueprint

CRM PoC

Strategy

Plan

Design

Build

Future State

Plan

Message Formats

EAI PoC

Requirements

EAI Platform

EAI-Build

EAI-Deploy

EAI Services

EAI-Design

Digital Product Lifecycle

Digital Product Lifecycle

Fast Fashion Retailing and Digital Brand Management

FAST FASHION RETAILING and BRAND MANAGEMENT

The fastest growing sales Channels for both Fast Fashion and Luxury Goods are Smart Apps on Mobile

Phones. Innovative new Retail Business Operating Models such as “Retail 2.0” and “Perfect Store” are driving the

development of these new Channels. For example, when a Customer enters a store, the Retailer of the Future can

detect and identify him from his Smart Phone Number, as the Customer accesses the In-store WiFi or WiMAX

Network Connection. Based on vast amounts of data describing in detail their intimate consumer behaviour – we

can alert the consumer to relevant In-store offers and promotions – based on Propensity Modelling –similar in

content and style to those offers and promotions the customer has responded to positively in the past When a

Customer Tweets that she is going to buy a “little black cocktail dress” – we can initiate a Social Media Conversation

.

Retail 2.0 and Perfect Store Business Operating Models and Customer Experience and Journey Business Value

Propositions are being driven by technology enablement such as Multi-channel Retail (eCRM), and Social Media

(sCRM), supported by SMAC Digital Technologies – Social Media, Mobile Platforms - Smart Apps and Mobile

Devices, Data Science, Big Data and Real-time Analytics @ Point-of-Sale: -

• Retail Business Models – “Retail 2.0” • “Perfect Store” •

• Retail Strategy – Retail Proposition • Channels • Media •

• Business Value Propositions – Customer Offer, Experience and Journey •

• Mobile Technologies – Mobile Computing • Smart Devices • Smart Apps •

• Customer Strategy – Customer Loyalty • Offers • Promotions • Campaigns •

• Retail Business Transformation – New Social Structures • Cultural Change •

• Emerging Technologies – Real-time Analytics @ POS • Smart Grid • Cloud Services

• Social Marketing – Internet Intelligence • Product Placement • Crowd Sourcing Events

• Fulfilment – Service Access • Service Brokering • Service Provisioning • Service Delivery

Luxury Goods Retailing and Digital Brand Management

LUXURY GOODS RETAILING and BRAND MANAGEMENT

Increasingly, many Luxury Brands are also launching more accessible entry-level Product Ranges in order to attract

younger, technically-savvy and fashion-aware mass-market consumers - to introduce them to a Lifestyle Experience

and Journey that creates brand loyalty and lock-in with entry-level Luxury Goods Product ranges. As these young,

mobile consumers careers develop and they begin to generate increased disposable income they also begin to

purchase "big-ticket" Luxury Goods items from their favourite Design Guru or Lifestyle Icon.....

• Mass-market younger, technically-savvy and fashion-aware consumers

• Entry-level Luxury Goods Product Ranges – Perfume, Cosmetics, Casual Wear, Sporting Goods

Retail 2.0 and Perfect Store Business Operating Models and Customer Experience and Journey Business Value

Propositions are being driven by technology enablement such as Multi-channel Retail (eCRM), and Social Media

(sCRM), supported by SMAC Digital Technologies – Social Media, Mobile Platforms - Smart Apps and Mobile

Devices, Data Science, Big Data and Real-time Analytics @ Point-of-Sale: -

• A winning Customer Contact Strategy to reach out to your target audience

• A stunning Customer Experience to engage and retain your target audience

• Understanding of Customer Profiling and Segmentation - to define your niche

• A unique Customer Offer and Journey to instil desire for your Ranges and Lines

• An enthralling Customer Experience to cultivate Consumer aspiration and desire

• An amazing Customer Journey Storyboard to grasp and keep Consumer attention

• A compelling Retail Proposition / Channels / Media to leverage Customer interest

• A mastery of Smart Devices • Smart Apps • Cloud Services to engage your Customer

• Total perfection of Product and Service Delivery Management for Consumer Fulfilment

• Influencer Programmes - the ability to turn Fashion Blogs into Revenue – to transform Clicks into Cash.....

Digital Product Lifecycle Strategy

• Everything that goes around, comes around – everything has its’ own

lifecycle, in its’ own time. Things are born, grows, ages, and ultimately

they die. It’s easy to spot a lifecycle in action everywhere you look. As

a person is born, grows, ages, and dies – then so does a star, a tree, a

bird, a bee, or a civilization – and so does a company, a product, a

technology or a market - everything goes around in a lifecycle of it own.

Digital Product Lifecycle Strategy

• Everything around us has a lifecycle. It is born, it grows, it ages, and it ultimately dies.

It’s easy to spot a lifecycle in action everywhere you look. As a person is born, grows,

ages, and dies – then so does a star, a tree, a bee, or a civilization – and so does a

company, a product, a technology or a market - everything has a lifecycle of it own.

• All lifecycles exist within a dynamic tension between system development and

system stability. When an entity is born, and during it’s early its development - it

has low stability. As it grows, both its development and stability increase until it

reaches maturity. After peaking, its ability to develop diminishes over time while its

stability keeps increasing over time. Finally, it becomes so stable that it ultimately

dies and, at that moment, it loses all stability as well.

• That’s the basics of all lifecycles. We can try to optimize the path or slow the effects of

aging, but ultimately every system makes this lifecycle progression. Of course, not

all systems follow a bell curve like the picture below. Some might die a premature

death. Others are a flash in the pan. A very few live long and prosper - but from

insects to stars and everything in between, we can say that all things comes into

being, grows, matures, ages, and ultimately fades away. Such is the way of life.

Digital Product Lifecycle Strategy

• Everything has a lifecycle. It is born, it grows, it ages, and it ultimately dies. It’s easy

to spot a lifecycle in action everywhere you look. As a person is born, grows, ages,

and dies – as does a star, a tree, a bee, or a civilization – and so does a company, a

product, or a market - everything has a lifecycle of it own.

Digital Start-ups – Launch-phase

Digital Product Lifecycle Strategy

Investment

Product

Lifecycle

Product

Design

Product

Launch

Product

Planning

Death

Plateau

Product

Maturity

Decline

Aging

Early Growth

Migrate

Customers

to new

Products

Withdraw

Innovation Prototype / Pilot / Proof-of-concept

Cash Cow Cease

Investment

Digital Product Lifecycle Strategy

• What do the principles of adaptation and lifecycles have to do with your business

strategy? Everything. Just as a parent wouldn’t treat her child the same way if she’s

three or thirty years old, you must treat your strategy differently depending on the

lifecycle stage. And when it comes to your business strategy, there are actually three

lifecycles you must manage. They are the product, market, and execution lifecycles: -

– The product lifecycle refers to the assets you make available for sale.

– The market lifecycle refers to the type of customers to whom you sell.

– The execution lifecycle refers to your company’s ability to execute.

• In order to execute on a successful strategy, the stages of all three lifecycles must be in

close alignment with each other. If not, like a pyramid with one side out of balance, it will

collapse on itself and your strategy will fail. Why? Because aligning the product, market,

and execution lifecycles gives your business the greatest probability of getting new

energy from the environment now and capitalizing on emerging growth opportunities in

the future. The goal of any digital product strategy is to get new energy from the

environment, now and in the future.) As we will see, aligning all three lifecycles also

decreases your probability of making major strategic product placement mistakes.

Digital Product Lifecycle

Strategy

• Each lifecycle please note that each stage blends into the next. Although every

lifecycle may have distinct stages, this is really only for convenience. There’s no

real, definitive, clean and clear break where you know when one stage has ended

and another begins. In addition, there are three basic prerequisites that you must

have before you can pursue any strategy.

• First, the strategy must be aligned with the company vision and values. Second, the

company must have or be able to get the resources – including staff, technology,

and capital – to execute the strategy. Third, the company must have or be able to

develop the core capabilities to execute the strategy. For now, I am going to assume

that you have all three prerequisites in place and that you’re currently acting on, or

about to act on, a strategy that meets these basic requirements.

Digital Product Lifecycle Strategy

Digital Failures – End-phase

Digital Marketing

The Fashion Cone™

The Fashion Cone™ – High Street / Designer / Luxury Brand Affinity

– turning Social Intelligence into Actionable Marketing Insights / Opportunities…

• Fanatics – (10%) Fashion Critics / Designers / Celebrities / Socialites / “Fashionistas”

• Enthusiasts – (20%) Fashion Consumers – spend up to 50% Disposable Income on Fashion

• Casuals – (30%) spend only on those Brands / Labels / Designers / Ranges that they like

• Indifferent – (40%) Once followed the brand - but have become disconnected over time…..

• Unconnected – no Brand Affinity; consume High Street / Discount Store / Charity Shop Items

FAST FASHION RETAILING and BRAND MANAGEMENT

In Europe, consumer spending is being re-focussed on either Value Brands or Luxury Goods Marques - squeezing out Retailers with mid-market Retail Propositions and traditional middle-of-the-road Branding Strategies. Traditional Fashion Retailers have seasons – Spring / Summer and Autumn / Winter - where popular lines are retained year-on-year. Fast Fashion Retailers (where Fast Fashion lines are only in-store for a few days or weeks, and Fast Fashion items are not subsequently repeated) are growing fast - at the expense of those conventional retailers with traditional Spring / Summer and Autumn / Winter Seasons which often feature “signature” popular repeatable core lines - always available, season on season, year on year..... Fast Fashion and Luxury Goods Retailers are now under intense competitive pressure to drive down costs by adopting a more Lean / Agile Supply Chain Model (a la mode de Wal-Mart), and by improving Supplier Relationships and Strategic Vendor Management. Fast Fashion Retailers are also required to be better at exploiting On-line and Mobile Sales Channels - which are growing much faster than traditional In-store and Catalogue Channels. Customers still like to mix-and-match Sales Channels - unwanted items purchased On-line are often exchanged In-store for replacement or refunds.

Retail 2.0 “Perfect Store” – Experience Digital Marketing – Fast Fashion

IBM WebSphere

SAP NetWeaver Pi and/ or IBM MQSI

SAP IS/Retail

SAP CRM

Stebo or IBM Product Centre

Internet

Contact

Centre

Mobile 3rd Party

SAP Solution Architecture

Customer Loyalty

EPOS / SEL

Sales Channels Fulfilment Channels

In-store

Home

Delivery

BI / BO / BW HANA

SAP ECC7, ERP

ATG Dynamo Oracle Fusion Oracle Retail

Oracle CRM

Stebo or Kalido

Internet

Contact

Centre

Mobile 3rd Party

Oracle Solution Architecture

Customer Loyalty

EPOS

Sales Channels

Fulfilment Channels

In-store

Home

Delivery

Oracle OBIE

Oracle e-Business Suite

Retail 2.0 “Perfect Store” – Multi-channel Architecture

E-commerce Platform

Integration Platform

Retail Platform

CRM Platform

Catalogue Platform

Internet

Contact

Centre

Mobile 3rd Party

Customer Loyalty

In-store Systems

Sales Channels Fulfilment Channels

In-store

Home

Delivery

Retail 2.0 “Perfect Store” Multi-channel Enterprise Architecture

Data Warehouse

Head Office Shared Services

Social Media Real-time Analytics

Mobile Platforms

Cloud Digital Channels Social Media

Conversations

Digital Marketing – Retail 2.0 Model

FAST FASHION RETAILING and BRAND MANAGEMENT

Consumers are becoming increasingly better educated. Across many urban conurbations in the Southern part of the UK, young people purchase cheap fashion items frequently and in large numbers - these items are worn for a single season (or until they fall apart.....) and are viewed by consumers almost as disposable items. Young consumers with similar disposable incomes in major Cities in Scotland and Northern Italy, for example - will spend the same amount in a season on just a few items chosen very carefully from Luxury Goods Brands - but keep them in their wardrobe for many years..... The sudden proliferation of pervasive Smart Devices communicating via the Smart Grid with the Cloud indicates that we may have just witnessed the beginning of a startling new episode in technology driven consumer behaviour – the advent of the always-on digital connected society – Smart individuals living in Smart households within the Smart Cities of the future. Smart Phones such as the Apple iPhone, HTC Desire, Google Nexus One, Windows Phones – are enabling innovative Customer Experience and Journey Stories, both in-store and mobile, including Social Media Conversations..

Retail 2.0 “Perfect Store” – Experience Digital Marketing – Fast Fashion

Multi-channel Retail Architecture

Multi-channel Retail

Retail Operations – Retail Merchandising and Logistics

Head Office – Finance, Planning and Strategy

Marketing – Customer Loyalty, Experience and Journey – Offers, Promotions and Campaigns

In-store EPOS – Internet – Home Delivery

Provisioning & Replenishment

In-store

Systems

Retail

Operations

Systems

ERP

Systems

Customers

Operations

Managers

Finance

Managers

Loyalty Mart

Financial Data Warehouse

CRM and

Marketing

Systems

Marketing

Managers

Multi-channel Sales Data

Warehouse

Marketing

Customer

Analytics

Reports

Retail

Multi-channel

Sales

Analysis

Operations

Warehousing &

Logistics

Reports

Head Office

Financial

Analysis

Reports

e-Commerce

Systems

Campaign Mart

Merchandising & Logistics Data

Supplier Data

Product Data

Stores Data

Merchandising

Inventory &

Provisioning

Reports

EPOS Data

Call Centre Data

Internet Data

Customer DWH

CRM Data

Retail

Managers

ERP Data

Catalogue

Systems

Planning &

Forecasting

Systems

“BIG DATA”

Retail and Logistics Data

Warehouse

Planning &

Forecasting

Systems

Apache Hadoop Framework

HDFS, MapReduce, MetLab, “R”

Catalogue Data

Autonomy, Vertical

Hadoop

SAP HANA

Digital Marketing – Retail 2.0 Model

FAST FASHION RETAILING and BRAND MANAGEMENT

The fastest growing sales Channels for both Fast Fashion and Luxury Goods are Smart Apps on Mobile Phones. Innovative new Retail Business Operating Models such as “Retail 2.0” and “Perfect Store” are driving the development of these new Channels. For example, when a Customer enters a store, the Retailer of the Future can detect and identify him from his Smart Phone Number, as the Customer accesses the In-store WiFi or WiMAX Network Connection. Based on vast amounts of data describing their previous consumer behaviour – we can alert the consumer to relevant In-store offers and promotions – based on Propensity Modelling –similar in content and style to those offers and promotions the customer has responded to positively in the past When a Customer Tweets that she is going to buy a “little black cocktail dress” – we can initiate a Social Media Conversation .

Retail 2.0 “Perfect Store” – Experience Digital Marketing – Fast Fashion

Fast Fashion

• ASOS • • Next • • New Look • • Primark • • Top Shop •

Luxury Brand Aggregators

• PPR • • LVMH • • Richemont•

Luxury Brands

• Channel • • Dior • • Hermes • • Gucci • • Prada •

Designer Labels

• Armani • • Burberry • • D&G • DKNY • • Ralph Lauren • • Versace •

Sports Apparel and Footwear

• Nike • • Adidas • • Columbia • • North Face •

FAST FASHION RETAILING and BRAND MANAGEMENT

Retail 2.0 and Perfect Store Business Operating Models and Customer Experience and Journey Business Value Propositions are being driven by technology enablement such as Multi-channel Retail (eCRM), and Social Media (sCRM), supported by Real-time Analytics @ Point-of-Sale: - • Retail Business Models – “Retail 2.0” • “Perfect Store” • • Retail Strategy – Retail Proposition • Channels • Media • • Business Value Propositions – Customer Offer, Experience and Journey • • Mobile Technologies – Mobile Computing • Smart Devices • Smart Apps • • Customer Strategy – Customer Loyalty • Offers • Promotions • Campaigns • • Retail Business Transformation – New Social Structures • Cultural Change • • Emerging Technologies – Real-time Analytics @ POS • Smart Grid • Cloud Services • Social Marketing – Internet Intelligence • Product Placement • Crowd Sourcing Events • Fulfilment – Service Access • Service Brokering • Service Provisioning • Service Delivery

Retail 2.0 “Perfect Store” – Experience Digital Marketing – Fast Fashion

LUXURY GOODS RETAILING and BRAND MANAGEMENT

Luxury Goods companies have traditionally targeted two primary “old money” customer segments – affluent fashion-conscious socialites (age range 25-35) who follow the skiing, sailing and social events seasons in major cities and exclusive resorts in either Europe or America - and retired or semi-retired individuals (age range 55-65) who have created and accumulated significant wealth during their Business and Professional careers– and who now have significant time and money available to devote towards their interests and leisure pursuits. Families are raised in the Gap Years (age range 35-55). Many familiar Luxury Goods brands now belong to just a few Luxury Brand Aggregators such as French PPR, Louis Vuiton Moet Hennessy (LVMH) and the Swiss conglomerate Richemont. In any economic downturn, these Brand Aggregators are no longer able to drive increased growth sufficient to meet their Shareholder expectations or maintain volume targets from Business Partner / Stakeholders, in traditional Markets and Customer Segments – and so are forced to expand their Market Coverage, Product Ranges and Brand Footprints (and at the same time risk suffering the dual unforeseen consequences of erosion of Product positioning, desirability and cache – along with the dilution of core Brand recognition, perception and value).

Retail 2.0 “Perfect Store” – Experience Digital Marketing – Luxury Goods

Digital Marketing – Luxury Goods Brand Status Brand Awareness Sales Volume

Luxury Brand

Aggregators

• PPR •

• LVMH •

• Richemont •

Luxury Brands

• Channel •

• Dior •

• Hermes •

• Gucci •

• Prada •

Designer Labels

• Armani •

• Burberry •

• D&G •

• Versace •

Cache Brands

• Du Maurier •

• Dunhill •

• Rolex •

Star Brands

• DKNY •

• Hilfiger •

• Hugo Boss •

• Ralph Lauren •

• Tiffany•

Premium Brands

• Coach •

• Fendi •

• Swarovski •

• Valentino •

Micro Brands

• Liberty • Asprey •

• Mappin & Webb •

Esoteric Brands

• Patek Phillippe •

• Van Cleef & Arples •

Bespoke Brands

• Leviev •

• Graff •

Aspirational Brands

• Bulgari • Cherutti •

• Mont Blanc • Tods •

LUXURY GOODS RETAILING and BRAND MANAGEMENT

Today, the new Luxury Goods marketing focus has turned towards two “new money” customer segments - newly wealthy individuals in the emerging economies of the BRICS;s (Brazil, Russia, India and China) – and young Media and Entertainment Professionals and Elite Team Sports Athletes (age range 20-30) in the West. Goldman Sachs forecast that China will be buying one 3rd of the world's luxury goods in under a decade,,,,,

• Young Media and Entertainment Professionals and Elite Team Sports Athletes (age range 20-30) • New, Emerging and Developing Markets for Luxury Goods– Brazil, Russia, India China (BRICs) •

Increasingly, many Luxury Brands are also launching more accessible entry-level Product Ranges in order to attract younger, technically-savvy and fashion-aware mass-market consumers - to introduce them to a Lifestyle Experience and Journey that creates brand loyalty and lock-in with entry-level Luxury Goods Product ranges. As these young, mobile consumers careers develop and they begin to generate increased disposable income they also begin to purchase "big-ticket" Luxury Goods items from their favourite Design Guru, Role Model or Lifestyle Icon.....

Retail 2.0 “Perfect Store” – Experience Digital Marketing – Luxury Goods

Digital Marketing – Luxury Goods

Luxury Brand

Aggregators

• PPR •

• LVMH •

• Richemont •

Luxury Brands

• Channel •

• Dior •

• Hermes •

• Gucci •

• Prada •

Designer Labels

• Armani •

• Burberry •

• D&G •

• Hugo Boss •

• Versace •

Brand Status Sales Volume

Pyramid of Fashion

Esoteric Brands

• Patek Phillippe •

• Van Cleef & Arples •

Cache Brands

• Du Maurier •

• Dunhill •

• Rolex •

Star Brands

• DKNY •

• Hilfiger •

• Hugo Boss •

• Ralph Lauren •

• Tiffany •

Premium Brands

• Coach •

• Fendi •

• Swarovski •

• Valentino •

Micro Brands

• Liberty • Asprey •

• Mappin & Webb •

Bespoke Brands

• Leviev •

• Graff •

Aspirational Brands

• Bulgari • Cherutti •

• Mont Blanc • Tods •

LUXURY GOODS RETAILING and BRAND MANAGEMENT

As young, mobile consumers careers develop they begin to purchase "big-ticket" Luxury Goods items from their favourite Design Guru, Role Model or Lifestyle Icon..... • Mass-market younger, technically-savvy and fashion-aware consumers • • Entry-level Luxury Goods Product Ranges – Perfume, Cosmetics, Casual Wear, Sporting Goods •

Retail 2.0 and Perfect Store Business Operating Models and Customer Experience and Journey Business Value Propositions are being driven by technology enablement such as Multi-channel Retail (eCRM), and Social Media (sCRM), supported by Real-time Analytics @ Point-of-Sale: - • A winning Customer Contact Strategy to reach out to your target audience • A stunning Customer Experience to engage and retain your target audience • Understanding of Customer Profiling and Segmentation - to define your niche • A unique Customer Offer and Journey to instil desire for your Ranges and Lines • An enthralling Customer Experience to cultivate Consumer aspiration and desire • An amazing Customer Journey Storyboard to grasp and keep Consumer attention • A compelling Retail Proposition / Channels / Media to leverage Customer interest • A mastery of Smart Devices • Smart Apps • Cloud Services to engage your Customer • Total perfection of Product and Service Delivery Management for Consumer Fulfilment • Influencer Programmes - turn Fashion Blogs into Revenue – transforming Clicks into Cash.....

Retail 2.0 “Perfect Store” – Experience Digital Marketing – Luxury Goods

Multi-channel Retail - Transformation

Multi-channel Retail

Business Transformation

RETAIL 2.0 “Perfect Store” BUSINESS TRANSFORMATION

Transition - Retail 1.0 to Retail 2.0 “Perfect Store” Business Operating Model = Innovation I

Part 2

Part 4

Part 3

Part 1

Strategic Enterprise

Management Framework

Enterprise Target Operating

Model (eTOM)

Future Management

and Innovation Plans

Solution Architecture

Enterprise Architecture

Model and Roadmap

Enterprise Architecture

Business Programme

Plan / Project Plans

Infrastructure

Architecture

Business Operating

Model (BOM)

Business Architecture

Strategic Outcomes,

Goals & Objectives

Innovation Research

and Development

Business Programme

Management

IS / IT Strategy

Technology Strategy

Systems Planning

Enterprise Governance,

Reporting and Controls

Infrastructure Planning

Business Planning

Organisation Structure

Retail 1.0 Strategic Foresight

Strategy Development

Organisational

Change

Enterprise Architecture

Framework

NGE – Next-

Generation

Enterprises

Collaborative

Business

Models

Service

Convergence I

Business

Transformation

Technology Change

NGA- Next-

Generation

Architectures

Enterprise

Application

Integration

Technology

Convergence I

Buy Move Sell

Smart

Devices

Mobile

Platform

Cloud

Services Retail 2.0

I

Retail Business Transformation

Organization Management

Human Resource Management

Business Operating Model

Business Process Outsource

Business Process Management

Enterprise Performance Management

Business Programme Management

Project Portfolio Management

Si nous faisons la même vieille chose, de la même vieille manière, nous obtiendrons toujours les mêmes vieux résultats…..

PS0004

Shelf / Space

Allocation

PS0001 Customer Offer

PS0002 Retail

Proposition

PS0003

Pricing

PS0019 Marketing

Communications (Advertise)

PS0012 Customer

Segmentation

PS0009 Global CRM

PS0011 Marketing Services -

(Analysis and Research)

PS0010 Customer

Experience and Journey

PS0006 Product

Assortment and Mix

PS0008 Forecasting and Replenishment

PS0007 Global Category

& Supplier

PS0021 Sales Analysis

and Value Chain Reporting

PS0022 Global Product

Sourcing

PS0023 Global Supply

Chain

PS0014 BUY

(Procurement)

PS0016 SELL Retail

Merchandising

PS0015 MOVE

(Logistics)

PS0017 Public Relations

PS0024 Global Shared

Services

PS0005

Business

Planning

PS00029

Analytics

PS0027

Social

Intelligence

PS0028

Digital Platforms

& Multi-channel

Retail

Digital Channels & Analytics

Retail Merchandising & Logistics Head Office

Customer Relationship Management

PS0018 Customer

Information & Services

PS0013 Customer

Loyalty Customer Services

PS0025

Global Product

Catalogue

PS0020,

Offers and

Promotions

PS0026

Local Product

Catalogue

Multi-channel Retail – Retail 2.0 Model

Strategy Development and Business Transformation

1. Business Strategy 1.1. Business Innovation

- Manufacturing, Procurement, Logistics

- Products and Services

- Partners and Channels-to-market

- Retail Proposition and Customer Offer

- Customer Experience and Journey

- Service Delivery Channels

- Service Management

1.2. Strategy Discovery - Business Drivers, Mission, Strategy

- Outcomes, Goals, Objectives

1.2. Strategy Development - CSF’s, KPI’s, Business Metrics

- Strategy Packs

2. Business Transition 2.1. Business Transition Planning

2.2. Business Process Design

2.3. Business Programme Planning

2.4. Business Change Management

3. Organization Management

4. Human Resource Management

5. Business Operating Model 5.1 Operational - Process Execution, Integration and

Orchestration

5.2 Tactical - Analysis, Reporting and Communication

5.3 Strategic - Command, Control and Co-ordination

6. Business Process Outsource 6.1. Business Process Outsource Planning

6.2. Business Process Outsource Transition

7. Business Process Management 7.1. Business Process Re-engineering

7.2. Continuous Process Improvement

8. Enterprise Performance Management

9. Business Programme Management 9.1. Benefits Realisation

9.2. Communications

9.3. Stakeholder Management

10. Project Portfolio Management 10.1. Resource Management

- Programmes, Projects, Work Streams

- Deliverables, Milestones

- Activities, Tasks, Resources

11. Enterprise Portfolio Management 11.1. Function Library

11.2. Service Catalogue

11.3. Application Inventory

11.4. Infrastructure Portfolio

12. Technology Planning & Strategic Investment 12.1. IS / IT Strategy

- Strategic Architectures & Technologies

- Strategic Vendors & Products

12.2. IS / IT Architecture - Blueprints, Roadmaps, Transition Planning

12.3. Technology Planning - Platform Replacement

- Technology Refreshment

12.4. Strategic Investment - Key Technology Enablers & “Quick Wins”

EA-envision: The Enterprise Framework for Business Transformation

Strategy Development Topics Business Transformation Topics

IBM WebSphere

SAP NetWeaver Pi and/ or IBM MQSI

SAP IS/Retail

SAP CRM

Stebo or IBM Product Centre

Internet

Contact

Centre

Mobile 3rd Party

SAP Solution Architecture

Customer Loyalty

EPOS / SEL

Sales Channels Fulfilment Channels

In-store

Home

Delivery

BI / BO / BW HANA

SAP ECC7, ERP

ATG Dynamo Oracle Fusion Oracle Retail

Oracle CRM

Stebo or Kalido

Internet

Contact

Centre

Mobile 3rd Party

Oracle Solution Architecture

Customer Loyalty

EPOS

Sales Channels

Fulfilment Channels

In-store

Home

Delivery

Oracle OBIE

Oracle e-Business Suite

Retail 2.0 “Perfect Store” – Multi-channel Architecture

E-commerce Platform

Integration Platform

Retail Platform

CRM Platform

Catalogue Platform

Internet

Contact

Centre

Mobile 3rd Party

Customer Loyalty

In-store Systems

Sales Channels Fulfilment Channels

In-store

Home

Delivery

Retail 2.0 “Perfect Store” Multi-channel Enterprise Architecture

Data Warehouse

Head Office Shared Services

Social Media Real-time Analytics

Mobile Platforms

Cloud Digital Channels Social Media

Conversations

Multi-channel Retail – Retail 2.0 Model

Business Programmes – the challenge

the challenge: Business Programmes

• Business Programmes – Business Transformation Programmes and their associated Processes, Enterprise Services, COTS Applications and Integration Architecture are very complex, high cost / high risk investments and are becoming increasingly difficult to understand and manage. They encompass a huge mass of detail and depend upon the success of a large number of embedded, mission-critical business and technology decisions.

• Enterprise Architecture – There is an overarching responsibility to understand the many impacts of these decisions and get them right first time – or risk potentially catastrophic business interruption or failure if we get these decisions wrong. A structured Enterprise Architecture and Service-oriented Architecture Framework guides us successfully through architecting, designing and delivering Enterprise Services via the Enterprise Service Bus.

Multi-channel Retail – Discovery Workshop

Product

Customer

Basket

Where?

Who?

What?

Store

Why? How?

When?

Motivation Sale

Time

Planning /

Forecast

‘Plan’

Purchase /

Procure

‘Buy’

Analysis /

Insight

‘Report’

Marketing /

Advertising/

‘Promote’

Supplier Location

What / Why? Where / How?

Provision /

Replenish

‘Move’

Merchandising

/ Retail / POS

‘Sell’

Category Tier

Business Transformation

• What are the detailed business strategies of the enterprise and how should these be implemented (Business Strategy Development and Organizational Change) ?

– Businesses Drivers – Mission – Strategies – Outcomes – Goals – Objectives

• What processes the enterprise executes, how they are integrated, and how they contribute to the strategy of the organization (Business Process Management) ?

• How human resources are being utilized and whether there is optimum use of skills and resources available across all processes and functions (Human Resource Management) ?

• To what extent is the organization establishment is a true and proper reflection of actual roles and responsibilities, is it optimised in order to carry out every work task efficiently and effectively (Organization Management) ?

• How does the individual performance of each process, each business function and each individual contribute to the organization’s overall performance (CSF’s, KPI’s and metrics) (Enterprise Performance Management) ?

• What IS / IT applications and resources are available within the enterprise, how do they interact, which processes / functions do they support (Enterprise Portfolio Management) ?

• What Business Programmes are planned, approved and in progress, how are they sponsored, communicated and controlled, how do they enable business change and how do they realise benefits into the business (Business Programme Management) ?

• What Business, IS and IT Projects are planned, approved and started, what deliverables will they contribute, how long will they take, how are they organised and resourced and how do they impact upon the business and each other (Project Portfolio Management) ?

• What business and technology work streams are currently underway, how they enable business change, what processes and applications do they impact upon and how does this contribute towards the strategy of the organization (Strategic Technology Enablement) ?

– ERP – CRM – EPM – Process Orchestration – Collaborative Working – Enterprise Services

Multi-channel Retail Architecture

Multi-channel Retail

Retail Operations – Retail Merchandising and Logistics

Head Office – Finance, Planning and Strategy

Marketing – Customer Loyalty, Experience and Journey – Offers, Promotions and Campaigns

In-store EPOS – Internet – Home Delivery

Provisioning & Replenishment

In-store

Systems

Retail

Operations

Systems

ERP

Systems

Customers

Operations

Managers

Finance

Managers

Loyalty Mart

Financial Data Warehouse

CRM and

Marketing

Systems

Marketing

Managers

Multi-channel Sales Data

Warehouse

Marketing

Customer

Analytics

Reports

Retail

Multi-channel

Sales

Analysis

Operations

Warehousing &

Logistics

Reports

Head Office

Financial

Analysis

Reports

e-Commerce

Systems

Campaign Mart

Merchandising & Logistics Data

Supplier Data

Product Data

Stores Data

Merchandising

Inventory &

Provisioning

Reports

EPOS Data

Call Centre Data

Internet Data

Customer DWH

CRM Data

Retail

Managers

ERP Data

Catalogue

Systems

Planning &

Forecasting

Systems

“BIG DATA”

Retail and Logistics Data

Warehouse

Planning &

Forecasting

Systems

Apache Hadoop Framework

HDFS, MapReduce, MetLab, “R”

Catalogue Data

Autonomy, Vertical

Hadoop

SAP HANA

Business Transformation – Retail 2.0 Model

Architecture Blueprint

End state

Retail

SAP IS OIL

MM

SD

FI

PM

BW

BANKRetail Site

Retalix BOS

Pump Pricing

- PriceNet

SAP IS Retail

DART

Dry Goods

Supplier

Retail HO

EFS

Cardex

Loyalty

system Retail Portal eMaintenance

Card

Clearing

System

Forecourt

controller

Veeder Root Tank

Gauge

Electonic Payment

Server - EPS

Card Acquirer

Intactix -

Space

Planning

Contracts

ManagementB2B CRM

Inte

rna

tion

al c

ard

tran

sa

ctio

ns

Logistics suite

Logistics HO

Tank meter

readings

GSS-DART gateway

Pric

e lis

t►

Invo

ice

►

Ma

inte

na

nce

wo

rk o

rde

rs►

Sch

ed

ule

of w

ork

s►

◄A

sse

t d

ata

Fuels sales admin

Con

tract

s, D

eale

rs

Merchandising

Sh

op

Forecourt

Shop orders►

◄Delivery info.

◄InvoiceCard transactions

Fuel card reimbursement

DD File►

◄Electronic Payment

◄Bank Statement

De

live

ry

ET

A

Retalix POS

Car Wash

◄C

usto

me

r id

◄S

ale

tra

nsa

ctio

n,

Po

ints

►

Sales

Card Issuer

Credit/debit card statement

Dealer reimbursement prices►

Customer & dealer accounts►

◄Customer invoices, dealer credit

notes

Cre

dit/d

eb

it c

ard

sta

tem

en

t

Pumps

Fuel Card

transactions

Pla

no

gra

ms

Loyalty fee data

◄Dealer and site info.

Wholesale prices►

Order status,

accounting info.

Marker prices, BP pump price►

◄Recommended Price

Architecture Roadmap

b

ERP Roll-out

Product Management

Customer Management

Prepare Blueprint Realisation

Current State Enterprise Application Integration

Implement

Requirements

Blueprint

Design

ERP PoC

Build

Rehearsals

Cut-Over

QUICK WIN – Product Information Management / Master Data Management

Validate PoC

Process Fitness Programme –Strategy Roadmap

PoC

Strategy

Plan

Mobilisation

Requirements

Blueprint MDM PoC

Plan

Design

Build

Implement

Requirements

Blueprint

CRM PoC

Strategy

Plan

Design

Build

Future State

Plan

Message Formats

EAI PoC

Requirements

EAI Platform

EAI-Build

EAI-Deploy

EAI Services

EAI-Design

Planned Date Product Work Stream / Area Product style key: = Project product ; = external

dependency

Summary Product Description

Application Property Infrastructure Business

20

06

Roadmap requirements

Checkpoint to ensure all data available to

proceed.

20

07

Ready for Online Services (Internet) & Direct

Services (Call Centre) from September 2007

System

Audit

IT Infrastructure

Requirements Plan

Application

development

Internet

Record Management &

Archiving Service

Server

Relocation

IT Review

Facilities

Audit

Stage sign

off

Call Centre

environment

prepared

BPR Projects

IS Review

Infrastructure BPR Review

Training

Centre

available

IT

Infrastructur

e Upgrade 1

Provisioning

replacement

Stage sign

off

Business Transformation Product Flow

Multi-channel Retail - Architecture

Multi-channel Retail

Enterprise Architecture

Enterprise Architecture – Discovery Workshop

Product

Customer

Basket

Where?

Who?

What?

Store

Why? How?

When?

Motivation Sale

Time

Planning /

Forecast

‘Plan’

Purchase /

Procure

‘Buy’

Analysis /

Insight

‘Report’

Marketing /

Advertising/

‘Promote’

Supplier Location

What / Why? Where / How?

Provision /

Replenish

‘Move’

Merchandising

/ Retail / POS

‘Sell’

Category Tier

Enterprise Architecture Topics

1. Enterprise Portfolio Management 1.1. Function Library

1.2. Service Catalogue

1.3. Application Inventory

1.4. Infrastructure Portfolio

1.5. Portfolio Rationalisation and Cost Reduction

1.6. Shared Services and On-demand Computing

1.6.1 Service Virtualisation, Automation, Integration

1.6.2 Server and Storage Consolidation

1.6.3 Technology Simplification

1.6.4 Platform Sharing and Rationalisation

1.6.5 Application Standardisation

2. Technology Planning & Strategic Investment 2.1. IS / IT Strategy

2.2. IS / IT Architecture

2.3. Business and IT Strategy Alignment

2.4. Technology Planning

2.5. Strategic Investment

2.6. Strategic Vendor Management

2.7. Enterprise Processes and Resources Optimization

3. Enterprise Architecture 3.1 Business Architecture

3.1.1. Organisation Architecture

3.1.2. Process Architecture

3.1.3. Data Architecture

3.1.4. Information Architecture

3.2. Enterprise Services Architecture

3.3. Enterprise Integration Architecture

3.4. Application Architecture

3.5. Infrastructure Architecture

4. Repository Management 4.1. Metadata Management

4.2. Architecture View-points and Views

4.3. Architecture Visualisation, Scenarios and Simulation

5. Enterprise Performance Management

EA-envision: The Enterprise Framework for Business Transformation

IS/IT Strategy and Architecture Topics

Retail Enterprise Architecture

Enterprise Portfolio Management

Technology Planning & Strategic Investment

Enterprise Architecture

Repository Management

“Take hold of your future - or your future will take hold of you…..” (Patrick Dixon - Futurewise. 2005)

Enterprise Architecture Context Diagram

Enterprise Architecture Context Diagram – EA Product Matrix

Organisation Process Data Function Application Infrastructure

STRATEGIC Enterprise Performance

Management Strategy,

Enterprise Vision &

Mission Statements

Business

Transition

Strategy,

Business

Process Re-

engineering

Data Management

Strategy

Data Architecture

Framework

Data Principles, Policies

and Procedures

Function

Catalogue

Application

Inventory

Technology Portfolio

CONCEPTUAL Operational Strategies &

Desired Outcomes,

Performance Plans,

Organisation Hierarchy,

Establishment Model

Process

Group Conceptual Data Model

Data Architecture

Description

Data Management

Functions

Function

Group

System Unit

LOGICAL Goals/Objectives/CSF’s,

Organisation Units,

Roles & Responsibilities

Performance Targets

Business

Process Logical Data Model

Data Catalogue,

Business Glossary, Data

Management Services

Function Sub-system Device

PHYSICAL Organisation Locations,

Posts & Post Holders,

KPI’s and Metrics

Elementary

Business

Process

Physical Data Model

Meta Data Repository,

Data Storage Strategy

Data Management

Modules

Service

Group

Module Assembly

ACTUAL Sites, Addresses,

Jobs and Employees,

Planned Objectives &

Actual Achievements

Process Step Data Placement

Strategy

Database Instances

DDL, Tables, Indices,

Storage Groups

Data Quality Reporting

Service Application

Component

Applet

Smart App

Component

Enterprise Service Framework

Enterprise

Services

Enterprise

Service

Use Case View

Scenarios

Data Mapping

Data Model

Process Mapping

Process ModelSystem Mapping

Infrastructure

Model

Function Mapping

Application Model

Enterprise

Services

Enterprise

Service

Use Case View

Scenarios

Data Mapping

Data Model

Process Mapping

Process ModelSystem Mapping

Infrastructure

Model

Function Mapping

Application Model

Application

Architecture

Infrastructure

Architecture

Application

Architecture

Infrastructure

Architecture

Organisation

ArchitectureProcess Architecture

1Organisation

Architecture

Organisation

ArchitectureProcess ArchitectureProcess Architecture

1

Business

Strategy

Enterprise

Architecture

Solution

Architecture

3

22Data Architecture

EAI Architecture

EAI

Data ArchitectureData Architecture

EAI Architecture

EAI

Application Inventory

Application System Module

Service Catalogue

Framework Regime Services

22

Functional

Architecture

ESB

Business

Transformation

Technology

Enablers

COTS

Packages

Business Intelligence Architecture

Data

Storage

Architecture

Data Quality

& ETL

Services

Query &

Reporting

Services

2

KPI

CSF

MetricsEPM

Business Intelligence Architecture

Data

Storage

Architecture

Data Quality

& ETL

Services

Query &

Reporting

Services

Business Intelligence Architecture

Data

Storage

Architecture

Data Quality

& ETL

Services

Query &

Reporting

Services

2

KPI

CSF

MetricsEPM

2

KPI

CSF

MetricsEPM

Portal

Work

Group

High Level

Design

Detailed Design

Specification

Strategy

Mission

Outcome

Goal

Objective

Strategic

RequirementsRequirement

Group

Functional

Requirement

Information

Need

Non- Functional

Requirement

Requirement

Group

Functional

Requirement

Information

Need

Non- Functional

Requirement

Business Strategy

Long-Term

5-10 years

Mid-Term

3-4 years

Short Term

1-2 years

Business Strategy

Long-Term

5-10 years

Mid-Term

3-4 years

Short Term

1-2 years1

Operational

Requirements

22

Data Warehouse / BI / Analytics / Financial Models

Repository

IS Strategy

Application Plan

IT Strategy

Technology Plan

IS Strategy

Application Plan

IS Strategy

Application Plan

IT Strategy

Technology Plan

IT Strategy

Technology Plan3

Roadmaps

Transition Plan

Blueprints

IS/IT Landscape

Roadmaps

Transition Plan

Roadmaps

Transition Plan

Blueprints

IS/IT Landscape

Blueprints

IS/IT Landscape

Programme Project Work Stream

Deliverables Resources Activities / Tasks

Programme Project Work StreamProgramme Project Work Stream

Deliverables Resources Activities / TasksDeliverables Resources Activities / Tasks

EAEA--envision: envision: The Enterprise Framework for Business TransformationThe Enterprise Framework for Business Transformation

Process Orchestration

CASE

ERP CRM

Content

DBMS

Portal

Technology Portfolio

Unit Device Component

Technology Portfolio

Unit Device Component

Enterprise Repository

Enterprise RepositoryProcess Model

Process Mapping

Infrastructure

Portfolio

System Mapping

Strategic

Requirements

Operational

Requirements

Application

Module

Use Case View

Scenarios

User

Acceptance

Test Scripts

Scenarios

Application

Module

Use Case View

Scenarios

User

Acceptance

Test Scripts

Scenarios

Data Model

Data Mapping

Service Catalogue

Service MappingFunction LibraryFunction Mapping

Enterprise

Services

Business Service

Business Strategy

Long-Term

5-10 years

Mid-Term

3-4 years

Short Term

1-2 years

Business Strategy

Long-Term

5-10 years

Mid-Term

3-4 years

Short Term

1-2 years

Programme Project Work Stream

Deliverables Resources Activities / Tasks

Programme Project Work StreamProgramme Project Work Stream

Deliverables Resources Activities / TasksDeliverables Resources Activities / Tasks

Roadmaps

Bus/IS/IT Roadmaps

IS/IT Blueprints

B/IS/IT Landscape

Transition Plan

Work Packages

Roadmaps

Bus/IS/IT Roadmaps

Roadmaps

Bus/IS/IT Roadmaps

IS/IT Blueprints

B/IS/IT Landscape

IS/IT Blueprints

B/IS/IT Landscape

Transition Plan

Work Packages

Transition Plan

Work Packages

Application

Inventory

Application Map

Use Case ModelUse Case Mapping

Requirements

Traceability

Model

Organization

Model

Enterprise Repository Design

• Enterprise Performance Management

– Capture strategic intent and ensure that it is understood throughout the enterprise

• Business Drivers, Competitive Pressure, Statutory and Regulatory Compliance

• Mission, Strategies, Outcomes, Goals, Objectives & Performance Criteria (CSF’s, KPI’s, and Metrics)

• Strategic and Operational Requirements – Functional / Non-functional

• Stakeholders – process owners and data stewards, information providers and consumers

• Processes, Information, Resources and Timelines

• Governance and Communication Mechanisms

– Develop Enterprise Architectures that align business and IT strategies, processes and resources

as the foundation for aligned, synchronized and accelerated business transformation

• Metadata Management

– Manage a large amount of disparate technical and business metadata, providing different end-

to-end views to a variety of user roles

– Collaborate on updating and managing the information, facilitate re-use, and manage change,

especially through future planning of different scenarios and timescales

– Construct end-to-end visualizations of the information flows from any point (e.g. origin, final

report, any intermediate point), in a form suitable for both business and technical users

Mapping Documents

Enterprise RepositoryProcess Mapping

Process Model

System Mapping

Infrastructure

Portfolio

Strategic

Requirements

Operational

Requirements

Application

Module

Use Case View

Scenarios

User

Acceptance

Test Scripts

Scenarios

Application

Module

Use Case View

Scenarios

User

Acceptance

Test Scripts

Scenarios

Data Mapping

Data Model

Service Mapping

Service

Catalogue

Function Map

Application

Inventory

Enterprise

Services

Business Service

Application Map

Application

Inventory

Use Case

Mapping

Use Case Model

Requirements

Traceability

Model

Organization

Mapping

Establishment

Enterprise Repository Management

• To manage large volumes of disparate technical and business metadata - providing different end-to-end architecture views to support a wide variety of Enterprise Architecture information provider / consumer roles

• To collaborate on authoring, maintaining, publishing and consuming EA information, to facilitate re-use, and to manage change, especially through the future planning of different Enterprise Architecture implementation scenarios and timelines

• To construct end-to-end visualizations and simulations of critical information flows from any point (e.g. data origin, system view, final report) via any intermediate point (e.g. XML message format, file), in a form suitable for both business and technical users

• For Business Architects and Analysts looking for the "single point of truth" including the necessary collaboration, workflow, and governance to ensure that their EA models and metadata is reliable and maintained in a proper fashion

• To support business initiatives such as Mergers and Acquisitions, Bulk Asset Transfer, Business Transformation, new Product and Service Launch, Statutory and Regulatory Compliance that require comprehensive, accurate and accessible repository for managing Enterprise Architecture information in the context of business and technical requirements

• To support technology initiatives such as COTS Package Implementation, Service-oriented Architecture and Enterprise Service Bus deployment, Platform Replacement and Technology Refreshment that require extensive IT Portfolio Planning and Management

• To identify redundancy and use of superseded, inappropriate or unsupported versions of Processes, IS/IT objects or metadata - and facilitate the re-use of Enterprise Services

• To assign fiscal values to information by measuring how data contributes towards improved business performance. This allows further decisions to be made with respect to contingency, risk, accuracy, timeliness and cost of Enterprise Performance information.

• To enforce data and process ownership and organisational accountability to ensure the continuing integrity and quality of data, processes and Enterprise Performance information

Enterprise Architecture – Engagement

the solution: Architecture Engagement

Database AdministratorsDatabase Administrators

Enterprise ArchitectEnterprise Architect

• Focus on ERP Planning,

Design & Implementation

• High-level documentation of,

ERP Integration & Enterprise

Service Architecture

• Mapping Enterprise OLTP

‘On-line Transaction

Processing’ functionally

• Supporting ERP

Project Teams in

Design Process

• Focus across the Enterprise

• Definition of EA Principles,

Policies and Standards

• Generation of Enterprise

Architecture plans, models,

diagrams and documents

• Publication of Enterprise

Architecture products

• Delivering ERP, CRM, DWH

and BI integration strategy

• Definition of Enterprise and

SoA / ESB Frameworks and

design of Enterprise Services

• Focus on DWH / BI Applications

• Implementation of “on-demand”

Information Delivery Strategy

• Definition of information handling

functionality within components

• Supporting DWH / BI Project

Teams in implementing the

Information Delivery Strategy

Project / Programme Architects

ERP Project Teams

DWH / BI Project Teams

Information Architects

Principles,

Policies.

Standards

Principles,

Policies.

Standards

EA ModelsEA Models

EA Planning

Documents

EA Planning

Documents

CRM Project Teams

IT Portfolio Management

• The performance improvements and benefits that can be realized through ITPM include: -

– Reduced costs due to minimizing application and data redundancy, streamlining software

component management and rationalizing hardware, software and network infrastructure

– Increased efficiency and productivity: designer and developer access to accurate, up-to-date

information about applications, components and data assets, alerts can be triggered when updates

take place and surveys generated on the IT artefacts to evaluate and monitor change initiatives

– Better, more informed decision-making: complete IT architecture design decision support

enabled by the ability to perform impact analysis on projects, processes, applications, and data

– Support for mergers and outsourcing, through the creation of future planning views, allowing

participants to evolve the vision of the future organization whilst still working on the current

assessments and decisions

– Planning future IT Architecture in line with business, by planning ahead for hardware,

infrastructure and application evolution. ITPM also allows the IT changes to be synchronized with

the business changes and enables organizations to construct hypothetical future views to

investigate the impact of business change

– Assessing and managing business exposure to IT risk, allowing the operational risk at the

hardware level (e.g. a server going out of service) to be reflected up at the business level (which

processes and which users would be affected)

– Tracing, rationalizing and protecting data and information flows. ITPM’s allows aggregated

visualization of the lineage of data throughout an enterprise in either direction: this ensures the

integrity and quality of data.

Enterprise Architecture – the solution…

the solution: How it all works out…..

Frameworks,

Methods.

Guidelines

Frameworks,

Methods.

GuidelinesPrinciples,

Policies.

Standards

Principles,

Policies.

Standards

Process ModelsProcess Models

High-Level

Data Models

High-Level

Data Models

High-Level

Information Flows

High-Level

Application Maps

ERP / CRM ProgrammesERP / CRM Programmes

DWH / BI ProjectsDWH / BI Projects

Accountable for the production

of the deliverable/ providing

support to project team

Consulted in the production

of the deliverable/ providing

input into the project teams

Pro

ject

Arc

hit

ect

Info

rmatio

n A

rchitect

Enterprise

Architecture

Models

Enterprise

Architecture

Models

Information

Strategy

Information

Strategy

En

terp

rise

Arc

hit

ect

Enterprise

Architecture

Products

Enterprise

Architecture

Products

ERP Planning

Documents

ERP Planning

Documents

Data Storage

and Access

Strategy

Data Storage

and Access

Strategy

Dat

abas

e A

dm

in.

Physical

Schema

Physical

Schema

Key

EA ModelsEA Models EA Planning

Documents

EA Planning

Documents

Multi-channel Retail - Architecture

Retail Solution Architecture

Enterprise Portfolio Management

Technology Planning & Strategic Investment

Enterprise Architecture

Repository Management

“Take hold of your future - or your future will take hold of you…..” (Patrick Dixon - Futurewise. 2005)

Multi-channel Retail

Solution Architecture

Retail 2.0 “Perfect Store” – Architecture Landscape

IBM WebSphere

SAP NetWeaver Pi and/ or IBM MQSI

SAP IS/Retail

SAP CRM

Stebo or IBM Product Centre

Internet

Contact

Centre

Mobile 3rd Party

E-commerce Platform

Integration Platform

Retail Platform

CRM Platform

Catalogue Platform

Internet

Contact

Centre

Mobile 3rd Party

ATG Dynamo Oracle Fusion Oracle Retail

Oracle CRM

Stebo or Kalido

Internet

Contact

Centre

Mobile 3rd Party

SAP Solution Architecture

Oracle Solution Architecture

Customer Loyalty

In-store Systems

Customer Loyalty

EPOS / SEL

Customer Loyalty

EPOS

Sales Channels

Fulfilment Channels

Sales Channels Fulfilment Channels

Sales Channels Fulfilment Channels

In-store

Home

Delivery

In-store

Home

Delivery

In-store

Home

Delivery

Retail 2.0 “Perfect Store” Multi-channel Retail Architecture

Data Warehouse

Head Office Shared

Services

BI / BO / BW HANA

SAP ECC7, ERP

Oracle OBIE

Oracle e-Business

Suite

Social Media Real-time Analytics

Mobile Platforms

Cloud Digital Channels Social Media

Conversations

Multi-channel Retail Architecture

Multi-channel Retail

Retail Operations – Retail Merchandising and Logistics

Head Office – Finance, Planning and Strategy

Marketing – Customer Loyalty, Experience and Journey – Offers, Promotions and Campaigns

In-store EPOS – Internet – Home Delivery

Provisioning & Replenishment

In-store

Systems

Retail

Operations

Systems

ERP

Systems

Customers

Operations

Managers

Finance

Managers

Loyalty Mart

Financial Data Warehouse

CRM and

Marketing

Systems

Marketing

Managers

Multi-channel Sales Data

Warehouse

Marketing

Customer

Analytics

Reports

Retail

Multi-channel

Sales Analysis

Operations

Warehousing &

Logistics

Reports

Head Office

Financial

Analysis

Reports

e-Commerce

Systems

Campaign Mart

Merchandising & Logistics Data

Supplier Data

Product Data

Stores Data

Merchandising

Inventory &

Provisioning

Reports

EPOS Data

Call Centre Data

Internet Data

Customer DWH

CRM Data

Retail

Managers

ERP Data

Catalogue

Systems

Planning &

Forecasting

Systems

“BIG DATA”

Retail and Logistics Data

Warehouse

Planning &

Forecasting

Systems

Apache Hadoop Framework

HDFS, MapReduce, MetLab, “R”

Catalogue Data

Autonomy, Vertical

Hadoop

SAP HANA

Architecture Blueprint

End state

Retail

SAP IS OIL

MM

SD

FI

PM

BW

BANKRetail Site

Retalix BOS

Pump Pricing

- PriceNet

SAP IS Retail

DART

Dry Goods

Supplier

Retail HO

EFS

Cardex

Loyalty

system Retail Portal eMaintenance

Card

Clearing

System

Forecourt

controller

Veeder Root Tank

Gauge

Electonic Payment

Server - EPS

Card Acquirer

Intactix -

Space

Planning

Contracts

ManagementB2B CRM

Inte

rna

tion

al c

ard

tran

sa

ctio

ns

Logistics suite

Logistics HO

Tank meter

readings

GSS-DART gateway

Pric

e lis

t►

Invo

ice

►

Ma

inte

na

nce

wo

rk o

rde

rs►

Sch

ed

ule

of w

ork

s►

◄A

sse

t d

ata

Fuels sales admin

Con

tract

s, D

eale

rs

Merchandising

Sh

op

Forecourt

Shop orders►

◄Delivery info.

◄InvoiceCard transactions

Fuel card reimbursement

DD File►

◄Electronic Payment

◄Bank Statement

De

live

ry

ET

A

Retalix POS

Car Wash

◄C

usto

me

r id

◄S

ale

tra

nsa

ctio

n,

Po

ints

►

Sales

Card Issuer

Credit/debit card statement

Dealer reimbursement prices►

Customer & dealer accounts►

◄Customer invoices, dealer credit

notes

Cre

dit/d

eb

it c

ard

sta

tem

en

t

Pumps

Fuel Card

transactions

Pla

no

gra

ms

Loyalty fee data

◄Dealer and site info.

Wholesale prices►

Order status,

accounting info.

Marker prices, BP pump price►

◄Recommended Price

Group Transaction Data based on E2E Processes

(products, cust, locs, supp, etc)

Infrastructure

Corporate

Portal

Industry/

Customer/

Partner

Systems

Internal

Collaboration

& KM

Business

Transactions

Information

Sharing

SC & Retail Event

Visibility & Tracking

B2B Services

& Information

Messages sourced

from applications

and D/B:

Messages derived

from ‘business event

tags’:

Technical interfaces/

transport protocols, IT

management,

controls, etc:

Integration

& Portal

Channel/Device

Presentation Support

All User client

environments supported

across the supply chain Factory Warehouse Personal Vehicle Office

Desktop PDA Industrial

Handheld

Mobile

Phone

In-Cabin

system

IT System & Service

Management & Reporting

Finance, HR, etc

Dist, DC/w/h, stores, etc

Business Application Function and Rules Sets

Bus App 1 Bus App 2

LM

FB

MP

Doc

Man SM

PM

SS

Group MIS & Business Data

inc. reporting tools

MIS

Reporting

Platforms &

Networks

Home

Interactive

System

Public house

Applications, Information &

Infrastructure Service Components

Integration/

Broker

Specialist

I/O Device

Security

Management

Internal

Systems

External

Systems

Data

Transformation

System

Interfaces

BPA/

Workflow

Package

Adapters

Mapping &

Routing

Message

Store

Store

Event

Consolidation

Authentication

Access Control

B2B Gateways

Kiosks

Conceptual Enterprise Model

EA-envision: The Enterprise Framework for Business Transformation

Contact Channels Network

Agents

Customers D H E W L E T T P A C A R D

CRM Provisioning

D H E W L E T T P A C A R D

Asset

Management

Works Order

Management

Data Marts Data

Warehouse

INTEGRATION HUB

D H E W L E T T P A C A R D

Collaborative Working

D H E W L E T T P A C A R D

Caching

BI Reports

Office Workflow

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

EPOS

Server

Content

D H E W L E T T P A C A R D

Portal Server

Workflow Server Office Server

ERP Servers

CRM Server

BI Server Warehouse Server

Mobile / Remote

Workers

Advisors

Operations

MIS

Reports

Transactions D

H E W L E T T P A C A R D

Logical Systems Architecture

Billing Mediation &

Rating

Bills

Payments

PIMS / MDM

D H E W L E T T P A C A R D

Switch

Data

Server D

H E W L E T T P A C A R D

GIS Server Gazetteers

D H E W L E T T P A C A R D

Customer Data

Handset /

Tariff Data

Business Continuity Architecture

Call Centre

Agents

Main Contact Centre

10/100 MBit Switched Ethernet

Customers

Advisors

Agents

10/100 MBit Switched Ethernet

Customers

Advisors

Remote (Failover) Contact Centre

PSTN

Switched Ethernet

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

CC-VCSs

Cisco Call

Manager

6509 Voice

Gateway

Cluster 1

Customers

PSTN

Switched Ethernet

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

CC-VCSs

Cisco Call

Manager

6509 Voice

Gateway

Cluster 2

Customers

Agents

Agents

Agents

Agents

Logical Infrastructure Architecture

PSTN /

ISDN

Broad

Band

B a y N e t w o k s

S D

B a

y

N

w o

r k

s

B a

y S

t a c

k

A c

c e

s s

P

n t

6 5

0

W r

e s

s

PABX

ISDN 30 Voice Gateway

(e.g. CISCO 2640)

QSIG

DPNSS

Westell Protocol

Converter

Fire walled DMZ D

H E W L E T T P A C A R D

D H E W L E T T P A C A R D

CC Voice Connection

Servers

ISP

H W L T T P A C D

D H E W E T P A A D

CC Message

Connection

Servers

D H E W L E T T P A C A R D

CC AIS /

ACD Cluster

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

LAN / WAN

SMSC Managed SMS

Platform

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

D H E W L E T T P A C A R D

EAI Hub

D H E E A C A R D

CISCO Call

Manager

10/100 MBit Switched Ethernet

D H E W L E T T P A C A R D

H323 FW

H W L T P C D

CC-ICS

H W L T P C D

Portal

W T C D

e-Mail

H W L T P C D

MIS

Internet

VPN

Feature Net

Mobile /

Remote

Workers

Agents

Mobile /

SMS

Customers

Physical Infrastructure Architecture

WANBroad

Band

Router Router

Firewalls

6513-1 6513-2

IDS Network

Sensors

6513-1 6513-2

Firewalls

Link to Second Switch

EAI / Workflow

Server Cluster

Portal Web Servers

Business Intelligence

Reporting Servers

NetScreen

Firewalls

B-direct application server clusters running: -

BT Contact Central

CRM Application

Operational Reporting

Active Directory /

E-mail Servers

RouterReplication to D/R Site

Neoteris

Remote Access

3512-1 3512-2

Encryption Devices

Cluster 1

Cluster 2

Database Database

FilestoreFilestore

SANTape Array

PSTN /

Mobile

Router

Internet

Router

Database Database

FilestoreFilestore

SAN

Backup / Archive Servers

Back Office Servers

Customer Experience Management

Multi-channel Retail

The Digital Customer

Experience and Journey

The Digital Enterprise

The Digital Enterprise • The Digital Enterprise is all about doing things better today in order to design and

build a better tomorrow. The Digital Enterprise is driven by rapid response to

changing conditions so that we can create and maintain a brighter future for our

stakeholders to enjoy. The Digital Enterprise evolves from analysis, research and

development into long-term Strategy and Planning – ranging in scale from the

formulation and shaping of Public-sector Political, Economic and Social Policies to

Private-sector Business Programmes, Work-streams and Projects for organisational

change and business transformation – enabling us to envision and achieve our

desired future outcomes, goals and objectives

• Many of the challenges encountered in managing Digital Enterprise Programmes

result from attempts to integrate the multiple, divergent Future Narratives from lots of

different stakeholders in the Enterprise – all with different viewpoints, drivers,

concerns, interests and needs. This may be overcome by developing a shared,

common Vision of the future state of the Digital Enterprise – along with a Roadmap to

help us to plan and realise the achievement of that Vision.

• The term “Web 2.0” is, by now - well outdated. It can be said that after years of

overselling the “2.0”” postfix, it has begun to fade away..... Now, modern marketers

talks about “Social Media“. Because with always newer services, always more

sophisticated concepts, copycat, dataset mash-ups. It begins to become confusing.

This is why it was important to divide this big “2.0”” postfix into smaller meta-

concepts to ease the understanding of Enterprise 2.0, Social Shopping, Social

Media, etc......

Social Media Landscape

The chart above illustrates the richness and diversity of social media.....

• A Social Media Club panel in San Francisco forecasting in 2012 proposed that “2013 will be the year in which the word ‘social’ is inserted in front of every other word.” While some may still complain that the term “social media” is inaccurate – it seems to me that the word ‘social’ has become fruitful and multiplied.....

• Off the top of my head I can name the following: - – Social analytics

– Social business

– Social commerce

– Social contacts

– Social conversations

– Social customer care

– Social CRM

– Social e-business

– Social enterprise

– Social graphs

– Social influence

– Social intelligence

– Social learning

– Social media

– Social network

– Social processes

– Social shopping

Social Media Landscape

The Cone™ – Social Intelligence

Social Intelligence – Brand Loyalty and Affinity

CONE SEGMENTS – Brand Loyalty and Affinity

Social Intelligence drives Brand Loyalty and Affinity, Lifestyle Understanding - Fan-base Profiling, Streaming and Segmentation and marketing Campaigns – expressed in the creation and maintenance of a detailed History and Balanced Scorecard for every individual in the Cone, allowing summation by Stream / Segment: -

1. Inactive – need to draw their attention towards the Brand

2. Indifferent – need to educate them about core Brand Values

3. Disconnected– need to re-engage with the Brand

4. Casuals – exhibit Brand awareness and interest

5. Followers – follow the Brand, engage with social media and consume brand communications

6. Enthusiasts – engaged with the Brand, participate in Brand / Product / Media events and merchandising

7. Supporters– show strong need, desire and propensity to support Brand / Product / Media consumption

8. Fanatics – demonstrate total Commitment / Dedication / Loyalty for all aspects of the Brand / Product / Media

PROPENSITY – Balanced Scorecard

• Balanced Scorecard – is a summary of all the data-points for an Individual / Stream / Segment

• Propensity Score – In the statistical analysis of observational data, Propensity Score Matching (PSM) is a statistical matching technique that attempts to estimate the effect of a Campaign / Offer / Promotion or other intervention by calculating the impact of factors that predict the outcome of the Campaign / Offer / Promotion.

• Propensity Model – is the Baysian probability of the outcome of an event in an Individual / Stream / Segment

• Predictive Analytics - an area of data mining that deals with extracting information from data and using it to predict trends and behaviour patterns. Often the unknown event of interest is in the future, however, Predictive Analytics can be applied to any type of event with an unknown outcome - in the past, present or future.

Social Intelligence – Streaming and Segmentation

Social Interaction

Brand Affinity

Geo-demographic Profile Experian Mosaic – 15 Groups (Streams), 66 Types (Segments)

Hybrid Cone – 3 Dimensions

The Cone™

Social Interaction

The Cone™ – Streaming & Segmentation

Social Intelligence – Social Interaction

Social Interaction Cone Rules

1. Inactive – not engaged – low evidence / low affinity / low interest in Social Media

2. Lone Wolf – sparse / thin social network - may share negative information (Trolling)

3. Home Boy – Social Network clustered around Home Location Postcodes (Gang Culture)

4. Eternal Student – Social Network clustered around School / College / University Alumni

5. Workplace – Social Network clustered around Work and Colleagues (e.g. City Brokers, Traders)

6. Friends and Family – Social Network clustered around physical social contacts - Friends and Family

7. Enthusiast – Social Network clustered around shared, common interests – Sport. Music and Fashion etc.

8. Promiscuous – Open Networker – virtual Social Network across all categories- will connect with anybody

Number of Segments

• With anonymous data (e.g. surveys and polls) then the number of initial Segments is 4 (Matt Hart). With people

data (named individuals) we can discover much richer internal and external data from multiple sources (Social

Media / User Content / Experian) - and therefore segment the population with greater granularity

Individuals Qualifying for Multiple Segments.

• When individuals qualify for multiple segments - we can either add these deviant (non-standard) individuals to

the Segment that they have the greatest affinity with - or kick out any such deviants into an Outlying / Outcast /

Miscellaneous Segment for further statistical processing or for processing throiugh manual intervention

Social Intelligence – Actionable Insights

Brand Affinity

Social Interaction

Geo-demographic Profile

Experian Mosaic – 15 Groups (Segments), 66 Types (Streams)

Hybrid Cone – 3 Dimensions

Fanatics - 10%

Enthusiasts - 20%

Casuals - 30%

Indifferent - 40%

The Cone™

Brand Loyalty & Affinity

The Cone™ – Actionable Insights

Social Interaction

How consumers use social media (e.g., Facebook, Twitter) to address and/or engage with companies around social and environmental issues.

The chart above illustrates the richness and diversity of social media.....

Patterns of Social Relationships.....

Social Media is the fastest growing category of user-provided global content and will eventually grow

to 20% of all internet content. Gartner defines social media content as unstructured data created,

edited and published by users on external platforms including Facebook, MySpace, LinkedIn, Twitter,

Xing, YouTube and a myriad of other social networking platforms - in addition to internal Corporate

Wikis, special interest group blogs, communications and collaboration platforms.....

Social Mapping is the method used to describe how social linkage between individuals define Social

Networks and to understand the nature of intimate relationships between individuals.

Social Conversations SCRM in the Cloud

Traditional CRM was very much based around data and information that brands could collect

on their customers, all of which would go into a CRM system that then allowed the company

to better target various customers. CRM is comprised of sales, marketing and service /

support–based functions whose purpose was to move the customer through a pipeline with

the goal of keeping the customer coming back to buy more and more stuff......

TRADITIONAL CRM – Customer Management Pipeline TRADITIONAL CRM – Customer Management Pipeline

Evolution of CRM to SCRM - The challenge for organizations now is adapting and evolving

to meet the needs and demands of these new social customers - many organizations still

do not understand the CRM value of social media.....

SOCIAL CRM – Social Media Conversations SOCIAL CRM – Social Media Conversations

In Social CRM - the customer is actually the focal point of how an organization operates. Instead of

marketing products or pushing messages to customers, brands now talk to and collaborate with

their customers to solve business problems, empower customers to shape their own Customer

Experience and Journeys and develop strong customer relationships - which will over time, turn

participants into brand evangelists and positive customer advocates.....

SOCIAL CRM – Social CRM Processes SOCIAL CRM – Social Media Conversations

Posted on April 20, 2010 by Laurance Buchanan - Capgemini

SOCIAL CRM – a Business Framework and Operating Model

Social CRM - a Business Framework and Operating Model

SOCIAL CRM – Business Framework and Operating Model

Social Graphs and Market Sentiment

• Using “BIG DATA” to drive Market Sentiment •

Unprompted online conversations, statements and news create an online reflection of real-life events and

issues – influencing the thoughts of individual consumers – managing Reputational Risk and so shaping

Market Sentiment. The Social Media data, Blogs and News feeds that form this digital mirror of the world

provides a gold mine of actionable information.....

• Influencer Programmes have a long history in

industries such as software, computers and

electronics, - but today they are successfully

deployed across all types of industries including

automotive, smart phones, fashion, health and

nutrition, wine, sports, music, technology, travel

tourism and leisure – and financial services.....

• In a hyper-connected world market-makers and

influencers increasingly provide the gateway to

decision makers who drive consumer behaviour.

• Unprompted online conversations, statements

and news create an online reflection of real-life

events and issues – influencing the thoughts of

individual consumers and so shaping Market

Sentiment.

• The Social Media data and News feeds that form

this digital mirror of the world provides a gold

mine of information. However, unlocking the

data is not straight forward as it requires a

complex and unique set of technologies, skills

and methods.....

INFLUENCER PROGRAMMES – Social Media Conversations

INFLUENCER PROGRAMMES – Social Media Conversations

INFLUENCER PROGRAMMES – Social Media Conversations

The Cone™ Application

Social Intelligence

Cloud CRM

Data

Profile

Data CRM / CEM

Big Data

Analytics

Customer Management (CRM / CEM)

Social Intelligence

Campaign Management e-Business

Big Data Analytics

The Cone™

Customer Loyalty

& Brand Affinity

The Cone™ Smart Apps

Audience Survey Data

Insights

Reports

TV Set-top Box

The Digital Enterprise

• SMAC Digital Technology – The term SMAC Digital Technologies describes the use of

digital resources to discover, analyse, create, exploit, communicate and consume useful

information within a digital context. This encompasses the deployment of Next Generation

Enterprise (NGE) Digital Enterprise Target Operating Model (eTOM) and development of

Social Media – sites such as Facebook, Spotify, Twitter, WhatsApp, UTube, MySpace,

LinkedIn and Xing. Mobile Platforms, Smart Devices and Smart Apps, Next Generation

Network (NGN - 4G / LTE) Communication Architectures, Analytics and Data Science -

Data “mashing” and Big Data – Hadoop Clusters, Cloud Computing – virtualisation and

integration with 3rd Party e-business platforms and Over-the-top (OTT) Partner APIs.

The Digital Enterprise

Multi-channel Retail

Social Media

Mobile Platforms

Analytics

Cloud Services

Si nous faisons la même vieille chose, de la même vieille manière, nous obtiendrons toujours les mêmes vieux résultats…..

Next Generation Enterprise (NGE) Business Models

Social Media Applications

Next Generation Network (NGN) Communications

Data Science / Big Data / Real-time Analytics @ POS

Digital and Social Customer Relationship Management

The Digital Enterprise Methodology

Digital Enterprise Planning Methodology: - • Understand business and technology environment– Business Outcomes, Goals and Objectives domains

• Understand business and technology challenges / opportunities – Business Drivers and Requirements

• Gather the evidence to quantify the impact of those opportunities – Business Case

• Quantify the business benefits of resolving the opportunities – Benefits Realisation

• Quantify the changes need to resolve the opportunities – Business Transformation

• Understand Stakeholder Management issues – Communication Strategy

• Understand organisational constraints – Organisational Impact Analysis

• Understand technology constraints – Technology Strategy

Digital Enterprise Delivery Methodology: - • Understand success management – Scope, Budget, Resources, Dependencies, Milestones, Timeline

• Understand achievement measures – Critical Success Factors / Key Performance Indicators / ROI

• Produce the outline supporting planning documentation - Business and Technology Roadmaps

• Complete the detailed supporting planning documentation – Programme and Project Plans

• Design the solution options to solve the challenges – Business and Solution Architectures

• Execute the preferred solution implementation – using Lean / Digital delivery techniques

• Report Actual Progress, Issues, Risks and Changes against Budget / Plan / Forecast

• Lean / Agile Delivery, Implementation and Go-live !

• The profiling and analysis of large

aggregated datasets in order to

determine a ‘natural’ structure of

groupings provides an important

technique for many statistical and

analytic applications.

• Cluster analysis on the basis of

profile similarities or geographic

distribution is a method where no

prior assumptions are made

concerning the number of groups

or group hierarchies and internal

structure.

• Geo-demographic techniques are

frequently used in order to profile

and segment populations by

‘natural’ groupings - such as

common behavioural traits,

Clinical Trial, Morbidity or

Actuarial outcomes - along with

many other shared characteristics

and common factors.....

Geo-demographics - “Big Data”

• The Temporal Wave is a novel and innovative method for Visual Modelling and Exploration

of Geospatial “Big Data” - simultaneously within a Time (history) and Space (geographic)

context. The problems encountered in exploring and analysing vast volumes of spatial–

temporal information in today's data-rich landscape – are becoming increasingly difficult to

manage effectively. In order to overcome the problem of data volume and scale in a Time

(history) and Space (location) context requires not only traditional location–space and

attribute–space analysis common in GIS Mapping and Spatial Analysis - but now with the

additional dimension of time–space analysis. The Temporal Wave supports a new method

of Visual Exploration for Geospatial (location) data within a Temporal (timeline) context.

• This time-visualisation approach integrates Geospatial (location) data within a Temporal

(timeline) dataset - along with data visualisation techniques - thus improving accessibility,

exploration and analysis of the huge amounts of geo-spatial data used to support geo-

visual “Big Data” analytics. The temporal wave combines the strengths of both linear

timeline and cyclical wave-form analysis – and is able to represent data both within a

Time (history) and Space (geographic) context simultaneously – and even at different

levels of granularity. Linear and cyclic trends in space-time data may be represented in

combination with other graphic representations typical for location–space and attribute–

space data-types. The Temporal Wave can be used in roles as a time–space data

reference system, as a time–space continuum representation tool, and as time–space

interaction tool.

4D Geospatial Analytics – The Temporal Wave

Social Intelligence – Brand Affinity

CONE SEGMENTS - BRAND AFFINITY

• Social Intelligence drives Brand Loyalty Understanding - Fan-base Profiling, Streaming and Segmentation – expressed in the creation and maintenance of a detailed History and Balanced Scorecard for every individual in the Cone, allowing summation by Stream / Segment: -

1. Inactive – need to draw their attention towards the Brand

2. Indifferent – need to educate them about core Brand Values

3. Disconnected– need to re-engage with the Brand

4. Casuals – exhibit Brand awareness and interest

5. Followers – follow the Brand, engage with social media and consume brand communications

6. Enthusiasts – engaged with the Brand, participate in Brand / Product / Media events and merchandising

7. Supporters– show strong need, desire and propensity to support Brand / Product / Media consumption

8. Fanatics – demonstrate total Commitment / Dedication / Loyalty for all aspects of the Brand / Product / Media

PROPENSITY

• Balanced Scorecard – is a summary of all the data-points for an Individual / Stream / Segment

• Propensity Score – In the statistical analysis of observational data, Propensity Score Matching (PSM) is a statistical matching technique that attempts to estimate the effect of a Campaign / Offer / Promotion or other intervention by calculating the impact of factors that predict the outcome of the Campaign / Offer / Promotion.

• Propensity Model – is the Baysian probability of the outcome of an event in an Individual / Stream / Segment

• Predictive Analytics - an area of data mining that deals with extracting information from data and using it to predict trends and behaviour patterns. Often the unknown event of interest is in the future, however, Predictive Analytics can be applied to any type of event with an unknown outcome - in the past, present or future.

Social Intelligence – Fan-base Understanding

Social Intelligence – Fan-base Understanding

CONE STREAMING and SEGMENTATION

• Multiple Cones can be created and cross-referenced using Social Intelligence and Brand

Interaction / Fan-base Profiling and Segmentation in order to deliver actionable insights for any

genre of Brand Loyalty and Fan-base Understanding – as well as for other Geo-demographic

Analytics purposes – e.g. Digital Healthcare, Clinical Trials, Morbidity and Actuarial Outcomes: -

– Music (e.g. BBC and Sony Music)

– Broadcasting (e.g. Radio 1 / American Idol)

– Digital Media Content (e.g. Sony Films / Netflix)

– Sports Franchises (e.g. Manchester City / New York City)

– Sport Footwear and Apparel (e.g. Nike, Puma, Adidas, Reebok)

– Fast Fashion Retailers (e.g. ASOS, Next, New Look, Primark)

– Luxury Brands / Aggregators (e.g. Armani, Burberry, Versace / LVMH, PPR, Richemont)

– Multi-channel Retailers – Brand Affinity / Loyalty Marketing + Product Campaigns, Offers & Promotions

– Financial Services Companies – Brand Protection and Reputation Management

– Travel, Leisure and Entertainment Organisations - Destination Events and Resorts

– MVNO / CSPs - OTT Business Partner Analytics (Sky Go, Netflix, iPlayer via Firebrand / Apigee)

– Telco, Media and Communications - Churn Management / Conquest / Up-sell / Cross-sell Campaigns

– Digital Healthcare – Private / Public Healthcare Service Provisioning: - Geo-demographic Clustering and

Propensity Modelling (Patient Monitoring, Wellbeing, Clinical Trials, Morbidity and Actuarial Outcomes)

Social Intelligence – Fan-base Understanding

Social Intelligence – Social Interaction

Social Interaction Cone Rules

1. Inactive – not engaged – low evidence / low affinity / low interest in Social Media

2. Lone Wolf – sparse / thin social network - may share negative information (Trolling)

3. Home Boy – Social Network clustered around Home Location Postcodes (Gang Culture)

4. Eternal Student – Social Network clustered around School / College / University Alumni

5. Workplace – Social Network clustered around Work and Colleagues (e.g. City Brokers, Traders)

6. Friends and Family – Social Network clustered around physical social contacts - Friends and Family

7. Enthusiast – Social Network clustered around shared, common interests – Sport. Music and Fashion etc.

8. Promiscuous – Open Networker – virtual Social Network across all categories- will connect with anybody

Number of Segments

• With anonymous data (e.g polls) then the

number of initial Segments is 4 (Matt

Holland). With named individuals we can

discover much richer internal and external

data sources (Social Media / User Content /

Experian) - and therefore segment the

population with greater granularity

Individuals Qualifying for Multiple Segments.

• When individuals qualify for multiple

segments - we can either add these deviant

individuals to the Segment that they have the

greatest affinity with - or kick out any such

deviants into an Outlying / Outcast /

Miscellaneous Segment for further

processing or manual intervention

Social Interaction

How consumers use social media (e.g., Facebook, Twitter) to address and/or engage with companies around social and environmental issues.

SMACT/4D Digital Technologies

Digital Technologies

Digital Technology • The term Digital Technologies is used to describe the exploitation of digital resources in

order to discover, analyse, create, exploit, communicate and consume useful information

within a digital context. This encompasses the use of various Smart Devices and Smart

Apps, Next Generation Network (NGN) Digital Communication Architectures, web 2.0 and

mobile programming tools and utilities, mobile and digital media e-business / e-commerce

platforms, and mobile and digital media software applications: -

• Cloud Services

– Secure Mobile Payments / On-line Gaming / Digital Marketing / Automatic Trading

– Automatic Data – Machine-generated Data for Remote Sensing, Monitoring and Control

• Mobile – Smart Devices, Smart Apps, Apps Shops and the Smart Grid

• Social Media Applications – FaceBook, LinkedIn, MySpace, Spotify, Twitter, U-Tube, WhatsApp

• Digital and Social Customer Relationship Management – eCRM and sCRM

• Multi-channel Retail – Home Shopping, e-commerce and e-business platforms

• Next Generation Network (NGN) Digital Communication Architectures – 4G, Wifi

• Next Generation Enterprise (NGE) – Digital Enterprise Target Operating Models (eTOM)

• Big Data – Discovery of hidden relationships between data items in vast aggregated data sets

• Fast Data – Data Warehouse Engines, Data Marts, Data Mining, Real-time / Predictive Analytics

• Smart Buildings – Security, Environment Control, Smart Energy, Multimedia/Entertainment Automation

Customer Management (CRM / CEM)

SMAC Digital Technologies

• • SOCIAL MEDIA STRATEGY • discovering and exploring intimate consumer insights from social media profiles

and social network relationships, special interest groups, business, leisure, social, political and economic

behaviour - derived from Social Media Analytics and Internet Content click-stream processing.

• • DIGITAL BRAND MANAGEMENT • driving the Digital Enterprise Strategy for clients across a wide variety of

industry sectors – from e-Government and Digital Democracy to Health and Welfare, Telco and Media, Wealth

Management and On-line Gaming, Financial Services, Retail, Utilities, Energy, Oil & Gas.

• • DIGITAL CUSTOMER EXPERIENCE and JOURNEY • shaping the Digital Customer Experience and Journey

by deploying Digital Marketing and Multi-channel Retail Architectures which support digital / mobile e-business / e-

commerce platforms for a world-class Digital Consumer interaction.

• • CONVERTING DATA STREAMS INTO REVENUE STREAMS • SMAC Digital Technologies describes the use

of digital resources in order to discover, analyse, create, exploit, communicate and consume useful information

within a digital context. This encompasses the deployment of Enterprise 2.0 Target Operating Model (eTOM) and

development of Smart Devices and Smart Apps, Next Generation Network (NGN) Mobile Communication

Architectures (4G / LTE), Analytics, Data Science and Big Data supported by Cloud Computing and integrated

with Network API Services for access by OTT Business Partners, Value-added Service Providers (VARs) and

other 3rd Party consumer platforms.

SMAC Digital Technologies

• Social Networks, Virtual Communities and Digital Ecosystems

• Mobile Communications Platforms / Smart Devices / Smart Apps

• Analytics / Data Science / Big Data / Hadoop / SSDs / GPUs

• Cloud Computing Platforms

Telematics The Internet of Things (IoT) – Smart Devices, Smart Apps, Wearable

Technology, Vehicle Telemetry, Smart Homes and Building Automation

SMACT/4D Digital Technologies

• CONVERTING DATA STREAMS INTO REVENUE STREAMS • SMAC Digital Technologies • describes the use of digital resources in order to discover, analyse, create, exploit, communicate and consume useful information within a digital context. This encompasses the deployment of Enterprise 2.0 Target Operating Model (eTOM) and development of Smart Devices and Smart Apps, Next Generation Network (NGN) Mobile Communication Architectures (4G / LTE), Analytics, Data Science and Big Data supported by Cloud Computing and integrated with Network API Services for access by OTT Business Partners, Value-added Service Providers (VARs) and other 3rd Party consumer platforms. Data sources include the following: - • Transactional Data Streams from Business Systems • Energy Consumption Data from Smart Metering Systems • SCADA and Environmental Control Data from Smart Buildings • Vehicle Telemetry Data from Passenger and Transport Vehicles • Market Data Streams – Financial, Energy and Commodities Markets • G-Cloud – NHS Communications Spine, Local and National Systems • Cable and Satellite Home Entertainment Systems – Channel Selection Data • Call Detail Records (CDRs) from Telco Mediation, Rating and Billing Systems • Machine-generated data from Computer-aided Design and Manufacturing Systems • Internet Browsers, Social Media and Search Engines – User Site Navigation and Content Data • Biomedical Data Streaming – Smart Hospitals / Care in the Community / Assisted Living @ Home • Other internet click-streams – Social Media, Google Analytics, RSS News / Market Data Feeds

• Geo-demographic techniques are frequently used in order to profile and segment population segments or clusters by ‘natural’ groupings - common behavioural traits, Epidemiology, Clinical Trial, Morbidity or Actuarial outcomes, along with many other shared characteristics and common factors – in order to discover and explore previously unknown, concealed or unrecognised patterns, trends and data relationships.

SMAC – Social, Mobile, Analytics, Cloud

Chart showing the growth of Smart-phones as compared to PCs. This remarkable trend has got all of the PC

manufacturers worried - they are all looking into transitioning into the manufacture of Smart-phones, PDAs and

Tablets. Now is the time to enter the Digital Enterprise and Mobile Platform marketplace - before its too late,,,,,

The Mobile Enterprise – Outlook for 2014

SMAC – Social, Mobile, Analytics, Cloud

OVERVIEW

• While Social, Mobile, Analytics and Cloud technologies add a new dimension

to the Telco 2.0 business operating model and technology landscape, to fully

maximize their value - consider the whole to be greater than sum of its parts.....

• The formula for the Future of Work is centred around SMAC - Social, Mobile,

Analytics and Cloud – integrated on a single technology stack, where every

function enables all of the others to maximize their cumulative impact. This is the

foundation of a new Enterprise Architecture model delivering Digital Technology

that supports an organization that is fully integrated in real-time – and is thus

more lean, agile, connected, collaborative productive and customer-focussed.

SMAC – Social, Mobile, Analytics, Cloud

• Social Media, Virtual Communities, Digital Ecosystems

• Mobile Communication Platforms / Smart Devices / Smart Apps

• Analytics / Data Science / Big Data / Hadoop / SSDs / GPUs

• Cloud Services Platforms

The Cone™ Application

Social Intelligence

Cloud CRM

Data

Profile

Data CRM / CEM

Big Data

Analytics

Customer Management (CRM / CEM)

Social Intelligence

Campaign Management e-Business

Big Data Analytics

The Cone™

Customer Loyalty

& Brand Affinity

The Cone™ Smart Apps

Audience Survey Data

Insights

Reports

TV Set-top Box

SMACT/4D OVERVIEW

• While Telematics, Social, Mobile, Analytics and Cloud technologies add a new

dimension to the Digital 2.0 business operating model and technology landscape, to

fully maximize their value - consider the whole to be greater than sum of its parts.....

• The formula for the Future of Work is centred around SMACT/4D – Telematics,

Social, Mobile, Analytics and Cloud – totally integrated on a single technology stack,

where every function enables all of the others to maximize their cumulative impact.

This is the foundation of a new Enterprise Architecture model delivering Digital

Technology that supports an organization that is fully integrated in real-time – and is

thus more lean, agile, effective, connected, collaborative, productive and customer-

focussed.

SMACT/4D – Telematics, Social, Mobile, Analytics and Cloud

• Telematics – the Internet of Things (IoT)

• Social Media / User Content / Virtual Communities / Digital Ecosystems

• Mobile Communication Platforms / Smart Devices / Smart Apps

• Analytics / 4D Geospatial Data Science / Big Data / Hadoop / SSDs / GPUs

• Cloud Services Platforms

SMAC – Social, Mobile, Analytics, Cloud

MOBILE ENTERPRISE (MEAP’s) - Vendors &

Technologies

SMACT/4D – Telematics, Social, Mobile, Analytics and Cloud

• Today’s SMAC Stack™ - ‘the fifth wave’ of IT architecture - is happening faster

and with greater impact than any other disruptive technology that has ever come

before. By 2020, as many as 30 billion fixed devices will be connected to the

internet and 70 billion mobile computing devices will be connected to the Cloud.

Enterprises will be managing 50 times the amount of data than they do currently.

So SMACT/4D will have a multiplying effect on businesses and increase

productivity across the organization – whilst placing a massive burden on Service

Providers of future Digital Communications Technology Stacks, Platforms and

Architectures.

The SMACT/4D Effect

• In all Industries across the business landscape, the SMACT/4D Technology

Stack™ is eroding the century-old blueprint of value chains and spawning new,

highly distributed, digital business models, social networks, virtual communities

and digital ecosystems. The power of SMACT/4D technology platforms is released

by treating SMACT/4D as an integrated digital technology stack – as core

components combine to create a massive multiplying effect when they are

integrated and deployed together.

SMAC – Social, Mobile, Analytics, Cloud

Telematics

• Telematics is an interdisciplinary field of Digital Communication Technology (DCT) for

the long-distance transmission and processing of automatic (machine generated) digital

information (telemetry). While this application might suggest a much more universally

encompassing definition than Machine-generated / Automatic Data Streams between

Smart Devices and the Cloud - it is simply the branch of SMACT/4D Digital technology

which deals with the Internet of Things (IoT) – the management of remote devices via

mobile telecommunications and cloud platforms.

• Telematics – pervasive Fixed / Mobile Internet-connected Smart Devices delivering

Machine-generated / Automatic Digital Data and Video Streams - Mobile-to-Mobile

(M2M) and Mobile-to-Cloud (M2C) – the Internet of Things (IoT) Typical Telematics

Data Sources might include: -

– Geophysical data from remote devices in Digital Oilfields

– Image Data from satellites, aircraft and drones in Digital Battlefields

– Wearable Technology – digital data streaming from wearable devices

– Environment data from remote oceanographic buoys and weather stations

– Vehicle Telemetry from spacecraft, aircraft, ships, trains and road transport

– Image Data from vehicles, aircraft and drones with Emergency Response Teams

SMACT/4D Digital Technologies SMAC – Social, Mobile, Analytics, Cloud

• A rapidly increasing rate of change is driving customer, businesses and technology interaction

together in an ever tighter embrace - the convergence of disruptive technologies eroding the

boundaries separating them. Businesses are becoming more and more agile, and technologies

such as social media, mobility, analytics and cloud computing are coming together to unleash

unlimited opportunities for everyone involved. This convergence – also known as SMAC – will

be the leading disruptive force in the business-technology ecosystem over the next few years.

SMACT/4D Digital Technologies SMAC – Social, Mobile, Analytics, Cloud

SMAC – Social, Mobile, Analytics, Cloud

• Today’s SMAC Stack™ - ‘the fifth wave’ of IT architecture - is happening

faster than anything that has ever come before. By 2020, as many as 30

billion fixed devices will be connected to the internet and 70 billion mobile

computing devices will be connected to the Cloud. Enterprises will be

managing 50 times the amount of data than they do currently. So SMAC will

have a multiplying effect on businesses and increase productivity across the

organization – whilst placing a massive burden on Service Providers of future

Digital Communications Technology Stacks, Platforms and Architectures.

THE SMAC EFFECT

• In all Industries across the business landscape, the SMAC Stack™ is eroding

the century-old blueprint of value chains and spawning new, highly distributed,

digital business models, social networks, virtual communities and digital

ecosystems. The power of SMAC technology platforms is released by treating

SMAC as an integrated digital stack – as core components combine to create

a massive multiplying effect when they are integrated and deployed together.

Internet of Things

“Everything

Everywhere” – IoT

Big Data Cloud

People,

Places

and

Things

Geo-

spatial

Data

Geo-spatial

Gazetteer

Geo-spatial

Analytics

People, Places and Things

Gazetteer (GIS / GPS)

Social Intelligence

Campaign Management GIS / GPS Insights

Big Data Analytics

The Cone™

People, Places &

Things Profiling

The Cone™ GIS / GPS

Smart Apps

Geographic &

Demographic

Survey Data

Insights

Reports

TV Set-top Box

The Internet of Things

Factory Office &

Warehouse

Wearable &

Personal

Technology

Transport Public

Buildings Smart

Homes

Public house

Mall,

Shop,

Store

Smart

Kiosks &

Cubicles

Mobile

Smart

Apps

CCTV /

ANPR

Data Science – Big Data Analytics

Hadoop Clustering and Managing Data.....

Managing Data Transfers in Networked Computer Clusters using Orchestra

To illustrate I/O Bottlenecks, we studied Data Transfer impact in two clustered computing systems: -

Hadoop - using trace from a 3000-node cluster at Facebook

Spark a MapReduce-like framework with iterative machine learning + graph algorithms.

Mosharaf Chowdhury, Matei Zaharia, Justin Ma, Michael I. Jordan, Ion Stoica

University of California, Berkeley

{mosharaf, matei, jtma, jordan, istoica}@cs.berkeley.edu

“Big Data” in Digital Healthcare

“Big Data” in Pharma / Life Sciences

• Big data now plays an important role in medical and clinical research. Digital Patient Records are now being harvested and analysed in large-scale patient population studies – which are yielding actionable clinical insights. The UK Government has made anonymised patient records from the National Health Service openly available. Medical Centres, Research Institutes and Pharma / Life Sciences funding agencies have all made major investments in this area.

Wave-form Analytics

• • WAVE-FORM ANALYTICS • is an analytical tool based on Time-frequency Wave-

form analysis – which has been “borrowed” from spectral wave frequency analysis in

Physics. Deploying the Wigner-Gabor-Qian (WGQ) spectrogram – a method which

exploits wave frequency and time symmetry principles – demonstrates a distinct trend

forecasting and analysis capability in Wave-form Analytics. Trend-cycle wave-form

decomposition is a critical technique for testing the validity of multiple (compound)

dynamic wave-series models competing in a complex array of interacting and inter-

dependant cyclic systems - waves driven by both deterministic (human actions) and

stochastic (random, chaotic) paradigms in the study of complex cyclic phenomena.

• • WAVE-FORM ANALYTICS in “BIG DATA” • is characterised as periodic alternate

sequences of, high and low trends regularly recurring in a time-series – resulting in

cyclic phases of increased and reduced periodic activity – Wave-form Analytics

supports an integrated study of complex, compound wave forms in order to identify

hidden Cycles, Patterns and Trends in Big Data. The existence of fundamental stable

characteristic frequencies in large aggregations of time-series Economic data sets

(“Big Data”) provides us with strong evidence and valuable information about the

inherent structure of Business Cycles. The challenge found everywhere in business

cycle theory is how to interpret very large scale / long period compound-wave

(polyphonic) temporal data sets which are non-stationary (dynamic) in nature.

Wave-form Analytics

Track and Monitor

Investigate and

Analyse

Scan and Identify

Separate and Isolate

Communicate Discover

Verify and Validate Disaggregate

Background Noise

Individual Wave

Composite Waves

Wave-form Characteristics

Hadoop Framework

• The workhorse relational database has been the tool of choice for businesses for well over 20 years now. Challengers have come and gone but the trusty RDBMS is the foundation of almost all enterprise systems today. This includes almost all transactional and data warehousing systems. The RDBMS has earned its place as a proven model that, despite some quirks, is fundamental to the very integrity and operational success of IT systems around the world.

• The relational database is finally showing some signs of age as data volumes and network speeds grow faster than the computer industry's present compliance with Moore's Law can keep pace with. The Web in particular is driving innovation in new ways of processing information as the data footprints of Internet-scale applications become prohibitive using traditional SQL database engines.

• When it comes to database processing today, change is being driven by (at least) four factors:

– Speed. The seek times of physical storage is not keeping pace with improvements in network speeds.

– Scale. The difficulty of scaling the RDBMS out efficiently (i.e. clustering beyond a handful of servers is notoriously hard.)

– Integration. Today's data processing tasks increasingly have to access and combine data from many different non-relational sources, often over a network.

– Volume. Data volumes have grown from tens of gigabytes in the 1990s to hundreds of terabytes and often petabytes in recent years.

RDBMS and Hadoop: Apples and Oranges?

• Below is Figure 1 - a comparison of the overall differences between

Database RDBMS and MapReduce-based systems such as Hadoop

• From this it's clear that the MapReduce model cannot replace the

traditional enterprise RDBMS. However, it can be a key enabler of a

number of interesting scenarios that can considerably increase

flexibility, turn-around times, and the ability to tackle problems that

weren't possible before.

• With Database RDBMS platforms, SQL-based processing of data sets

tends to fall away and not scale linearly after a specific volume ceiling,

usually just a handful of nodes in a cluster. With MapReduce, you can

consistently obtain performance gains by increasing the size of the

cluster. In other words, double the size of Hadoop cluster and a job will

run twice as fast - quadruple it will rub four times faster - its the same

linear relationship, irrespective of data volume and throughput.

Comparing Data in DWH, Appliances, Hadoop Clusters and Analytics Engines

RDBMS DWH DWH Appliance Hadoop Cluster Analytics Appliance

Data size Gigabytes Terabytes Petabytes Petabytes

Access Interactive and

batch

Interactive and batch Batch Interactive

Structure Fixed schema Fixed schema Flexible schema Flexible schema

Language SQL SQL Non-procedural

Languages (Java, C++,

Ruby, “R” etc)

Non-procedural

Languages (Java, C++,

Ruby, “R” etc)

Data Integrity High High Low Very High

Architecture Shared memory -

SMP

Shared nothing - MPP Hadoop DFS In-memory Processing

– GPGPUs / SSDs

Virtualisation Partitions / Regions MPP / Nodal MPP / Clustered MPP / Clustered

Scaling Non-linear Nodal / Linear Clustered / Linear Clustered / Linear

Updates Read and write Write once, read many Write once, read many Write once, read many

Selects Row-based Set-based Column-based Array-based

Latency Low – Real-time Low – Near Real-time High – Historic

Reporting

Very Low – Real-time

Analytics

Figure 1: Comparing RDBMS to MapReduce

Hadoop Framework

• These datasets would previously have been very challenging and expensive to take on with a traditional RDBMS using standard bulk load and ETL approaches. Never mind trying to efficiently combining multiple data sources simultaneously or dealing with volumes of data that simply can't reside on any single machine (or often even dozens). Hadoop deals with this by using a distributed file system (HDFS) that's designed to deal coherently with datasets that can only reside across distributed server farms. HDFS is also fault resilient and so doesn't impose the overhead of RAID drives and mirroring on individual nodes in a Hadoop compute cluster, allowing the use of truly low cost commodity hardware.

• So what does this specifically mean to enterprise users that would like to improve their data processing capabilities? Well, first there are some catches to be aware of. Despite enormous strengths in distributed data processing and analysis, MapReduce is not good in some key areas that the RDMS is extremely strong in (and vice versa). The MapReduce approach tends to have high latency (i.e. not suitable for real-time transactions) compared to relational databases and is strongest at processing large volumes of write-once data where most of the dataset needs to be processed at one time. The RDBMS excels at point queries and updates, while MapReduce is best when data is written once and read many times.

• The story is the same with structured data, where the RDBMS and the rules of database normalization identified precise laws for preserving the integrity of structured data and which have stood the test of time. MapReduce is designed for a less structured, more federated world where schemas may be used but data formats can be much looser and freeform.

The Emerging “Big Data” Stack

Targeting – Map / Reduce

Consume – End-User Data

Data Acquisition – High-Volume Data Flows

– Mobile Enterprise Platforms (MEAP’s)

Apache Hadoop Framework HDFS, MapReduce, Metlab “R” Autonomy, Vertica

Smart Devices Smart Apps Smart Grid

Clinical Trial, Morbidity and Actuarial Outcomes Market Sentiment and Price Curve Forecasting Horizon Scanning,, Tracking and Monitoring Weak Signal, Wild Card and Black Swan Event Forecasting

– Data Delivery and Consumption

News Feeds and Digital Media Global Internet Content Social Mapping Social Media Social CRM

– Data Discovery and Collection

– Analytics Engines - Hadoop

– Data Presentation and Display

Excel Web Mobile

– Data Management Processes Data Audit Data Profile Data Quality Reporting Data Quality Improvement Data Extract, Transform, Load

– Performance Acceleration GPU’s – massive parallelism SSD’s – in-memory processing DBMS – ultra-fast database replication

– Data Management Tools DataFlux Embarcadero Informatica Talend

– Info. Management Tools Business Objects Cognos Hyperion Microstrategy

Biolap Jedox Sagent Polaris

Teradata SAP HANA Netezza (now IBM) Greenplum (now EMC2) Extreme Data xdg Zybert Gridbox

– Data Warehouse Appliances

Ab Initio Ascential Genio Orchestra

Hadoop Framework

• Each of these factors is presently driving interest in alternatives that are significantly better at dealing with these requirements. I'll be clear here: The relational database has proven to be incredibly versatile and is the right tool for the majority of business needs today. However, the edge cases for many large-scale business applications are moving out into areas where the RDBMS is often not the strongest option. One of the most discussed new alternatives at the moment is Hadoop, a popular open source implementation of MapReduce. MapReduce is a simple yet very powerful method for processing and analyzing extremely large data sets, even up to the multi-petabyte level. At its most basic, MapReduce is a process for combining data from multiple inputs (creating the "map"), and then reducing it using a supplied function that will distill and extract the desired results. It was originally invented by engineers at Google to deal with the building of production search indexes. The MapReduce technique has since spilled over into other disciplines that process vast quantities of information including science, industry, and systems management. For its part, Hadoop has become the leading implementation of MapReduce.

• While there are many non-relational database approaches out there today (see my emerging IT and business topics post for a list), nothing currently matches Hadoop for the amount of attention it's receiving or the concrete results that are being reported in recent case studies. A quick look at thelist of organizations that have applications powered by Hadoop includes Yahoo! with over 25,000 nodes (including a single, massive 4,000 node cluster), Quantcast which says it has over 3,000 cores running Hadoop and currently processes over 1PB of data per day, and Adknowledge who uses Hadoop to process over 500 million clickstream events daily using up to 200 nodes

The Cone™ Application

Social Intelligence

Cloud CRM

Data

Profile

Data CRM / CEM

Big Data

Analytics

Customer Management (CRM / CEM)

Social Intelligence

Campaign Management e-Business

Big Data Analytics

The Cone™

Customer Loyalty

& Brand Affinity

The Cone™ Smart Apps

Audience Survey Data

Insights

Reports

TV Set-top Box

HP HAVEn Big Data Platform

Informatica / Hortonworks Vibe

From sports to scientific research, a surprising range of industries will begin to find value in big data.....

Big Data – Products

The MapReduce technique has spilled over into many other disciplines that process vast

quantities of information including science, industry, and systems management. The Apache

Hadoop Library has become the most popular implementation of MapReduce – with

framework implementations from Cloudera, Hortonworks and MAPR

Split-Map-Shuffle-Reduce Process

Big Data Consumers

Split Map Shuffle Reduce

Key / Value Pairs Actionable Insights Data Provisioning Raw Data

Apache Hadoop Component Stack

HDFS

MapReduce

Pig

Zookeeper

Hive

HBase

Oozie

Mahoot

Hadoop Distributed File System (HDFS)

Scalable Data Applications Framework

Procedural Language – abstracts low-level MapReduce operators

High-reliability distributed cluster co-ordination

Structured Data Access Management

Hadoop Database Management System

Job Management and Data Flow Co-ordination

Scalable Knowledge-base Framework

Data Management Component Stack

Informatica

Drill

Millwheel

Informatica Big Data Edition / Vibe Data Stream

Data Analysis Framework

Data Analytics on-the-fly + Extract – Transform – Load Framework

Flume

Sqoop

Scribe

Extract – Transform - Load

Extract – Transform - Load

Extract – Transform - Load

Talend Extract – Transform - Load

Pentaho Extract – Transform – Load Framework + Data Reporting on-the-fly

Big Data Storage Platforms

Autonomy

Vertica

MongoDB

HP Unstructured Data DBMS

HP Columnar DBMS

High-availability DBMS

CouchDB Couchbase Database Server for Big Data with NoSQL / Hadoop

Integration

Pivotal Pivotal Big Data Suite – GreenPlum, GemFire, SQLFire, HAWQ

Cassandra Cassandra Distributed Database for Big Data with NoSQL and

Hadoop Integration

NoSQL NoSQL Database for Oracle, SQL/Server, Couchbase etc.

Riak Basho Technologies Riak Big Data DBMS with NoSQL / Hadoop

Integration

Big Data Analytics Engines and Appliances

Alpine

Karmasphere

Kognito

Alpine Data Studio - Advanced Big Data Analytics

Karmasphere Studio and Analyst – Hadoop Customer Analytics

Kognito In-memory Big Data Analytics MPP Platform

Skytree

Redis

Skytree Server Artificial Intelligence / Machine Learning Platform

Redis is an open source key-value database for AWS, Pivotal etc.

Teradata Teradata Appliance for Hadoop

Neo4j Crunchbase Neo4j - Graphical Database for Big Data

InfiniDB Columnar MPP open-source DB version hosted on GitHub

Big Data Analytics Engines / Appliances

Big Data Analytics and Visualisation Platforms

Tableaux Tableaux - Big Data Visualisation Engine

Eclipse Symentec Eclipse - Big Data Visualisation

Mathematica Mathematical Expressions and Algorithms

StatGraphics Statistical Expressions and Algorithms

FastStats Numerical computation, visualization and programming toolset

MatLab

R

Data Acquisition and Analysis Application Development Toolkit

“R” Statistical Programming / Algorithm Language

Revolution Revolution Analytics Framework and Library for “R”

Hadoop / Big Data Extended Infrastructure Stack

SSD Solid State Drive (SSD) – configured as cached memory / fast HDD

CUDA CUDA (Compute Unified Device Architecture)

GPGPU GPGPU (General Purpose Graphical Processing Unit Architecture)

IMDG IMDG (In-memory Data Grid – extended cached memory)

Vibe

Splunk

High Velocity / High Volume Machine / Automatic Data Streaming

High Velocity / High Volume Machine / Automatic Data Streaming

Ambari High-availability distributed cluster co-ordination

YARN Hadoop Resource Scheduling

Big Data Extended Architecture Stack

Cloud-based Big-Data-as-a-Service and Analytics

AWS Amazon Web Services (AWS) – Big Data-as-a-Service (BDaaS)

Elastic Compute Cloud (ECC) and Simple Storage Service (S3)

1010 Data Big Data Discovery, Visualisation and Sharing Cloud Platform

SAP HANA SAP HANA Cloud - In-memory Big Data Analytics Appliance

Azure Microsoft Azure Data-as-a-Service (DaaS) and Analytics

Anomaly 42 Anomaly 42 Smart-Data-as-a-Service (SDaaS) and Analytics

Workday Workday Big-Data-as-a-Service (BDaaS) and Analytics

Google Cloud Google Cloud Platform – Cloud Storage, Compute Platform,

Firebrand API Resource Framework

Apigee Apigee API Resource Framework

Gartner Magic Quadrant for BI and Analytics Platforms

Hadoop Framework Distributions

FEATURE Hortonworks Cloudera MAPR Pivotal

Open Source Hadoop Library Yes Yes Yes Pivotal HD

Support Yes Yes Yes Yes

Professional Services Yes Yes Yes Yes

Catalogue Extensions Yes Yes Yes Yes

Management Extensions Yes Yes Yes

Architecture Extensions Yes Yes

Infrastructure Extensions Yes Yes

Library

Support

Services

Catalogue

Job Management

Library

Support

Services

Catalogue

Hortonworks Cloudera MAPR

Library

Support

Services

Catalogue

Job Management

Resilience

High Availability

Performance

Pivotal

Library

Support

Services

Catalogue

Job Management

Resilience

High Availability

Performance

Gartner Magic Quadrant for BI

Data Warehouse Appliance / Real-time Analytics Engine Price Comparison

Manufacturer Server

Configuration Cached Memory

Server

Type

Software

Platform Cost (est.)

SAP HANA

(BI, BO, BW)

32-node (4

Channels x 8 CPU)

1.3 Terabytes

SMP Proprietary $ 6,000,000

Teradata 20-node (2

Channels x 10 CPU)

1 Terabyte

MPP Proprietary $ 1,000,000

Netezza

(now IBM)

20-node (2

Channels x 10 CPU)

1 Terabyte

MPP Proprietary $ 180,000

IBM ex5 (non-HANA

configuration)

32-node (4

Channels x 8 CPU)

1.3 Terabytes

SMP Proprietary $ 120,000

Greenplum (now

Pivotal)

20-node (2

Channels x 10 CPU)

1 Terabyte

MPP Open Source $ 20,000

XtremeData xdb 20-node (2

Channels x 10 CPU)

1 Terabyte

MPP Open Source $ 18,000

Zybert Gridbox 48-node (4

Channels x 12 CPU)

20 Terabytes

SMP Open Source $ 60,000

• SAP is a Growth Company. SAP wishes to elevate itself to become a trusted innovator for all

of their customers – whether it’s achieving business outcomes, simplifying everything through

the cloud or driving business efficiency and growth using Mobile and In-memory Computing.

• Industry Focused. In 2013 SAP was global the market leader for supplying ERP application

software across 25 different Industry Sectors – and will continue to increase its Industry Sector

focus to make SAP HANA the standard business platform for world-class Industry Sector

applications and process execution.

• The Digital Enterprise. SAP grew its mobile, cloud and in-memory computing businesses

heavily in 2013 and will continue to strengthen its transition into products supporting the Digital

Enterprise area even more so in 2014. BIW (Business Information Warehouse) and ECC6 (ERP

Central Components version 6) Business Suite – will ultimately be fully integrated into Cloud,

Mobile and SAP HANA High-availability Analytics in-memory computing platform environments.

• Key Technology Platforms and Industry Sector areas for SAP in 2014 include the following: -

1. Digital Healthcare

2. Multi-channel Retail

3. Financial Technology

Industry Sectors Technologies 1. Cloud Services

2. The Mobile Enterprise

3. In-memory Computing

SAP – Outlook for 2015

SAP HANA Version 6 – Outlook

• Patient Experience and Journey

– Patient Administration and Billing

– Patient Relationship Management

• Clinical Delivery

– Clinical Treatment and Care

• Digital Imaging – (MRI / CTI / X-Ray / Ultrasound)

• Robotic Surgery – (Microsurgery / Remote Surgery)

• Patient Monitoring – (Clinical Trials / Health / Wellbeing)

• Biomedical Data – (Data Streaming / Biomedical Analytics)

• Emergency Incident Management – (Response Team Alerts)

• Epidemiology – (Disease Transmission / Contact Management)

– Enterprise Healthcare Mobility (Mobile Devices / Smart Apps)

• Activity Monitor – (Pedometer / GPS)

• Position Monitor – (Falling / Fainting / Fitting)

• Sleep Monitor – (Light Sleep / Deep Sleep / REM)

• Cardiac Monitor – (Heart Rhythm / Blood Pressure)

• Blood Monitor – (Glucose / Oxygen / Liver Function)

• Breathing Monitor – (Breathing Rate / Blood Oxygen Level)

• Care Collaboration

– Connected Care

– Referral Management

Healthcare: - SAP Solution Roadmap

SAP HANA Version 6 – Roadmap

• SAP HANA is a new Database Appliance hosting a Hardware and Software bundle (SAP software powered by

INTEL core technologies with Veola Garda SSD In-memory Architecture). Introduced in late 2010 – HANA initially

focused on Real-time Analytics – processing vast quantities of data on the fly. SAP HANA now address many of

the challenges facing customers needing to make instant Management Decisions using very large data volumes.

• The SAP HANA Appliance was massively developed and further extended in 2012 to support the many upcoming

user requirements for processing Very Large Scale (VLS) data volumes in the realm of real time analytics. SAP

AG, together with INTEL, has expended massive effort in order to meet the emerging challenges of the Real-time

world – optimising Enterprise Resources in manufacturing, financial services, healthcare, national security, etc.

• SAP HANA presents a novel opportunity for businesses that needs instant access to Real-time Data for analytic

models that drive automated processing and Intelligent Agents / Alerts for instant decision-making. SAP HANA

also allows users to federate external data sources (ERP / CRM databases, message queues, Data Warehouse

Appliances, Real-time Data Feeds Internet Content and Click-stream Processing) with their Analytics Engines.

SAP HANA Version 6 – Overview

SAP HANA Applications and Analytics

In its current form, SAP HANA (Version 2) can be used for five fundamental types of System Template: -

1. Agile Data Mart for supporting Real-time Analytics

2. SAP Business Suite Application Accelerator

3. Primary Database for SAP NetWeaver Business Warehouse

4. Development Platform for new end-user applications.

5. SAP Rapid Deployment Solutions (RDS)

Analytics– The Major Categories of Real-time analytics for which HANA is optimised: -

– Operational Reporting – real-time insights from transaction systems such as SAP ERP Applications or third-party

solutions from IBM, Oracle or Microsoft.

– Data Warehousing (SAP NetWeaver BW on HANA) – BW customers can run their entire BW application suite on

the SAP HANA Platform.

– Predictive and Text analysis on Big Data – To succeed, companies must go beyond focusing on delivering the

best product or service and uncover customer/employee /vendor/partner trends and insights, anticipate behaviour

and take proactive action from predictive insights into ERP transaction data.

– Core process accelerators – HANA accelerate business reporting and enterprise performance management by

powering ERP, Data Warehouse and Data Mart Accelerators,

– Planning and Optimization Apps – SAP HANA excels at applications that require complex, interactive planning

and scheduling in real-time with ultra-fast results,

– Sense and Response Apps – These applications offer real-time insights from “Big Data” such as global markets

data and newsfeeds (Automatic Trading) , remote sensing and monitoring data from Intelligent Buildings and Smart

Homes smart meter data (energy demand / supply optimisation), satellites, drones and fixed HDCCTV cameras

(optical recognition) Electronic point-of-sale (EPOS) data, social media data, global internet content (Market

Sentiment) , Streamed Biomedical Data ,for Clinical Trials, Emergency Response and much more besides.....

SAP HANA - Applications and Analytics

BW powered by HANA

• In this scenario, SAP NetWeaver Business Warehouse (BW) uses the SAP HANA appliance software as the

primary database. Having the data stored in columns in the main memory means that measures, or columns, can

be read much faster, and totals and averages can be calculated quickly – even for vast numbers of data records.

InfoProviders designed specifically for SAP HANA, such as DataStore objects and InfoCubes optimized for SAP

HANA, further accelerate the loading and analysis of data in BW, since complex and performance-intensive

processes, such as activating DSO requests, can be done in the SAP HANA appliance software itself.

SAP HANA as a data mart

• In this deployment scenario, the SAP HANA appliance software is used alongside an existing database.

Operational data from SAP or non-SAP systems can be replicated to the SAP HANA database using the SAP LT

Replication Server or SAP BusinessObjects Data Services. Whereas SAP BusinessObjects Data Services is used

to set up complex processes to extract, transform, and load data, the SAP LT Replication Server brings about a

trigger-based replication of all relevant tables using Sybase ultra-fast Database Replication. When data is inserted

or updated in the ERP system, it is automatically transmitted to the SAP HANA database so that it is available for

almost real-time reporting. Data in the SAP HANA appliance software is accessed using information models such

as attribute, analytic, and calculation views - which can be created using the SAP HANA (Eclipse) studio.

Agile Data Mart for supporting Real-time Analytics

• This System Template has advantages of (1) being completely non-disruptive to the existing application landscape

and (2) providing an immediate, focused solution to an urgent business analytics problem. Example Application

Scenarios for a stand-alone Data Mart supporting Real-time Analytics include: -

– Sales Analysis Data Mart

– Traded Instrument Data Mart

– Smart Meter Reading Data Mart

SAP HANA - Applications and Analytics

• Using Emerging Technologies such as in-memory Data Warehouse Appliances with

Real-time and Predictive Analytics Engines - we can now achieve so much more than

we could ever do before.....

• Real-time and Predictive Businesses are transforming the way that they think, plan

and operate. Based firmly on a foundation of In-Memory Computing technology, and

an extended Time dimension from Past (Historic) through Present (Real-time) into

Future (Predictive) Data - there is now a very new paradigm for enterprise information

management, which supports the three key business reporting requirements: -

DEVICE INFORMATION TIMELINE PURPOSE

Data Warehouse Appliances Historic Data Past Historic Reporting

Real-time Analytics Engines Current Data Present Real-time Analytics

Predictive Analytics Engines Forecast Data Future Predictive Analytics

MODELLING

HORIZON RESULTS

RANGE

(years) TIMELINE

DATA

TYPE FISCAL PERIOD AGGREGATION Financial

Management

Previous,

Current, Planned 5 - 7 Past, Present,

Future

Actual /

Forecast

Day, Week, Month,

Quarter, Annual Atomic and Cumulative

Strategic

Management

Previous,

Current, Planned 5 - 10 Past, Present,

Future

Actual /

Forecast

Day, Week, Month,

Quarter, Annual Atomic and Cumulative

Future

Management

Previous,

Current, Planned 50 - 100

Past, Present,

Future

Actual /

Forecast

Day, Week, Month,

Quarter, Annual Atomic and Cumulative

SAP HANA Version 6 – Features

SAP HANA Planning Methodology: -

• Understand business opportunities and threats – Business Outcomes, Goals and Objectives

• Understand business challenges and issues – Business Drivers and Requirements

• Gather the evidence to quantify the impact of those issues – Business Case

• Quantify the business benefits of resolving the issues – Benefits Realisation

• Quantify the changes need to resolve the issues – Business Transformation

• Understand Stakeholder Management issues – Communication Strategy

• Understand organisational constraints – Organisational Impact Analysis

• Understand technology constraints – Technology Strategy

SAP HANA Delivery Methodology: -

• Understand success management – Scope, Budget, Resources, Dependencies, Milestones,

Timeline

• Understand achievement measures – Critical Success Factors / Key Performance Indicators / ROI

• Produce the outline supporting planning documentation - Business and Technology Roadmaps

• Complete the detailed supporting planning documentation – Programme and Project Plans

• Design the solution options to solve the challenges – Business and Solution Architectures

• Execute the preferred solution implementation – using Lean / Agile delivery techniques

• Report Actual Progress, Issues, Risks and Changes against Budget / Plan / Forecast

• Delivery, Implementation and Go-live !

SAP HANA – Methodology

SAP HANA Architecture Overview

APPLICATION CATEGORY VENDOR SAS SAP JEDOX

USER INTERFACE

Mobile Enterprise Application

Platforms

MEAPs Sybase Unwired Platform

(SUP)

Mobile Apps

Data Presentation & Display GUI SAS Add-In for Microsoft Office Enterprise Portal Excel, Web

Graphic Visualisation BLOBs Enterprise Guide, BI Dashboard,

SAS/Graph

PowerPoint

ENTERPRISE SERVER

Database Server Servers Base SAS Software SAP BW, BO, BI OLAP Server

Application Server Servers SAS Enterprise Business

Intelligence Server

HANA Accelerator

Data Warehouse Appliance Fast Data SAS Scalable Performance Data

Server (SPDS)

BW, BO, BI, HANA Accelerator

Analytics Engines Big Data Hadoop, “R” Hadoop, Pentaho

PERFORMANCE

ACCELERATION Massive Parallelism GPUs Accelerator

In-memory Processing SSDs HANA Accelerator

ENTERPRISE SOFTWARE

Data Analysis and Reporting Reporting SAS Enterprise Business

Intelligence Server

Crystal Reports / Business

Objects

OLAP Server /

Excel

Business Intelligence BI Base SAS Software BI / BO / BW OLAP Server

Information Management OLAP OLAP Cube Studio “R” OLAP Server

Statistical Analysis SAS/STAT, Stat Graphics

Data Mining Enterprise Miner, SAS/INSIGHT

Analytics SSM OLAP Server, SSAS

Financial Consolidation Controlling FI, CO, BPC / BHP OLAP Server

Enterprise Performance

Management

Planning SAS Strategy Management SEM / EPM OLAP Server

SAP HANA Applications

SAP HANA Architecture

• SAP HANA is a new Technology Appliance Coupled with Hardware and Software bundle (Intel

Architecture powered by SAP In memory Technology). Introduced in to the market late 2010, initially

focusing on Analyzing Huge volume of DATA in real time. It Address the whole challenge what customers

are facing with extreme volumes of data to make Management Decisions Quicker than Never before.

• The Appliance has fine-tuned Very Aggressively in 2012 It meets most of the challenge in the Real-time

world. SAP to gether with INTEL, has deployed Huge resources to meet upcoming challenges in the real

time world. You may call it analysing your health, managing your resources, Prevention of crime etc.,

Making us to run our live Happier Like Never Before.

• Data in real-time provides a completely unique capability for businesses that require instant access to their

information. In addition, SAP HANA allow users to federate external data sources (including CEP engines,

message queues, tick databases, traditional relational databases, and OData sources) into their analytic

models in order to further amplify the utility.

Unified Communications

Multi-channel Retail - Digital Architecture

• The last decade has seen an unprecedented explosion in mobile platforms as the internet and mobile worlds came of age. It is no longer acceptable to have only a bricks-and-mortar high-street presence – customer-focused companies are now expected to deliver their Customer Experience and Journey via internet websites, mobiles and more recently tablets.

TELCO 2.0

DOMAINS

Operational Support Systems Business Support Systems Support Systems

Environment

Management

Network Smart and

Hand Held

Devices

Retail Customer

Management

Telco Billing

Rating and

Mediation

Marketing Settlement Head Office

Future

Management

Sustainability

Renewable

Resources

NGN - Next

Generation

Network

Architectures

4G / Edge

Future Handset

PDA and Hand

Held Devices

Smart Device

Propositions

Future Telco

Retail Model and

Landscape

Social Anthropology

Ethno-graphics

Demographics

Telco Consolidation

and Convergence

ETOM

Future Telco

Markets and

Landscape

Future Telco

Interconnect

Wholesale

Contracts and

Agreements

Strategic Foresight

and Future

Management

Future Telco

Policy and

Legislation

Strategy and

Planning

Hydroelectricity

Solar, Wind and

Tidal Power

Geothermal

Energy

Bio-fuels

Future Shared

Network

Planning

IMS / SIP

Cloud

Computing

MVNO / VPN

Propositions

Smart Metering

-Planning and

Transition

Electronic Toll

& Congestion

Mgt.

Telco Retail

Proposition and

Customer Offer

Product / Service

Packaging and

Development

Customer Offer,

Experience and

Journey Planning

Micro-marketing and

Mass-customisation

Fixed-to-Mobile

Convergence - FMC

BSS / ESS

Convergence - SDP

Mediation Rating

and Telco Billing IS /

IT Planning and

Strategy

Customer

Insight &

Loyalty

Strategy

Customer

Profiling,

Streaming and

Segmentation

Risk Management

Frameworks

- Outsights

- COSO

Governance,

Reporting &

Controls

- IFRS

- COBIT

- SOX

Business

Operations

Micro-Generation

CHP Combined

Heat & Power

Civil Engineering

Environment

Management

Inventory

Provisioning

Work

Scheduling

Job

Management

Smart Metering

and IDEX

Energy Data

Management

Electronic

Traffic

Management

Retail Operations

Value Chain

Management

Customer

Relationship

Management

Business Operating

Model (CRM BOM)

Mediation, Rating

and Telco Billing

Business Operating

Model (BOM)

Product / Tariff

Management

Campaign

Management

Contracts and

Settlements

Balancing, &

Optimisation

Performance

Managements

DWH / BI

Analytics

Data

Mining

Architecture Asset and

Environment

Management

Architecture

Network

Infrastructure

Architecture

Smart Meter

Infrastructure

Architecture

MVNO / VPN

Platforms

Supply Chain,

EPOS, Retail

Merchandising

Architecture

Customer Domain

Architecture

Customer Profiling,

Streaming and

Segmentation

Mediation Rating and

Telco Billing

Architecture

PLCM / CRM

Architecture

Contracts and

Settlements

Architecture

Financials and

Settlements

Document

Management

Solution

Architecture

Asset and

Environment

Management

Solution Design

Network

Infrastructure

Management

Solution Design

Smart Meter

Information

Management

MVNO / VPN

Solution Design

Supply Chain ,

EPOS, Retail

Merchandising

Solution Design

Contact Centre

Solution Design

Mediation Rating and

Telco g Billing

Solution Design

PIMS / CRM

Contact and

Campaign

Management

Solution Design

Contracts and

Settlements

Management

Solution Design

Performance

Management

DWH and BI

Architecture

Systems

Management

Plant, Building,

Site and

Environment

Management

Systems

GIS Mapping

and Network

Gazetteer

Network

Monitoring &

Control

Systems

Energy Data

Collection and

Aggregation

Systems -

IDEX

MVNO / VPN

Meter Network

Management

Supply Chain

EPOS / Retail

Systems and

CRM Systems

Contact Centre and

Customer Systems

– Oracle CRM

– SAP CRM

– Unica /

Cognos

– Clarity

– Onyx

Telco Billing and

Collection Systems

– Oracle BRM

– SingleView

– Amdocs

– Keenan

PIMS Systems

CRM Systems

Campaign

Management

Systems

Contracts and

Settlements

Management

Systems

Oracle e-business

Suite, BRM, CRM

SAP IS Retail, Ent.

Portal, MDM, Pi, FI

CO SD BPEM,

SEM, SSM. BI and

BW

IBM FileNet, ECM

Infrastructur

e

Management

Telco Network

Infrastructure

Telco Network

Monitoring and

Control

Network

Security

Anti-trafficking

and Counter-

terrorist

measures

Smart Device

Infrastructure

Management

Standardised

Terminating

Equipment

Business

Continuity

Disaster

Recovery

EPOS Network

Multi-media Channel

Access and

Fulfilment

Avaya, Genesys,

Nortel Switches

Multi-media Channel

Access and

Fulfilment

Document Print

Management

Diallers / Routers

On-demand

Computing and

Shared

Services

VR IVR /

Diallers

Cisco Routers

Virtualisation,

Automation

On-demand

Computing and

Shared Services

Desktop Services

Client Inventory,

Provisioning, Help

Desk and Support

Business

Continuity

Telco 2.0 Business and Technology Domains Telco 2.0 “Unified Communications”

Unified Communications

Unified Communications

Unified Communications is the

integration of real-time

communication services - such

as unified messaging, rich

presence, security and identity

access information, telephony,

video streaming, conferencing,

desktop sharing, data sharing,

call monitoring and control,

speech recognition - with real-

time and non-real-time

communication services - such

as instant messaging

Unified Communications

Unified Communications

With so many ideas and

definitions of Unified

Communications (UC), it is

often difficult to determine the

value stream that UC delivers

to businesses.

However, managing the

volume and priority of e-mails,

voicemails, SMS texts,

telephone calls and instant

messages that the average

person reads, composes,

sends and receives during the

working day - it becomes clear

the abundance of information

propels employees into a

much faster, more challenging

and dynamic environment.

Unified Communications

Unified Communications

Unified Communications – Service Management

Abiliti: Digital Technology

ABILITI: Future Systems – Strategic Partners

• ABILITI is part of a consortium of Future Management and Future Systems Consulting firms for Intelligent Buildings and Smart Homes Strategy – Cloud Computing / Smart Devices / Smart Grid / Next Generation Network (NGN) Telco 2.0 Architecture / Renewable & Alternative Energy

• Colin Mallett Former Chief Scientist @ BT Laboratories, Martlesham Heath

– Board Member@ SHABA and Visiting Fellow @ University of Hertfordshire

– Email: (Office)

– Telephone: (Mobile)

• Graham Harris Founder and MD @ Abiliti: Future Systems

– Email: (Office)

– Telephone: (Mobile)

• Nigel Tebbutt 奈杰尔 泰巴德

– Future Business Models & Emerging Technologies @ INGENERA

– Telephone: +44 (0) 7832 182595 (Mobile)

– +44 (0) 121 445 5689 (Office)

– Email: Nigel-Tebbutt@hotmail.com (Private)

ABILITI: Future Systems - Strategic Enterprise Management (SEM) Framework ©