retail 2.0 strategy - perfect store pdf
TRANSCRIPT
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
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: [email protected] (Private)
ABILITI: Future Systems - Strategic Enterprise Management (SEM) Framework ©