The document discusses fast fashion retailing, luxury goods retailing, and digital marketing strategies. It focuses on how retailers are adopting new digital business models and omni-channel retail approaches to drive revenue and engage customers. Key points discussed include the rise of fast fashion retailers, targeting of new customer demographics by luxury brands, and the importance of technologies like mobile, social media, and real-time analytics to create compelling customer experiences.

1. Connected Fashion™

2. Retail Revenue Accelerator™
Next-Generation Enterprise (NGE) Digital Business Models –
driving emerging Digital product and service providers.
The Digital Enterprise is all about doing things better today in
order to design and build a better tomorrow. Digital Marketing is
driven by rapid response to changing social conditions so we can
generate and maintain increased stakeholder value - and create
a brighter future for all of our stakeholders to enjoy today……

4. 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

5. 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 ChannelsSocial Media
Conversations
Digital Marketing – Retail 2.0 Model

6. 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

7. 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

8. 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 •

10. 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

12. 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

13. 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 •
• Valentino •
• Versace •
Cache Brands
• Du Maurier •
• Dunhill •
• Rolex •
Star Brands
• Calvin Klein •
• DKNY •
• Hilfiger •
• Hugo Boss •
• Ralph Lauren •
Premium Brands
• Balman •
• Galliano •
• Tiffany •
• Swarovski •
Micro Brands
• Liberty • Asprey •
• Mappin & Webb •
Esoteric Brands
• Patek Phillippe •
• Van Cleef & Arples •
Bespoke Brands
• Leviev •
• Graff •
Aspirational Brands
• Bulgari • Cerutti •
• Mont Blanc • Tods •
Fashion Brands
• Brooks Bros. •
• Kate Spade •
• La Croix •
• Marc Jacobs •
• Nicole Farah •
Challengers
• Coach •
• Diesel •
• Fendi •
• Superdry •

14. 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

15. Digital Marketing – Luxury Goods
Luxury Brand
Aggregators
• PPR •
• LVMH •
• Richemont •
Luxury Brands
• Channel •
• Dior •
• Hermes •
• Gucci •
• Prada •
Designer Labels
• Armani •
• Burberry •
• D&G •
• Valentino •
• Versace •
Brand Status Sales Volume
Pyramid of Fashion
Esoteric Brands
• Patek Phillippe •
• Van Cleef & Arples •
Cache Brands
• Du Maurier •
• Dunhill •
• Rolex •
Star Brands
• Calvin Klein •
• DKNY •
• Hilfiger •
• Hugo Boss •
• Ralph Lauren •
Premium Brands
• Balman •
• Galliano •
• Tiffany •
• Swarovski •
Micro Brands
• Liberty • Asprey •
• Mappin & Webb •
Bespoke Brands
• Leviev •
• Graff •
Aspirational Brands
• Bulgari • Cherutti •
• Mont Blanc • Tods •
Fashion Brands
• Brooks Bros. •
• Kate Spade •
• La Croix •
• Marc Jacobs •
Challengers
• Coach •
• Diesel •
• Fendi •
• Superdry •

16. 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

17. Retail Revenue Accelerator™
The Fashion Pyramid™ – 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

19. Qubix Digital™ - Digital Marketing
7. Enthusiasts
8. Fanatics
5. Followers
6. Supporters
3. Inactive
4. Casuals
1. Disconnected
2. Indifferent
Customer Profile FECI Segments: -
4%
8%
14%
18%
The Unconnected…..
“Donut and Ice Cream Cone™”
Big
Data
Cloud
Services
Analytics
Multi-Channel
Retail
Social
Intelligence
Campaign
Management
6%
12%
16%
22%

20. Market Value Proposition
Omni-channel Digital Retail supports the following sales channels:-
– In-store
– Catalogue
– Call-centre
– e-Commerce
– Mobile
– Social Media
• Social Media is now the fastest-growing Sales Channel in the most
affluent Demographic Segments and socially active Customer Streams
• Digital Revenue Acceleration – driving sustainable growth through
incremental sales, market share and revenue streams – by deploying
Digital Platforms / Data Science Analytics / Social Intelligence Insights

21. / Promcoples/
Brand
DNA
Brand
Personality / CSFs
Brand Promise / Cache
Brand Core Values / Principles
Brand Benefits – Category / Product Features
Brand Consumer Perception / Loyalty
Brand Audience – Consumer Metrics / Analytics / Insights
Market Insights – Brand Positioning / Market Share
On-line Brand Management
Target –
Who ?
Attention –
What?
Interest –
When ?
Need –
Where ?
Desire –
How ?
Aspirations –
Why ?
Customer Experience and Journey
Lifestyle –
Channels ?
Omni-channel Digital Retail
In-store
Catalogue
Call-centre
e-Commerce
Mobile
Social Media
Campaigns
Offers
Promotions

22. Lifestyle Analytics
• Digital Retailers seek to enhance their Consumer Data with Lifestyle Analytics - Who, What,
Where, Why When, How. Consumer Lifestyle aspirations and motivation are often expressed
through the lifestyle events that people choose to make happen - and these lifestyle choices
are documented in their Consumer Spending, Social Media and Audience Metrics Data.
• Lifestyle Events - "People and Places" Data: -
– Who are they interacting with - People
– What ideas are they connecting with - Trends
– Where are they going - Places
– Why are they doing this - Lifestyle
– When are they doing it - Time
– How are they doing it - Channels
• Lifestyle "People, Places and Events" Data is valuable - so we don't usually find it in "free"
Public Domain or Open Source data sets. What we do find in Public Sources is lots of object
or "Thing" Data - generic environmental and transport information such as "Trains and Boats
and Planes" Data - which may be re-used in order to enhance our customer experience.....
Sport
Music
Fashion

23. Lifestyle Analytics - Subjects
Sport Music Fashion
School College Work
Trends People Places Media

24. Education and Work
Lifestyle and
Aspirations
Lifestyle Analytics - Clusters
Friends and Family
Leisure and
Entertainment

25. Cluster Analysis in Data Science
• Cluster Analysis is a technique where similar data item values are identified and grouped together in Cluster Centrums -- in
order to discover previously unknown or concealed data relationships - using a variety of Clustering Algorithms. This model
is used to explore very large volumes of transactional or machine generated (automatic) data, social media and internet
content. Hundreds of spatial, mechanical, mathematical and statistical clustering algorithms are available. Many of these
clustering algorithms may be “admissible” – but no single algorithm when used alone can be considered “optimal”: -
– K-means
– Kernel K-means
– Nearest neighbour
– Spectral Clustering
– CHAID Analysis / R
– Ranking Algorithms
– Gaussian mixture model
– Latent Dirichlet Allocation
• The CHAID Analysis (Chi Square Automatic Interaction Detection) in R is a natural form of numeric analysis that identifies
each independent variable to discover implicit data relationships (interactions) with dependant variables, along with other
data outcomes, in and across single / multiple Data Sets - without any explicit prior assumptions as to the number or nature
of Cluster Centrums. This model – using automatic determination in order to identify how each dependent variable is related
and explain implicit natural groupings and reveal any other previously hidden data outcomes– is used in cases of market
penetration, predicting and interpreting responses and a multitude of other data-driven research problems.
• Exploring Baysean, Clustering and Wave-form algorithms against time-series and cross-section Big Datasets are the key to
unlocking Cycles, Patterns and Trends in complex (non-linear) systems – Cosmology, Climate and Weather, Economics and
Fiscal Policy – in order to forecast future outcomes and events by modelling the impact of Random Events (Weak Signals,
Wild Cards and Black Swan Events) acting on Human Activity data (Schumpeter Political, Economic, Social, Industrial,
Agronomy and Technology Waves) and Natural data (Bond Cycles - Solar, Oceanic and Atmospheric Climate Forcing).

26. The Pyramid™ - Digital Marketing
Customer Profile FECI Segments: -
The Unconnected…..
“Donut and Ice Cream
Big
Data
Cloud
Services
Analytics
Multi-Channel
Retail
Social
Intelligence
Campaign
Management
7. Enthusiasts
8. Fanatics
5. Followers
6. Supporters
3. Indifferent
4. Casuals
1. Disconnected
2. Inactive
4%
8%
14%
18%
6%
12%
16%
22%
Big
Data

27. Social Media Customer Profiling
‣ SCENARIO – Social Media Campaigns, Offers and Promotions
‣ Sky IQ combine Debenham's Credit Card Transaction Data with detailed EPOS, mobile
and on-line Orders / Deliveries / Cancellations / Returns at the SKU level, enhanced
with Sky TV Audience data - to create a "Single View of Customer". This IT Services
expenditure is viewed as a "cost centre" by Debenhams Finance.
‣ We load this Sky IQ Single View of Customer data set onto an Oracle Cloud platform to
profile and rank Customers by spend volume. This is further enhanced with Social
Media data where Debenham's and it's core brands - including Ted Baker, John Rochas
and Mantaray labels - are mentioned.
‣ This reveals numerous interesting clusters which yield actionable insights - one cluster
centrum is that of males aged 20 - 40 who purchase casual fashion (predominantly
John Rochas and Mantaray brands) from Debenhams. What ideas are they connecting
with in Social Media – in Music, Sport, Fashion – and what does this tell us about their
lifestyle and aspirations? Where do they buy their formal and business fashion? Can
we use these Market Insights in order to discover cross-sell / up-sell opportunities for
business wear and formal attire from Debenhams brands such as Ted Baker

29. Business Strategy – Implementation Pathways
Mission Capital Restructuring and
Business Flotation
Strategy Theme Business Restructuring
Desired Outcomes Governed Business Functions Approved Business Processes Certified Business Systems
Goals Business Models, Organisational
Standards, Quality and Compliance
Process Models, Business Process
Standards, Quality and Governance
Enterprise Architecture Models,
Business Systems Standards,
Quality and Governance
Objectives Operational Standards, Enterprise
Governance, Reporting, Controls
Auditable / Traceable / Compliant Business
Processes / Documentation
World-class Process Execution
Auditable / Traceable / Compliant
Business Systems
Strategic
Requirements
Statutory and Regulatory Reporting -
Controls, Auditability, Traceability,
Statutory and Regulatory Compliance,
Health and Safety Accreditation
Business Process Modelling / Mapping
Business Process Re-engineering Business
Process Improvement
Business Process Quality Management
Business-as-Usual (BaU)
Systems Failover / Recovery
Contingency Planning
Disaster Recovery
Business Enabler Smart Blueprint and Capability Roadmap
for Long-term Organisational
Sustainability
Smart Blueprint and Capability Roadmap for
Business Continuity
Smart Blueprint and Capability
Roadmap for Platform Upgrade /
Technology Refreshment / Business
Systems Replacement
Technology Enabler Human Capital Management
Financial Management
Asset Management
Business Process Modelling and
Management, Workflow, Data / Process /
Systems Integration
Mobile Platforms
ERP / CRM / BI
Analytics / Insights
Cloud Services
CSF
KPI

30. Return on Investment
• Digital Business Transformation - Value Pathways
– Achieve Strategic CSF’s, Outcomes, Goals and Objectives
• Digital Business / Enterprise Model - Value Pathways
– Achieve Operational Targets and KPI’s
• SMACT/4D Digital Technology Stack - Value Pathways
– Achieve Technology Refreshment and Digital Re-platforming

31. Pathway Benefit Business Transformation Use Case
1 Achieve
Strategic
Requirements
Achieve Strategic outcomes, goals and
objectives through delivering a Digital
Business Transformation Programme
Strategy outcomes, goals and objectives achieved: – CSFs /
KPIs / Financial Targets / Value Chain Management achieved
through delivering a Digital Business Transformation Programme
2 Reduce
Indirect Costs
Establishment
Reduce Establishment – Fixed Assets
(Buildings, Office and DCT Equipment)
and Staff (Direct and Indirect costs)
Establishment Costs Reduced: – Fixed Assets and Staff costs
reduced by delivering Organisational Change through a Digital
Business Transformation Programme
3 Improve
Business
Operational
Performance
Improve Business Operational
Performance by introducing a Digital
Business Operating Model
Business Operating Model: – Functional Requirements met by
introducing a Digital Business Operating Model – supporting
Organisation Change / Process Improvement Management /
Strategic Vendor Management / Inventory Management
4 Simplify
Organisation
Structure
Improve Business Process Execution
by introducing a Digital Organisation
Structure
Organisation Hierarchy Model: – People Requirements met
by introducing a Digital Business Operating Model – supporting
Organisation Change and Process Improvement Management
5 Simplify
Business
Processes
Improve Business Process Execution
by introducing a Digital Business
Process Hierarchy
Digital Business Process Model: – Process Requirements met
by introducing a Digital Business Operating Model – supporting
Organisation Change and Process Improvement Management
6 Reduce Direct
(Trading) Costs
Deliver efficiency, cost-effectiveness
performance, and future-proofing by
deploying a Digital Business Model
Digital Business Model: – Migrating customers, products and
services from a traditional bricks-and-mortar Business Model
(F2F High Street presence and Call Centres / Contact Centres)
to a Digital Business Model will reduce overheads by up to 40%
7 Increase
Revenue
Drive Sales Performance by deploying a
Digital Business Model
Digital Business Model: – Migrating customers, products and
services from a traditional bricks-and-mortar Business Model
(F2F High Street presence and Call Centres / Contact Centres)
to a Digital Business Model increases sales revenue up to 40%
CASE STUDY 1: – Medical AnalyticsDigital Business Transformation - Value Pathways

32. Pathway Benefit Business / Enterprise Architecture Model Use Case
8 Business
Performance –
Functional
Requirements
Deliver efficiency, cost-effectiveness
performance, and future-proofing by
deploying a Digital Solution Model and
SMACT/4D Digital Technology Platform
Digital Solution Model: – Migrating customers, products and
services from a traditional Technology Platform (EPOS / Call
Centres / Contact Centres) onto a SMACT/4D Digital Technology
Platform will reduce costs by 40% (annual repeatable benefits).
9 Increase Social
Media and
Internet Traffic
Stakeholders can build increased digital
presence, market share, financial
value, reputational value and good will
through massively increasing Internet
Traffic and Social Media Conversations.
Digital Presence: – Social Media Conversations and Internet
Traffic volume is increased, generating incremental stakeholder
value by yielding Actionable Insights for campaigns, offers and
promotions revenue Analysis of Internet data allows Product
Managers to support marketing strategies and campaigns that
consistently out-perform competitor product / service offerings.
10 Increase Sales
Units / Volume
Implementing SalesForce.com could
increase Sales Volume by an average of
40% in the first year. Mining Actionable
Commercial Insights using AWS EMR
Big Data Analytics may yield a further
increase in Sales Volume by up to 40%.
Internet Traffic Analysis: – SalesForce.com and AWS EMR Big
Data Analytics reduces the cost to process Sales Data, yielding
increased data processing rates to support marketing decisions.
Analysis of this information allows Digital Marketing Managers to
promote sales and marketing strategies that consistently achieve
market-leading retail outcomes and financial results / outcomes.
11 Increase Sales
Revenue and
Contribution
Drive increased cost-effectiveness,
efficiency, sales performance, and
Market Presence from the Digital
Business Model and Technology Stack
Digital Business Architecture – Lean Scenarios / Use Cases
and Agile Epics / Stories are delivered via the Digital Technology
Stack (e.g. Internet Social Media and User Content Analysis, Big
Data Analytics, Mobile Platforms, 4D Geospatial Data Science)
12 Increase EBIT
Profitability –
enhance ROI
Ensure efficiency, accuracy and cost-
effectiveness of Market and Financial
Analysis – both routine / ad-hoc tasks.
Financial / Market Data Analysis: AWS EMR Cloud Big Data
Analytics reduces the cost to store Customer, Market, Financial
Transactional Data, allowing longer retention of data to support
offers / promotions and campaign management / analysis upsell /
cross-sell campaigns and rise in Market Sentiment, Good Will,
Reputational Value and Stock Market Valuation scenarios
CASE STUDY 1: – Medical AnalyticsDigital Business / Enterprise Model - Value Pathways

33. Pathway Benefit “SMACT/4D Digital Technology Stack” Use Case
13 Real-time Data
Streaming and
Monitoring
Stakeholders get the most timely and
appropriate alarms and alerts of any
emerging disruptive market, technology,
political, social and economic events.
Horizon Scanning, Tracking and Monitoring: Global Internet
Content, Social Intelligence, News Feeds and Market Data are
mined as sources for early warning of disruptive Weak Signals
predicating possible future Wild Card and Black Swan events.
14 Predictive
Analytics
Stakeholders can build financial value
by taking an active role in self-service
management of their own Enterprise
Risk Management, Market Sentiment /
Price Curve Forecast Data and Models.
Scenario Planning and Impact Analysis : - Social Intelligence
and Market Data is mined for early warning of emerging trends
and Actionable Insights in Market Sentiment / Price Movement.
Monte Carlo Simulation generates Business Scenario clusters /
Bayesian Analysis of the probability of each scenario occurring.
15 Technical
(Quantitative)
Analysis
Financial Technology capabilities and
resources matched to the nature and
complexity of the Analytics assignment
– the evaluation and selection of those
future options that provide the best
possible fit with target future outcomes.
Financial Portfolio Management: - Buy-Hold-Sell decisions -
Big Data reduces the cost to analyse Market Data, allowing
faster processing of data to support investment decisions and
model financial outcomes. Analysis of this data allows Portfolio
Managers to support appraisal practices and investment fund
strategies that consistently out-perform their Financial Markets.
16 Financial
Analysis and
Economic
Modelling
Ensure efficiency, accuracy and cost-
effectiveness of Economic Modelling
Econometric Analysis and Financial
Planning tasks.
Historical Market Data Analysis: Business Cycles, Patterns
and Trends - Big Data reduces the cost to store Market Data,
allowing longer retention of data to support investment decisions
and model financial outcomes. Analysis of this data allows Fund
Managers to promote appraisal practices and investment
strategies that consistently achieve market-leading results.
17 SMACT/4D
Digital
Technology
Platform
Deliver efficiency, cost-effectiveness
performance, and future-proofing by
investing in a SMACT/4D Digital
Technology Architecture and Platform
Analytics Platform – Functional / Non-functional Requirements
delivered via the Digital Technology Platform Components (e.g.
Internet Content, Social Media and User Content Analysis, Big
Data Analytics, Mobile Platforms, 4D Geospatial Data Science)
CASE STUDY 1: – Medical AnalyticsSMACT/4D Digital Technology Stack - Value Pathways

34. Balanced Scorecard – Customer Value

35. Big Data Analytics Templates
There are just two Big Data Analytics Templates required to support all of the various Scenarios below: -
1. CUSTOMER and CITIZEN PROFILE / ANALYTICS - MODEL TEMPLATE
• “TROUBLED FAMILIES" DATA ENHANCEMENT SCENARIO - NHS and Local / Central Gov. Data
• CUSTOMER and CITIZEN PROFILE / ANALYTICS SCENARIO - Customer / Citizen Data
• LIFESTYLE DATA ENHANCEMENT SCENARIO - Social Media and Audience Metrics Data
• GEO-DEMOGRAPHIC DATA SCENARIO – GIS Mapping / Spatial Analysis Experian / CACI Data
2. PREDICTIVE ANALYTICS MODEL TEMPLATE
– Data Load / Model Initialisation / Tuning / History Matching / Prediction Runs
• ECONOMETRICS / ECONOMIC MODELLING SCENARIO
– Long-range Forecasting and Economic Analysis

36. / Promcoples/
Brand
DNA
Brand
Personality / CSFs
Brand Promise / Cache
Brand Core Values / Principles
Brand Benefits – Category / Product Features
Brand Consumer Perception / Loyalty
Brand Audience – Consumer Metrics / Analytics / Insights
Market Insights – Brand Positioning / Market Share
On-line Brand Management
Target –
Who ?
Attention –
What?
Interest –
When ?
Need –
Where ?
Desire –
How ?
Aspirations –
Why ?
Customer Experience and Journey
Lifestyle –
Channels ?
Omni-channel Digital Retail
In-store
Catalogue
Call-centre
e-Commerce
Mobile
Social Media
Campaigns
Offers
Promotions

37. “DATA SCIENCE” – my own special area of Business expertise
Targeting – Split / Map / Shuffle / Reduce
Consume – End-User Data
Data Provisioning – 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 data 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 Pivotal)
Extreme Data xdg
Zybert Gridbox
– Data Warehouse Appliances
Ab Initio
Ascential
Genio
Orchestra
SOCIAL INTELLIGENCE – The Emerging Big Data Stack
Information Management Strategy
Data Acquisition Strategy

38. 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

39. Qubix Digital™ - Digital Marketing App
Qubix Digital™
Social Intelligence
and Market
Sentiment Cloud
CRM /
CEM
Data
Profile
Data
CRM / CEM
Big Data
Analytics
Customer Management
(CRM / CEM)
Social
Intelligence
Campaign
Management
e-Business
Smart Apps
Big Data Analytics
Qubix Digital™
Customer Loyalty
& Brand Affinity
Qubix Digital™
Analytics
Smart Apps
Insights
Reports
Market
Survey DataTV Set-top Box
Channel
Selections
Smart App
Playlists

41. Social Intelligence

42. 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.....