Big Data: Real-life examples of Business Value Generation with Cloudera

Big Data: Real-life examples of Business Value Generation
Richard Brown
Global Programme Leader
Big Data & Analytics

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BIM
Copyright © 2014 Capgemini. All rights reserved.
Big Data: Real-life Examples of Business Value Generation | Richard Brown
Over 40% of the companies that were in the fortune 500 in 2000 were not there in 2010

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BIM
Big Data: A confluence of Sources and Technology
New Opportunities
New Sources
Public
Social
Geo
RFID
Meters
Mobile
Web
New Technologies
Sensors

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Improving Revenue
Existing products & services
Data as a Revenue Stream
Improving Revenue
New products and different markets
4 Ways in which the opportunity is being exploited
Cost Reduction

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US Retail Chain
Hadoop: Data storage cost down from $30k/Tb  $1k/Tb.
The Situation
Massive EDW
4000 stores
650m SKUs
50 Tb per day
The Solution
440 node Hadoop cluster
POS, Inventory, Social
Data optimized across EDW &HDFS.
Max use of Opensource
The Benefits
$23m saving p.a.
Higher level of forecast accuracy
Improved collaboration with vendors
Improved data integrity
Cost Reduction

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60% of Hadoop implementations are for new business applications

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Insight at the point of action
Online enquiry
Service B
Product A
Product selected
Up-sell x-sell
Customer Sales history
Web transaction
Success rate from 5% → 20%
Stock out in store
Source D
Source C
Sources indentified
Supply
Available stock
Delivery lead times
On-shelf Availability up 7%
Product in transit – RFID location
Model of optimum revenue for replenishment scenarios
Shipping partner: Route data
Current performance of supply routes
Stores: live sales performance
Competitor sales data in locality from 3rd party provider
Recent social media activity
Success rate for product in x-sell scenario
Customer web profile data
Predictive model of customer response
Available Products
Recent call history: Sentiment data
Existing Revenue

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Global Media & Entertainment company
Existing Revenue
Rapid correlation of social media and operational data
The Ask
How to improve box office takings?
The Solution
Social media analysis
•Sentiment
•Mentions
Theatre counts
Key influencers
Format release analysis
The Benefits
Improved release schedules
Improved marketing effectiveness
Rapid response to market changes
Improved yields ($ m)

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$ 90 Billion: Global Pharmaceutical Promotion Spend in 2012*
$19.7 Billion: Pharmaceutical Promotion Spend in 2012 in European Union (EU5).**
European Pharmaceutical
*Source: Cegedim Strategic Data, “2012 Pharmaceutical Promotional Spending: Global Trends”.
** EU top 5 = France, Germany, Italy, Spain, United Kingdom.
Physicians are key opinion leaders on drug selection
Selection of right Opinion Leaders can allow more effective targeting of marketing funds
More effective identification of Opinion leaders can deliver significant ROI.
Emerging Trends in European Pharma Market.
As Pharmaceutical promotional spends shrink (EU5 -3.6% in 2012 *) and sales force is reduced, effective identification segmentation and targeting of doctors becomes important.
1-to-1 Physician interaction (Detailing)
Direct to Customer
Existing Revenue

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Opinion Leader Identification Process
Network Influence Score gives measure of Influence in the Referral Network of doctors.
Publication Score gives measure of Influence in Publication activities.
Prescription Score gives measure of Influence from drugs’ Prescription activities.
Affiliation Perception Score gives measure of perception based on affiliations to Prestigious Hospitals & Academic Institutes.
Social Media Score gives measure of influence in social media, blogs etc.
Opinion Leaders
Prescription Data
Publication Data
Referral Data
Survey Data
Social Media Data
Affiliation Data
Existing Revenue
Referral Data of doctors.
Prescriptions Data.
3rd Party Survey Data.
Hospitals, Institutes & Academic Institutes affiliation Data.
PubMed Data for medical publications; clinical trials, research papers, news etc.
Pharma blogs, forums and other social networking sites.

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“Shifting sands” In today’s information landscape new islands of value are appearing across organisation & industry boundaries

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1234 123456 12345
Banks owning data on consumer spend behaviours – moving to sell data to Retailers and Consumer Products companies
Insurers owning data on car, house... ownership and getting into services around this - becoming Estate Agents
Telco providers holding information on retail activity
– becoming retailers
Consumer products companies gaining consumer data through social media to drive connection through on-line channels, bypassing Retailers
Utilities owning data about households and selling services around the house – eg security, insurance, maintenance..
Changing Industry...

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Global Telecommunications Provider
The Ask
Traffic volumes
Plan the network
Data to help negotiate with partners
The Solution
Socio-thermodynamic modeling
Network modeling
Fault and fraud detection
Traffic imbalance analysis
Opening up new revenue streams
The Benefits
Major cost saving
Increase customer service / response to issues
Identified new business opportunities:
•New markets
•New customer .
New Revenue

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Global HR / Employment Consultancy
The Ask
Large volume of CVs
Large volume of vacancies
Need to rapidly and accurately match
The Solution
A learning algorithm processes the text within CVs and jobs
Vectorization of documents
Automatic matching by geo-location
Visualization of results
Users have been amazed by the accuracy of the system
The Benefits
Better market visibility
Improved role matching
200,000 documents processed in a 2 hours
15 new business applications
Advisory service for employers relocating .
New Revenue

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Data Monetization
Data Monetization
“Data is the new oil.”

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Public Sector
Fraud Detection
Crime Prevention
Service Optimization

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How are organisations getting there?
Digital Capability
Leadership Capability
The How: Successful transformations depend as much on how firms manage digital transformation than solely on implementing new technologies
The What: Using digital technology to transform the customer experience, operational processes and business models

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How are organisations getting there?
Digital Capability
DIGITAL MASTERS
FASHIONISTAS
CONSERVATIVES
BEGINNERS

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Revenue Generation
Digital Capability
Revenue Generation
+9%
-10%
-4%
+6%

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Profitability
Digital Capability
Profitability
+26%
+9%
-24%
-11%

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It is not from the edge You need Vision, Strategy and Business & IT working together

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Cloudera Enterprise Data Hub Next Generation Data Management Platform
Open, agile and reliable platform
Open source and enterprise-grade, constantly enhanced. Agility to handle more types of data without defining structure upfront. Focus on performance and security.
Mixed workload integration
Supports and manages different types of workloads for different types of analytics and users population (Batch processing, Interactive SQL, Search, Machine Learning, In memory processing)
Easiness of integration
CDH certified with all major technologies our customers have already (Informatica, SAS, Tableau, SAP BOBJ, Microstrategy, Talend, Teradata, etc.) and new technologies (Revolution Analytics, Splunk’s Hunk, etc;). Cloudera can be an “add-on” to existing architectures to enhance scalability and analytical features.
Scalable and Cloud “Infinite” Storage capacity as the cost is an order of magnitude lower than traditional DB. Choice to deploy on-prem as well as in the Cloud (eg. Elastic Analytics).
An open solution for Big Data

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Enterprise Data Hub Accelerator
Run
Transform
Scale
Initiate
Initiate
Scale
Transform
Run
Business Drivers
Governance
Platform
Data
Analytics
1st tactical wins
3-6m execution time
Set up 1st business driver.
Core team and core agile processes initialized
Kick start communication.
Adapt current analytics processes to new platform.
Core data blocks initialized, Initiate MDM, DQ, Data Privacy processes.
Set up first data platform and learn.
Expand 1st wins
Execute on 1st business driver
Build 9-12m plan.
Industrialization & data exploration processes set up
Increase comm. on successes.
Keeping same analytical algorithms, expend depth, scope and granularity of datasets.
Extend scope of data to peripheral data and external data.
Scale to enterprise industrialized deployment.
Set up strategic drivers needed for Corporate Development and execute.
Broaden governance to operational processes to drive transformation.
Use new types of analytics (machine learning, discovery algorithms, scientific algorithms).
Increase acquisition rhythm, eg. leverage real time streaming.
Connect to operational mission critical systems.
Fuel innovation roadmap with quarterly updates on business drivers priorities.
Iterative continuous improvement
and innovation.
Continuously refine models
Iteratively test out new algorithms and new data.
Continuous improvement on data provisioning/data management.
Continuous platform optimization (TCO, overall efficiency).

The information contained in this presentation is proprietary. Copyright © 2014 Capgemini. All rights reserved.
Rightshore® is a trademark belonging to Capgemini.
www.capgemini.com/bim
About Capgemini
With almost 140,000 people in over 40 countries, Capgemini is one of the world's foremost providers of consulting, technology and outsourcing services. The Group reported 2013 global revenues of EUR 10.1 billion.
Together with its clients, Capgemini creates and delivers business and technology solutions that fit their needs and drive the results they want. A deeply multicultural organization, Capgemini has developed its own way of working, the Collaborative Business Experience™, and draws on Rightshore®, its worldwide delivery model.

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Big Data: Real-life examples of Business Value Generation with Cloudera