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Proactive Services
Making Machine Data Valuable for Customer and Business
A collection of IoT assets creatd by CC, SES, DCX, Sogeti, and Sogeti High Tech by
Prof. Dr. Michael J. Capone
v 16.10.2015
Reactive B2B service processes are slow and
expensive
1. Operator reports an issue, asks
for help or orders parts.
2. Customer service creates a case.
6. Makes appointment with customer.
3. Account Management checks SLA. 4. Engineering determines resolution and
creates ticket.
5. Service Manager checks
availability of technician, parts,
and tools. Orders parts.
7. Dispatches technician.8. Technician performs repair and completes report.
9. Wrong problem, part or tool.
1. Reactive
2. Manual
3. Time-Consuming
4. Subjective
5. Dissatisfaction
Reactive B2C service processes intensify
dissatisfaction
1. Driver reports an issue.
2. Customer service logs call.
3. Customer service dispatches
roadside assistance.
9. Calls customer to notify vehicle
ready.
3. Service Manage reviews case.
6. Checks part availability. Orders part.
7. Parts delivered.
5. Mechanic diagnoses problem.
8. Repairs vehicle.
It made a
klunk klunk
kind of
noise.
You have
to bring it
in for
diagnosis.
1. Reactive
2. Manual
3. Time-Consuming
4. Subjective
5. Dissatisfaction
Reactive service creates new opportunities to
intensify dissatisfaction
Copyright © Capgemini 2013. All Rights Reserved
4Connected World IoT Portfolio.pptx
t1 Issue t2 Problem t3 Recognition t4 Report t5 Record t6 Response t7 Resolution
DissatisfactionSatisfaction
1. An anomoly in operating data is identified that has a high-probability of impacting performance.
2. The issue manifests itself as a performance problem, failure or outage.
3. The customer is aware of the
problem. Dissatisfaction is
sensed, but not yet expressed.
4. The customer contacts the
manufacturer. Dissatisfaction is
expressed.
5. The manufacturer logs and
reviews the case.
6. The manufacturer
plans action.
7. The resolution is
complete.
1 2
3
4
5
6
7
Recovery
When service processes are sucessfully
executed, recovery is achieved. Recovery
means the cause of dissatisfaction is
resolved. Satisfaction is theoretically
restored.
Capgemini takes IoT “2 Steps Ahead” by making data
actionable.
M2M
Machine-to-machine involves
the communication between
machines to improve
productivity and safety.
Connected devices is a pre-
requisite for M2M.
IoT
Internet-of-Things
involves making the
data from connected
devices available in the
cloud for monitoring
and reporting.
Connected THINGS are
a pre-requisite for IoT.
CSX - 2 Steps Ahead
Connected Service eXperience
involves using the data from
connected devices in real-time to
identify a „Next Best Action“ and
trigger 1:1 interactions between the
sales, customer care, service and
the customer. Connected devices
and IoT are pre-requisites for CSX.
1
2
3
Control Tower Applications
New Value-added
Services
Production Automation
There are several valuable interactions that machine
data can trigger.
Performance and usage
data is acquired and
transmitted every x
seconds.
Data from
many
connected
devices is
aggregated
and stored
When the data indicates an issue
that can cause a problem or
opportunity, a case is created and
a resolution is selected
An actor takes action:
1. Customer Care provides the
operator tips and instructions,
2. Sales & Marketing proactively
sends the customer offers and
orders
3. Technical Service is dispatched
to perform maintenance
4. System sends messages to
machine or person
New proactive business
models are created when
sensor data is used in
real-time.
1
2
4 5
The resolution is
recorded. Outages and
accidents are prevented,
sales are captured, and
customer dissatisfaction
is prevented.
6
Data is analyzed
in real-time to
identify issues or
opportunities.
3
GDL
New data-driven services can create a competitive
advantage
GDL
Goods Dominant Logic
PQT
Service
Inherent
Services
New
IoT-enabled
Proactive
Value-adding
SDL
Service Dominant Logic
Capgemini 5-A Model for Architectural Framework
Copyright © Capgemini 2013. All Rights Reserved
8Connected World IoT Portfolio.pptx
IoT Maturity Assessment, Architecture Framework & Project Plan
Functional Layer Description Technology
Action (A5)
A task is automatically created
for sales, contact center, service,
or system.
ERP Integration, Contact Center,
Field Service Management, Mobile
Apps
Assignment (A4) A recommendation or „Next
Best Action“ is proposed.
Knowledge Base, Expert System,
Product Information System
Analysis (A3) Data is viualized, tabulated, and
analyzed. Insights are produced.
Dashboards, Reporting, Analytic
Tools
Aggregation (A2)
Data from multiple, different
sources are combined and
stored.
Big Data, Data Lake, In-Memory
Database
Acquisition (A1) Data is created and transmitted. Sensors, Gateway, Connectivity
Infrastructure
Actionable IoT Stack
Copyright © Capgemini 2013. All Rights Reserved
9BLANK.POTX
Sensors
Connectivity Gateway
Database
Dashboards
Predictive
Analytics
CEP
CEP
KBM PIM
Call
Center
Acquisition
Aggregation
Analytics
Assignment
Action
MLS
IoTPlatformIoTDomaine
Security
Control Tower
Components
Master Data
Management
Connected
Service
Components
ID Management
Supply Chain
Human
Resources
Inventory
Finance
Asset
Management
Document
Management
ERP
License
Management
Device
Management
Field
Service
Mobile
Sales
Partner Eco-System for 5A Architecture
Platform
Partners
Solution
Partners
Available Best-of-Suite IoT Stacks Side-by-Side
Function IBM HP SFDC SAP
A5 Action CRM, FSM, Call Center
Maximo, ServiceEngage,
ControlDesk, Predictive
Maintenance & Quality, Intelligent
Operations Center
ServiceCloud ServiceCloud
A4 Assignment
Knowledge Base,
Product Management,
Expert System
MDM for PIM, Watson Explorer,
Decision Optimization,
Operational Decision Manager,
Business Process Manager
HP IDOL
(Intelligent Data
Operating Layer)
Knowledge
HCP Core (HANA
Rules engine), HANA
Search
A3 Analytics
Predictive Analytics SPSS, R, Spark, SystemML
HP Distributed R BlueYonder
HCP Core (R), Hana
Search
Historical Analytics
Cognos BI, GeospatialAnalytics,
Streams
Dashboards, Reporting
Cognos BI
MicroStrategy AnalyticsCloud
Fiori Launch Pad,
itelligent, Lumira
A2 Aggregation
Storage
DB2, dashDB, Cloudant,
BigInsights, Informix
HP Vertica (structured),
HP Hortonworks Hadoop
(unstructured), HP
Vertica Place
Heroku Thunder HANA, Sybase IQ
Event Processor
Integration Bus, Spark, Streams,
IoT Foundation
HP CMDB (Data
Modeling)
IoT Cloud XP Engine, ESP, PCO
A1 Acquisition
M2M Gateway eObjects, TrafficSoft, IO LITE, Cumulocity
Connectivity GSM, Satellite, Radio, Wifi, Hardware
Sensor Sogeti High Tech Proprietary Hardware Off-the-Shelf Sensors
Available Best-of-Suite IoT Stacks Side-by-Side
Function Intel Software AG
A5 Action CRM, FSM, Call Center WebMethods
A4 Assignment
Knowledge Base,
Product Management,
Expert System
A3 Analytics
Predictive Analytics
IoT Analytics Apama
Historical Analytics
Dashboards, Reporting
A2 Aggregation
Storage Hadoop, Cloudera
Terracota
Event Processor
Moon Island
A1 Acquisition
M2M Gateway
TrafficSoft, IO LITE,
Cumulocity
Connectivity GSM, Satellite, Radio, Wifi, Hardware
Sensor Sogeti High Tech Proprietary Hardware
Connected World IoT Portfolio.pptx 13
Phases of Digitalization
1
2 3
Proactive
Service
PaaS
Fleet
Management
IoT Use Cases for “Things”
Machines
Industrie 4.0
Assets
Shipments
Products
INTERNALEXTERNAL
People
OPTIMIZETRANFORMATIONAL
Decrease Energy Costs
Decrease Loss & Theft
Decrease Misuse & Accidents
Improve Efficiency & Productivity
Decrease Assets
Decrease Unplanned Downtime
Decrease Inventory Costs
Decrease Labor Costs
Decrease Cost of Waste
Decrease Costs for Parts & Supplies
Decrease Early Retirement
Decrease Shipping Costs
Extend Machine Life
Improve Productivity
Decrease Accidents
Decrease Energy Costs
Decrease Mishandling & Loss
Improve On-time Delivery
Grow After-Market Sales
Decrease Misuse & Warranty Costs
Decrease Accidents
Offer Value-Added Services
Improve First-Call Resolution Rate
Decrease Rearly Retirement
Improve Product Development
Reduce Undesired Side Effects
Reduce Accidents
Reduce Trial and Treatment Periods
Improve Efficacy
Improve Health
IoT Use Cases in the Supply Chain
Quantifiable Business Impact in the Value Chain
Application Area Use Case Clusters Logistics R&D, Production Marketing Sales After-Sales /
Service
CSX Finance
Building Automation
Access Control
Environment Control
Predictive Maintenance
Anytime Delivery
(Shorter Wait Times,
Lower Fuel Costs)
Lower Energy Costs
Improve Conditions
Decrease Downtime
Greater Productivity
JiT Inventory
Revenue Growth
(Anytime Sales)
Revenue Growth
(Anytime Service)
Revenue Growth
(Anytime Shopping,
Personal
Environment)
Factory Automation
Real-time Inventory
Flow Optimization
Asset Track
Safety
Predictive Maintenance
JiT Inventory
Optimize Disposition
Decrease Loss & Theft
Improve Quality
Decrease Downtime
Improve Productivity
Improve Efficiency
Decrease Loss/Theft
Decrease Accidents
Lower Inventory
Optimize Resources
Improve Quality
Faster Delivery Revenue Growth
(Custom Config)
Faster Delivery
Connected Products
(Vehicles)
Infotainment
Telemetry
Predictive Maintenance
Lower Fuel Costs
Optimize Routes
Decrease Accidents
JiT Inventory
Lower Repair Costs
JiT Inventory
Steer Product Dev
Simplify Update Mgt
Improve Productivity
1:1 Offers
based on
Location &
Behavior
Grow Sales visavis
Cross-selling & Up-
selling
Fewer/Shorter
Outages
JiT Inventory
Grow Service Rev
Decrease
Recovery Time
1:1 Configuration
Improve Safety
Optimize Resources
Better Performance
Fewer / Shorter
Downtime
New Rev
Models
SmartCity & eDorf
Intelligent Infrastructure
Asset Tracking
Mobility
Surveillance
Environment Monitoring
Decrease Traffic
Improve Security
Improve Health
Improve Health
Improve Efficiency
1:1 Offers
based on
Location &
Behavior
Decrease Wait Times
Improve Svc Quality
Improve Environment
Wearables
Entertainment
Performance Mgt
Location Tracking
Education/Instruction
Improve Safety
Improve Health
Improve Safety
Decrease Resolution
Improve Productivity
Improve Efficiency
Lower Training Costs
1:1 Offers
based on
Location and
Condition
Grow Sales visavis
Cross-selling & Up-
selling
Improve Health
Improve Safety
Improve Performance
New Revenue Models for Machine Data
• Mobility Guarantees, Uptime Guarantees & Pre-emptive SLAs.
Instead of a 24-hour response time, the manufacturer will offer to service a product before it
breaks and before the customer repotrs an issue. Example: Mobility Concierge.
• Pay-as-you-Use. Companies will offer pay-for-use, where price or rates reflect actual usage
and behavior. Customers will opt-in to save money. Example: Pay-as-you-Drive.
• New Subscription Services. Companies are developing new subscription services for
customers. Customers will subscribe to services in order to get tips to save fuel, improve
performance, lower operating costs, and prevent accidents. Example: Car Net.
• Factory-as-a-Service or Product-as-a-Service. Products will be free. The
company will replace the one-time sale of a product with a recurring revenue model or
subscription. Example: Grocery Services.
• Data Remarketing. Products will be free. The data generated by the product will be
packaged and sold to third-parties. This revenue will more than offset the cost of the product,
because it is recurring, and the marginal cost of the data is almost zero. Example: Smart Lights.
www.capgemini.com
About Capgemini
With more than 120,000 people in 40 countries, Capgemini is one of
the world's foremost providers of consulting, technology and
outsourcing services. The Group reported 2011 global revenues of
EUR 9.7 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
ExperienceTM, and draws on Rightshore ®, its worldwide delivery
model.
Rightshore® is a trademark belonging to Capgemini
The information contained in this presentation is proprietary.
Copyright © 2013 Capgemini. All rights reserved.

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Proactive Services Through Insights and IoT by M. Capone

  • 1. Proactive Services Making Machine Data Valuable for Customer and Business A collection of IoT assets creatd by CC, SES, DCX, Sogeti, and Sogeti High Tech by Prof. Dr. Michael J. Capone v 16.10.2015
  • 2. Reactive B2B service processes are slow and expensive 1. Operator reports an issue, asks for help or orders parts. 2. Customer service creates a case. 6. Makes appointment with customer. 3. Account Management checks SLA. 4. Engineering determines resolution and creates ticket. 5. Service Manager checks availability of technician, parts, and tools. Orders parts. 7. Dispatches technician.8. Technician performs repair and completes report. 9. Wrong problem, part or tool. 1. Reactive 2. Manual 3. Time-Consuming 4. Subjective 5. Dissatisfaction
  • 3. Reactive B2C service processes intensify dissatisfaction 1. Driver reports an issue. 2. Customer service logs call. 3. Customer service dispatches roadside assistance. 9. Calls customer to notify vehicle ready. 3. Service Manage reviews case. 6. Checks part availability. Orders part. 7. Parts delivered. 5. Mechanic diagnoses problem. 8. Repairs vehicle. It made a klunk klunk kind of noise. You have to bring it in for diagnosis. 1. Reactive 2. Manual 3. Time-Consuming 4. Subjective 5. Dissatisfaction
  • 4. Reactive service creates new opportunities to intensify dissatisfaction Copyright © Capgemini 2013. All Rights Reserved 4Connected World IoT Portfolio.pptx t1 Issue t2 Problem t3 Recognition t4 Report t5 Record t6 Response t7 Resolution DissatisfactionSatisfaction 1. An anomoly in operating data is identified that has a high-probability of impacting performance. 2. The issue manifests itself as a performance problem, failure or outage. 3. The customer is aware of the problem. Dissatisfaction is sensed, but not yet expressed. 4. The customer contacts the manufacturer. Dissatisfaction is expressed. 5. The manufacturer logs and reviews the case. 6. The manufacturer plans action. 7. The resolution is complete. 1 2 3 4 5 6 7 Recovery When service processes are sucessfully executed, recovery is achieved. Recovery means the cause of dissatisfaction is resolved. Satisfaction is theoretically restored.
  • 5. Capgemini takes IoT “2 Steps Ahead” by making data actionable. M2M Machine-to-machine involves the communication between machines to improve productivity and safety. Connected devices is a pre- requisite for M2M. IoT Internet-of-Things involves making the data from connected devices available in the cloud for monitoring and reporting. Connected THINGS are a pre-requisite for IoT. CSX - 2 Steps Ahead Connected Service eXperience involves using the data from connected devices in real-time to identify a „Next Best Action“ and trigger 1:1 interactions between the sales, customer care, service and the customer. Connected devices and IoT are pre-requisites for CSX. 1 2 3 Control Tower Applications New Value-added Services Production Automation
  • 6. There are several valuable interactions that machine data can trigger. Performance and usage data is acquired and transmitted every x seconds. Data from many connected devices is aggregated and stored When the data indicates an issue that can cause a problem or opportunity, a case is created and a resolution is selected An actor takes action: 1. Customer Care provides the operator tips and instructions, 2. Sales & Marketing proactively sends the customer offers and orders 3. Technical Service is dispatched to perform maintenance 4. System sends messages to machine or person New proactive business models are created when sensor data is used in real-time. 1 2 4 5 The resolution is recorded. Outages and accidents are prevented, sales are captured, and customer dissatisfaction is prevented. 6 Data is analyzed in real-time to identify issues or opportunities. 3
  • 7. GDL New data-driven services can create a competitive advantage GDL Goods Dominant Logic PQT Service Inherent Services New IoT-enabled Proactive Value-adding SDL Service Dominant Logic
  • 8. Capgemini 5-A Model for Architectural Framework Copyright © Capgemini 2013. All Rights Reserved 8Connected World IoT Portfolio.pptx IoT Maturity Assessment, Architecture Framework & Project Plan Functional Layer Description Technology Action (A5) A task is automatically created for sales, contact center, service, or system. ERP Integration, Contact Center, Field Service Management, Mobile Apps Assignment (A4) A recommendation or „Next Best Action“ is proposed. Knowledge Base, Expert System, Product Information System Analysis (A3) Data is viualized, tabulated, and analyzed. Insights are produced. Dashboards, Reporting, Analytic Tools Aggregation (A2) Data from multiple, different sources are combined and stored. Big Data, Data Lake, In-Memory Database Acquisition (A1) Data is created and transmitted. Sensors, Gateway, Connectivity
  • 9. Infrastructure Actionable IoT Stack Copyright © Capgemini 2013. All Rights Reserved 9BLANK.POTX Sensors Connectivity Gateway Database Dashboards Predictive Analytics CEP CEP KBM PIM Call Center Acquisition Aggregation Analytics Assignment Action MLS IoTPlatformIoTDomaine Security Control Tower Components Master Data Management Connected Service Components ID Management Supply Chain Human Resources Inventory Finance Asset Management Document Management ERP License Management Device Management Field Service Mobile Sales
  • 10. Partner Eco-System for 5A Architecture Platform Partners Solution Partners
  • 11. Available Best-of-Suite IoT Stacks Side-by-Side Function IBM HP SFDC SAP A5 Action CRM, FSM, Call Center Maximo, ServiceEngage, ControlDesk, Predictive Maintenance & Quality, Intelligent Operations Center ServiceCloud ServiceCloud A4 Assignment Knowledge Base, Product Management, Expert System MDM for PIM, Watson Explorer, Decision Optimization, Operational Decision Manager, Business Process Manager HP IDOL (Intelligent Data Operating Layer) Knowledge HCP Core (HANA Rules engine), HANA Search A3 Analytics Predictive Analytics SPSS, R, Spark, SystemML HP Distributed R BlueYonder HCP Core (R), Hana Search Historical Analytics Cognos BI, GeospatialAnalytics, Streams Dashboards, Reporting Cognos BI MicroStrategy AnalyticsCloud Fiori Launch Pad, itelligent, Lumira A2 Aggregation Storage DB2, dashDB, Cloudant, BigInsights, Informix HP Vertica (structured), HP Hortonworks Hadoop (unstructured), HP Vertica Place Heroku Thunder HANA, Sybase IQ Event Processor Integration Bus, Spark, Streams, IoT Foundation HP CMDB (Data Modeling) IoT Cloud XP Engine, ESP, PCO A1 Acquisition M2M Gateway eObjects, TrafficSoft, IO LITE, Cumulocity Connectivity GSM, Satellite, Radio, Wifi, Hardware Sensor Sogeti High Tech Proprietary Hardware Off-the-Shelf Sensors
  • 12. Available Best-of-Suite IoT Stacks Side-by-Side Function Intel Software AG A5 Action CRM, FSM, Call Center WebMethods A4 Assignment Knowledge Base, Product Management, Expert System A3 Analytics Predictive Analytics IoT Analytics Apama Historical Analytics Dashboards, Reporting A2 Aggregation Storage Hadoop, Cloudera Terracota Event Processor Moon Island A1 Acquisition M2M Gateway TrafficSoft, IO LITE, Cumulocity Connectivity GSM, Satellite, Radio, Wifi, Hardware Sensor Sogeti High Tech Proprietary Hardware
  • 13. Connected World IoT Portfolio.pptx 13 Phases of Digitalization 1 2 3 Proactive Service PaaS Fleet Management
  • 14. IoT Use Cases for “Things” Machines Industrie 4.0 Assets Shipments Products INTERNALEXTERNAL People OPTIMIZETRANFORMATIONAL Decrease Energy Costs Decrease Loss & Theft Decrease Misuse & Accidents Improve Efficiency & Productivity Decrease Assets Decrease Unplanned Downtime Decrease Inventory Costs Decrease Labor Costs Decrease Cost of Waste Decrease Costs for Parts & Supplies Decrease Early Retirement Decrease Shipping Costs Extend Machine Life Improve Productivity Decrease Accidents Decrease Energy Costs Decrease Mishandling & Loss Improve On-time Delivery Grow After-Market Sales Decrease Misuse & Warranty Costs Decrease Accidents Offer Value-Added Services Improve First-Call Resolution Rate Decrease Rearly Retirement Improve Product Development Reduce Undesired Side Effects Reduce Accidents Reduce Trial and Treatment Periods Improve Efficacy Improve Health
  • 15. IoT Use Cases in the Supply Chain Quantifiable Business Impact in the Value Chain Application Area Use Case Clusters Logistics R&D, Production Marketing Sales After-Sales / Service CSX Finance Building Automation Access Control Environment Control Predictive Maintenance Anytime Delivery (Shorter Wait Times, Lower Fuel Costs) Lower Energy Costs Improve Conditions Decrease Downtime Greater Productivity JiT Inventory Revenue Growth (Anytime Sales) Revenue Growth (Anytime Service) Revenue Growth (Anytime Shopping, Personal Environment) Factory Automation Real-time Inventory Flow Optimization Asset Track Safety Predictive Maintenance JiT Inventory Optimize Disposition Decrease Loss & Theft Improve Quality Decrease Downtime Improve Productivity Improve Efficiency Decrease Loss/Theft Decrease Accidents Lower Inventory Optimize Resources Improve Quality Faster Delivery Revenue Growth (Custom Config) Faster Delivery Connected Products (Vehicles) Infotainment Telemetry Predictive Maintenance Lower Fuel Costs Optimize Routes Decrease Accidents JiT Inventory Lower Repair Costs JiT Inventory Steer Product Dev Simplify Update Mgt Improve Productivity 1:1 Offers based on Location & Behavior Grow Sales visavis Cross-selling & Up- selling Fewer/Shorter Outages JiT Inventory Grow Service Rev Decrease Recovery Time 1:1 Configuration Improve Safety Optimize Resources Better Performance Fewer / Shorter Downtime New Rev Models SmartCity & eDorf Intelligent Infrastructure Asset Tracking Mobility Surveillance Environment Monitoring Decrease Traffic Improve Security Improve Health Improve Health Improve Efficiency 1:1 Offers based on Location & Behavior Decrease Wait Times Improve Svc Quality Improve Environment Wearables Entertainment Performance Mgt Location Tracking Education/Instruction Improve Safety Improve Health Improve Safety Decrease Resolution Improve Productivity Improve Efficiency Lower Training Costs 1:1 Offers based on Location and Condition Grow Sales visavis Cross-selling & Up- selling Improve Health Improve Safety Improve Performance
  • 16. New Revenue Models for Machine Data • Mobility Guarantees, Uptime Guarantees & Pre-emptive SLAs. Instead of a 24-hour response time, the manufacturer will offer to service a product before it breaks and before the customer repotrs an issue. Example: Mobility Concierge. • Pay-as-you-Use. Companies will offer pay-for-use, where price or rates reflect actual usage and behavior. Customers will opt-in to save money. Example: Pay-as-you-Drive. • New Subscription Services. Companies are developing new subscription services for customers. Customers will subscribe to services in order to get tips to save fuel, improve performance, lower operating costs, and prevent accidents. Example: Car Net. • Factory-as-a-Service or Product-as-a-Service. Products will be free. The company will replace the one-time sale of a product with a recurring revenue model or subscription. Example: Grocery Services. • Data Remarketing. Products will be free. The data generated by the product will be packaged and sold to third-parties. This revenue will more than offset the cost of the product, because it is recurring, and the marginal cost of the data is almost zero. Example: Smart Lights.
  • 17. www.capgemini.com About Capgemini With more than 120,000 people in 40 countries, Capgemini is one of the world's foremost providers of consulting, technology and outsourcing services. The Group reported 2011 global revenues of EUR 9.7 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 ExperienceTM, and draws on Rightshore ®, its worldwide delivery model. Rightshore® is a trademark belonging to Capgemini The information contained in this presentation is proprietary. Copyright © 2013 Capgemini. All rights reserved.