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

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4 Connected World IoT Portfolio.pptx

t1 Issue t2 Problem t3 Recognition t4 Report t5 Record t6 Response t7 Resolution

Dis

sati

sfac

tio

n

Sat

isfa

ctio

n

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

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8 Connected 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

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9 BLANK.POTX

Sensors

Connectivity Gateway

Database

Dashboards Predictive Analytics

CEP

CEP

KBM PIM

Call Center

Acquisition

Aggregation

Analytics

Assignment

Action

MLS

IoT

Pla

tfo

rm

IoT

Do

mai

ne

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

INT

ER

NA

L E

XT

ER

NA

L

People

OP

TIM

IZE

T

RA

NFO

RM

AT

ION

AL

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.

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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.

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The information contained in this presentation is proprietary. Copyright © 2013 Capgemini. All rights reserved.