A quick summary on the Internet of Things (IoT), Big Data and Analytics and how that is shaping our world

1. Internet of Things, Big Data and Analytics 101
Frost & Sullivan’s Global Digital Media Research
Mukul Krishna, Senior Global Director, Digital Media Practice
Frost & Sullivan

2. Universal Theme: Seamless, intelligent and ubiquitous
interactivity is a key theme across all verticals
Manufacturing: Intelligent
interconnectivity across the
enterprise for enhanced
control, speed and efficiency
Retail: Highly personalized
customer experience across
channels and devices
Seamless, Inte
lligent and
Ubiquitous
Interactivity
Healthcare:
Integrated and smart
patient care systems
and processes
Banking and Finance:
Seamless customer
experience across all
banking channels
Automotive:
V2V and V2I
communication

3. Universal components of seamless, intelligent and
ubiquitous interactivity
Back-end and
Front-end
Integration
Analytics Engine
Mobile, Wireless,
Smart Devices
Across verticals, the need for integration or interconnectivity
between various systems, databases, and devices, both in
the back-end and the front-end, is recognized as requisite for
delivering a seamless experience.
Analytics to process both internal and external data
provide the intelligence to guide or trigger alerts, or
automated adjustments to processes, offerings to
customers, treatments for patients, or automotive driving
controls.
BYOD, tablets, and other mobile devices, sensors, smart
systems, and robotics, are part of the overall vision and are a
source of excitement across verticals. These enable
ubiquitous and real-time interactivity, both in the back-end
(e.g., among hospital staff), and the front-end (e.g., shopper
with the retailer).

4. Technology Lifecycle Analysis
Manufacturing: The sector is the most
advanced, relatively, in terms of utilizing
intelligent systems to optimize production
processes. Predictive maintenance and
condition-based monitoring has historically
been implemented by most manufacturers
with varying degrees of sophistication.
IoT in Manufacturing
IoT in Automotive
IoT in Retail
IoT in Healthcare
Automotive: The segment made tremendous
strides in achieving its long-term vision of truly
connected vehicles that are context-aware at all
times. The convergence of in-car
technologies, wireless communication and mobile
devices has provided the concept of IoT with
greater traction in this vertical.
IoT in Banking and Finance
Introduction
Banking and Finance: Despite
significant progress made in the
direction of multi-channel and
mobile banking, protecting
sensitive customer information
and deriving actionable business
intelligence from the sheer volume
of data that banks collect is a
restraint for this vertical.
Growth
Maturity
Healthcare: Despite the compelling value
proposition that IoT offers in terms of
integrating siloed domains of operation like
EMR and advanced equipments, persistent
concerns around data security breaches
(and associated financial liabilities) continue
to slow uptake.
Source: Frost & Sullivan
Retail: Retail has been lagging behind in
embracing the idea of IoT. Challenges
associated with data security, top
management buy-in, OS fragmentation
and overall weak macro-economic
conditions will negatively impact
investments in intelligent systems in the
short and medium terms.

5. Internet of Things: Strategically Positioned To Drive
Greater Efficiencies in Process-dominated Markets
Process
Records
IoT Position within the Larger Technology Ecosystem
Designs
CAD drawings
Documents
Master Data
Asset Life Cycles
Schedules &
Maintenance
Testing & Operations
Plant
Management
Ecosystem
• CAE Systems
Content Organization
/ Asset Registry
Objects and Relationships
Authentication, Access,
& User Policies
Collaboration Platform
Interoperability
and Integration
Compliance
Assurances
• Enterprise Content
Management
• Collaboration
Platform
• Enterprise
Resource Planning
• Project
Management
• Supply Chain
Management
• Inventory
Management
• HR, Accounting and
Marketing
management

6. The Four Pillars for an Effective Big Data Strategy
Content Discovery
and Management
Digital intelligence and
Analytics
Storage
User Experience
Just these segments account for more than $10 billion in served, addressable markets.

7. Building a Connected and Smart Ecosystem: A Roadmap
to Business Nirvana
The Internet of Things
connects all manner of endpoints, unraveling a treasure
trove of data
IoT
Ubiqitous networks
and device
proliferation enable
access to a massive
and growing amount of
traditionally siloed
information
Big Data
Analytics and business
intelligence tools
empower decision
makers as never before
by extracting and
presenting meaningful
information in realtime, helping us be
more predictive than
reactive
Analytics

8. Motivation for Specialized Big Data Systems
• Cost of data storage is dropping, but rate of data capture
is soaring
• Sources: online/digital, communications, messaging, usage, transactions…
• Furthermore, need for real-time data-driven insights is also more urgent
• Traditional data warehouses and RDBMS systems cannot keep up
• They are unable to capture, manage and optimize the volume and diversity of
data marketers are seeking to harness today
• Structured, unstructured, and semi-structured data are all essential ingredients in
today‟s marketing mix; traditional systems cannot handle this
• Big Data systems: cluster-based, commodity priced, distributed
computing database management system
• Most often based on Hadoop, but usable without MapReduce programming skills
• Key features: linear scalability, parallel computing, node redundancy, and
centralized access to data
• Server clusters behave like a massive single mainframe: What traditional
databases do in months, a Big Data management system can do in hours

9. Data Alone Has No Direct Utility
• Data on its own is just bits and bytes of
zeros and ones
• Understanding correlations and making
predictions is key
• Understand the consumer decision
process and leverage that in real-time to
find and monetize opportunities
• Analytics makes data come to life and
unlocks its potential
• Helps marketers overcome the complexity
of their data and find winning opportunities
• It‟s the “secret sauce” that, done well,
makes marketing a hero and wins you a
seat at the revenue table

10. Customer-Centric Analytics are a
Business Imperative
• The challenge in providing better service to connected
customers is to “know” them better.
• The majority of retailers are making customer service strategies their
primary strategic focus.
• Economist Intelligence Unit (EIU) survey shows analytics skill relevance
is growing rapidly:
• 37% of executives reported "using data analysis to extract predictive findings
from „Big Data'“ was the marketing skill that mattered most (up >2X from 17%
five years ago)
• 85% of respondents agreed Big Data can help businesses make "more
informed," data-driven decisions

11. Analytics is Transforming
Marketing Automation
• Marketing automation solutions optimize the execution
of three key tasks: lead capture and retention, lead
scoring, and follow-up.
• Big Data adds tools such as clickstream web data to the arsenal
• Analytics can then enhance marketing automation functions
• Lead scoring is an art, not a science. Analytics + Big Data =
• Generate and fully leverage detailed understanding of consumer behavior
• Leverage historical data and benchmarks to score more effectively
• Account for patterns in visitor‟s online behavior – now and earlier, at your site
and others
• Follow up also becomes more powerful
• Successfully (and quickly!) predict which follow-up actions generate the greatest
return for each situation
• Optimize marketing spend by focusing it more effectively on a micro-segment
basis
• There is vast potential for social media engagement combined with
analytics to transform customer relationships.

12. Challenges In Achieving Utopia
• Big Data is daunting
• Clickstreams, weblogs, social media, smart phone analytics, call
transcriptions and medical records yield complex data sets that are
difficult to capture, manage and process
• Unstructured data, non-normalized data, need to use data across various silos,
errors in data, incomplete data – all further complicate the scenario
• Analyzing data is easier said than done
• Nearly half of marketing executives consider limited competency in data analysis
a major obstacle to implementing more effective strategies, and less than half of
organizations that evaluate marketing analytics tools actually use them
• That said, Big Data is also the next frontier for innovation, competitive advantage
and productivity
• “Analysis Paralysis” is a real risk
• Data is over-analyzed without being able to take meaningful decisions or actions
• Unless you can quickly draw accurate conclusions, analytics serves no purpose
• More on that in the next slide

13. Conquering Analysis Paralysis
• Come to terms with the data
• Leverage the cloud and Big Data technologies
• Break up data into manageable sets, and don‟t feel like you have to use all of it
at one time – or ever
• Be tolerant of imperfect data
• Seek to leverage real-time streams as much as archives
• Focus on gathering specific actionable insight
•
•
•
•
Start with simple questions, and refine them over time
Seek correlation, not cause
Pay as much attention to exceptions and outliers as you do to trends
Embrace convergence of data intelligence tools with marketing automation
systems
• Automation is key, but humans are irreplaceable
• Automation is a productivity tool, not a replacement, for humans
• Automation tools are only effective if leveraged intelligently – by humans

14. Bottom Line
• Promise of Big Data analytics is real
• Implement behavioral targeting to increase customer loyalty and grow sales
• More effectively nurture prospects into warm leads, and warm leads into
customers
• Make a bigger impact by discovering unknown unknowns
• Need balance between Big Data capabilities and analytics
• Too much data, too little analytics – you‟ll drown in information and lose
customers
• Too little data, too much analytics – you‟ll draw misleading conclusions
• Balance = ability to react quickly and accurately to raise revenue and profits
• It may be daunting to tackle the ocean of Big Data – but knowledge
workers have only two options: sink or swim

15. Frost & Sullivan’s 360º Research Perspective
Integration of 7 Research Methodologies Provides Visionary Perspective
15

16. Global Perspective
40+ Offices Monitoring for Opportunities and Challenges
16

17. Connect with Frost & Sullivan
@FS_ITVision Twitter
https://twitter.com/FS_ITVision
Visionary IT Portal
http://visionary-it.gilcommunity.com/
LinkedIn Group: Ask the Frost & Sullivan Digital Media Team
https://www.linkedin.com/groups?gid=1787024
Facebook
https://www.facebook.com/FrostandSullivan
SlideShare
http://www.slideshare.net/FrostandSullivan
17