Exploring the potential of the “Internet of Things”

1. Exploring the potential of
the “Internet of Things”
Alumni Webcast
March 10, 2010
CONFIDENTIAL AND PROPRIETARY
Any use of this material without specific permission of McKinsey & Company is strictly prohibited

2. McKinsey & Company 1
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When will the future arrive?
Poll question:
When will billboard systems
such as these become a reality?
o 2025
o 2020
o 2015
o 2010 (today)
o Already in wide distribution

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When will the future arrive?

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The future is becoming
the present

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2000 2005 2010 2015
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2012
2010
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2006
Battery energy
density
Watt-hours/liter
Assigned IP
addresses
Count /8s
A number of technology trends are enabling the emergence of an Internet
of Things (IoT)
Sensors in everything
SOURCE: On World, Yankee Group, “Improving FLOPS/Watt by Computing Reversibly, Adiabatically, & Ballistically”, Workshop on Energy and
Computation: Flops/Watt and Watts/Flop; BeyeNETWORK; APNIC; McKinsey (PD #726413)
Sensors are
integrated into
more physical
devices:
▪ Improved power
management
▪ Miniaturization
▪ Reduced costs
▪ Location-based
awareness

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25
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A number of technology trends are enabling the emergence
of an Internet of Things
Networks everywhere
SOURCE: On World, Yankee Group, “Improving FLOPS/Watt by Computing Reversibly, Adiabatically, & Ballistically”, Workshop on Energy and
Computation: Flops/Watt and Watts/Flop; BeyeNETWORK; APNIC; McKinsey (PD #726413)
1 Includes all mobile devices priced above $350
Area coverage
of GSM
Percent of global
Standards-com-
pliant sensor
chipsets
MM shipments
Networks are
becoming
ubiquitous, driven
in particular by
advances in wireless
technologies,
including:
▪ Increasing band-
width capabilities
▪ Open standards
▪ Reduced costs

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A number of technology trends are enabling the emergence
of an Internet of Things
Analyze everything
SOURCE: On World, Yankee Group, “Improving FLOPS/Watt by Computing Reversibly, Adiabatically, & Ballistically”, Workshop on Energy and
Computation: Flops/Watt and Watts/Flop; BeyeNETWORK; APNIC; McKinsey (PD #726413)
1 Includes all mobile devices priced above $350
900
800
700
600
500
400
300
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1,000
100
0
2010
2005
2000
1995
Size of
largest data
warehouse
TB
Systems have greater
flexibility/intelligence
for data processing and
increasing autonomy,
driven by:
▪ Increased
computational power,
memory, and storage
▪ Remote
programmability
▪ Probabilistic decision
making
0
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400
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1,200
2000 2005 2010 2015
Smart
phone
processor
speed*
Average
Mhz

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An “Internet of Things” system is comprised of 6 primary components
An “Internet of Things” includes data sources (sensors) and
other devices (e.g., actuators) embedded in the physical
world connected by networks to analytic computing resources
Definition
Observing the
physical world
Changing the
physical world
Analysis
Visualization
Aggregation
Internet
Closed-loop
actuation
Networked data
sources
Sensors
Discovery & id
1
2
3
4
5
6

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6 categories illustrate the breadth of potential IoT applications…
Category Description
Achieving real-time awareness of physical
environment
Enhanced
situational
awareness
B
Control consumption behavior to optimize
resource use across a network
Optimized
resource
consumption
E
Automated control of closed (self-contained)
systems
Process
optimization
D
Assisting human decision-making through
deep analysis and data visualization
Sensor-driven
decision
analytics
C
Monitoring the behavior of persons, things
or data through space and time
Tracking
behavior
A
Automated control in open environments
with great uncertainty
Complex
autonomous
systems
F
Information
& analysis
Automation
& control

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Tracking behavior: Behavior-based insurance pricing
▪ Automobile insurance is typically priced by demographic factors such as age,
gender, place of residence, which imperfectly approximate risk
▪ Some insurance companies have offered plans that require drivers to install a
location sensor in their car, enabling the insurance company to price risk based
on actual behavior (where, when and how the car is driven)
▪ Can reduce insurance premiums for many drivers while enabling insurance
companies to more precisely price risk
A

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Tracking behavior: Augmented reality
A
▪ Mobile phones are one of the most widely deployed sensor platforms
▪ Augmented reality combines GPS location information with image recognition from
camera to deliver real-time information about where a user is pointing their phone,
e.g., tourist information about nearby sites, restaurant and other recommendations
▪ Telecom carriers, handset manufacturers and software applications providers are
actively experimenting in this space

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Enhanced situational awareness: Gunfire detection and location
B
▪ Network of directional microphones detects the sound of gunfire
▪ Data is relayed to a central application which aggregates it and analyzes it to
determine the location of the source of gunfire
▪ Gunshot location then plotted on a map for further investigation

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Sensor-driven decision analytics: Chronic disease management
C
▪ Remote health monitoring sensors report data on patient symptoms, e.g.,
through wireless bedside reader
▪ Physicians can tailor treatments based on continuous monitoring rather than
periodic testing
▪ Could reduce treatment costs by $billions for congestive heart failure alone

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Process optimization: Deep sea oil extraction and pumping
D
▪ Deep sea oil wells subject pipelines to extreme pressures and low temperatures,
which can affect the viscosity of oil being pumped.
▪ Variations in oil viscosity can cause the equivalent of “water hammer” in a shower
▪ Sensors embedded pipeline infrastructure can detect variations in flow, allowing
computers to automatically signal adjustments to well pumps
▪ Tremendous value in preventing damage to wells and pipelines

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Optimized resource consumption: Datacenter energy management
E
▪ For major data centers, power consumption is a significant determinant of total costs
of ownership (global greenhouse gas footprint of data centers approaches that of
Argentina)
▪ However, data center managers generally have little visibility into actual energy loads
▪ Internet of Things sensors can enable real-time sensing of power usage, enabling
energy usage to be optimized, e.g., by shifting server loads

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Optimized resource consumption: Smart electrical grid
E
▪ Smart electrical grid deploys sensors throughout the transmission and distribution
system from generation down to end user metering
▪ In the transmission & distribution system, sensor data can enable reduced line losses,
and reduced maintenance costs and downtime through advanced monitoring and
diagnostics, amongst other benefits
▪ Advanced metering infrastructure and home area networks enable reduced meter
reading costs and shifting energy usage away from expensive peak times

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Complex autonomous systems
F
▪ Detection of pedestrians and distance to adjacent cars through radar and camera
monitors car’s position and potential obstacles
▪ If collision is likely, system first alerts driver via heads-up display; if driver ignores
warning car automatically induces full system brakes to prevent accident. System
can prevent accidents with car speeds of less than 20 km/h, and reduce impact
force in accidents at greater speeds
▪ More advanced technology under development would enable cars to coordinate
driving together on the freeway, reducing overall system congestion

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The Internet of Things can create value through several economic levers
Levers
Create new dynamic pricing models for
inputs and outputs
Create new service models and products
to monetize information assets
Improve safety for consumers and workers
Increase efficiency and reduce costs
of energy, materials, capital, and labor
Allow new customer interactions with
opportunities to engage end-users on a
dynamic, ongoing basis
Enable new
ways of doing
business
Improve quality of delivered products
and services
Enhance &
optimize today’s
operations

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The Internet of Things can create value through several economic levers
Enable new
ways of doing
business
Enhance &
optimize today’s
operations
Poll question:
Which of these will be most impactful?
Create new dynamic pricing models for
inputs and outputs
Create new service models and products
to monetize information assets
Improve safety for consumers and workers
Increase efficiency and reduce costs
of energy, materials, capital, and labor
Allow new customer interactions with
opportunities to engage end-users on a
dynamic, ongoing basis
Improve quality of delivered products
and services
o
o
o
o
o
o

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Continuing challenges for Internet of Things
Technology challenges
▪ Data privacy
▪ Data security
▪ Legal liability
▪ Organizational implications
(e.g., role of IT function)
▪ Cost and capability of sensors and actuators
▪ Reliability for critical networks
▪ Technical standards for open networks
▪ Software for massive data analytics in real-time
▪ Visualization technology
Policy and organizational challenges

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Continuing challenges for Internet of Things
Technology challenges
Policy and organizational challenges
o Data privacy
o Data security
o Legal liability
o Organizational implications
(e.g., role of IT function)
o Cost and capability of sensors and actuators
o Reliability for critical networks
o Technical standards for open networks
o Software for massive data analytics in real-time
o Visualization technology
Poll question (choose as many as applicable)
Which of these challenges are most important to address?

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Next steps for companies
Explore immediate
applications in:
▪ Process optimization
▪ Optimized resource
consumption
No regrets moves
Conduct small-scale
pilots with emerging
technologies
Experimentation
Explore partnerships
with Internet of Things
technology suppliers
Alliances

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Presenters
To submit a question: Q&A icon
Michael Chui (michael_chui@mckinsey.com)
Roger Roberts (roger_roberts@mckinsey.com)
Dr. Markus Löffler (markus_loeffler@mckinsey.com)
Michael Chui is a Senior Fellow of the McKinsey Global Institute (MGI). He is based in San Francisco, where
he directs research on the impact of information technologies, such as Web 2.0 and the Internet of Things, on
business and the economy. He has served clients in the high tech, media and telecom industries on strategy,
innovation and product development, IT, sales & marketing, M&A and organization. His research has been
cited globally in publications such as Fast Company, The New York Times, Wall Street Journal, and Les Échos.
Roger Roberts is a Principal in McKinsey & Company’s Silicon Valley office where he concentrates on
technology issues of strategic importance to senior managers. He is the North American leader of McKinsey’s
IT strategy service line. He serves a wide range of clients with a primary focus in the high tech and industrial
sectors, helping leaders conceive and apply technology solutions to enhance innovation and productivity.
He chairs the global Editorial Board for McKinsey on Business Technology, the Firm’s quarterly publication for
CIOs and other senior business leaders on business technology issues.
Type your question into the Q&A panel located in the lower right side
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Dr. Markus Löffler is a Principal with McKinsey & Company, Inc. in Germany. He co-leads the Business
Technology Office's global Technology Infrastructure practice and is a leader in the IT Architecture practice.
Dr. Löffler advises clients primarily in the industrial and high tech sectors. He focuses on technology-enabled
business strategies, IT infrastructure and architecture, and IT performance management. Dr. Löffler has lead IT
infrastructure transformations for major users and providers of infrastructure.

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