for the Year Ahead Allan E Alter Senior Research Fellow Accenture Institute for High Performance 30 2 Copyright 2016 Accenture All rights reserved T he state of the IIoT is good Lets make it better ID: 708511
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Slide1
Three Numbers and Three Messages
for the Year Ahead
Allan E. Alter
Senior Research Fellow
Accenture Institute for High PerformanceSlide2
30
2
Copyright © 2016 Accenture All rights reserved.
T
he state of the IIoT is good.
Let’s make it better.Slide3
3
Copyright © 2016 Accenture All rights reserved.
2017 total:
US $971B
2019 total:
US $1.3T
CAGR 24%
CAGR 15%
CAGR 21%
CAGR 8%
CAGR 23%
CAGR 22%
CAGR 15%
CAGR 17%
2017 looks bright for the
Internet of
Things market
Source: IDC,
Worldwide Semiannual Internet of Things Spending by Vertical Market 2015–2019 Forecast,
Doc
# US40221915Slide4
4
Copyright © 2016 Accenture All rights reserved.
IoT ecosystems are forming
Source
: “To
Predict the Trajectory of the Internet of Things, Look to the Software
Industry,” Bala
Iyer
,
HBR.org, February
25,
2016
https://hbr.org/2016/02/to-predict-the-trajectory-of-the-internet-of-things-look-to-the-software-industry Slide5
5
The IIoT is moving towards platforms, services and AI
Copyright © 2016 Accenture All rights reserved.
Fragmentation
Connectivity
Data management
Access to data and equipment
Pricing
Data
monetization
Data ownership and access
Skills and workforce
Managing algorithms
Trusting algorithmsSlide6
300
6
Give the people the IIoT they want.
Copyright © 2016 Accenture All rights reserved.Slide7
An IIoT that creates opportunity.
Cumulative GDP Impact of IoT
US$ trillion
With additional measures
Under current
conditions
Source: Accenture and Frontier Economics
Copyright © 2016 Accenture All rights reserved.
7
Business Commons
Educated workforce Access to capital Supplier & distributors
Transfer Factors
Consumer to industrial IOT
Knowledge transfer
Privacy and security
Take-off Factors
STEM talent
Government R&D support
Standards and connectivity
Innovation Dynamo
Maker movement
University-industry
Entrepreneurship
Absorptive capacity factors
The IoT could be worth US$14.2 trillion by 2030, if nations boost
their absorptive
capacitySlide8
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An IIoT that converts business opportunity into jobs
Industrial Internet service sectorProduct/Service developers: product managers, software developers, data scientists, UX designers, security Digital service operations: data scientists, intelligent equipment operators
Solution sellers and evangelists: sales engineers, consultants, marketers and educators.
Copyright © 2015 Accenture All rights reserved.
Mercedes Boots Robots from the Production Line
“Robots can’t deal with the degree of individualization and the many variants that we have today
, We’re
saving money and safeguarding our future by employing more people
.” – Markus Schaefer, Daimler AG
IIoT industrial jobs
Process and hardware designers
Centaur jobs
Robot farmers and trainers
Quality assurance and testing
Maintenance and repairSlide9
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An IIoT that makes our work easier, safer and more interesting
Human-machine collaboration means: Sharpening human vision and judgmentIncreasing the capacity for discovery
Freeing people from administrative tedium and dangerous tasksSpotting and solving problems faster
Machines that respond to gestures, facial expressions and speech
Copyright © 2016 Accenture All rights reserved.Slide10
10
Copyright © 2016 Accenture All rights reserved.
Reimagine business processes with algorithms
30,0
00%Slide11
New capabilities, new value
Companies can achieve value they could not achieve before, and solve problems they could not solve before.
The opportunity of machine-reengineering
Exponential
process
i
mprovement
We
see evidence
of 10x or more improvements
in
speed and
KPIs.
Automating process change
Using IoT data and machine learning, processes can
optimize,
repair
and adapt themselves to
changing business conditions.
Copyright © 2016 Accenture All rights reserved.Slide12
12
By machine-reengineering, companies are often speeding up core business processes by at least
2xCopyright © 2016 Accenture All rights reserved.
Based on your experience to date, how much can machine learning-enabled processes
speed up the
following processes
?
Source: Accenture Institute for High Performance Machine Learning and Business Processes survey,
Jan 2016.Slide13
13
Copyright © 2016 Accenture All rights reserved.
Improvement measured by
key process performance indicators -- e.g., quality, error reduction, scale, capability, etc.)
Q19b
Based on your experience to date, how much can machine learning-enabled processes
improve
the following processes
?
A
majority
of companies are also seeing significant improvements in process KPIs in the range of 2x to
10x
Source: Accenture Institute for High Performance Machine Learning and Business Processes survey, Jan. 2016Slide14
Quickly locate the root cause of complex problems
Machine-reengineering is taking us to a world where companies will…
Copyright © 2016 Accenture All rights reserved.
Optimize factories and warehouses with autonomous robots
3D print a footbridge
MD3X
The Fraunhofer Institute for Material Flow and Logistics
Sight Machine
http://www.iml.fraunhofer.de/
MD3XSlide15
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30,000 pounds of peachesSlide16
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Copyright © 2016 Accenture All rights reserved.
People first
Make the state of the IIoT better
Give people the IIoT they want
Reimagine processesSlide17
17
Copyright © 2014 Accenture All rights reserved.
Thank you.
allan.e.alter@accenture.com