surviving the change agents - how business survive the next evolution
TRANSCRIPT
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Change AgentsHow Consumer Centric Technology Companies Are Changing the World and How to Survive |
@KylePLacy 10/23/17
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My Career
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Lessonly is used by thousands of teams
to translate important work knowledge
into lessons that accelerate productivity.
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We must understand change.
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Louis CK Video
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Why is this happening?
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Companies are struggling to
keep up with the rate of
modern change
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TechnologyR
ate
of
Ch
an
ge
Time
Deloitte University Press | dupress.deloitte.com
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Technology
Highest Performing Teams
and Businesses
Ra
te o
f C
ha
ng
e
Time
Deloitte University Press | dupress.deloitte.com
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Technology
Highest Performing Teams
and Businesses
Ra
te o
f C
ha
ng
e
Time
Typical Businesses
Deloitte University Press | dupress.deloitte.com
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My morning
before 8am…
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Deloitte University Press | dupress.deloitte.com
Ra
te o
f C
ha
ng
e
Time
Individuals
Technology
Highest Performing Teams
and Businesses
Typical Businesses
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Deloitte University Press | dupress.deloitte.com
Ra
te o
f C
ha
ng
e
Time
Highest Performing Teams
and Businesses
Typical Businesses
THE
DIVIDE
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The gap between those who can find,
create, manage, process and
disseminate information and those
who are impaired in the process.
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The impact of this divide is real.
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“People are falling behind because
technology is advancing so fast
and our skills and organizations
aren’t keeping up.”
— Erik Brynjolfsson, MIT
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Netflix vs. Blockbuster (2004 - 2010)
$6 Billion
Time
$4 Billion
$2 Billion
$0
Blockbuster Revenue
Netflix Revenue
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Netflix vs. Blockbuster (2004 - 2010)
$6 Billion
Time
$4 Billion
$2 Billion
$0
Blockbuster Revenue
Netflix Revenue
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Netflix is a $60 billion company.
That’s 12x Blockbuster’s peak value.
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“Companies rarely die from moving too fast,
and they frequently die from moving too slowly.”
—Reed Hastings, Netflix
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Industrial
Revolution1760-1840
Cotton Gin
Steam Engine
Bessemer Process
Model T
Telephone
Transistor
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Industrial
Revolution1760-1840
Information
Revolution1940-1990
Computers
Radio
Television
Internet
Cotton Gin
Steam Engine
Bessemer Process
Model T
Telephone
Transistor
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Industrial
Revolution1760-1840
Information
Revolution1940-1990
Consumer
Revolution2000-2016
Mobile
Social
SaaS
Cloud
Machine Learning
Computers
Radio
Television
Internet
Cotton Gin
Steam Engine
Bessemer Process
Model T
Telephone
Transistor
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Industrial
Revolution1760-1840
Information
Revolution1940-1990
Consumer
Revolution2000-2016
Intelligence
Revolution2020+
Mobile
Social
SaaS
Cloud
Machine Learning
Computers
Radio
Television
Internet
Cotton Gin
Steam Engine
Bessemer Process
Model T
Telephone
Transistor
Nanotechnology
Artificial Intelligence
Virtual Reality
Deep Learning
Blockchain
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SURVIVING CHANGE
We need to understand the trends to survive.
• Micro-Moments
• Data at Scale
• Assisted Intelligence
• Machine Intelligence
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1. Micro-Moments
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29
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We are the Google Generation.
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100,000,000,000Number of monthly Google searches
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When you need it now
Type to search
Google Search I’m Feeling Lucky
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FB Mobile = 1,100,000,000
monthly active users
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1999
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JUST-IN-TIME: denoting a
manufacturing system in which
materials or components are delivered
immediately before they are required in
order to minimize inventory costs.
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“Amazon says it may box and ship products
it expects customers in a specific area will
want—based on previous orders and other
factors…”
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@KYLEPLACY
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CUSTOMER
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CONSUMER
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AND THE
EXPERIENCE
IS SEAMLESS
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@KYLEPLACY
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“…Amazon blimps would circle over cities at
45,000 feet and launch drones carrying
orders. The drones would initially fall to
earth relying largely on gravity, and their
motors would fire up for the final stretch.”
Source: http://money.cnn.com/2016/12/29/technology/amazon-aerial-warehouse/
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2. Data at Scale
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“We must move from numbers
keeping score to numbers that
drive better actions.”
— David Walmsley
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A rorschach test…
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EXAMPLE OF AN IMPACT SLIDE TEXT
Example of supporting information or sourcing information goes here
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How do you feel?
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EXAMPLE OF AN IMPACT SLIDE TEXT
Example of supporting information or sourcing information goes here
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Now?
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70% of technology
implementations fail because
of bad data.
— Forrester
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There is one source of truth and
everyone is responsible for keeping it
clean.
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File Management and Email Chat and Collaboration
Project & Process ManagementLearning and Development
Journey & Email Management
Data Management List Development
CRM
Business Intelligence
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@KYLEPLACY
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@KYLEPLACY
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3. Assisted Intelligence
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@KYLEPLACY
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Meet Amy Ingram
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“If Alexa were a human assistant,
you’d fire her, if not have her
committed.”
- Farhad Manjoo
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Machine Intelligence
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ASSISTED INTELLIGENCE
What needs to happen to gain true machine intelligence?
• Deep Learning
• Natural Language Processing
• Quantum Computing
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Deep Learning
is a subfield of machine learning concerned
with algorithms inspired by the structure and
function of the brain called artificial neural
networks.
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Location Based
Intelligence
Personalization &
Interaction Engine
Reverse Logistics
Solution
Personalization
Engine
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Natural Language Processes (NLP)
is the ability of a computer program to
understand human speed as it is spoken.
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Deep Learning & NLP
More data + More Intelligence = Highly
Personalized Experiences
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Final Thoughts:
How do we adapt?
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Deloitte University Press | dupress.deloitte.com
Ra
te o
f C
ha
ng
e
Time
Individuals
Technology
Highest Performing Teams
and Businesses
Typical Businesses
THE
DIVIDE
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The company is viewed as an agile
network, empowered by team
leaders and fueled by collaboration
and knowledge-sharing.
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The creation and management of the
customer experience is the only
thing that makes you relevant.