grab ‘n go: session 1 - deloitte us · revolution machines replace ... data-driven insight...
TRANSCRIPT
Grab ‘n Go: Session 1
Velkommen til den
digitale revolution
This is not a car
2
The 4th Industrial Revolution
3
Digital
Revolution
Machines replace
knowledge work
IT
Revolution
Machines replace
repetitive and tedious work
Industrial
Revolution
Machines replace
dangerous and heavy work
Industry 1.0 and 2.019th century
Industry 3.020th century
Industry 4.021st century
Exponential technological advances drive changes in business models.
Products, services and processes are innovated in order to create
competitive advantage. Entire industries may be disrupted.
The Digital Revolution
4
Product or service enhancementsImproved customer relations
Cost reductions
Disruptive business models Strong differentiation
Incremental innovation Radical innovation
Exponential technology advances
5
RobotsDrones
Network
capacity
Digital communications
Machine translation
Cognitive computing
New materials
Bio tech
Speech recognition
3D printers
Mobile devices
Virtual reality
Sensors
Web 2.0
Cloud computing
Processing power
Data storage
Energy storage
6
“Datafication” of all activity doubles the amount of data every 1.2 years.
Everything becomes connected
Observations
By 2020, 50 billion devices and even more sensors will be connected
• Mobile devices
• Wearables
• Vehicles
• City and road infrastructure
• Home infrastructure
• Industrial equipment and machinery
• Consumer products
Transactions
Transactions in business applications
e.g. ERP and e-commerce
Interactions
Interactions on social media
• Facebook users like over 4 million posts every minute
• Instagram users like over 1.7 million photos per minute
• Tinder users swipe over 300k potential lovers per minute
• Twitter users send over 350k tweets every minute
• Snapchat users share over 280k snaps per minute
The Internet of Everything
Mobile
Cloud
Socia
l
Big data
7
Different types of digital innovation
Middle and back office
Operational efficiency
Cost reductions
Quality improvements
Compliance
Front office
Differentiation / disruption
Revenue growth
Customer service
improvements
Digital innovation
Digital business models and
services
Digital customer
experience
Data-driven insight
Intelligent process
automation
8
Different types of digital innovation
Digital innovation
Digital business models and
services
Digital customer
experience
Data-driven insight
Intelligent process
automation
Examples of digital business models
9
Digital business models
eCommerce
Digital advertising
Crowd sourcing
Servici-fication
Additivemanu-
facturing
Platform economy
Digital payments
Data-driven government
Smart city
Examples of digital business models
10
Digital business models
eCommerce
Digital advertising
Crowdsourcing
Servici-fication
Additivemanu-
facturing
Platform economy
Digital payments
Data-driven government
Smart city
The platform economy
11
TRADITIONAL VALUE
CHAIN DISRUPTED
Different types of platform economy
12
Servicification
Diffe
rentiatio
n
Data-driven servicification
Analog
products
Smart
products
Connected
services
Outcome
economy
Remote diagnostics as a service
Predictive maintenance as a service
Remote calibration as a service
Insight as a service
Products as a service
Quality management as a service
Business model innovations enabled by the industrial IoT
Value chain as a service
Pay per product - Data monetization - Service subscription – Pay per use - Pay per outcome
Com
moditiz
atio
n
13
Servicification at Vestas.
14
Connected services at Volvo.
15
16
Different types of digital innovation
Digital innovation
Digital business models and
services
Digital customer
experience
Data-driven insight
Intelligent process
automation
Data-driven insight
Internal
CRMERP
R&D
Str
uctu
red
External
Un
str
uctu
red
Data sources
Insig
ht fo
r o
pe
rational
pro
ce
sse
s
Insight for management
Insig
ht a
s a
se
rvic
e
BI
From data to insight
Sensor Data
Video & Picture
Text
Voice & Sound
Spreadsheet Data
Database
Reg
res
sio
n Linear Regression
Non-Linear Regression
Ordinary Least Squares
Maximum Likelihood
Neu
ral
Netw
ork
Feedforward NN
Recurrent NN
Convolutional NN
Kohonen Self-
Organizing
Ran
do
m
Fo
res
t
Decision Trees
Classification
Regression
Kohonen Self-
Organizing
Clu
ste
rin
g K-Nearest Neighbors
Principal Components
Support Vector Machine
Gaussian Mixture Model
What
happened?
Why did
it happen?
What will
happen?
What do we
want to
happen?
De
scriptive
Pre
dic
tive
Pre
scriptive
Inte
rne
t o
f E
ve
ryth
ing
Qualify data and build cognitive model
Bu
sin
ess o
utc
om
e
Data
Mo
de
l o
utc
om
e
From data to insight
Sensor Data
Video & Picture
Text
Voice & Sound
Spreadsheet Data
Database
Reg
res
sio
n Linear Regression
Non-Linear Regression
Ordinary Least Squares
Maximum Likelihood
Neu
ral
Netw
ork
Feedforward NN
Recurrent NN
Convolutional NN
Kohonen Self-
Organizing
Ran
do
m
Fo
res
t
Decision Trees
Classification
Regression
Kohonen Self-
Organizing
Clu
ste
rin
g K-Nearest Neighbors
Principal Components
Support Vector Machine
Gaussian Mixture Model
What
happened?
Why did
it happen?
What will
happen?
What do we
want to
happen?
De
scriptive
Pre
dic
tive
Pre
scriptive
Inte
rne
t o
f E
ve
ryth
ing
Math StatisticsData
Management
VisualizationArtificial
intelligence
Programming Business Modeling
Th
e d
ata
scie
ntist
Qualify data and build cognitive models
Bu
sin
ess o
utc
om
e
Data
Mo
de
l o
utc
om
e
An example of data-driven insight.
21
Different types of digital innovation
Digital innovation
Digital business models and
services
Digital customer
experience
Data-driven insight
Intelligent process
automation
Intelligent Process Automation
User emulation (simple robotics)
Emulate simple, repetitive manual tasks
in and between existing IT-systems
Com
ple
xity a
nd v
alu
e
Maturity
Process automation
Model workflows and business rules in order to automate
complex processes
Decision automation
Add data-driven insight into the process for
judgement, predictions and recommendations
Swivel chair
process
User
emulationBusiness
automation
Workflow
automation
The automation of knowledge work.
Automation choices
In the not so distant future.
The future of knowledge work
26
Sixty percent of CEOs believe that the emergence of smart machines capable
of absorbing millions of middle-class jobs within 15 years is a "futurist
fantasy”. However, Gartner predicts that smart machines will have
widespread and deep business impact within only seven years through 2020.
Garner, 2013
“47 percent of total employment
is “at risk” from computerization
over the next decade or two”
Study from Oxford University
“By 2029 robots will have
reached human levels of
intelligence”
Ray Kurzweil, Director of
engineering at Google
“By 2030, 90 percent of jobs as we
know them today will be replaced
by smart machines”
Gartner
27
Different types of digital innovation
Digital innovation
Digital business models and
services
Digital customer
experience
Data-driven insight
Intelligent process
automation
28
The rise of the demanding Generation Y customer
One vocal customer now reaches
1375 people
89% began doing business
with a competitor following a
poor experience4
46% of the customers of
financial institutions will be
Gen Y by 20203
72% of all Internet users are now
active on social media1
The largest social network, Facebook,
currently has more than 1.28 bn.
monthly active users
1% of customers feel their expectations
for a good customer experience are
always met2
90% of Denmark’s families
have Internet access
85% of the Danish Internet users
browse the Internet for product
information and service comparison
On average, a smartphone is checked
150 times a day
Decreasing customer loyaltyIncreasing customer
expectations
1. Socialmediatoday.com
2. New Media Trendwatch
3. Deloitte
4. Rightnow.com
y
Increasing importance of the
online channel
29
Understanding the behavior and needs is the key
EXPOSURE INQUIRY EXPLORATION STABALIZATION MATURITY ATTRITION
Life Events
App Usage
Social Influence
Call/Text
Usage
Billing Behavior
Demographics
Data Usage
Volatility
Caller NetworkOffer History
Complaint History
Client website
Clickstream
Social Attributes
The customers’ data DNA
360 view of customer behavior
30
Omni-channel is a prerequisite for a great customer experience
Increased
Market Share
Customer and shareholder value Increased
Share of
Customer
Wallet
Higher Margin
Product
Portfolio
Lower
Acquisition
Costs and
Cost to Serve
Accelerated
Time to
Market
Improved
Customer
Engagement
Improved
Lifetime Value
of Customer
Sales
Organization
Customer Service
Marketing & Customer Engagement
Omni-channel Engagement
Capabilities
Product and Service Development
Customer Insights
Business Strategy and Brand Promise
Strategy and Transformation
Mobile
Social
Direct
Marketing
Contact Center
Media &
Advertising
In-store
Web
Discover
Choose
Evolve
Service
Use
Buy
Customer
Insight
360º+
31
Traditional and digital retail are the future.
32
New ways of engaging customers.
33
What does it take?
Digital innovation
Digital business models and
services
Digital customer
experience
Data-driven insight
Intelligent process
automation
Who is responsible?
CIO
CEO
Chief Operating OfficerChief Digital Officer
Chief Data Officer
Chief Analytics Officer
Chief Marketing Officer
Chief Financial Officer
Chief Innovation OfficerChief Customer Officer
Focus short term as well as long term
1 Understand the business
and where to focus2 Conceptualise and identify
digital use cases3 Implement pilot digital
solution
1 Make “innovation” part
of the strategy mix2 Define the
“digital innovation radar” 3 Design and implement
an “innovation factory”
Drive a multi-year innovation program (that never ends) to
harness the power of new digital opportunities
Identify and implement digital use cases
A portfolio of digital use cases
”The digital radar”
Act0-6 months
Investigate6-18 months
Explore+18 months
Digital business models and services
Data-driven insight
Digital customer experience
Intelligent process automation
Investigate6-18 months
Explore+18 months
Customer experiences
and engagement
Value propositions
and differentiation
Ecosystems and
collaboration models
Operating models and
organizational impacts
Digital innovation requires something completely new
Traditional IT Fast IT
IT industrialization Era Digital transformation
Core systems of record
IT operationsFocus
Systems of differentiation
Systems of innovation
Inside-out
Outsourcing
Atomization
Service level culture
Waterfall
Risk averse
Approach
Outside-in
Business centricity
Co-creation
Entrepreneurial culture
Agile
Fail fast
Behavioral
psychologists
Graphic
designers
User experience
designersScience fiction
writers
Artists
Data
scientists
”Right speed IT” ”Purple skills”
In summaryThe digital revolution is here It involves different types of innovation
We need a new approach And we need to act
Michael BorgesPartner and Technology Leader
Deloitte Consulting
Rasmus Winther MølbjergDirector
Deloitte Digital