From Digital Transformation to Digital Revolution

30/08/2018

Abstract

From Digital Transformation to Digital Revolution

 This paper looks at digital transformation and digital revolution. It proposes a unified framework for digital transformation. It also overviews 10 10 digital revolutionaries in the process of from digital transformation to digital revolution. The proposed approach in this paper might facilitate the research and development of intelligent big data analytics, digital transformation, business intelligence, artificial intelligence and data science.  Citation:  Sun Z (2018) From Digital Transformation to Digital Revolution. PNG UoT BAIS 3(13): 1-40. DOI: 10.13140/RG.2.2.29601.86888

Prof. Dr Zhaohao Sun, PhD Department of Business Studies PNG University of Technology, Lae, PNG Phone: +675 473 4406 Email: [email protected] (private)

 Keywords: intelligent big data analytics, intelligent analytics, digital transformation, intelligence, artificial intelligence, big data.

2

Outline    

Motivation

Motivation Digital Transformation A Unified Framework for Digital Transformation From Digital Transformation to Digital Revolution  12 Digital revolutionaries

 Trends For Digital Transformation

3

© Prof. Dr Zhaohao Sun, PNG University of Technology 2018


 Keep abreast of all the state of art ICT, market and business with my EMBA students  Global vision driven thinking, R&D  Why is digital transformation important?  Big data, analytics and artificial intelligence (AI) leads to big digital transformation  Digital transformation will lead to big digital revolution  What is digital revolutionaries? …

4


Why is digital transformation important?

Digital Transformation (DT)

 Mathematically, a transformation is a function F from set X to set Y,

 DT is not necessarily about digital technology, but about the fact that technology, which is digital, allows people to solve their traditional problems. And they prefer this digital solution to the old solution  DT encompass many new avatars of technology including block chain, sharing economy and digital workforce, Artificial Intelligence (AI) /Augmented Intelligence Machine Learning/Deep Learning  These have drawn increasing attention

 F(x) = y, where x is in X, y is in Y

 For digital transformation, what are X, and Y?  X = data set, knowledge set, model set, algorithm set, analytics set, AI technology set, ICT tool set, app set. ICT systems set. …  Y = digital services, digital systems, digital workers, digital leaders, …

 what are X, and Y? is still a issue in digital transformation

5


 Ref: Caudron, Jo; Van Peteghem, Dado (2014). "How Digital Finally Became Important". Digital Transformation. A model to master digital disruption. p. 280.

6


1

30/08/2018

Digital Transformation Models

Digital Transformation 2018

 Above:

http://www.copyright.com/blog/smallsteps-giant-leaps-digitaltransformation-experience/  Right: https://www.i-scoop.eu/digitaltransformation/  On 27 August 18

 Ref:https://dionhinchcliffe.files.wordpress.com/2018/01/two_dimensions_of_digital_tra nsformation_opportunity_cybersecurity_governance.png

7


8


DIGITAL TRANSFORMATION BENEFITS

Digital Transformation Framework Technology Examples:

IoT

Digital Transformation

Better Business Decisions and Outcomes Edge Devices & IoT Platforms

Digital Ready Infrastructure

Business Process & Customer Experience

• •

Focus: decrease human costs, increased accuracy, new abilities Leverage: Vertical expertise, analytics to provide business insight or foresight from new data not previously available

$6 Trillion Spend

•

Focus: instrumenting the physical world, data collection and analysis, new business problem solutions Leverage: Edge sensors, IoT Platforms, Data Fabric

To Transform to New Models

•

• •

Focus: infrastructure driven differentiation Leverage: extended enterprise, wireless & wireless location based services

• •

Focus: transformed process & customer experience Leverage: Cloud & applications

$10

Trillion Benefit

Security Required Within Each Block Sources: IDC, Forrester, Cisco market projections

Digitization, digitalization & digital transformation

Digital Transformation Phenomena

 Digitization (the conversion),  digitalization (the process) and the  digital transformation (the effect) therefore accelerate and illuminate the already existing and ongoing horizontal and global processes of change in society

 The phenomena resulted from  the Internet of Things, the Internet of services,  Industrial Internet,  Industry 4.0,  machine to machine communication (MMC),  blockchain,  cryptocurrencies  AI  Big data  Analytics

 Where AI, Big data, Analytics and their integrations play a fundamental role in digital transformation. 11


12


2

30/08/2018

A Unified Framework for Digital Transformation© IoT Industry 4.0

Industrial Internet

Cryptocurre ncies

Digital Transformation

Sharing economy

Blockchain

Input, Digital Transformation, output  Input = X mentioned in the paper, in particular including big data, analytics and AI in the Framework  Output is Y in the paper, in particular, including blockchain, digital workforces, sharing economy, industry 4.0 etc in the Framework in the paper.  Three big issues are  How to digitally transform Input to output?  How to digitally transform Input to output competitively?  What are 10 most important digital transformers?

MMC



Digital workforce

AI + Big Data + Analytics 13


14


Internet of Things (IoT)

Cryptocurrency

 IoT is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enables these things to connect and exchange data, creating opportunities for more direct integration of the physical world into computer-based systems, resulting in efficiency improvements, economic benefits, and reduced human exertions [2]  Gartner estimates more than 8.4 billion "Things" are on the internet today, up more than 30% from 2016 (Newman, 2017)  Analytics revolution, edge computing, and 5G cell processing are all driven by the IoT at their core. In fact, IDC predicts that up to 40% of all compute will happen at the edge in just the next couple of years.

 A digital asset designed to work as a medium of exchange that uses strong cryptography to secure financial transactions, control the creation of additional units, and verify the transfer of assets.  Cryptocurrencies are a kind of digital currency, virtual currency or alternative currency.

 Ref: [1] Daniel Newman, (Sep 26, 2017) Top 10 Trends For Digital Transformation In 2018  [2] https://en.wikipedia.org/wiki/Internet_of_things

15


 use decentralized control as opposed to centralized electronic money and central banking systems.  The decentralized control of each cryptocurrency works through distributed ledger technology, typically a blockchain, that serves as a public financial transaction database.

 Bitcoin, first released as open-source software in 2009, is generally considered the first cryptocurrency.  Ref: https://en.wikipedia.org/wiki/Cryptocurrency, retrieved on 27 08 18 16


Blockchain

Big market and Value of Blockchain

 A continuously growing list of records, called blocks, which are linked and secured using cryptography.  Each block typically contains a hash pointer as a link to a previous block, a timestamp and transaction data  It is the more popular cousin Bitcoin  It is a core component of the digital currency bitcoin  Bitcoin has become a billion level industry

 Worldwide spending on blockchain solutions is forecast to reach

 https://en.wikipedia.org/wiki/Block_chain

$11.7 billion in 2022, according to the Worldwide Semiannual Blockchain Spending Guide from International Data Corporation (IDC). IDC expects blockchain spending to grow at a robust pace throughout the 2017-2022 forecast period with a five-year compound annual growth rate (CAGR) of 73.2%. Worldwide blockchain spending is expected to be $1.5 billion in 2018 [1]  Asia/Pacific excluding Japan (APeJ) spending on blockchain solutions is forecast to reach USD 2.1 billion in 2022, according the IDC. IDC expects blockchain spending to grow rapidly over the forecast period 2017-22, with a five-year CAGR of 72.6%. APeJ blockchain solutions spending is expected to reach USD 272.7 million in 2018 [2]  Ref:  1. https://www.idc.com/getdoc.jsp?containerId=prUS44150518  2. https://www.idc.com/getdoc.jsp?containerId=prAP44184718

17


18


3

30/08/2018

MMC or M2M

Sharing economy

 Machine-to-machine communication is that: two machines “communicating,” or exchanging data, without human interaction. This includes serial connection, powerline connection (PLC), or wireless communications in the industrial Internet of Things (IoT) [1].  Machine-to-machine (M2M) communications is used for automated data transmission and measurement between mechanical or electronic devices. The key components of an M2M system are: Fielddeployed wireless devices with embedded sensors or RFID-Wireless communication networks with complementary wireline access includes Wi-Fi, ZigBee, WiMAX, wireless LAN (WLAN), generic DSL (xDSL) and fiber to the x (FTTx). [2]

 an umbrella term with a range of meanings, often used to describe economic activity involving online transactions  Uber largest taxi company, without taxi cars and drivers  DiDi,  Airbnb  Sharing knowledge, data, information, wisdom  Sharing borders and countries

 Ref: [1] https://www.link-labs.com/blog/what-is-m2m  [2] https://www.gartner.com/it-glossary/machine-tomachine-m2m-communications/, retrieved on 30 08 18 19


 Sharing … EU

 Z Sun, A Mathematical Theory of Sharing©,2018  Ref: https://en.wikipedia.org/wiki/Sharing_economy

20

Digital workers as a digital workforce

Digital Workforce  as a robotic process automation  Digital workforce is coined to describe a variety of robotic and automated solutions for driving productivity efficiencies in the workplace [4].

 Digital Workforce: Robotic Process Automation  Digital worker is Robotic Process Automation software which automates patterns of how humans use computers in rulesbased tasks.  A digital worker is a team member that is trained to carry out the process just like any employee, only faster and without mistakes. All teams have digital workers alongside humans in the future.  Digital Workers apply leading intelligent automation technology including Robotic Process Automation, Machine Learning and Cognitive Automation.

 In most cases, the digital workforce will not be a physical embodiment of a digital worker [4].

 3D printing technology is a kind of digital workforce.  Blue Prism’s digital workforce is built, managed and owned by the user or customer, spanning operations and technology, adhering to an enterprise-wide robotic operating model [3].  Ref: [1] What knowledge workers stand to gain from automation, Harvard

Business Review.  [2]White Collar Robots: The Virtual Workforce, TEDx Talks  [3] Wikipedia- Blue Prism  [4] Managing the digital workforce 2017 – Deloitte https://www2.deloitte.com/.../deloitte-au-hc-managing-digital-workforce131017.pdf

21



 Who is the digital leader? What is digital leadership?  Ref: https://digitalworkforce.eu/, retrieved on 27 08 18 22


Industrial Internet

Industry 4.0

 Integration and linking of big data, analytical tools and wireless networks with physical and industrial equipment, or otherwise applying meta-level networking functions, to distributed systems.  The term was coined by General Electric (GE), a U.S. corporation.  The Industrial Internet incorporates ideas of intelligent machines, or specific pieces of equipment, with embedded technology and IoT .  Examples: pieces of machinery or vehicles that are equipped with intelligent technologies, including

 Introduced in 2011 at Hannover Fair (CeBIT) by German Researchers for German Government  Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things, cloud computing and cognitive computing.  4 Design principles  Interoperability  Information transparency  Technical assistance  Decentralized decisions

 machine to machine (M2M) technologies that allow manufacturing equipment or other types of equipment to send data back and forth, or "talk among themselves."

 Ref: https://www.techopedia.com/definition/30044/industrialinternet, retrieved on 27 0818

 It is also 4th Industrial Revolution.  Ref: https://en.wikipedia.org/wiki/Industry_4.0

23


24


4

30/08/2018

AI Goes From Newbie To Mainstream  AI have been embedded in everything from customer service and robotics to analytics and marketing.  Companies will continue to use AI to surprise, connect, and communicate with their customers in ways they may not even appreciate or realize.  This includes faster, cheaper, and smarter automation of everything from emails and content generation to industrial manufacturing.  IBM Watson, SAP Leonardo, Salesforce Einstein and other major software companies all launch embedded AI right into their platforms  Ref: Daniel Newman, (Sep 26, 2017) Top 10 Trends For Digital Transformation In 2018 25


Intelligent big data analytics in trinity

Intelligent big data analytics is at the core

the age of

Age of Big data

Age of AI

Age of Analytics


From digital transformation to digital Revolution  Global Giants: digital revolutionaries  these Giants and digital revolutionaries have managed to be embedded into our day-to-day lives like we could never have anticipated  The following 12 Digital companies revolutionize the world.  Ref: https://trendingstock.today/the-top-10-tech-companies-who-arechanging-society, retrieved on 07 Aug 18

29


Big Data and Analytics  The bigger the data is, the more important is the data  Intelligent Big data analytics = Big data analytics + AI  Intelligent Big data analytics = Intelligent Big data + Intelligent Data analysis + Intelligent DW + Intelligent DM + Intelligent SM + Intelligent ML+ Intelligent Visualization + Intelligent optimization  "Intelligent Big Data Analytics“ has only 66 indices in Google Scholar, (retrieved on 06 Aug 2018)  It is at its infancy stage for development

 It is at the centre of the age of trinity: big data, analytics and AI  It is the core of data science.  Sun, Z (2018) Intelligent Big Data Analytics: Foundations and Applications. DOI: 10.13140/RG.2.2.11037.41441. 26


Analytics, big analytics, intelligent analytics  The mass amount of information being created by the IoT has the power to revolutionize everything from manufacturing and healthcare to the layout and functioning of entire cities  Tech giants such as Microsoft, IBM, SAS and SAP are all heavily investing in Analytics, more specifically IoT Analytics as they are seeing the power of this combination in driving new business insights across a vast array of industries and applications  IoT Analytics

 big analytics, intelligent analytics  Ref: Daniel Newman, (Sep 26, 2017) Top 10 Trends For Digital Transformation In 2018  Sun Z, Wang PP (2017) Big Data, Analytics and Intelligence: An Editorial Perspective, Journal of New Mathematics and Natural Computation.13(2): 75–81. 28


APPLE & AMAZON  APPLE (AAPL)  The founder of the company in 1976– Steve Jobs – was actually fired in 1985, when he was 30 years old  Market Cap: $875.3 billion and growing

 AMAZON (AMZN)  Founded by Jeff Bezos on July 5, 1994  Market Cap: $719.1 billion and growing  Jeff Bezos had been the VP of a Wall Street firm before moving to Seattle to start an internet company after feeling like he missed the boat with the online boom  Ref: https://trendingstock.today/the-top-10-techcompanies-who-are-changing-society, retrieved on 07 Aug 18 30


5

30/08/2018

FACEBOOK & Alphabet (GOOG)

Alphabet

 FACEBOOK ( FB)  founded by Mark Zuckerberg, Eduardo Saverin, Andrew McCollum, Dustin Moskovitzand Chris Hughes, 2004  Market Cap: $520 billion and growing

 Alphabet (GOOG)  Founded by: Larry Page and Sergey Brin 2015  Market Cap: $784.2 billion and growing

 Ref: https://trendingstock.today/the-top-10-techcompanies-who-are-changing-society, retrieved on 07 Aug 18

31


32


Microsoft & TWITTER

ALIBABA & PAYPAL

 Microsoft (MSFT)

 ALIBABA (BABA)

 his Company Created The Richest Person In The World Once  Founded by: Bill Gates & Paul Allen 1975  Market Cap: $ 724.2 billion and growing

 TWITTER (TWTR)  This Company Restricts People For 140 Characters  Founded by Jack Dorsey, Noah Glass, Biz Stone & Evan Williams 2006  Market Cap: $24.15 billion

33


 This Company Is Amazon’s Biggest Fear.  Founded by Jack Ma & Peng Lei on April 4, 1999  Market Cap: $496 billion and and growing  Chinese Amazon

 PAYPAL (PYPL)  Without This Company Amazon Would Have Never Been a Huge Success  This company was voted as one of the 10 worst business ideas of 1999.  Founded by Ken Howery, Luke Nosek, Max Levchin, Peter Thiel & Elon Musk 1998  Market Cap: $95.6 billion 34

 one of the top online payments processors in the world. © Prof. Dr Zhaohao Sun, PNG University of Technology 2018

SAMSUNG

AIRBNB

 SAMSUNG

 AIRBNB: This Company Destroyed the Hotel Business

 This Company Rules The Electronic Industry  Founded by Lee Byung-chul on March 1, 1938  Market Cap: $285.8 billion  One of the top global producers of televisions, smartphones, home appliances

35


 it’s the biggest accommodation provider in the world, Airbnb doesn’t own any actual real estate.  Founded by Brian Chesky, J. Gebbia & N. Blecharczyk in 2008  Market Cap: $31 billion  With this peer-to-peer platform, users can stay in other people’s homes instead of a hotel or other type of accommodation

36


6

30/08/2018

LinkedIn & UBER

Trends For Digital Transformation

 LinkedIn ( acquired by Microsoft in 2016)

 VR Goes From Hero To Zero. Poor VR  Failure As A Service: FaaS

 This Company Changed The Way People Find Their Next Job  Founded by Reid Hoffman, Allen Blue, Konstantin Guericke, Eric Ly & Jean-Luc Vaillant 2002  Market Cap: $26.2 billion and growing

 UBER  This Company Valued at $50 Billions and Changed Everything We Know About Public Transportation  Founded by Travis Kalanick & Garrett Camp in 2009  Market Cap: $69 billion  peer-to-peer ride sharing service

37


Conclusion

 Culture Remains a Hurdle  As the pace of change increases and the number of new technologies continue to grow, companies must move fast forward toward growth  Ref: Daniel Newman, (Sep 26, 2017) Top 10 Trends For Digital Transformation In 2018

38


References

 A Unified Framework for Digital Transformation  From Digital Transformation to Digital Revolution  12 Digital revolutionaries

 Trends For Digital Transformation  Digital Transformation becomes a must  Digital revolution: who is the next most successful digital revolutionary

39

 failure will soon be a service on the aaS menu  FaaS will provide visualization, rapid prototyping, and other fast fail methods that will help companies strategize fast for greater success


 https://en.wikipedia.org/wiki/Digital_transformation, retrieved on 01 101 17  The Top 10 Tech Companies Who Are Changing Society, CNN, retrieved on 07 08 18  Daniel Newman, (Sep 26, 2017) Top 10 Trends For Digital Transformation In 2018, Forbes. https://www.forbes.com/sites/danielnewman/2017/09/26/top10-trends-for-digital-transformation-in-2018/#1f0a0a86293a  Sun, Z (2018) Intelligent Big Data Analytics: Foundations and Applications. DOI: 10.13140/RG.2.2.11037.41441.  Prof. Zhaohao Sun, LN- 7: From digital transformation to digital revolution, at PNG UoT, 24 August 2018.  Sun Z, Wang PP (2017) Big Data, Analytics and Intelligence: An Editorial Perspective, Journal of New Mathematics and Natural Computation.13(2): 75– 81.  Sun Z (2018) Managerial Perspectives on intelligent big data analytics, IGIGlobal, 2019. In Press.

40


7