Mais conteúdo relacionado Semelhante a Digital Twin Metaverse Enterprise (20) Mais de Alex G. Lee, Ph.D. Esq. CLP (20) Digital Twin Metaverse Enterprise1. ©2021 TechIPm, LLC All Rights Reserved www.techipm.com
Digital Twin Metaverse Enterprise
October 13, 2021
Alex G. Lee
3. ©2021 TechIPm, LLC All Rights Reserved
I. Metaverse Ecosystem
-Present and Future of Metaverse Infographics
-Why Metaverse Now?
II. Digital Twin Metaverse
-Digital Twin Types
-Digital Twin Models
-Digital Twin Patent Landscape
-Digital Twin Metaverse Use Case: AI Innovation Platform
III. Metaverse Enterprise & ESG Applications
-Metaverse Enterprise
-ESG Strategic Planning and Program Management
-Scenario Planning for Metaverse Enterprise
-TCFD Scenario Analysis
IV. ESG Digital Transformation
-ESG Sustainability Imperative
-ESG Investing and Management Consideration Core Factors
-ESG + Digital Integrated Transformation (ESGDX) Imperative
-How ESGDX Can Create New Revenue Streams?
-ESGDX for ESG Sustainability Management
-ESG Sustainability Management/Assessment Issues & Challenges & Solutions
-ESG DX Forum
V. Sustainable Smart City Development
-Metaverse for Sustainable Smart City
-Smart City Components
-Smart City Design and Development
-Smart City Management
-Smart City Financing and Business Development
Agenda
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Present and Future of Metaverse Infographics
Metaverse = Physical + Virtual Converged World
Virtually Augmented
Physical World
Physically Augmented Virtual World = Interoperable Interconnected (To Be) Virtual 3D Spaces
Constructed on the Internet; Physically Persistence (To Be)
Me
Digital Me (Avatar)
You Digital You
Digital
People/Objects/Environments
Mixed Reality
Virtual Reality
Reality Technology Innovation
Wearable Devices HCI Digital Senses
Augmented Reality
Extended Reality
AI Digital Human Innovation
People can interact freely in a variety of ways
and forms with one another, digital objects
and environments for a variety of virtual
experiences.
Physical Earth:
Space/time/resource
limitations
Digital Twin Earth:
Space/time/resource
limitations
ICT/Digital+ Digital Twin Innovation
IoT Sensors
AI Predictions
Digital Twins
Metaverse is a collection of fully
connected interoperable physically
augmented digital worlds with
physical persistence that are
converged with the virtually
augmented physical world in which
people and digital representations of
people (digital people) can fully
interact with one another and digital
objects/environments (including
digital twins) with full reality.
Metaverse is the converged world of
augmented physical world and
virtual world that is hyper-
decentralized ,hyper-connected,
hyper-visualized, hyper-interacted,
and hyper-reality enabled.
Metaverse can create economic
values without space/time/resource
limitations
Metaverse NFT Projects AT A Glance:
https://www.slideshare.net/alexglee/metaverse
-nft-projects-at-a-glance
NFT
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Why Metaverse Now?
The metaverse concept is not a new one. Back in 1992, Neal Stephenson's novel Snow
Crash coined the term metaverse for the first time. My recent patent research about the
metaverse technology innovation also showed a long history of the metaverse
technology innovation. My patent research also showed that there were active
innovation activities around 2007-2010. Why, then, the metaverse revives now?
HBS Professor Marco Iansiti , the author of “The Keystone Advantage,” suggested
technological assimilation as a new engine for technological innovations in his article
“Creative Construction.” In the technological assimilation frameworks, a core innovation
that once provided stand-alone products or services for a specific market can be the
building blocks for mass market generating innovation through assimilation to broader
platforms and exploitation of innovation infrastructures that were not existed at the time
of innovation.
Therefore, if we consider the integration of broader platforms such as smartphones, 3D
computing, XR devices, digital twins, cloud computing and innovation infrastructures
such as AI, blockchain, IoT and 5G into the metaverse, we can give an answer about
the “why metaverse now” based on the technological assimilation.
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Appendix. Metaverse Reference Videos
TTI Global Impact Award: https://www.youtube.com/watch?v=vT9iDDUYfWU
NFT for Metaverse: https://www.youtube.com/watch?v=ANO29CzQXUA
Ghost Pacer-Mixed Reality: https://www.youtube.com/watch?v=wKEW_c6NEIU
Arcona AR Metaverse: https://www.youtube.com/watch?v=o0kFlw7NEew
Building the Oasis in Ready Player One: https://www.youtube.com/watch?v=LtEYVjbm2CY
Facebook Horizon Workrooms: https://www.youtube.com/watch?v=frZQrEBVkkk
Nissan Metaverse Use Case: https://www.youtube.com/watch?v=-YVTobt-wVQ
MS Digital Twins, Mixed Reality and Metaverse Apps:
https://www.youtube.com/watch?v=GAkB98ewcjI&t=7s
Cloned Shanghai: https://www.youtube.com/watch?v=hOJZhsNtB6g&t=152s
Apple Glasses: https://www.youtube.com/watch?v=5QimDrnA8wM
Creating Virtual Humans: https://www.youtube.com/watch?v=PHQhCiVLRpE
Teslasuit XR: https://www.youtube.com/watch?v=U8ex4rLMwLU
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Appendix. Next Move of Epic Games
Source. https://www.dezeen.com/2021/07/23/digital-twins-metaverse-david-weir-mccall-epic-games/
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Appendix. Microsoft Metaverse Solution
“Converging the physical and digital world with digital twins, mixed reality, and metaverse apps.
Metaverse apps are the culmination of the intelligent cloud and intelligent edge working in
harmony together—at their foundation is digital twins. Digital twins enable you to create rich digital
models of anything physical from simple assets or products to complex environments. Once it’s
modeled, it can be brought to life and synchronized with the physical world using two-way IoT
connections. This initial binding of the physical and digital is foundational to enabling
metaverse apps.”
Source. https://azure.microsoft.com/en-us/blog/converging-the-physical-and-digital-with-digital-twins-mixed-reality-and-metaverse-
apps/
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Appendix. Nissan Metaverse Use Case
People joining through the Metaverse appear as 3D avatars in the real world through MR
(Mixed Reality), letting people in both worlds share the experience of space and movement in
real-time. A family member or friend from anywhere in the world can join the vehicle as an avatar
to accompany on the journey via the Metaverse. The avatar would occupy a seating position to give
a sense they are actually in the vehicle. If needing driving instruction or guidance, a pro driver
from the Metaverse could join the drive as an avatar and assist in real-time.
*Digital twin: A digital representation of the physical world including vehicles, buildings and
infrastructure is created in real-time through massive amounts of data collected through
IoT/sensing technology. Linked to virtual spaces and the real world, the Digital Twin can be utilized
to share information and support augmented and mixed reality interfaces in the real world.
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Appendix. Metaverse Industry Ecosystem (As Is)
Source. https://newzoo.com/insights/infographics/metaverse-ecosystem-
infographic/
Source. https://www.gsma.com/futurenetworks/wiki/cloud-ar-vr-whitepaper/
Source. https://robindchnt.medium.com/the-current-state-of-industrial-
startups-in-europe-an-update-september-2020-908b22e862d1
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Appendix. Metaverse Industry Ecosystem (Another View)
Source. https://medium.com/building-the-metaverse/market-map-of-the-metaverse-
8ae0cde89696
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Digital Twin Types
A product digital twin is created when a new product is designed. The product digital twin
enables the functionality validation of the new product.
A production process digital twin is a virtual model of the production process. The
production process digital twin can be used to predict the behavior and to optimize the
performance of the production process.
A digital reality of a human is called a digital human, and can be created by a 3D avatar
integrating with artificial intelligent (AI).
A digital twin of an organization (DTO)–developed by Gartner–is a realistic digital
representation of any organization ‘s operation of its business model
Source. https://www.iiconsortium.org/news/joi-articles/2019-November-JoI-Artificial-and-Human-Intelligence-with-
Digital-Twins.pdf
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Digital Twin Models
A digital twin is usually consist of software models that mimic a real-world system. A
digital twin model takes input data from the real-world system, simulates how the
processes will behave using those inputs, and then produces predictive data about how
the system will perform. The software models inside digital twins may be different from
each other, depending on the type of the twin, the specific use case and the required
level of details.
Analytic digital twin models use all types of advanced data analytics including descriptive
analytics, predictive analytics, and prescriptive analytics. A decision-making can be
performed based on the results of the analytic models.
Simulation digital twin models use simulation models to improve decision-making.
Simulation digital twin models can enable asking what-if questions to test various
conditions and scenarios that are impractical to create in real life.
AI digital twin models are using Artificial Intelligence technologies to leverage real-time-
data, generating insights into and deeper understanding of operating environments. AI
digital twin models can correct and process data, and detect, predict, optimize, and
make decisions dynamically based on the data.
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Appendix. Digital Twins + IoT + Big Data Analytics + AI
Source. https://ieeexplore.ieee.org/document/9359733
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Digital Twin Patent Landscape
Patents are a good information resource for obtaining the state of the art of deep
learning for digital twin technology innovation insights. Patents that specifically describe
the major digital twin technologies/applications are a good indicator of the digital twin
technology innovations in a specific innovation entity. To find the digital twin technology
innovation status, patent applications in the USPTO as of September 15, 2021 that
specifically describe the major technologies/applications in digital twin are searched and
reviewed. 190 published patent applications that are related to the key digital twin
technology innovation are selected for detail analysis.
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Digital Twin Metaverse Use Case: AI Innovation Platform
US20210004076 illustrates an AI innovation platform that provides a virtual AI
development and testing environment. In the metaverse virtual AI development
processes, AI model training data, system validation, system deployment, and system
testing can be performed within a real-time 3D virtual environment incorporating objects,
camera systems, sensors and digital human avatars representing the collaborating
developers (who can interact using AR/VR/MR devices). The virtual 3D spatial
environment can be networked with external computer resources and their digital twins
to simulate the end-use environment of the AI system. This environment can include
various sub-systems that feed data into the AI system. This data can be captured and
utilized to train and validate the AI system, which can then itself be deployed into the
same real-time virtual environment. Finally, real-time motion capture techniques and
human actors can be used to drive humanoid avatars within the virtual environment.
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Metaverse Enterprise
&
ESG Applications
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Metaverse Enterprise
A metaverse enterprise is consist of a physical enterprise and virtual enterprise which is
a realistic digital representation of the physical enterprise.
The digital representation of the physical enterprise is called a digital twin of the physical
enterprise. Physical and digital enterprises are connected through real-time data.
Based on actual real-time data in the physical enterprise, the virtual enterprise is
created, and then, tested using simulation models, big data analytics, and scenario
analysis to obtain meaningful insights regarding businesses of the physical enterprise.
Digital world decisions based on the obtained meaningful insights are transferred back
towards the physical enterprise to improve businesses of the physical enterprise.
Digital twins combined with extended reality (XR) devices provide a feeling of a real
physical presence in virtual space for remote workers to operate digital twin models
collaboratively as if remote workers feel that they are at the same place.
Gamification is a process of using game mechanics, elements, and principles and
applying them to non-game contexts to engage people better. Gamification can be used
in a metaverse enterprise for providing remote collaborative working operations as a
means to keep the workforce engaged and to drive productivity.
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ESG Strategic Planning and Program Management
Step 1.
Identify ESG
Issues &
Conduct
Materiality
Assessment
Step 2.
Assess As-Is
Current State
Step 3. Set
To-Be Goals
& Develop
As-Is to To-
Be Roadmap
Step 4. Set
ESG
Strategic
Framework
& Action
Plans
Step 5.
Execute
Step 6.
Review &
Improve
Program
Identify the most relevant ESG issues
dynamically considering double materiality
•Identify ESG issues that can create risks and opportunities
•Identify ESG risks and opportunities that can impact on business (financial materiality) and impact on people and the environment (impact materiality)
•Monitor and update the change of material ESG risks/opportunities/impacts over time
Diagnosis of current program management state
and maturity regarding material ESG issues
•Set ESG program management priorities
•Set specific ways to ESG integration into business
•Set specific ways to implement roadmap
•Set specific ways to work systematically
•Set specific ways to measure material ESG metrics/KPIs
•Set specific ways to leverage technology and expertise
ESG
Program
Management
•Measure the level of governance over ESG program management
•Measure the level of ESG integration into business objectives,
strategy, risk management, and corporate culture
•Measure the performance of ESG program management expected
from stakeholders
•Measure the quality of ESG disclosure and communication
Establish clear objectives/goals & develop
roadmap to achieve the goals
•Define purpose of ESG program management and target goals to
achieve
•Identify measurable outcomes and material ESG metrics/KPIs for
performance measurement
•Identify gap between current state and target state
•Set the short-term, mid-term, long-term time frames
•Specify specific to-do key actions along the roadmap time lines
Set clear framework and actions for ESG
program execution
Implement management program and monitor
& evaluate progress and performance
•Integrate ESG into business practices and processes
•Monitor constantly ESG program progress
•Measure material ESG metrics/KPIs
•Evaluate ESG program management performance
Evaluate outcomes and revise any needed
part of program
•Compare outcomes to target goals
•Disclose and communicate result of outcome analysis
•Identify needed changes and specific was to improve program
•Revise ESG program management
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Scenario Planning for Metaverse Enterprise
Scenario planning is a structured way for businesses to explore and think about
the future.
Scenario planning is a tool to research potential impacts of the external world
on business.
Digital twins enable low-risk and low-cost experimentation of potential options
in scenario planning that can minimize uncertainty.
Digital twins can reduce risks by giving opportunity to notice potential risks in
advance. For example, global climate change presents two risks: physical risks
and transition risks. Digital twins can be used in climate change scenario
planning under uncertain external business environments such as policy,
regulation, and technology changes.
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TCFD Scenario Analysis
1. GOAL AND
SCOPE
DEFINITION
2. ANALYZE
EXTERNAL
AND INTERNAL
ENVIRONMENT
3. SCENARIO
BUILDING
4.
ASSESSMENTS
5. STRATEGIC
RESPONSES
•Identify core problem
(leadership/stakeholders)
•Define scope/boundary and level of
analysis
•Set time horizon
The objective of the scenario analysis is to evaluate the impacts of climate change-related risks and
opportunities on business and examine the resilience of current climate change-related strategy.
The scenario analysis is used as an essential tool for organization’s strategic plans or risk management
processes.
The scope of analysis can
include value/supply chain
beyond direct operations, to
achieve a more comprehensive
understanding of the possible
indirect impacts of change-
related risks and opportunities
on business. After familiar with
the qualitative scenario
analysis, a data-driven
quantitative analysis can be
added to further develop the
possible pathways to the
scenarios. The scope of impact
can extend to the impact of a
company’s activities to climate
change (financial v. ES
materiality).
The identified time frames are short (2025),
medium (2035) and long term (2050).
•Identify the key forces and uncertainties
•Identify material risks
•Identify opportunities
Acquire information to predict trends/uncertainties in
environmental and socio-economic conditions such as changes
in policies/regulations, market/technology/investment shifts,
energy supply/demand, changes in population/ GDP.
Material risks include climate-related risks (transition and physical risks).
Specifically, transition risks include climate change-related policy and regulation,
technology development, and reputation. Physical risks include chronic longer-term
climate shifts, such as sustained higher temperatures, sea level rise and acute
event-driven extreme weather, such as heat waves, water stress, wild fires, floods,
drought, and hurricanes.
Climate change-related opportunities include resource efficiency,
energy source, new products and services, markets, revenue
generation, and resilience.
•Select the right public scenarios
•Develop scenarios through internal modeling under
key uncertainties
Commonly used reference scenarios are the physical scenarios, such as the
Intergovernmental Panel on Climate Change (IPCC) scenarios and the transition
scenarios, such as the International Energy Agency (IEA) scenarios. Other
publicly available climate change scenarios include the International Renewable
Energy Agency (IRENA) scenarios and the Network for Greening the Financial
Systems’ (NGFS) Transition scenarios.
Climate change scenarios are can be developed using projections
of what can happen by creating plausible, coherent and internally
consistent descriptions of possible climate change pathways
towards certain goals such as the Paris Agreement targets of 2°C
(or less) of global temperature warming.
•Evaluate impacts of each
identified risk on business for
each scenario per defined time
flame (scenario analysis
outcomes)
To assess a risk until a time frame, a selection of
relevant external variables can be used to
simulate a scenario. These variables can include
carbon pricing and sectoral carbon intensities.
For example, for a policy transition risk, carbon
price of around 2$ per ton by 2025 with low
financial impacts was expected.
•Develop narrative
•Implement strategy
•Derive action plan
•Monitor developments
Specify plan to decrease greenhouse gas
(GHG) emission (e.g., halve GHG
emissions by 2030 for Scope 1/2/3
emission) and implement the net zero
roadmap to achieve net zero by 2050.
Reference Books
Reference TCFD Reports
BNP Paribas TCFD Report 2020
Chevron TCFD Report 2020
Daimler TCFD Report 2020
Eaton TCFD Report 2021
Macquarie TCFD Report 2020
Moodys TCFD Report 2020/Decarbonization Plan 2020
Nasdaq TCFD Report 2020
Nestlé's TCFD Report 2020/Net Zero Roadmap 2021
Wells Fargo TCFD Report 2020
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ESG Investing and Management Consideration Core Factors
Source: Bradley, Brendan. ESG Investing For Dummies, Wiley (2021)
Opportunities (Return) Risks (Cost)
Impacts (Value Creation)
universal risks
(e.g., climate change)
industry specific risks
business specific risks
ESG issue specific risks
(e.g., Environmental
physical/transition/liability
risks)
market competitiveness
better placed to win investment
rise of company value
return on reputation
employees' better performance
regulation compliance
business resiliency
circular business model
increase positive impact
limit negative impact
Intended/unintended impact
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ESG + Digital Integrated Transformation (ESGDX) Imperative
Source. The European double up https://www.accenture.com/us-en/insights/strategy/european-double-up
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How ESGDX Can Create New Revenue Streams?
Digital transformation is the adoption and integration of digital technologies to transform all areas of
business functions. It can fundamentally change how a business operates internally and
transform employees and the customer experience. Digital transformation is also about cultural
change over an organization’s way of working.
Technology is the engine of digital transformation, data is the fuel, process is the guidance
system, and organizational change capability is the landing gear. They must function well together.
Business model describes how a company creates and captures value: customer value
proposition is to offer the created value, operating model is to deliver the created value, product
and service innovation is to create the value, and value capture is to monetize the created value
through the pricing mechanism and cash flow generation.
The essential part of digital transformation is using data and digital capabilities to reshape
customer value propositions, transforming operating models for greater customer interaction
through the efficiency and productivity gains, and accelerating product and service innovation,
which introduce a new digital business model, and then, lead to new revenue streams and new
revenue opportunities.
Sustainable Digital Business Model:
By Integrating ESG sustainability into value propositions, operating models and innovation
process of products and services of the digital business model, a company can generate cost
savings, reduced business and ESG risks, sustainable resource use, improve business resilience,
customer trust, and expanded market opportunities through new customer experiences.
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ESGDX for ESG Sustainability Management
Real-time informed decision-makings regarding the management of
strategic and material ESG issues by:
Integrated and centralized ESG data management for transparency
Continuous tracking/improvement of ESG management performance KPIs
Continuous assessments of ESG management performance
Scenario analyses for identifying and reducing exposure to ESG risks and
assessments of ESG impacts
Implementation of virtual collaboration tools
Visibility/traceability across the value/supply chain
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ESG Sustainability Management/Assessment Issues &
Challenges & Solutions
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Forum for ESG + digital transformation (DX) integrated management for
sustainability impacts & digital technology innovation for sustainable
development acceleration.
LinkedIn Group: https://www.linkedin.com/groups/8956651/
Facebook Group: https://www.facebook.com/groups/822562128365739
ESG DX Forum
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The Sustainable Development Goals (SDGs) are a collection of 17 interlinked
global goals designed to be a "blueprint to achieve a better and more
sustainable future for all". The SDGs were set up in 2015 by the UN General
Assembly and are intended to be achieved by the year 2030.
(https://sdgs.un.org/goals)
UN Sustainable Development Goals (SDGs)
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SDGs Performance Assessment for S&P 500 High-Tech Industry
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ESG + Digital Transformation Integrated Management
Conduct assessment to determine which ESG risks, opportunities, and
impacts are of strategic significance to the company and stakeholders;
Monitor and measure them with data-driven tools
Set and communicate long-term value creation and
ESG sustainability strategy, supported by targets,
resources and technology foundations; Establish
metrics and KPIs that enable management to monitor
performance against goals; Embed management of
ESG sustainability issues in wider business processes
Define governance structure to embed ESG
sustainability throughout the digital transformation
strategy; Ensuring the entire C-suite
understands how ESG sustainability issues are
relevant to their respective areas of responsibility.
Integrate ESG sustainability into value
propositions and customer experiences,
enabled by digital- and data-driven efficiencies
for end users; Set a data-and-analytics
strategy to collect ESG sustainability data
across business units and create new revenue
streams by making this data available to
customers and partners.
Build capabilities needed to adopt digital business
models that improve ESG sustainable resource use
through intelligent provisioning, coordination or
optimization; Enable data-sharing across isolated
organizational groups to optimize and track the ESG and
economic savings realized by digitally enabled business
models, and to understand the aggregated impact of
these outcomes; Facilitate a data-sharing with real-time
analytics and optimization to match supply and demand;
Use digital platforms and channels to collect more
distributed, inclusive customer feedback for ESG
sustainable digital business model innovation
Develop a roadmap for investment in IT capabilities to
support transparent and integrated data-led efficiency
improvements; Factor ESG considerations into
operational decision-making criteria where impacts are
most significant; Enable intelligent workflows and
process automation to create measurable efficiency
gains and improve resource use
Create a control-tower solution that integrates real-time
data across the supply chain with external data sources
to improve visibility and resilience; Design a data model
that integrates internal and external data sources to
identify and reduce exposure to acute and chronic
ESG risks (e.g. weather events, supply volatility), as well
as tracking performance against environmental goals
Exchange data insights in organization and value chain, using
diverse sources to inform action while ensuring data compliance,
privacy and security; Ensure ESG sustainability data is a core
factor of decision-making; Conduct continuous ESG assessments
using data analytics, combined with AI technology, to monitor
changes in strategic issues and make real-time decisions;
Democratize access ESG impact data/insights through self-service
portals for all employees, including a dashboard that tracks
company-wide KPIs aligned with ESG sustainability reporting
standards
Develop/ implement measurement tools and impact
assessment frameworks to value ESG externalities and
return on investment; Incorporate digital tools into
financial assessment processes in order to conduct
sound assessments of ESG sustainability impacts
within a defined set of future scenarios; Integrate and
centralize data in order to report performance against
environmental KPIs aligned to global sustainability
reporting standards
Provide employees with the digital
and data tools and capabilities to
deliver innovation aligned to the
company purpose and ESG
sustainability KPIs; Effectively
communicate the company’s long-
term growth plans, including any
digital and ESG goals; Continuously
improve KPIs that combine digital
transformation and ESG
sustainability goals
Source. Bridging Digital and Environmental Goals: A Framework for Business Action
http://www3.weforum.org/docs/WEF_Bridging_Digital_and_Environmental_Goals_2021.pdf
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Next Generation ESG Digital Solution/Platform Development
modular based flexible component solutions
development
-data management solution
-data analysis solution
-performance management solution
- ...
data governance solution for data
availability/visibility/transparency and quality control
-end to end data flow management with advanced
search capabilities
assessment solution for ESG sustainability-related
risks, opportunities, real-world impacts
-development of new metrics that can represent the
processes and systems governing outcomes and
impacts
solution for maturity evaluation
-forward-looking analytic tools for assessing likely
future performance
solution for tracking the ROI of ESG sustainability
management efforts across enterprise
AI & big data analytics-driven automatic real-
time data capture, processing, and storing
standardized analytically rigorous metrics
measurement ways to ensure consistency and
comparability
capture business/industry/jurisdiction-specific
dynamic and time-sensitive material ESG
sustainability considerations based on double
materiality approach
provide a reliable foundation for cross-company
comparisons
use of right framework to evaluate ESG
sustainability-related information critically and
appropriately
capture matters that potentially significant,
monetary implications over time
link between a company’s management in ESG
sustainability-related risks, opportunities and
impacts and its financial performance over time
Management Platform Assessment Platform
Linking Solution
blockchain
based
secure and
credible data
sharing
Integrated Platform
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Balancing Green (MIT Press) One Page Book Summary
1. The Growing Pressures
3. Impact Assessment
4. Making with Less Taking
5. The Sorcery of
Sustainable Sourcing
2. The Structure of Supply Chains
6. Moving More, Emitting Less
7. All’s Well That Ends Well 8. Green by Design
9. Talking the Walk:
Communicating Sustainability
10. Managing Sustainability
11. Creating Deep Sustainability
12. The Travails of Scale
13. A Road to Sustainable Growth
Sustainability-focused
stakeholders' forces
regarding environmental
impacts create economic
incentives for corporate
environmental initiatives.
Examination of sustainability risks, opportunities, and impacts in a
company and across a supply chain is crucial because the vast majority
of environmental (and the associated potential improvements) issues
take place outside the four walls of most companies.
a. Life cycle assessment (LCA) and Greenhouse Gas Protocol (GGP) are
example methodologies for estimating a product's total environmental
impact.
b. Materiality assessment plays a crucial role in allowing companies to make
sound business decisions about which impacts to tackle.
Carbon footprint
evaluation of the supply
chain of bananas sold in
the United States.
BASF environmental
materiality assessment
Case studies of sustainability improvements
regarding carbon footprint, water consumption, and
toxin emissions
Upstream supply chain sustainability case studies: IKEA
and Starbucks cases for reducing negative environmental
impacts and the risk of reputational damage
Examples that show how companies can make significant
reductions in GHG emissions through transportation and
distribution management
Sustainability improvements at the end-of-life of the product
and beyond (circular economy)
Product design and engineering changes that can markedly
affect environmental impact across the full product life cycle
including packaging design and design for recycling
Chapter 16: Circularity for Design
-Redesigning Design
-Recognizing the Problems Designers
-Face Creating a Framework for Circular Design
Sustainability-related labeling, annual corporate social
responsibility reporting, and other marketing
communications
In-depth case studies of three “deep green”
companies: Dr. Bronner's Magic Soaps,
Patagonia, and Seventh Generation
Management issues regarding sustainability
initiatives across an organization
Fundamental challenges of replicating deep green
practices on a larger scale
Trade-off between financial and
environmental performance
Companies can achieve both of environmental and financial goals within the grayed region.
This is the case with initiatives motivated by eco-efficiency, eco-risk management, and/ or
eco-segmentation considerations. However, once companies reach the Pareto frontier,
without radical change, they will face unavoidable trade-offs between environmental and
financial performance.
The set of options
available for creating
new opportunities to
achieve both economic
growth and a reduction
in environmental
impacts.
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ESG Investing For Dummies (Wiley) One Page Book Summary
1. Entering the World of ESG
2. Evolution and Growth of ESG Investing
7. Approaches to
ESG Investing
8. Equity-Based Instruments
3. Environmental Component
15. Elaborating the ESG Endgame
12. Creating Value through ESG
10. Derivative and Alternative Instruments
11. Geographical Differences
14. ESG Performance and Reporting
ESG Investing Consideration Core Factors: industry
sectors, ESG strategies, material indicators
Impact investing is an
approach to investing in
initiatives, organizations, and
funds that pursue the
development of both financial
returns and quantifiable social
and environmental impact.
Benefits of integrating ESG
factors into organization’s
management, strategy, and
goal and effective ESG
practices: generating
enhanced returns;
attracting more customers;
reducing costs; increasing
productivity and attracting
talent
Greenwashing appears to have become more prevalent,
but it’s difficult to prove, given the lack of a common
definition for what constitutes good corporate behavior.
Part 1: Getting to Know ESG
13 Devising an ESG Policy
4. Social Component
5. Governance Component
6. Greenwashing
Understanding Why ESG Is
Important:
global sustainability challenges;
interest of millennial investors in
ESG; producing more systematic,
quantitative, impartial, and
financially applicable approaches to
highlight the core ESG factors.
The ‘E’ in ESG considers the company’s use of
natural resources and the effect its operations have
on the environment, in terms of direct operations
and throughout its supply chains.
climate change: rapid reduction in GHG emissions + offsetting
(e.g., carbon credits) to reach net carbon zero; energy efficiency:
decrease hydrocarbon-sourced energy consumption by displacing
it with clean energy sources, or to integrate systems to improve
energy usage; global water crisis: water access, pollution, and
scarcity; air and water pollution: pollutant emissions ; biodiversity
and deforestation crisis; waste management: circular economy,
waste-to-energy solutions Qualitative nature of social performance and the
wide range of related issues make ‘S’ to be the most
difficult to analyze, measure, and integrate into
investment strategies.
Social performance indicators: customer satisfaction, data security and privacy, gender and
ethnic equality, diversity and inclusion, employee engagement, community relations, , human
rights, labor standards, health, safety, and wellbeing
Corporate governance principally describes the systems a company uses to balance
the competing demands of its diverse stakeholders,
Evaluating governance: board responsibilities
and composition, audit committee structure,
bribery and corruption, executive compensation,
lobbying, political contribution, whistleblower
schemes
Part 2: Investing in ESG
Socially Responsible
Investing SRI);
Impact Investing;
Green Investing;
Faith-based
Investing
Integrating ESG Strategies into equity-based investment
funds are either actively managed (the portfolio manager
decides where and what to invest in) or passively
managed.
Positive screening strategies based on ESG scores
can raise the ESG quality of both passive and active
traditional and smart beta portfolios, without
reducing risk-adjusted returns. However, instead of
focusing on maximizing financial performance from
ESG criteria, many investors are now concentrating
on maximizing ESG performance subject to risk-
return constraints.
9. Fixed Income Instruments
Using ESG factors to inform fixed income investment (Bond) decision-
making is primarily about identifying risks and opportunities that might
otherwise be overlooked.
Integration of ESG factors into
fixed income portfolio
strategies: positive/negative
screening, best-in-class,
engagement, thematic
ESG indexes are becoming
fundamental building
blocks for asset allocation.
Derivative and alternative
instruments can achieve
passive returns using ESG
indexes.
ESG investing is expected
to top US$50 trillion in the
next 20 years confirms that
it has moved from niche to
mainstream.
Part 3: Applying ESG Philosophy
Investors' key
considerations to
develop an ESG
framework:
material ESG
metrics, internal
governance
structure, peer
reviews
a. criteria and metrics for material
ESG factors for performance
measurement b. frameworks for
related reporting of the data behind
material ESG factors
A materiality analysis is a method used to
pinpoint and prioritize the issues that are
most important to an organization’s value
chain and its stakeholders. ESG ratings
grade companies against given ESG
standards, evaluating their performance
on a sustainability scale.
Part 4: The Part of Tens
16. Ten Frequently Asked Questions
17. Ten Issues Surrounding ESG Portfolio
Construction
18. Ten Factors Influencing the Growth of ESG Investing Climate Change
ESG strategies have mostly outperformed
the most popular conventional passive
ETFs.
ESG evolved to mainstream strategy
45. ©2021 TechIPm, LLC All Rights Reserved
On Leading Digital Transformation (HBR Press) One Page Book Summary
2. The Transformative
Business Model
3. Digital Doesn’t Have to
Be Disruptive
4. What’s Your
Data Strategy?
1. Discovery-Driven Digital
Transformation
5. Competing in the Age of AI 6. Building the AI-Powered
Organization
7. How Smart, Connected Products Are
Transforming Companies
8. The Age of Continuous
Connection
9. The Problem with Legacy
Ecosystems
10. Your Workforce Is
More Adaptable Than You
Think
The essential part of digital-transformation strategy is using data and digital capabilities to
create new value for customers. A key part of discovery-driven digital transformation is
identifying organizational problems that can be addressed with digital technology, the desired
improvement for each, and a metric for assessing progress toward it.
Business model describes how a company creates
and captures value. Business model defines the
customer value proposition and the pricing
mechanism, indicate how the company will organize
itself and whom it will partner with to produce value,
and specify how it will structure its supply chain.
Coherent dynamic strategy for organizing, governing, analyzing,
and deploying an organization’s information assets is needed.
Companies need a coherent strategy that strikes
the proper balance between two types of data
management: defensive, such as security and
governance, and offensive, such as increasing
revenue, profitability, and customer satisfaction.
To scale up AI, companies must make three shifts:
(1) Develop cross-functional teams with a mix of
skills and perspectives for interdisciplinary
collaboration ; (2) Develop data-driven decision
making procedure at the front line; (3) Develop
agile, experimental, and adaptable mindset
To launch successful AI, leaders should devote
early attention to several tasks:
(1) Explaining why AI is important to the business
and how they’ll fit into a new, AI-oriented culture; (2)
Anticipating unique barriers to change; (3)
Budgeting as much for integration and adoption as
for technology ; 4) Balancing feasibility, time
investment, and value
Through what we call connected
strategies such that companies are
addressing customers’ needs the
moment they arise nd sometimes even
earlier, customers get a dramatically
improved experience, and companies
boost operational efficiencies and lower
costs.
Identifies a problem, describes what a
solution would achieve, and proposes a
way to measure progress on that
solution
Digital
transformative
business model
can link a new
digital technology
to an emerging
market need.
Smart, connected products require (1)
companies to build and support an
entirely new technology infrastructure;
(2) a fundamental rethinking of product
development and manufacturing; (3) a
new organizational structure.
Smart, connected products create (1) new
production requirements and
opportunities; (2) new services.
Identify metrics that are more closely
linked to the specific improvements you
hope digital transformation initiatives
will bring about
Transformative business model
features: (1) personalization, (2)
a closed-loop process, (3) asset
sharing, (4) usage-based pricing,
(5) a collaborative ecosystem,
and (6) an agile and adaptive
organization
Digital transformation means using digital tools to
better serve the known customer.
Digital transformation often enables the elimination of
inefficient intermediaries and costly physical
infrastructure. But that doesn’t mean the physical
goes away entirely.
Digital transformation requires slow replacing of
legacy systems in a modular, agile fashion.
Balancing offense and defense requires
balancing data control and flexibility.
A company’s data architecture describes how
data is collected, stored, transformed,
distributed, and consumed.
A robust a single source of truth (SSOT) for
control and multiple versions of the truth
(MVOTs) data architecture for flexibility are
need.
The SSOT works at the data level; MVOTs
support the management of information.
Competing in the Age of AI
One Page Book Summary
Companies need to make continuous
connection a fundamental part of their
business models. They can do so with
four strategies: respond to desire,
curated offering, coach behavior, and
automatic execution.
11. How Apple Is
Organized for Innovation
Bonus. Digital
Transformation Comes
Down to Talent in Four
Key Areas
They must function
well together.
To build effective new business models that
take advantage of digital technology, older
companies need to agree on the way forward,
adopt new performance metrics, and rebuild
their supplier, distributor, and partner
networks.
Companies need to start thinking of their
employees as a reserve of talent and energy
that can be tapped by providing smart on-the-
job skills training and career development.
The Apple Model: The company
is organized around functions,
and expertise aligns with
decision rights. Leaders are
cross-functionally collaborative
and deeply knowledgeable about
details.
Technology is the engine of digital
transformation, data is the fuel, process is the
guidance system, and organizational change
capability is the landing gear.
46. ©2021 TechIPm, LLC All Rights Reserved
Competing in the Age of AI (HBR Press) One Page Book Summary
2. Rethinking the Firm
3. The AI Factory
4. Rearchitecting
the Firm
1. The Age of AI
5. Becoming an AI Company 6. Strategy for a New Age
7. Strategic Collisions
8. The Ethics of Digital Scale,
Scope, and Learning
9. The New Meta
10. A Leadership Mandate
a. AI is transforming the very nature of companies—how they operate and how they compete.
b. AI is restructuring the economy.
Understanding the new
opportunities and challenges
has become essential, and
many time-honored
assumptions about strategy
and leadership no longer
apply.
Emergence of firms that are
designed and architected to
release the full potential of
digital networks, data,
algorithms, and AI (digital
operating models).
Case studies of three digital unicorns: Ant Financial,
Ocado, and Peloton
Firms need a fundamentally different operating architecture
to remove constraints on firm scale, growth, and learning
exploiting the full power of digital networks and AI.
Operating architecture for an AI-powered firm: a
common foundation of data inputs, software
technology and algorithms that are provided by an
AI factory, easily accessible (but carefully designed
and secure) interfaces that agile teams developing
individual applications can use.
Digital firms enable and require a
new approach to strategy exploiting
the digital network and learning
effects.
Leaders should be aware of how their newly
deployed digital capabilities can be misused
in ways they never intended-or possibly even
imagined.
The age of AI is defining a new
set of challenges for leaders.
Amazon's digital operating model
illustrates the advantages of digital
scale, scope, and learning. Its digital
systems scale more easily and
continue to improve despite the size
and complexity of its operation.
Digital unicorns’ operating model (delivers value) enables
striking capacity to drive scale, scope, and learning and their
business model enables creation and capture of value without
operational limitation.
The AI factory is the scalable decision engine that enable
data-driven and AI-driven automation, analysis, and
insights and powers the digital operating model of the
twenty-first-century firm.
AI factory components: the AI algorithms that make predictions
and influence decisions, the data pipeline that feeds them, and
the software, connectivity, and infrastructure that power them.
To become an AI-enabled firm that can leverage the power of
data, networks, and AI requires the transformation journey
of deploying a digital operating model.
Five guiding principles that characterize an
effective transformation process:
1. Development of strategic clarity and commitment
2. Development of a clear operating architecture
3. Development of a product-focused agile
organization
4. Development of a deep foundation of capability in
software, data sciences, and advanced analytics
5. Development of a clear multidisciplinary
governance
The stronger the network and
learning effects, the sharper the
increase in value with scale:
a. The most important value
creation dynamic of a digital
operating model is its network
effects.
b. Learning effects can either add
value to existing network effects or
generate value in their own right.
A new generation of digital operating
models transform the economics and
nature of service delivery, and thus,
competition.
As collisions between digital firms and
traditional firms multiply across the
economy, different industries become
increasingly connected to each other
coalescing around a small number of
digital superpowers (hub firms).
Ethical challenges created by the combination of
digital networks and AI: digital amplification,
algorithmic bias, data security and privacy, platform
control, fairness and equity
The age of AI is changing the rules of the game. The new rules are
defining the new age, shaping key arenas, and transforming our
collective future.
Rule 1: The age of AI is driven by a relentless and systemic driver
of change.
Rule 2: AI-driven world has more to do with a universal and
horizontal capabilities.
Rule 3: Traditional industry boundaries are disappearing.
Rule 4: As digital operating models continue to displace traditional
industrial processes, they also remove traditional operating
constraints.
Rule 5: Concentration and inequality will likely get worse.
Enterprise transformation
Entrepreneurial opportunity
Regulation
Community
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Sustainable
Smart City Development
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Metaverse for Sustainable Smart City
Cities are responsible for more than two-thirds of the world’s energy use and greenhouse gas
(GHG) emissions. A comprehensive reduction in GHG emissions requires an increased focus on
transforming energy use in buildings, transportation systems, as well as a shift from fossil fuels to
renewable energy sources. It also requires a holistic approach to the de-carbonization of city
operations, infrastructure, and services (e.g., waste management systems).
Integrated Environmental Solutions (IES) developed the environmental digital twin technology that
can reduce carbon emissions of cities worldwide. The environmental digital twin enables energy-
efficient design and continuous optimization of buildings using AI by incorporating real-world
operational data obtained by IoT sensors.
The city of York is the first city in the UK to use a real-time
transport model for live traffic management exploiting digital twins.
Digital twins can help to realistically simulate and analyze a city’s
current and future traffic, to test and validate different measures
and thus find the best locations for new traffic.
Digital twins can provide a holistic view of a utility’s electricity/water
systems and enable data-driven decision-making for
energy-efficient and resource-saving management of the systems.
Metaverse City Management Center enable citi-wide ESG
sustainability monitoring and control exploiting integrated hierarchies
of digital twins (metaverse for ESG digital transformation).
Source. https://learn.iesve.com/digital-twin-
white-paper/?utm_source=ies-
website&utm_campaign=navigant
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The GDS-Index for top 20 sustainable cities (https://www.gds.earth/top-20/)
Appendix. Sustainable City Ranking
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Smart City Components
Source. Smart Cities Technologies and applications : BIM-GIS- IOT-AI@udemy
Metaverse
Applications
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Smart City Design and Development
Source. Smart Cities Technologies and applications : BIM-GIS- IOT-AI@udemy
BIM (Building Information Modeling for 3D digital
representations of infrastructure to get proper design,
construction, operation, and maintenance
GIS (Geographic Information System) to map and
analyze geographic features
IoT (Internet of Things) monitoring for real-time
data sensing of smart city components
Smart City Digital Twin
Metaverse Project Management Platform
Design Team Construction Team Management Team
Digital Twin of Helsinki Kalasatama District:
https://www.youtube.com/watch?v=9Vgilm8ZrO4&t=160s
Cloned Shanghai:
https://www.youtube.com/watch?v=hOJZhsNtB6g&t=152s
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Smart City Management
Smart City
ESG Digital Transformation
Platform
Smart City
Metaverse Project Management
Platform
Smart City
Management Center
City of the future
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Smart City Financing and Business Development
Green infrastructure funds are an
investment funds for clean transportation
systems (e.g., electric vehicle), green
buildings (e.g., energy-efficient buildings),
renewable energy systems (e.g.,
wind/solar power system), waste
management system (recycling system) to
invest in sustainable design, reductions in
energy- and water-use, greenhouse gas
emissions reduction, air quality
improvement, and natural resource
protection
Metaverse NFT based DeFi Financing
DeFi Platform Design and Development:
https://www.youtube.com/watch?v=onsUB
hWBrfU&t=1629s
Metaverse City Living Lab
metaverse platform for
public–private–people partnerships
for city-wide circular economy
development
public–private–people collaboration
for sustainable city management
and development
co-creation of eco-friendly city
environment
test-bed for innovation
commercialization of new business
ideas
Metaverse City Service Portal
metaverse platform for city government
services: call center; citizen portal;
utility management; waste
management; license/permit
management; asset/land management;
public security and health
management; mobility and parking
management; job search service
Metaverse Commerce Portal
metaverse platform for digital
billboards/shops/showroom where
users can access products/services
from companies based on brand
reputations and try them virtually;
market place for direct transaction
among people; active marketing
campaigns; real/virtual property
renting/sales; land sales
Metaverse IR/PR Portal
metaverse platform for linking
investors and investees; virtual
fund raising events; virtual public-
private investment partnerships
platform; virtual PR event with
tour of cities for global investors
and tourist
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Appendix. u-City Development Projects in S. Korea
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Appendix. Sustainable City Development Projects in S. Korea