1.
ESG + Digital Transformation Integration One Page Summary
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
Reference Source: Bridging Digital and Environmental Goals: A Framework for Business Action
http://www3.weforum.org/docs/WEF_Bridging_Digital_and_Environmental_Goals_2021.pdf
Edited by Alex G. Lee
(https://www.linkedin.com/in/alexgeunholee/)

2.
ESG
Digital Transformation
Reference Books

3.
Balancing Green (MIT Press) One Page Book Summary
Edited by Alex G. Lee (https://www.linkedin.com/in/alexgeunholee/)
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.

4.
ESG Investing For Dummies (Wiley) One Page Book Summary
Edited by Alex G. Lee (https://www.linkedin.com/in/alexgeunholee/)
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

5.
On Leading Digital Transformation (HBR Press) One Page Book Summary
Edited by Alex G. Lee (https://www.linkedin.com/in/alexgeunholee/)
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.

6.
Competing in the Age of AI (HBR Press) One Page Book Summary
Edited by Alex G. Lee (https://www.linkedin.com/in/alexgeunholee/)
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