ESG + Digital Transformation Integration One Page Summary
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The document outlines the integration of ESG (Environmental, Social, Governance) factors with digital transformation strategies to enhance long-term value creation and sustainability for companies. It emphasizes the importance of a governance structure, data-driven decision-making, and continuous monitoring of ESG impacts throughout the organization and supply chain. Additionally, it highlights the significance of building capabilities in data management, analytics, and innovative business models to achieve both environmental and financial performance.
ESG + Digital Transformation Integration One Page Summary
- 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/)
- 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