Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 1 describes the concept of emerging technologies, which includes any technology old or new that has unrealized potential. Through development or application, emerging technologies have the capability to change society. A brief history of technological disruption is provided, along with a description of the current "Fourth Industrial Revolution." Emergining technologies of the Fourth Industrial Revolution include data science/AI, blockchain, the Internet of Things (IoT), 3D printing, 5G technology, quantum computing, and robotics. Descriptions of all these technologies, as well as ways they can transform business, are offered. Ultimately, data science/AI and blockchain are two of the biggest emerging technologies right now and therefore are what decision makers need to know about. If businesses don't adopt these technologies, those businesses will eventually become obsolete.
Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 2 offers a brief overview of what data science is, how it can be useful, and how it can be applied. A short history of data science is provided. There are three core fields of data science: AI, machine learning (ML), and statistics; each of these fields and how they are part of data science is described. Machine learning is particularly essential to data science, and there are three main ML types: supervised learning, unsupervised learning, and reinforcement learning. These approaches are discussed along with other types of ML and how decision makers can use ML to their benefit. A thorough introduction to statistics is also given, including a description of different types of statistics and the benefits, applications, and potential problems of statistics-such as bias-for business. Case examples are offered, highlighting how data science can impact business.
Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 3 builds on the previous chapter and explores data strategies. A data strategy should be constantly updated, cover technical and organizational aspects, and ultimately point toward and work with the business strategy. Data strategies can offer additional revenue and a competitive advantage to companies. Guidelines for how to create a data strategy are provided, including starting with the business strategy, building data use cases, understanding data architecture and data governance, and managing AI projects. The data science hierarchy of needs model is described. CRISP-DM is a process used for planning data science projects; its six main phases are business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Tesseract Academy's 2-actor process is another popular process in data science and focuses on the problem definition, data management, the solution to the problem, and creating value through actionable insights. Several case studies are offered throughout the chapter.
Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 4 discusses data scientists-characteristics of good data scientists, skills they should have, their motivations, and how to effectively manage them. Essential skills for a data scientist include hacking skills, math and statistics knowledge, and substantive expertise. Data scientists tend to be curious, proactive, and innovative; many need to be mentally engaged, stimulated, and challenged. When hiring a data scientist, make sure to capitalize on these traits and their skill set. Ways for a company to attract data scientists are offered. Data scientists can be categorized into six groups: computer scientists, statisticians, quantitative specialists, self-taught data scientists, software platform users, and domain specialists. Each of these is described. The idea of a data-centric organization is also explored as well as how to build a data science culture and overcome resistance to change.
Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 5 explores blockchain, specifically what a nontechnical decision maker needs to know about it. A brief history of money and payment systems is offered, including the rise of blockchain. Blockchain is a decentralized ledger of records, a distributed database stored on multiple computers. Advantages of blockchain and differences between it and traditional databases are described. The elements of blockchain are explained, specifically blocks (containing data, nonces, and hashes), nodes, and miners. The relationship between cryptography and blockchain is discussed. The four main types of blockchain networks-public, private, hybrid, and consortium or federated-are explored, including their advantages, disadvantages, and uses. There are many applications of blockchain, several of which are described, including Bitcoin, nonfungible tokens (NFTs), and decentralized finance.
Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 6 explores how blockchain can be applied to and improve several industries, such as finance, cybersecurity, shipping, and the metaverse. All capital market participants will benefit from blockchain, including issuers, fund managers, investors, and regulators. Blockchain can improve supply chains as well, especially with development sourcing, production logistics, information systems management, and coordination. The likelihood of fraud regarding the authenticity of legal documents could be eliminated with blockchain; the shipping industry could increase efficiency while decreasing costs; cybersecurity could be enhanced; and file sharing could become decentralized. Blockchain could also assist in building the metaverse through providing proof of ownership, offering safe value transfer, and ensuring fair and transparent governance. Case examples are given throughout the chapter.
Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 7 discusses the maturity curve, a framework used to think about a technology's level of adoption within a business. Adopting emerging technologies tends to require a change in mindset. An organization must analyze its capabilities and the industry's potential to be disrupted by AI and blockchain. AI maturity is a concept that refers to various levels of adoption and looks at how much value a company can derive from AI. Four main components are needed to reach full adoption: knowledge, data, culture, and talent. All four of these are discussed. Questions are offered to help organizations find out if blockchain will be beneficial for them; these questions are categorized into business, technology, and legal questions. Businesses must be mindful of and adapt to technological changes in order to be successful in the future.
Emami is facing the heat from activist-consumers as well as its competitors. Competitors have renamed their cosmetic products by dropping the controversial word 'fair.' This was in response to the Black Lives Movement that erupted in the United States in May 2020. However, the movement against fairness is somewhat muted in India and is mostly occurring amongst urban, highly educated, younger cohort who are unlikely to be the users of the product anyway. The significant consumer base yearns for fairness and is willing to spend money on products which help them achieve the same. In such a scenario, how should Emami respond to competitor actions and consumer-activist pressure? The case provides an opportunity to discuss the significance of the brand name, role of advertising and gender stereotypes.
In October 2019, the regional chief data and analytics officer at Allianz AG, Belgium, attended a two-hour strategy meeting with the Allianz Benelux chief executive officer, who had expressed concerns about the company's digitalization strategy. A few days earlier, the marketing department had found that online sales channel results had fallen unexpectedly. The chief executive officer was worried that the company could lose market share if it did not react accordingly, which would damage the company's competitive position in the market. Therefore, the regional chief data and analytics officer was asked to gather a team to investigate why online sales were low and to design an effective customer acquisition strategy. In addition to his data office staff, the regional chief data and analytics officer asked for the business transformation unit to provide assistance. He had to consider how best to approach this challenging task.
The case describes the scientific approach taken by the founders of Mimoto - an electric scooter-sharing company offering dockless, keyless scooters available 24/7 - to develop their business idea. After a successful launch, they must decide whether to scale up their current strategy of renting scooters to individual customers or enter a new segment - renting to businesses (moving goods rather than people).
Most large companies take a similar approach to corporate innovation, running it out of centralized innovation groups. But companies in China, both domestic and foreign, are much more likely to turn to market-facing sources of innovation, including customers, competitors, and front-line employees. China's fast growth is producing a disproportionately large share of new customers for many industries, which demands an orientation toward generating ideas closer to customers to drive more market-led innovation.
Setting goals regarding relationship conversion, leverage, and defense can drive future revenue and lower costs, but this work requires a clear understanding of the heterogeneity of customer needs and economies of scale as they emerge over time. To inform and act upon this understanding, companies need an integrated approach to customer portfolio management and customer portfolio lifetime value.
By 2021, Manvendra "Manny" Saxena had acquired three small California street sweeping firms through a search fund and had combined them under the umbrella company PowerSweeping. Consistent with the search fund model, his goal was to streamline PowerSweeping's operations, help it grow, and then one day sell it at a high valuation. That was easier said than done. The three firms that made up PowerSweeping played in two different sweeping subindustries--municipal and construction--which used different equipment, served different types of customers, and had different revenue characteristics. The firms also employed both non-unionized and unionized workers from two unions, which limited Saxena's ability to integrate them. As Saxena generated a strategy, he also faced increased fuel, repair, maintenance, parts, and labor costs in the post-COVID environment, as well as intense competitive pressure from ASC, the largest street sweeping conglomerate in the United States. ASC was eyeing a roll-up merger through California and had made an offer to buy PowerSweeping--though the offer was less than what Saxena believed was its actual value. How could Saxena quickly streamline PowerSweeping and stave off inflation and competition long enough to unlock the company's true value for himself and his investors?
This case provides brief descriptions of 18 examples of corporate leaders confronting questions of whether and how to engage with societal issues, including social, political, and environmental issues. Social issues include COVID-19; social and racial justice; discrimination and prejudice; gender, sex, and sexual orientation; and humanitarian crises. Political issues included voting rights, abortion rights, and geopolitical conflict and rivalry. Environmental issues included climate change. The examples took place between 2014 and 2022. The examples are: 1. Delta Airlines/Ed Bastian: Vaccine Mandates (2021) 2. Racial Justice: Starbucks/Howard Schultz: "Race Together" (2015) 3. Merck/Ken Frazier: Charlottesville, President Trump, and Race (2017) 4. Starbucks/Kevin Johnson: Philadelphia Incident (2018) 5. OneTen Initiative: Living Wage Jobs for Black Americans (2020) 6. Tech Leaders: Oppose the Trump Travel Ban (2017) 7. Delta Airlines/Ed Bastian: Rescinding NRA Discounts after the Parkland Shooting (2018) 8. Corporate Leaders: Responding to Anti-Asian Hate (2021) 9. Salesforce.com/Marc Benioff: Indiana Boycott for Religious Freedom Restoration Act (2015) 10. Target/Brian Cornell: North Carolina "Bathroom Bill" (2016) 11. Disney/Bob Chapek: The Florida "Don't Say Gay" Bill (2022) 12. H&M/Helena Helmersson: China, Uighurs, and Human Rights (2020) 13. Corporate Leaders: Voting Rights and Election Bills (2021) 14. Corporate Leaders: Texas Abortion Ban (2021) 15. Unilever/Alan Jope: Ben & Jerry's, Israel, and Occupied Palestinian Territory (2021) 16. Google: Ceasing Search in China (2018) 17. Apple/Tim Cook: Data Privacy in China (2021) 18. Amazon/Jeff Bezos: Co-Founding Climate Pledge (2019)
On May 27, 2020, a blowout occurred in Well No. 5 at Baghjan (Assam); the well, owned by Oil India Ltd., caught fire on June 9, 2020. For almost five and a half months, the company tried to douse the 200-foot high flame but failed to do so. Finally, on Day 173, Oil India Ltd succeeded in capping the well. Biswajit Roy, Director (Human Resources and Business Development), was tasked with investigating the nature and cause of the crisis. Roy pondered on the nature of the crisis: Had it been purely technical or stakeholder-induced? What had led to the chaotic condition? Could things have been done differently?
On July 24, 2021, Chinese authorities issued the Double Reduction Policy to ease the burden of excessive homework and off-campus tutoring for students undergoing compulsory education in China. Off-campus English tutoring became strictly regulated, and hiring foreign teachers abroad to carry out training activities was strictly prohibited. 51Talk had achieved great success in the K–12 English online tutoring market, and this business accounted for more than 95 per cent of the company’s total revenue. However, the company would not be able to continue its K–12 student English online tutoring business in the Chinese market under the Double Reduction Policy. Jack Huang, 51Talk’s founder and chief executive officer, had to consider how to transform the company in order to survive.
In June 2022, Kelvin Van Rijn, owner of The Fritter Shop in London, Ontario, is considering multiple options for the future success of his business. The Fritter Shop had experienced significant growth over its first years in business and had recently relocated to a new production facility. This facility provided approximately 1,500 square feet of unused production space and Van Rijn is wondering how to make the best use of it. Van Rijn’s options include maintaining the status quo, seeking additional franchisees, wholesaling his fritters, selling the business, and exploring co-tenancy.