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By 2009 Netflix had all but trounced its traditional bricks-and-mortar competitors in the video rental industry. Since its founding in the late 1990s, the company had changed the face of the industry and threatened the existence of such entrenched giants as Blockbuster, in large part because of its easy-to-understand subscription model, policy of no late fees, and use of analytics to leverage customer data to provide a superior customer experience and grow its e-commerce media platform. Netflix's investment in data collection, IT systems, and advanced analytics such as proprietary data mining techniques and algorithms for customer and product matching played a crucial role in both its strategy and success. However, the explosive growth of the digital media market presents a serious challenge for Netflix's business going forward. How will its analytics, customer data, and customer interaction models play a role in the future of the digital media space? Will it be able to stand up to competition from more seasoned players in the digital market, such as Amazon and Apple? What position must Netflix take in order to successfully compete in this digital arena? To examine the benefits and risks of investment in analytical technology as a means for mining customer data for business insights. Students will develop a strategy position for Netflix's investment in technology and its digital media business. Students must also consider how new corporate partnerships and changes to the customer channel model will allow the company to prosper in the highly competitive digital space.
By 2009 Netflix had all but trounced its traditional bricks-and-mortar competitors in the video rental industry. Since its founding in the late 1990s, the company had changed the face of the industry and threatened the existence of such entrenched giants as Blockbuster, in large part because of its easy-to-understand subscription model, policy of no late fees, and use of analytics to leverage customer data to provide a superior customer experience and grow its e-commerce media platform. Netflix's investment in data collection, IT systems, and advanced analytics such as proprietary data mining techniques and algorithms for customer and product matching played a crucial role in both its strategy and success. However, the explosive growth of the digital media market presents a serious challenge for Netflix's business going forward. How will its analytics, customer data, and customer interaction models play a role in the future of the digital media space? Will it be able to stand up to competition from more seasoned players in the digital market, such as Amazon and Apple? What position must Netflix take in order to successfully compete in this digital arena? To examine the benefits and risks of investment in analytical technology as a means for mining customer data for business insights. Students will develop a strategy position for Netflix's investment in technology and its digital media business. Students must also consider how new corporate partnerships and changes to the customer channel model will allow the company to prosper in the highly competitive digital space.
A field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples. In How To Lead in Data Science you will learn: Best practices for leading projects while balancing complex trade-offs Specifying, prioritizing, and planning projects from vague requirements Navigating structural challenges in your organization Working through project failures with positivity and tenacity Growing your team with coaching, mentoring, and advising Crafting technology roadmaps and championing successful projects Driving diversity, inclusion, and belonging within teams Architecting a long-term business strategy and data roadmap as an executive Delivering a data-driven culture and structuring productive data science organizations How to Lead in Data Science is full of techniques for leading data science at every seniority level—from heading up a single project to overseeing a whole company's data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they've developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas. About the technology Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite. About the book How to Lead in Data Science shares unique leadership techniques from high-performance data teams. It’s filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You’ll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you’ll build practical skills to grow and improve your team, your company’s data culture, and yourself. What's inside How to coach and mentor team members Navigate an organization’s structural challenges Secure commitments from other teams and partners Stay current with the technology landscape Advance your career About the reader For data science practitioners at all levels. About the author Dr. Jike Chong and Yue Cathy Chang build, lead, and grow high-performing data teams across industries in public and private companies, such as Acorns, LinkedIn, large asset-management firms, and Fortune 50 companies. Table of Contents 1 What makes a successful data scientist? PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP 2 Capabilities for leading projects 3 Virtues for leading projects PART 2 THE MANAGER: NURTURING A TEAM 4 Capabilities for leading people 5 Virtues for leading people PART 3 THE DIRECTOR: GOVERNING A FUNCTION 6 Capabilities for leading a function 7 Virtues for leading a function PART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY 8 Capabilities for leading a company 9 Virtues for leading a company PART 5 THE LOOP AND THE FUTURE 10 Landscape, organization, opportunity, and practice 11 Leading in data science and a future outlook
Author : Michael D. Smith Publisher : MIT Press Page : 229 pages File Size : 36,71 MB Release : 2017-08-25 Category : Business & Economics ISBN : 0262534525
How big data is transforming the creative industries, and how those industries can use lessons from Netflix, Amazon, and Apple to fight back. “[The authors explain] gently yet firmly exactly how the internet threatens established ways and what can and cannot be done about it. Their book should be required for anyone who wishes to believe that nothing much has changed.” —The Wall Street Journal “Packed with examples, from the nimble-footed who reacted quickly to adapt their businesses, to laggards who lost empires.” —Financial Times Traditional network television programming has always followed the same script: executives approve a pilot, order a trial number of episodes, and broadcast them, expecting viewers to watch a given show on their television sets at the same time every week. But then came Netflix's House of Cards. Netflix gauged the show's potential from data it had gathered about subscribers' preferences, ordered two seasons without seeing a pilot, and uploaded the first thirteen episodes all at once for viewers to watch whenever they wanted on the devices of their choice. In this book, Michael Smith and Rahul Telang, experts on entertainment analytics, show how the success of House of Cards upended the film and TV industries—and how companies like Amazon and Apple are changing the rules in other entertainment industries, notably publishing and music. We're living through a period of unprecedented technological disruption in the entertainment industries. Just about everything is affected: pricing, production, distribution, piracy. Smith and Telang discuss niche products and the long tail, product differentiation, price discrimination, and incentives for users not to steal content. To survive and succeed, businesses have to adapt rapidly and creatively. Smith and Telang explain how. How can companies discover who their customers are, what they want, and how much they are willing to pay for it? Data. The entertainment industries, must learn to play a little “moneyball.” The bottom line: follow the data.
The New York Times bestseller Shortlisted for the 2020 Financial Times & McKinsey Business Book of the Year Netflix cofounder Reed Hastings reveals for the first time the unorthodox culture behind one of the world's most innovative, imaginative, and successful companies There has never before been a company like Netflix. It has led nothing short of a revolution in the entertainment industries, generating billions of dollars in annual revenue while capturing the imaginations of hundreds of millions of people in over 190 countries. But to reach these great heights, Netflix, which launched in 1998 as an online DVD rental service, has had to reinvent itself over and over again. This type of unprecedented flexibility would have been impossible without the counterintuitive and radical management principles that cofounder Reed Hastings established from the very beginning. Hastings rejected the conventional wisdom under which other companies operate and defied tradition to instead build a culture focused on freedom and responsibility, one that has allowed Netflix to adapt and innovate as the needs of its members and the world have simultaneously transformed. Hastings set new standards, valuing people over process, emphasizing innovation over efficiency, and giving employees context, not controls. At Netflix, there are no vacation or expense policies. At Netflix, adequate performance gets a generous severance, and hard work is irrelevant. At Netflix, you don’t try to please your boss, you give candid feedback instead. At Netflix, employees don’t need approval, and the company pays top of market. When Hastings and his team first devised these unorthodox principles, the implications were unknown and untested. But in just a short period, their methods led to unparalleled speed and boldness, as Netflix quickly became one of the most loved brands in the world. Here for the first time, Hastings and Erin Meyer, bestselling author of The Culture Map and one of the world’s most influential business thinkers, dive deep into the controversial ideologies at the heart of the Netflix psyche, which have generated results that are the envy of the business world. Drawing on hundreds of interviews with current and past Netflix employees from around the globe and never-before-told stories of trial and error from Hastings’s own career, No Rules Rules is the fascinating and untold account of the philosophy behind one of the world’s most innovative, imaginative, and successful companies.
Technological advancements in computing have changed how data is leveraged by businesses to develop, grow, and innovate. In recent years, leading analytical companies have begun to realize the value in their vast holdings of customer data and have found ways to leverage this untapped potential. Now, more firms are following suit and looking to monetize Big Data for big profits. Such changes will have implications for both businesses and consumers in the coming years. In From Big Data to Big Profits, Russell Walker investigates the use of Big Data to stimulate innovations in operational effectiveness and business growth. Walker examines the nature of Big Data and how businesses can use it to create new monetization opportunities. Using case studies of Apple, Netflix, Google, LinkedIn, Zillow, Amazon, and other leaders in the use of Big Data, Walker explores how digital platforms such as mobile apps and social networks are changing the nature of customer interactions and the way Big Data is created and used by companies. Such changes, as Walker points out, will require careful consideration of legal and unspoken business practices as they affect consumer privacy. Companies looking to develop a Big Data strategy will find great value in the SIGMA framework, which he has developed to assess companies for Big Data readiness and provide direction on the steps necessary to get the most from Big Data. Rigorous and meticulous, From Big Data to Big Profits is a valuable resource for students, researchers, and professionals with an interest in Big Data, digital platforms, and analytics
Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite. "How to lead in data science" shares unique leadership techniques from high-performance data teams. It's filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You'll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you'll build practical skills to grow and improve your team, your company's data culture, and yourself.
Netflix is the definitive media company of the 21st century. It was among the first to parlay new Internet technologies into a successful business model, and in the process it changed how consumers access film and television. It is now one of the leading providers of digitally delivered media content and is continually expanding access across a host of platforms and mobile devices. Despite its transformative role, however, Netflix has drawn very little critical attention-far less than competitors such as YouTube, Apple, Amazon, Comcast, and HBO. This collection addresses this gap, as the essays are designed to critically explore the breadth and diversity of Netflix's effect from a variety of different scholarly perspectives, a necessary approach considering the hybrid nature of Netflix, its inextricable links to new models of media production, distribution, viewer engagement and consumer behavior, its relationship to existing media conglomerates and consumer electronics, its capabilities as a web-based service provider and data network, and its reliance on a broader technological infrastructure.
Business model innovations are conceived and implemented by a special type of entrepreneur: business model pioneers. This book presents 14 compelling case studies of business model pioneers and their companies, who have successfully introduced new business ideas to the market. The examples range from industries such as retail, media and entertainment to services and industrial projects. For each example, the book provides information on the market environment at the time of launch and illustrates the driving forces behind these business models. Moreover, current market developments are highlighted and linked to the evolution of the business models. Lastly, the authors present the profile of a typical business model pioneer.
On the surface, design practices and data science may not seem like obvious partners. But these disciplines actually work toward the same goal, helping designers and product managers understand users so they can craft elegant digital experiences. While data can enhance design, design can bring deeper meaning to data. This practical guide shows you how to conduct data-driven A/B testing for making design decisions on everything from small tweaks to large-scale UX concepts. Complete with real-world examples, this book shows you how to make data-driven design part of your product design workflow. Understand the relationship between data, business, and design Get a firm grounding in data, data types, and components of A/B testing Use an experimentation framework to define opportunities, formulate hypotheses, and test different options Create hypotheses that connect to key metrics and business goals Design proposed solutions for hypotheses that are most promising Interpret the results of an A/B test and determine your next move