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To succeed in this world, you need to change your perspective on competition, growth, and leadership. In this book, strategy expert Ron Adner offers a new way of thinking, illustrating breakthrough ideas with compelling cases. How did a strategy of ecosystem defense save Wayfair and Spotify from being crushed by giants Amazon and Apple? How did Oprah Winfrey redraw industry boundaries to transition from television host to multimedia mogul? How did a shift to an alignment mindset enable Microsoft's cloud-based revival? Each was rooted in a new approach to competitors, partners, and  timing that you can apply to your own organization. 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In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning projects, aka predictive AI projects, from conception to deployment. He illustrates the practice with stories of success and of failure, including revealing case studies from UPS, FICO, and prominent dot-coms. This disciplined approach serves both sides: It empowers business professionals, and it establishes a sorely needed strategic framework for data professionals.  Beyond detailing the practice, this book also upskills business professionals—painlessly. It delivers a vital yet friendly dose of semi-technical background knowledge that all stakeholders need to lead or participate in machine learning projects, end to end. 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While Silicon Valley and Greater Boston are popularly known for web-based digital technology and biotechnology, respectively, the logic of innovation ecosystems is not solely American so this guide takes in new locations and varied sectors such as Singapore (smart cities), Perth (mining), Cairo and Dubai (fintech), London and Lagos (fintech and media), Copenhagen (quantum computing), Rio de Janeiro (energy), Halifax (oceans), and Tel Aviv (cybersecurity). Drawing practical advice from a synthesis of works on tech, innovation, entrepreneurship, and strategic management, and from a decade of their own research and teaching at the intersection of these topics, Budden and Murray distill insights and interconnections from all these different worlds into a useful and globally applicable set of frameworks and models. 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Most organizations view data monetization converting data into money too narrowly: as merely selling data sets. But data monetization is a core business activity for both commercial and noncommercial organizations, and, within organizations, it s critical to have wide-ranging support for this pursuit. In Data Is Everybody s Business, the authors offer a clear and engaging way for people across the entire organization to understand data monetization and make it happen. The authors identify three viable ways to convert data into money improving work with data, wrapping products with data, and selling information offerings and explain when to pursue each and how to succeed.   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