Reinventing Jobs

A 4-Step Approach for Applying Automation to Work
 
 
Harvard Business Review Press
  • erscheint ca. am 9. Oktober 2018
 
  • Buch
  • |
  • Hardcover
  • |
  • 256 Seiten
978-1-63369-407-1 (ISBN)
 
Once the decision has been made to adopt automation and artificial intelligence technologies, leaders face difficult and stubborn questions about how to implement that decision: How, when, and where should we apply automation in our organizations? Is it a stark choice between humans versus machines? How do we stay on top of these technological trends as work and automation continue to evolve?Work and human capital experts Ravin Jesuthasan and John Boudreau argue that leaders need a new set of tools to answer these daunting questions. Going beyond traditional concepts like a "job," Jesuthasan and Boudreau show leaders that automation calls for a reexamination of what a job really is and show how to determine variations of tasks within jobs and then reconstruct those elements into new and different combinations. Furthermore, transcending the endless debate about humans being replaced by machines, the authors show how smart leaders instead are optimizing human-automation combinations that are not only more efficient but generate higher returns on improved performance.Based on groundbreaking primary research, this book provides an original, structured approach and a new set of tools for applying automation and artificial intelligence in your organization. Jesuthasan and Boudreau provide a practical four-step framework--deconstruct, optimize, automate, and reconfigure--through which you and others throughout your organization can collaborate to proactively and continuously "reconstruct" work and create optimal human-machine combinations.With numerous examples of companies that are redefining jobs and work through human-automation combinations and a real-world guide for applying the practical four-step process, Reinventing Jobs gives leaders a more precise, systematic, and actionable way to decide how, when, and where to apply automation.
  • Englisch
  • USA
  • Gewebe-Einband
  • Höhe: 235 mm
  • |
  • Breite: 156 mm
978-1-63369-407-1 (9781633694071)
1633694070 (1633694070)
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Ravin Jesuthasan is Managing Director at Willis Towers Watson and a recognized global thought leader on the future of work, human capital, and the automation of work. He is a regular participant and presenter at the World Economic Forum's annual meeting in Davos and a member of the forum's Steering Committee on Work and Employment. He has also been featured extensively by leading business media including CNN, CNBC, the Financial Times, the Nikkei (Japan), Les Echos (France), Valor Economico (Brazil), and the South China Morning Post. He has been recognized as one of the top 25 most influential consultants in the world. He is the author of Transformative HR: How Great Companies Use Evidence-Based Change for Sustainable Advantage and Lead the Work: Navigating a World Beyond Employment and has authored more than fifty articles, including seven for Harvard Business Review.John Boudreau is a professor and Research Director at the University of Southern California's Marshall School of Business and Center for Effective Organizations. For more than thirty years he has been recognized globally for breakthrough research on the bridge between superior human capital, talent, and sustainable success. He studies, consults, and develops executives in companies worldwide that seek to maximize work effectiveness by discovering the specific strategic bottom-line impact of superior people and human capital strategies. He has more than 200 publications and has won scholarly and professional achievement awards. He is a fellow of leading research and professional associations. His work is frequently featured in Harvard Business Review, The Wall Street Journal, Fortune, Fast Company, BusinessWeek, Talent Management, CFO.com, and NPR, among others.Author social media/website info:@ravinjesuthasan, willistowerswatson.com@JohnWBoudreau, ceo.usc.edu, drjohnboudreau.com/

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