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Data-Based Decision Making and Digital Transformation

  • E-Book (epub)
  • 106 Seiten
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Digital disruption is accelerating. Implementing a successful digital transformation strategy requires that senior managers make ... Weiterlesen
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Beschreibung

Digital disruption is accelerating. Implementing a successful digital transformation strategy requires that senior managers make trade-off decisions to reinvent a business. Equally important all decision makers must learn to ask the right questions, use data and computer support in decision making, and increase their knowledge and skills. Creating a data-centric culture and rewarding data-based decision making leads to successful digital transformation. Join the digital journey. This book is targeted at managers, especially middle-level managers who are trying to come to grips with using data-based decision making in a transforming organization. The authors explore a number of broad questions including: How can managers become data-based decision makers? How can digital transformation become part of an organi­zational strategy? What new skills do managers need to implement digital transformation? How will we know an organization has been successfully transformed?



Autorentext

Dr. Daniel J. Power is professor of information systems at the College of Business Administration, University of Northern Iowa, Cedar Falls, Iowa. He has published more than 80 articles/chapters/papers, and five books. Power was the founding chair of the Association for Information Systems interest group on decision support and analytics (SIG DSA). From his vantage point as editor of DSSResources.COM and Decision Support (DSS) News, a bi-weekly e-newsletter, he tracks a broad range of contemporary analytics and decision support topics.

Produktinformationen

Titel: Data-Based Decision Making and Digital Transformation
Untertitel: Nine Laws for Success
Autor:
EAN: 9781631576591
Digitaler Kopierschutz: Adobe-DRM
Format: E-Book (epub)
Hersteller: Business Expert Press
Genre: Wirtschaft
Anzahl Seiten: 106
Veröffentlichung: 31.05.2018
Dateigrösse: 1.3 MB
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