Peter C. Bell, Gregory S. Zaric

Analytics for Managers (eBook, PDF)

With Excel

• Format: PDF

Produktbeschreibung

Analytics is one of a number of terms which are used to describe a data-driven more scientific approach to management. Ability in analytics is an essential management skill: knowledge of data and analytics helps the manager to analyze decision situations, prevent problem situations from arising, identify new opportunities, and often enables many millions of dollars to be added to the bottom line for the organization.

The objective of this book is to introduce analytics from the perspective of the general manager of a corporation. Rather than examine the details or attempt an encyclopaedic review of the field, this text emphasizes the strategic role that analytics is playing in globally competitive corporations today.

The chapters of this book are organized in two main parts. The first part introduces a problem area and presents some basic analytical concepts that have been successfully used to address the problem area. The objective of this material is to provide the student, the manager of the future, with a general understanding of the tools and techniques used by the analyst.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 320
• Erscheinungstermin: 4. Januar 2013
• Englisch
• ISBN-13: 9781136255359
• Artikelnr.: 38246346

Autorenporträt

Peter C. Bell Professor

Peter C. Bell earned BA and MA degrees from Oxford University and MBA and PhD degrees from the Graduate School of Business, the University of Chicago, and is a Professor of Management Science at Ivey.

Gregory S. Zaric Associate Professor

Gregory Zaric earned a BSc degree from the University of Western Ontario, an MASc from the University of Waterloo, and MS and PhD degrees from Stanford University. He is an Associate Professor of Management Science at Ivey and holds a Canada Research Chair in Health Care Management Science.

Inhaltsangabe

Introduction: Analytics 1. An Introduction to Management Analytics 2.
Models and Model Building 3. Analyzing Sequential Decisions 4. Data Driven
Decision Making 5. Predictive Modelling 6. Simulating the Future 7.
Simultaneous Decision Problems 8. Revenue Management 9. Creating
Competitive Advantage Using Analytics