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The art of computer modeling for business analytics : paradigms and case studies / Gerald Feigin.

By: Material type: TextTextSeries: Publication details: New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press, (c)2016.Edition: First editionDescription: 1 online resource (xiv, 115 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781631573767
Subject(s): LOC classification:
  • HD30 .A786 2016
Online resources: Available additional physical forms:
Contents:
2. Assessing risk and opportunities of a manufacturing plant expansion -- 3. Scheduling semiconductor fabs -- 4. Rationalizing a distribution network for a chemical distributor -- 5. Identifying inventory and cycle time reduction opportunities for a steel manufacturer -- 6. Optimizing inventory distribution for a musical instrument rental company -- 7. Modeling for modeling's sake: a cautionary tale -- 8. Calculating price elasticity curves for a packaged vacation tourism company -- 9. Understanding the impact of variability through modeling -- 10. The limits of computer modeling -- Reference -- Index.
Abstract: In just about every sphere of business today, companies routinely utilize computer models to help make decisions. These models take many forms, from simple spreadsheets to sophisticated computer simulations. They may be bespoke models built for a specific company or they may be commercial software packages designed to be used by many different companies. They can be intended for one-time use to help decision makers think through a significant business decision or they can be tools designed for ongoing use within a company. They may be static or dynamic, deterministic or stochastic. This book is about constructing and using computer models to help decision makers in the business world make more informed decisions. It is intended to provide useful paradigms and case studies for individuals who are interested in building effective decision models--ones that will get used to drive important business decisions. The focus is on practice, not theory. In particular, the book does not focus on the underlying methods for building models--for example, how to construct a discrete event simulation, how to solve a linear program, or how to perform a multivariable linear regression.
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1. Introduction -- 2. Assessing risk and opportunities of a manufacturing plant expansion -- 3. Scheduling semiconductor fabs -- 4. Rationalizing a distribution network for a chemical distributor -- 5. Identifying inventory and cycle time reduction opportunities for a steel manufacturer -- 6. Optimizing inventory distribution for a musical instrument rental company -- 7. Modeling for modeling's sake: a cautionary tale -- 8. Calculating price elasticity curves for a packaged vacation tourism company -- 9. Understanding the impact of variability through modeling -- 10. The limits of computer modeling -- Reference -- Index.

In just about every sphere of business today, companies routinely utilize computer models to help make decisions. These models take many forms, from simple spreadsheets to sophisticated computer simulations. They may be bespoke models built for a specific company or they may be commercial software packages designed to be used by many different companies. They can be intended for one-time use to help decision makers think through a significant business decision or they can be tools designed for ongoing use within a company. They may be static or dynamic, deterministic or stochastic. This book is about constructing and using computer models to help decision makers in the business world make more informed decisions. It is intended to provide useful paradigms and case studies for individuals who are interested in building effective decision models--ones that will get used to drive important business decisions. The focus is on practice, not theory. In particular, the book does not focus on the underlying methods for building models--for example, how to construct a discrete event simulation, how to solve a linear program, or how to perform a multivariable linear regression.

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