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Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics

Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics

by Andrew Greasley

Paperback

$59.99
Available for Pre-Order. This item will be available on May 20, 2019

Product Details

ISBN-13: 9781547416745
Publisher: De|G Press
Publication date: 05/20/2019
Pages: 250
Product dimensions: 6.69(w) x 9.45(h) x (d)
Age Range: 18 Years

About the Author

Andrew Greasley lectures in Simulation Modeling and Operations Management at Aston Business School, Birmingham, UK. He has taught in the UK, Europe, and Africa for a number of institutions. Dr. Greasley has over 100 publications including five books (Operations Management, Wiley; Operations Management: Sage Course Companion, Sage; Simulation Modeling for Business, Ashgate; Business Information Systems, Pearson Education (co-author); and Enabling a Simulation Capability in the Organisation, Springer Verlag). He has provided a simulation modeling consultancy service for 30 years to a number of companies in the public and private sectors including ABB Transportation Ltd. (now Bombardier), Derbyshire Constabulary, GMT Hunslet Ltd., Golden Wonder Ltd., Hearth Woodcraft Ltd., Luxfer Gas Cylinders Ltd., Pall-Ex Holdings Ltd., Rolls Royce Ltd. (Industrial Power Group), Stanton Valves Ltd., Tecquipment Ltd., Textured Jersey Ltd. and Warwickshire Police.

Table of Contents

  1. Introduction to Process Simulation (10000)
  2. Introduction to Simulation in Business

    The 3 main types of Simulation – Process Simulation (Discrete Event Simulation), Agent Based Modeling and System Dynamics

    The History of Process Simulation

    Application Areas of Process Simulation

  3. Why is Process Simulation Needed for Analytics? (5000)
  4. Static (LP, Regression, Forecasting) vs. Dynamic (Process Simulation) Modeling

    Variability and Interdependence of Processes in Business Systems

    What-If vs Optimization of Processes with Analytics

    Analytics Performance Metrics – Speed, Cost, Dependability, Quality, Flexibility

  5. Enabling a Process Simulation Capability (5000)
  6. Selection of process simulation software and training needs

    Preparing a Process Simulation Proposal

  7. Undertaking a Process Simulation Study (25000)
  8. Data Collection

    Process mapping

    Input Modeling

    Building the Model

    Output Modeling

    The booking clerk: An illustrative example

  9. Process Simulation Case Studies (30000)
  10. Speed: Warwickshire Police Force

    Cost: Derbyshire Police Force

    Dependability: Pallex Ltd.

    Quality: Jinsheng Group Ltd.

    Flexibility: Golden Wonder Ltd.

  11. Challenges and the Future (15000)

Modeling People’s behavior

Incorporating Big Data

Servitization and Advanced Services