Handbook of Integrated Risk Management for E-Business: Measuring, Modeling, and Managing Risk

By: 
Abderrahim Labbi, ed.
Published: 
2005
Pages: 
318
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Book Description

This ground-breaking professional reference integrates converging views of e-business processes and offers ways to manage their inherent risks with advanced modeling techniques. Contributors from leading academic and business organizations explore state-of-the-art adaptive risk analysis systems that support business processes in project portfolio management, operations management, supply chain management, inventory control, data mining for customer relationship management, information technology security, finance, e-banking, and more.

Today’s new business environments are characterized by increasing sources of uncertainty and variability which challenge current decision-making processes. Handbook of Integrated Risk Management for E-Business: Measuring, Modeling, and Managing Risk provides a roadmap for identifying and mitigating the primary risks associated with each critical e-business process. It also shows you how to transform your processes by empowering decision-making systems and how to design appropriate risk management systems for decision support.

Key Features:

  • Presents an integrated view of the main e-business processes, the different challenges and opportunities underlying these processes, and how to manage them under uncertainty using predictive models

     

  • Discusses the value of effective decision support system tools for preemptive management and for gaining a competitive advantage
  • Supplies real-world case studies illustrating advanced predictive modeling methodologies and the latest technologies for managing the risks inherent in e-business processes
  • Provides a blueprint for identifying and mitigating the primary risks associated with each critical e-business process and shows how to design appropriate risk management systems for decision support
  • Explains how to use boosting to identify and prioritize risk

Member Reviews: 

Review By: Karin Hodyl
07/09/2010

This handbook integrates different views of e-business processes and offers ways to manage business risks using complex formulas and predictive models. The book's content comes from twenty-three contributors from different academic and business organizations (fifteen are IBMers, three are from University-background, and five are from business/industry). Mainly, this reference book explores adaptive risk-analysis systems that support business processes across industries, but more specifically in these sectors: project portfolio management, finance, operations management, supply chain management, inventory control, and customer relationship management.

The book is written very logically, albeit very dry. It does pose to the reader the different challenges and opportunities underlying business processes and their risks, as well as how to manage them under uncertainty. Uncertainty is a key value (i.e., beta) in many of the formulas and models. Often historical performance figures are used to predict future outcomes.

This book isn’t targeted towards QA or testing folks, but rather executive-level or management associates who control or manage risk. It provides them with a roadmap for identifying and mitigating the risks associated with the various critical e-business processes. It even goes so far as to explain how to design the appropriate risk management systems for decision support. The handbook is great for management and for gaining a competitive advantage in this area of managing risk.

Although the delivery method is complicated at times (some formulas having over nine variables), the book does a good job in making the reader understand what is needed to calculate the optimal solution. The algorithms and frameworks are explained in depth, and the various real-world examples are meaningful and elaborate.

Even though the content of this book is geared toward business associates (versus technical employees), all parts of the organization (testing, QA, management, etc.) can use it to learn how to identify and prioritize risk. Testing folks who also design risk management or decision support systems can use it to better understand their applications. By understanding that risk is always out there and managing it, many people can improve their work.

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