Book Image

Analytics: How to Win with Intelligence

By : John Thompson, Shawn P. Rogers
Book Image

Analytics: How to Win with Intelligence

By: John Thompson, Shawn P. Rogers

Overview of this book

Today, business is moving into an era where information is more valuable than services. Organizations that connect information with their products will have a huge advantage. This book helps people understand the power of data analytics and explains how some of the tools available can be applied to a wide range of applications. It begins with a brief history of analytics and explains how it all began. You'll learn about several common analytical approaches and the tools that data scientists use to analyze data. You'll gain insight into some staffing models, technologies, organizational structures, and analytical approaches used in the previous two eras of analytics. As you progress through the chapters, you'll also get a glimpse into the future of the analytical marketplace. After reading this book, you will be able to help your team deploy analytical elements into your operations and become competitive in your business.
Table of Contents (11 chapters)
Free Chapter
1
Foreword by Tom Davenport

Financial services

Like the marketing and sales function, the financial operations of a company can also benefit greatly from the use of advanced analytics. As it turns out, very sophisticated tools and techniques in this area have already been developed by the financial services industry. Consider just one function of the finance department of many companies: assessing the credit-worthiness of customers.

The granting of credit in the consumer, industrial, institutional, and governmental environments is a crucial part of the global economy. All players in these markets need to understand the risks that they are undertaking, as well as the financial profiles and histories of the entities to whom they are considering offering credit-based deals. Every organization that grants credit to another party must have a threshold or limit at which they draw the line on risk. For automobile loans, that threshold could be based on a person’s credit history or credit score, income level...