From Beer To Derivatives: The Evolution Of Analytics In Business

$ 4.07

by David J. Fogarty (Author)

ISBN Number :978 – 1- 73042 – 804 – 3

SKU: SBP_1553 Category:


David J. Fogarty

Faculty Member University of Liverpool, University of Phoenix, Trident University and Columbia University in the City of New York

I was inspired to write this book after serving as a contributing author leading to a book title â€�Analytics at Workâ€� where my friends and authors Professor Thomas Davenport, Jeanne Harris and Robert Morrison revealed how all managers can effectively deploy analytics in their day-to-day operations – one business decision at a time. The authors showed from the research which I participated in how many types of analytical tools, from statistical analysis to qualitative measures like systematic behavior coding, can improve decisions about everything from what new product offerings might interest customers to whether marketing dollars are being most effectively deployed. In their previous book. â€�Competing on Analyticsâ€�, Davenport and Harris showed how pioneering ï��rms were building their entire strategies around their analytical capabilities. Rather than â€�going with their gutâ€� when pricing products, maintaining inventory, or hiring talent they showed that managers in these ï��rms use data, analysis and systematic reasoning to make decisions that improve efï��ciency, risk management and proï��ts. Davenport also wrote a follow-up article in the Harvard Business Review on doing proper experiments in business as I also used as inspiration for this book. Firms which do more experimentation instead of reacting and using too much gut feel can really make the continuous improvements which are required by their shareholders. Many managers fail to get this point. If the organization has a culture of testing then it will anticipate changes in the marketplace and test out possible scenarios. At GE Money I was responsible for testing and the goal was to not only increase the number of tests we do every year but also to measure the number of challengers we converted into true champions. Of course the drawback of this strategy is that if managers are concerned with champions turning to challengers then we may not be taking enough risks. However, being GE we wanted to have measurable results of our ability to execute! At GE Money we would do about 5000 test per year and our challengers which eventually were turned into champions was > 25%. Of course, no testing in the world could have predicted the global ï��nancial crisis which eventually curbed GE Money’s annual double-digit growth rates.