Behind Every Good Decision: How Anyone Can Use Business Analytics to Turn Data into Profitable Insight

Behind Every Good Decision: How Anyone Can Use Business Analytics to Turn Data into Profitable Insight

Behind Every Good Decision: How Anyone Can Use Business Analytics to Turn Data into Profitable Insight

Behind Every Good Decision: How Anyone Can Use Business Analytics to Turn Data into Profitable Insight

Synopsis

There is a costly misconception in business today- that the only data that matters is BIG data, and that complex tools and data scientists are required to extract any practical information. Nothing could be further from the truth.

In Behind Every Good Decision, authors and analytics experts Piyanka Jain and Puneet Sharma demonstrate how professionals at any level can take the information at their disposal and leverage it to make better decisions. The authors' streamlined frame work demystifies the process of business analytics and helps anyone move from data to decisions in just five steps…using only Excel as a tool. Readers will learn how to:

Clarify the business question • Lay out a hypothesis-driven plan • Pull relevant data • Convert it to insights • Make decisions that make an impact

Packed with examples and exercises, this refreshingly accessible book explains the four fundamental analytic techniques that can help solve a surprising 80% of all business problems. Business analytics isn't rocket science- it's a simple problem-solving tool that can help companies increase revenue, decrease costs, improve products, and delight customers. And who doesn't want to do that?

Excerpt

PIYANKA:

I hate statistics. What I really wanted to do in 1999, in an environmental engineering thesis at Texas A&M University, was to track events that caused a hazardous waste site to be, well, hazardous. While researching in the lab, I was frankly mortified as it became clear to me that the only way I could solve this was by building an inverse speciation model using nonlinear regression.

I have always loved numbers and math—having derived the Pythagorean theorem in my own fashion four years too early for my grade. I have always questioned the impact of every engineering feat, including my dad’s breakthrough “waste-to-energy” invention. Math and engineering define me for what I am today, but in 1999, I worked to make sure that statistics could not only analyze a problem, but solve it, and have true tangible business impact. I had befriended the enemy, and found my passion.

For a second master’s degree in computer engineering at the University of Minnesota, statistical modeling and simulation helped me design a self-updating network routing table using the concept of ant pheromones. I taught calculus and statistics to third- and fourth-year undergraduates. I now felt empowered to solve different types of problems with statistics and analytics.

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.