Analytics

The Agile Way

Phil Simon

• Editorial: Wiley
• Año: 2017
• ISBN:
  9781119424192
• Edición: 1
• Categoría: Business
• Categoría: Decision Making

For years, organizations have struggled to make sense out of their data. IT projects designed to provide employees with dashboards, KPIs, and business-intelligence tools often take a year or more to reach the finish line...if they get there at all.

This has always been a problem. Today, though, it's downright unacceptable. The world changes faster than ever. Speed has never been more important. By adhering to antiquated methods, firms lose the ability to see nascent trends—and act upon them until it's too late.

But what if the process of turning raw data into meaningful insights didn't have to be so painful, time-consuming, and frustrating?

What if there were a better way to do analytics?

Fortunately, you're in luck...

Analytics: The Agile Way is the eighth book from award-winning author and Arizona State University professor Phil Simon.

Analytics: The Agile Way demonstrates how progressive organizations such as Google, Nextdoor, and others approach analytics in a fundamentally different way. They are applying the same Agile techniques that software developers have employed for years. They have replaced large batches in favor of smaller ones...and their results will astonish you.

Through a series of case studies and examples, Analytics: The Agile Way demonstrates the benefits of this new analytics mind-set: superior access to information, quicker insights, and the ability to spot trends far ahead of your competitors.

PART ONE
Background and Trends

Part One sets the stage for the rest of the book. It provides foundations in data and analytics on which the other parts build.

This part contains the following chapters:

• Chapter 1: Signs of the Times: Why Data and Analytics Are Dominating Our World
• Chapter 2: The Fundamentals of Contemporary Data: A Primer on What It Is, Why It Matters, and How to Get It
• Chapter 3: The Fundamentals of Analytics: Peeling Back the Onion

CHAPTER 1
Signs of the Times
Why Data and Analytics Are Dominating Our World

Technology is eating the world.

—Marc Andreessen, August 20, 2011

On August 20, 2011, the ex-Netscape founder and current rock-star venture capitalist uttered these five words—perhaps the most telling and quoted words of the Internet age. In a nutshell, technology has spawned powerful new companies and industries and decimated others. It has led to revolutions, unprecedented wealth, and new social mores and change that many institutions and individuals are barely beginning to process.

I am in the privileged position to have lived through all of this; consequently, I can wax poetic about things to which students probably cannot relate. (In a few of my books, I have done just that.) Yes, I remember getting my first e-mail as a sophomore at Carnegie Mellon in 1991. (I was blown away.) I too once thought that entering your credit card information into a computer was downright weird. I recall telephone booths, answering machines, flip phones, primitive web browsers, search results that weren’t remotely accurate, when Napster was a thing, and nascent social networks such as Friendster that went down more often than they stayed up.

This is not a book about technology per se; it is a book about one of the most important consequences of ubiquitous technology: the explosion of data and the practice of analytics. Make no mistake: These are direct descendants of our tech-centric times. Absent the arrival of the World Wide Web, the smartphone explosion, cheap data storage, and the digitization of books, newspapers, songs, photos, and more, analytics and data wouldn’t be nearly as critical as they are today. This chapter looks at those trends.

THE MONEYBALL EFFECT

Billy Beane attained fame in baseball and analytics circles long before Brad Bitt portrayed him in the 2011 film Moneyball. In fact, Beane was making quite the name for himself even prior to Michael Lewis’s 2004 book of the same name.

It’s no overstatement to claim that as general manager of the small-market Oakland A’s, Beane changed the game of baseball forever. Big-market powerhouses such as the New York Yankees, Boston Red Sox, and Los Angeles Dodgers could effectively print their own money. Not Beane. He had to compete with a relatively paltry annual budget of roughly $60 million. That meant that he couldn’t even dream of chasing other teams’ pricey free agents. In fact, he had to let many of his own stars walk.^* Case in point: Beane had no shot of re-signing all-star first baseman Jason Giambi in 2001. The slugger and later admitted steroid user upped with the Yankees for nearly $120 million over seven years. Beane couldn’t justify spending nearly 30 percent of his budget on a single player—no matter how prolific.

Instead, Beane proved that necessity is the mother of invention. He famously plucked players off other teams’ scrap heaps, especially if they possessed odd skills. Player X can’t hit home runs? No problem. Can he frustrate opposing pitchers by being “a tough out”? Can he just get on base? Beane drafted players who “just didn’t look” like effective baseball players. His unorthodox methods angered many longtime Oakland scouts, men who had spent their careers watching players and developing a supposed eye for talent, not staring at spreadsheets. (The case study in Chapter 9 will have much more to say about resistance to analytics.)

You probably know how this story turns out. Would Michael Lewis write a book about you that turns into a movie starring Brad Pitt if you failed miserably? Pretty soon, even big-market teams such as the Yankees and Red Sox began hiring their own analytics experts, and later, teams of experts. The Moneyball movement spread beyond baseball to all other major sports. In fact, analytics are starting to move from the back room to the field. In their 2016 book The Only Rule Is It Has to Work: Our Wild Experiment Building a New Kind of Baseball Team, Ben Lindbergh and Sam...