But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool.In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling.Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics.

    Dozens of examples in innumeracy show us how it affects not only personal economics and travel plans, but explains mis-chosen mates, inappropriate drug-testing, and the allure of pseudo-science.

    Along the way we’ll learn how selection bias can explain why your boss doesn’t know he sucks (even when everyone else does); how to use Bayes’ Theorem to decide if your partner is cheating on you; and why Mark Zuckerberg should never be used as an example for anything. See the world in a whole new light, and make better decisions and judgements without ever going near a t-test. Think. Think Statistically.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    This entertaining guide builds on scores of case studies taken from business, sports, the movies, politics, and gambling. It outlines the basics of good strategy making and then shows how you can apply them in any area of your life.

    But many managers can't read a balance sheet, wouldn't recognize a liquidity ratio, and don't know how to calculate return on investment. Worse, they don't have any idea where the numbers come from or how reliable they really are. In Financial Intelligence, Karen Berman and Joe Knight teach the basics of finance--but with a twist. Financial reporting, they argue, is as much art as science. Because nobody can quantify everything, accountants always rely on estimates, assumptions, and judgment calls. Savvy managers need to know how those sources of possible bias can affect the financials and that sometimes the numbers can be challenged. While providing the foundation for a deep understanding of the financial side of business, the book also arms managers with practical strategies for improving their companies' performance--strategies, such as "managing the balance sheet," that are well understood by financial professionals but rarely shared with their nonfinancial colleagues. Accessible, jargon-free, and filled with entertaining stories of real companies, Financial Intelligence gives nonfinancial managers the financial knowledge and confidence for their everyday work. Karen Berman and Joe Knight are the owners of the Los Angeles-based Business Literacy Institute and have trained tens of thousands of managers at many leading organizations. Co-author John Case has written several popular books on management.

    But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models—from linear regression to random walks and far beyond—that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.

      Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

    One was mathematician Claude Shannon, neurotic father of our digital age, whose genius is ranked with Einstein's. The other was John L. Kelly Jr., a Texas-born, gun-toting physicist. Together they applied the science of information theory—the basis of computers and the Internet—to the problem of making as much money as possible, as fast as possible.Shannon and MIT mathematician Edward O. Thorp took the "Kelly formula" to Las Vegas. It worked. They realized that there was even more money to be made in the stock market. Thorp used the Kelly system with his phenomenonally successful hedge fund, Princeton-Newport Partners. Shannon became a successful investor, too, topping even Warren Buffett's rate of return. Fortune's Formula traces how the Kelly formula sparked controversy even as it made fortunes at racetracks, casinos, and trading desks. It reveals the dark side of this alluring scheme, which is founded on exploiting an insider's edge.Shannon believed it was possible for a smart investor to beat the market—and Fortune's Formula will convince you that he was right.

    Rather than a "how to" for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques.You have been predicted — by companies, governments, law enforcement, hospitals, and universities. Their computers say, "I knew you were going to do that!" These institutions are seizing upon the power to predict whether you're going to click, buy, lie, or die.Why? For good reason: predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales.How? Prediction is powered by the world's most potent, booming unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn.Predictive analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future — lifting a bit of the fog off our hazy view of tomorrow — means pay dirt.In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: -What type of mortgage risk Chase Bank predicted before the recession. -Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves. -Why early retirement decreases life expectancy and vegetarians miss fewer flights. -Five reasons why organizations predict death, including one health insurance company. -How U.S. Bank, European wireless carrier Telenor, and Obama's 2012 campaign calculated the way to most strongly influence each individual. -How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! -How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. -How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free. -What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia. A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.Predictive analytics transcends human perception. This book's final chapter answers the riddle: What often happens to you that cannot be witnessed, and that you can't even be sure has happened afterward — but that can be predicted in advance?Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.

    Richard Rumelt shows that there has been a growing and unfortunate tendency to equate Mom-and-apple-pie values, fluffy packages of buzzwords, motivational slogans, and financial goals with “strategy.” He debunks these elements of “bad strategy” and awakens an understanding of the power of a “good strategy.” A good strategy is a specific and coherent response to—and approach for overcoming—the obstacles to progress. A good strategy works by harnessing and applying power where it will have the greatest effect in challenges as varied as putting a man on the moon, fighting a war, launching a new product, responding to changing market dynamics, starting a charter school, or setting up a government program. Rumelt’snine sources of power—ranging from using leverage to effectively focusing on growth—are eye-opening yet pragmatic tools that can be put to work on Monday morning.Surprisingly, a good strategy is often unexpected because most organizations don’t have one. Instead, they have “visions,” mistake financial goals for strategy,and pursue a “dog’s dinner” of conflicting policies and actions.Rumelt argues that the heart of a good strategy is insight—into the true nature of the situation, into the hidden power in a situation, and into an appropriate response. He shows you how insight can be cultivated with a wide variety of tools for guiding yourown thinking.Good Strategy/Bad Strategy uses fascinating examples from business, nonprofit, and military affairs to bring its original and pragmatic ideas to life. The detailed examples range from Apple to General Motors, from the two Iraq wars to Afghanistan, from a small local market to Wal-Mart, from Nvidia to Silicon Graphics, from the Getty Trust to the Los Angeles Unified School District, from Cisco Systems to Paccar, and from Global Crossing to the 2007–08 financial crisis.Reflecting an astonishing grasp and integration of economics, finance, technology, history, and the brilliance and foibles of the human character, Good Strategy/Bad Strategy stems from Rumelt’s decades of digging beyond the superficial to address hard questions with honesty and integrity.From the Hardcover edition.

    

    In a brilliant and unconventional book, Phil Rosenzweig unmasks the delusions that are commonly found in the corporate world. These delusions affect the business press and academic research, as well as many bestselling books that promise to reveal the secrets of success or the path to greatness. Such books claim to be based on rigorous thinking, but operate mainly at the level of storytelling. They provide comfort and inspiration, but deceive managers about the true nature of business success.The most pervasive delusion is the Halo Effect. When a company's sales and profits are up, people often conclude that it has a brilliant strategy, a visionary leader, capable employees, and a superb corporate culture. When performance falters, they conclude that the strategy was wrong, the leader became arrogant, the people were complacent, and the culture was stagnant. In fact, little may have changed -- company performance creates a Halo that shapes the way we perceive strategy, leadership, people, culture, and more.Drawing on examples from leading companies including Cisco Systems, IBM, Nokia, and ABB, Rosenzweig shows how the Halo Effect is widespread, undermining the usefulness of business bestsellers from "In Search of Excellence" to "Built to Last" and "Good to Great."Rosenzweig identifies nine popular business delusions. Among them:"The Delusion of Absolute Performance: " Company performance is relative to competition, not absolute, which is why following a formula can never guarantee results. Success comes from doing things better than rivals, which means that managers have to take risks."The Delusion of Rigorous Research: " Many bestselling authors praise themselves for the vast amount of data they have gathered, but forget that if the data aren't valid, it doesn't matter how much was gathered or how sophisticated the research methods appear to be. They trick the reader by substituting sizzle for substance."The Delusion of Single Explanations: " Many studies show that a particular factor, such as corporate culture or social responsibility or customer focus, leads to improved performance. But since many of these factors are highly correlated, the effect of each one is usually less than suggested.In what promises to be a landmark book, "The Halo Effect" replaces mistaken thinking with a sharper understanding of what drives business success and failure. "The Halo Effect" is a guide for the thinking manager, a way to detect errors in business research and to reach a clearer understanding of what drives business success and failure.Skeptical, brilliant, iconoclastic, and mercifully free of business jargon, Rosenzweig's book is nevertheless dead serious, making his arguments about important issues in an unsparing and direct way that will appeal to a broad business audience. For managers who want to separate fact from fiction in the world of business, "The Halo Effect" is essential reading -- witty, often funny, and sharply argued, it's an antidote to so much of the conventional thinking that clutters business bookshelves.

    To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok.In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information (Alan Turing's role in breaking Germany's Enigma code during World War II), and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security.Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.

    System 1 is fast, intuitive, and emotional; System 2 is slower, more deliberative, and more logical. Kahneman exposes the extraordinary capabilities—and also the faults and biases—of fast thinking, and reveals the pervasive influence of intuitive impressions on our thoughts and behavior. The impact of loss aversion and overconfidence on corporate strategies, the difficulties of predicting what will make us happy in the future, the challenges of properly framing risks at work and at home, the profound effect of cognitive biases on everything from playing the stock market to planning the next vacation—each of these can be understood only by knowing how the two systems work together to shape our judgments and decisions.Engaging the reader in a lively conversation about how we think, Kahneman reveals where we can and cannot trust our intuitions and how we can tap into the benefits of slow thinking. He offers practical and enlightening insights into how choices are made in both our business and our personal lives—and how we can use different techniques to guard against the mental glitches that often get us into trouble. Thinking, Fast and Slow will transform the way you think about thinking.