دانلود کتاب ترکیدن حباب کلان داده – موردی برای تصمیم گیری مبتنی بر شهود

Why a book on intuition-based decision making? Is it because a November 2012 research study at Tel Aviv University found that executives were 90% accurate in their decisions when relying on just their intuition? Is it because, according to Akinci and Sadler-Smith’s 2012 historical review of “Intuition in Management Research,” intuition research in management has been conducted since the 1930s and there continues to be a need for greater cross-disciplinary collaboration and integration? Or perhaps do we want to challenge the “Big Data” community to show, as evidenced by Woiceshyn’s 2009 research on how CEOs use intuition, that intuition should also be applied to complement rational analysis? Daniel Kahneman talked about the two systems (System 1 as intuition and System 2 as deliberative thinking) and their interaction. In Moxley et al.’s 2012 research on these two systems, their finding was that both experts and less-skilled individuals benefit significantly from extra deliberation no matter how easy or difficult the problem. This book is not meant to discount “rational thought,” or databased decision making, when making decisions, especially those that are important and complex. However, the contributors want to emphasize the importance of applying intuition, gut feel, spirituality, experiential learning, and insight as key factors in an executive’s decision-making process. An interesting question surfaces: When faced with conflicting opinions (i.e., one formed from data and analytics, and the other based on intuition), which one do you trust the most? For example, does a physician rely strictly on the evidence-based research and lab results in diagnosing a patient’s problem? Or does intuition have a key role to play? What are the legal implications if the physician decides to rely more on his or her intuition and experience, which may run counter to the medical data and lab results, even after repeating various lab tests? These are fascinating questions, especially as the big data revolution continues to unfold. In the 2012 movie, Trouble with the Curve, Gus, the experienced, older baseball scout (played by Clint Eastwood), who didn’t rely strictly on computer statistics but preferred to judge a player from the sound of a fly ball or from the grip on the bat, used his experiential learning and intuition to determine whether to draft a given baseball player. In the same movie, the younger scout, who favored judging a player by computer data analytics versus even watching the player on the field, made a call to draft a player as their number one pick, but Clint Eastwood thought otherwise and intuition won in this case (as the player couldn’t hit a curve ball, along with some fast balls). Sometimes, the old-fashioned method may be the way to go.