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Big Data - a Management Revolution

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First, they can get in the habit of asking “What do the data say?” when faced with an important decision and following up with more-specific questions such as “Where did the data come from?,” “What kinds of analyses were conducted?,” and “How confident are we in the results?” (People will get the message quickly if executives develop this discipline.) Second, they can allow themselves to be overruled by the data; few things are more powerful for changing a decision-making culture than seeing a senior executive concede when data have disproved a hunch.

We just have more data.” HOW DATA-DRIVEN COMPANIES PERFORM The second question skeptics might pose is this: “Where’s the evidence that using big data intelligently will improve business performance?” The business press is rife with anecdotes and case studies that supposedly demonstrate the value of being data-driven.  We’ve seen big data used in supply chain management to understand why a carmaker’s defect rate in the field suddenly increased, in customer service to continually scan and intervene in the health care practices of millions of people, in planning and forecasting to better anticipate online sales on the basis of a data set of product characteristics, and so on.

We conducted structured interviews with executives at 330 public North American companies about their organization and technology management practices, and gathered performance data from their annual reports and independent sources.  They can only give you answers.” FIVE MANAGEMENT CHALLENGES Companies won’t reap the full benefits of a transition to using big data unless they’re able to manage change effectively.

WHAT’S NEW HERE? Business executives sometimes ask us, “Isn’t ‘big data’ just another way of saying ‘analytics’?” It’s true that they’re related: The big data movement, like analytics before it, seeks to glean intelligence from data and translate that into business advantage.  SPEEDIER, MORE PERSONALIZED PROMOTIONS A couple of years ago, Sears Holdings came to the conclusion that it needed to generate greater value from the huge amounts of customer, product, and promotion data it collected from its Sears, Craftsman, and Lands’ End brands.

When data are scarce, expensive to obtain, or not available in digital form, it makes sense to let well-placed people make decisions, which they do on the basis of experience they’ve built up and patterns and relationships they’ve observed and internalized.  Because skills and knowledge related to new data technologies were so rare in 2010, when Sears started the transition, it contracted some of the work to a company called Cloudera.  The PASSUR and Sears Holding examples illustrate the power of big data, which allows more-accurate predictions, better decisions, and precise interventions, and can enable these things at seemingly limitless scale.  It calculated these times by combining publicly available data about weather, flight schedules, and other factors with proprietary data the company itself collected, including feeds from a network of passive radar stations it had installed near airports to gather data about every plane in the local sky.  

Too often, we saw executives who spiced up their reports with lots of data that supported decisions they had already made using the traditional HiPPO approach.  For instance, our colleague Alex “Sandy” Pentland and his group at the MIT Media Lab used location data from mobile phones to infer how many people were in Macy’s parking lots on Black Friday — the start of the Christmas shopping season in the United States.  The best data scientists are also comfortable speaking the language of business and helping leaders reformulate their challenges in ways that big data can tackle.  Many in the big data community maintain that companies often make most of their important decisions by relying on “HiPPO” — the highest-paid person’s opinion.  Obviously, it would be valuable to combine and make use of all these data to tailor promotions and other offerings to customers, and to personalize the offers to take advantage of local conditions.  What’s more, the company keeps all the data it has gathered over time, so it has an immense body of multidimensional information spanning more than a decade.

A NEW CULTURE OF DECISION MAKING The technical challenges of using big data are very real.  Simply put, because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved decision making and performance.  The same holds for smartphones and the other mobile devices that now provide enormous streams of data tied to people, activities, and locations.  Some of the most

crucial of these are data scientists and other professionals skilled at working with large quantities of information.  Analytics brought rigorous techniques to decision making; big data is at once simpler and more powerful.  As the tools and philosophies of big data spread, they will change long-standing ideas about the value of experience, the nature of expertise, and the practice of management


The article introduces Big Data and states how likely it is to revolutionize management. Having fluency in Big Data, managers can better understand their businesses and maximize overall company and employee performance. The article mentions several reasons how Big Data impacts businesses. An advantage of why getting a solid understanding of how Big Data works is towards improving predictions and analytics. This described advantage provides insight and an example regarding the airline industry, predicting ETAs (Estimated Time of Arrival) and PASSUR Aerospace, a provider of decision-support technologies for the aviation industry. Another advantage that Big Data has towards businesses is its impact towards the increase of Exabytes of data that continues to double. This provides an advantage to the company towards being able to work with many petabytes of data in a single data set.



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