Analytics & Performance

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Can Sensors Fuel Productivity Growth?

The Internet Revolution has so far not produced the kind of long-term productivity growth seen during the Industrial Revolution. Digital technology drove U.S. productivity growth above three percent annually only between 1996 and 2004. Since then, productivity has fallen to about 1.6 percent a year. General Electric argues that productivity growth will jump again as the industrial Internet emerges, connecting machines like turbines and jet engines to factories, and using analytics to make better decisions about maintenance and production.


Video: Big Data and Analytics Right Now

Erik Brynjolfsson, director of the MIT Center for Digital Business, talks about the big data revolution with Tom Davenport, who helped get that revolution started with his seminal article “Competing on Analytics.” Their discussion illuminates what’s different about big data and how big data is changing management and the way businesses run.


Business Quandary? Use a Competition to Crowdsource Best Answers

Top data scientists often share three characteristics: they are creative, they are curious and they are competitive. Anthony Goldbloom, CEO of Kaggle, a company that hosts data prediction competitions, has figured out how to tap all three of these characteristics to help companies crowdsource their analytics problems.

Veronika Belokhvostova, head of Global Business Analytics at PayPal.

Mining Data at PayPal to Guide Business Strategy

“The kind of people we hire want to know that their work is not gathering dust on some shelf, but has a real impact on the company,” says Veronika Belokhvostova, head of Global Business Analytics at PayPal. And indeed, business analysts there are collaborating with business leaders to answer the “what should we do next?” question.

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Innovating With Analytics

A data and analytics survey conducted by MIT Sloan Management Review in partnership with SAS Institute Inc. found a strong correlation between the value companies say they generate using analytics and the amount of data they use. The creators of the survey identified five levels of analytics sophistication, with those at Level 5 being most sophisticated and innovative. These analytical innovators in Level 5 had several defining traits. This article explores those traits.


Image courtesy of IBM.

Winning the Race With Ever-Smarter Machines

The capabilities of computers are now improving so quickly that concepts can move from the realm of science fiction into everyday life in just a few years, rather than a lifetime. Rapid advances in information technology — computer hardware, software and networks — are yielding applications that can do anything from answering game show questions to driving cars. But to gain true leverage from these ever-improving technologies, companies need new processes and business models.



Analytics: The Widening Divide

In this second joint MIT Sloan Management Review and IBM Institute for Business Value study, we see a growing divide between those companies that, on one side, see the value of business analytics and are transforming themselves to take advantage of these newfound opportunities, and those, on the other, that have yet to embrace them.

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Tim Harford on Trial, Error and Our "God Complex"

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Financial Times journalist Tim Harford and author of “Adapt: Why Success Always Starts With Failure” argues that companies that have a God complex look for smart people (what he calls “little Gods”) to solve complex problems — when what they should really be doing is establishing systematic processes of trial and error.


How Fast and Flexible Do You Want Your Information, Really?

Almost all executives want more and faster information, and almost all companies are racing to provide it. What many of them overlook, though, is that the real aim should be not faster information but faster decision making — and those aren’t the same things. "Few organizations have reached an optimum with regard to how fast important information reaches in boxes, desks and brains," write the authors. "Decision makers can digest only so much information, and only so fast."



Improve Data Quality for Competitive Advantage

ERRORS IN DATA CAN COST A COMPANY MILLIONS OF DOLLARS, ALIENATE CUSTOMERS, AND MAKE IMPLEMENTING NEW STRATEGIES DIFFICULT OR IMPOSSIBLE. The author describes a process AT&T uses to recognize poor data and improve their quality. He proposes a three-step method for identifying data-quality problems, treating data as an asset, and applying quality systems to the processes that create data.

Showing 21-39 of 39