- Research Feature
- Read Time: 19 min
Our new survey suggests that companies experienced in analytics use are increasingly gaining competitive advantage — but their approaches vary.
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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.
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.
Regular readers of MIT Sloan Management Review will recognize the name Gary Loveman.
Loveman earned a Ph.D. in economics at MIT and went on to become CEO, president, and chairman of Caesars Entertainment, owner of Harrah's casinos and other resorts worldwide.
How the smartest organizations are embedding analytics to transform information into insight and then action. Findings and recommendations from the first annual New Intelligent Enterprise Global Executive study.
I was in a meeting in Dallas when I looked out the window to see dark clouds on the horizon. Armed with my laptop, I monitored the storms around Dallas on weather.com, checked delays at Dallas/Fort Worth International Airport at dfwairport.com, and clicked over to flightstats.c
Electronic information can easily overwhelm people with large volumes of data. An abundance of information often strains human limits: attention, memory, motivation or other factors. In response to this challenge, software that assists humans in filtering and organizing information into more digestible amounts and formats have appeared (Alba et al.,
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.
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