The ability to look critically at data and assess its validity is a vital managerial skill. when decision makers are presented with wrong data, the results can be disastrous. and these problems can get amplified if bad data is fed to automated systems. as an example, look at the series of man-made and computer-triggered events that brought about a billion-dollar collapse in united airlines stock. in the wee hours one sunday morning in september 2008, a single reader browsing back stories on the orlando sentinel's web site viewed a 2002 article on the bankruptcy of united airlines (ual went bankrupt in 2002, but emerged from bankruptcy four years later). that lone web surfer's access of this story during such a low-traffic time was enough for the sentinel's web server to briefly list the article as one of the paper's "most popular." google crawled the site and picked up this "popular" news item, feeding it into google news. early that morning, a worker in a florida investment firm came across the google-fed story, assumed united had yet again filed for bankruptcy, then posted a summary on bloomberg. investors scanning bloomberg jumped on what looked like a reputable early warning of another united bankruptcy, dumping ual stock. blame the computers again—the rapid plunge from these early trades caused automatic sell systems to kick in (event-triggered, computer-automated trading is responsible for about 30 percent of all stock trades). once the machines took over, ual dropped like a rock, falling from twelve to three dollars. that drop represented the vanishing of $1 billion in wealth, and all this because no one checked the date on a news story. welcome to the new world of paying attention (harvey, 2008)!