Some question value of poll data

For an American public that relies on data for everything from where to find the best taco to the likely victor in a baseball game, Election Day offered a jarring wake-up: The data was wrong.

Many took the predictions of polling aggregators as gospel — and their forecasts of Hillary Clinton’s chances of winning the presidency went as high as 99 percent.

“Big data” has been a buzzword for the last decade in Silicon Valley. Investors and tech companies, from little-known startups to corporate giants, have poured billions of dollars into software and computer systems that promise to pore through mountains of information and glean useful insights into business trends or consumer behavior. David Dill, a computer science professor at Stanford University, said it has opened the door to do things that weren’t possible before. It enabled the collection of vast stockpiles of information all while advances in computing hardware and online networking have made it possible to run more sophisticated analytical programs and crunch bigger sets of data more quickly.

Even so, there’s plenty of hype and unreasonable expectations for what analytics can do.

“Even if you have a lot of data and you go after it with the most sophisticated, amazing techniques, it may not tell you anything or it may mislead, because the data doesn’t have the information you need,” Dill said.

Khalid Khan, who heads analytics at the management consulting firm A.T. Kearney, said people are being influenced by data points without fully understanding what those numbers represent. He encourages companies weighing the direction of data to also consider — and discuss — “the softer side of things.”

Speaking of data alone, he said: “If you take it at face value, you’re going to get burnt. Without those conversations, you’re only doing half of what you need to do when it comes to decision making.”