We live in a time when there is incredible bias toward data. Companies create goals for employees and force them to say that they are “35 percent complete” halfway through the year, which usually indicates no progress has been made. Cost-cutters measure the price of office space per square foot and ignore commuting impacts on performance that result from consolidating offices. Put simply, for many firms, if you can’t measure it, it doesn’t exist. That’s Moneyball taken too far.

Sales managers have known for years that the occasional free football ticket or pricey steak dinner is key to closing big sales. But which steak dinner got the signature on the check? No one knows. But everyone knows that if there’s no steak dinner, there’s no sale. How do you measure good will? Trust? Loyalty? These qualities are the backbone of any successful venture, but they have taken a severe hit during a time when many seem to hold measurement above all else. This is foolish, especially when data itself is often the problem. As you’ve no doubt heard many times, there’s lies, damn lies, and then there’s statistics.

What matters most, your best-selling product during the past month, or your best-selling product during the past year? Who really has the most watched show on television, the program with the most family sets turned on, the show with the most adults who are 25-54, or the show whose viewers have the highest per capita income? It all depends on what story you are trying to tell. Data can go very bad, very quickly, if you don’t watch it carefully. And in the hands of manipulative people, it can be used for pure evil.

One data crisis arises from something called conformance metrics, which simply means that companies tend to measure the exact same things that other companies measure, because that is the only thing their tools are built to do. It’s a bit like a game of copycat, and a bit like anchoring. For years, Web sites published the number of “hits” they received, some bragging they’d been “hit” a billion times in a month. Ultimately, advertisers soured on this measurement because it had many flaws, like this one: hits could represent the same person refreshing the same page over and over again. Next, unique visitors became the standard, with the thought that advertisers really wanted to get their material in front of as many people as possible. So all sites started bragging about visitors and doing all they could to amass as many visitors as possible. But “Wait!” advertisers said soon. “Throwing ads at random millions isn’t really that effective. We don’t care how many millions of readers you have. We care how many people looking at your site are geared up and ready to buy our product. We want to target only those people.” And so, the cycle continues.

Meanwhile, even good data isn’t always persuasive. While reading illiteracy is seen as a national scandal, worthy of creation of large non-profit foundations, an estimated 50 million U.S. adults can’t do something as simple as calculate a tip after getting a lunch bill. That’s one reason data doesn’t make its way into the work force more; when people are afraid of something, they build false gods. When people don’t understand numbers, they ignore them. “Just forget all the figures on this mortgage disclosure document,” the mortgage broker said over and over. “Just concentrate on that first month’s payment. That’s all you have to worry about.” That ended badly.

Take a work force that’s afraid of numbers and try to get them to use data to find undervalue assets, and you’re likely to get the same response, something therapists have taken to calling “flooding.” When hit with too much information, people’s brains turn off. Then, they can be talked into almost anything, just to escape a stressful situation. Flood your employees with too much data at your own risk, and you will create a high priest class of manipulative people who act like they know everything, but really know just a tiny bit more than their innumerate counterparts. Some psychologists called this phenomenon “downshifting.” When stressed, some people downshift from thoughtful, neo-cortex decision making to emotion-based impulsive choices. However you look at it, the result will be the same: You’ll follow the bad data as it drives you and your business off a cliff.

We live in an age of almost endless information, but more times than not, this confuses our thought process and does more harm than good. It creates plateaus. Acknowledging this Plateau Effect exists should help you shift your thinking about the splits and metrics you look at every day to judge success and failure. And here’s the great news: It might mean you are already doing all the right things, but simply not giving yourself credit for it.

The use of data to break through plateaus might be seen as a continuum; if you’ve used no data, you should start immediately. If you’ve adopted data, you should seriously question its accuracy. But even if you believe your metrics are sound and true, avoid the trap which lies ahead: data idolatry.

Bob Sullivan and Herbert Thompson are the authors of The Plateau Effect: Getting from Stuck to Success. They have more than 40 years of experience between them researching,writing, and analyzing systems and human nature. Their new book helps you bust through the plateaus in your own life.