Every day we generate 2.5 quintillion bytes of data. This information has led to some tremendous breakthroughs with the potential to improve thousands of lives. As leaders, we also have mountains of data available to us—honestly, more than we can assimilate or make sense of. Yet huge decisions are made every day based solely on the numbers.

Now, don’t get me wrong. I love numbers! But, in my years working with many leaders, I’ve seen too many of them make unwarranted or uninformed decisions because they have over-relied on data. Anecdotal evidence is also critical. More importantly, one without the other is a recipe for mistakes.

Let me give you an example from a story I heard while writing my new book. In 2009, Nokia was the world’s largest cell phone manufacturer. A woman named Tricia Wang was working in the company’s research department at the time, and she held the position of Technology Ethnographer. Similar to a cultural anthropologist, Wang’s job was to identify market trends and potential new customers by analyzing the qualitative side of human behavior related to cell phone usage.

Wang was specifically assigned to study the preferences and habits of low-income consumers in China. To say that she immersed herself in this task is putting it mildly.

She spent several years living with Chinese migrants, and she worked as a street vendor selling dumplings. She observed and interacted daily with people in neighborhood Internet cafes. She asked questions, and she listened to the answers. Really listened. Reading between the lines to capture the emotions and subtext lurking below the surface of their verbalized responses.

Using a boots-on-the-ground approach, she gathered a wide range of profound personal insights directly from these people. Through her many conversations with the locals, Wang discovered something she didn’t anticipate.

Despite their very limited incomes, many Chinese people were so enamored with the new “smartphones” that they would sacrifice half of everything they earned in a month to have one. And those who didn’t have smartphones desperately wanted one. The demand was enormous—and completely unexpected in this demographic group.

Essentially, Wang had uncovered a massive, hidden market for affordable smartphones.

Wang enthusiastically shared this great news with Nokia executives, who quickly responded with a polite, “Thanks, but no thanks.” Their extensive quantitative research with millions of data points was driving a clear strategy to produce full-featured smartphones for high-end users.

In their opinions, Wang’s qualitative data and small sample size didn’t measure up to the mountain of numbers they’d already collected.

Fast forward a few years, and you’ll see that Nokia paid a huge price for ignoring Wang’s recommendation. Looking at the numbers alone sent them down the wrong road with their brand strategy. In 2012, the company ended up losing $4 billion and, ultimately, was forced to sell off its phone business to Microsoft.

How often does this happen? I imagine more often than we know.

But the more important question is, why does it happen? First of all, leaders are under greater and greater pressure to produce more, win more, and make a larger impact on the bottom line. So, when push comes to shove, it’s easier to justify a critical decision based on the hard data.

The truth is, the best modern leaders embrace Whole Data—a more comprehensive view of the facts—that stretch beyond the usual quantitative boundaries to incorporate intangible elements as they plan for next steps.

They pay attention to stories and narratives, emotions and attitudes, worries and complaints, risks and vulnerabilities. They dig down to find the motivations behind customer decisions, and they identify how policies, processes, and products all impact the lives of the people behind the statistics. They search for the qualitative information that paints a more vivid picture.

These leaders take a new approach. They demonstrate the wisdom of integrating hard data and soft intelligence to make better decisions. They ask the hard questions.

Am I confident that this data reveals the entire story? What might be missing? Does this view of the data include the human factor? Is this data merely a reflection of the preferences, assumptions and experiences of those who aggregated it?

The answers to those questions may change the decisions they make and the results they deliver in unexpected, positive ways. So here’s my challenge. Study the data. Parse it every way you can, looking for trends and patterns. Then take the time to ask your employees, customers, or strategic partners what they are seeing. You might be surprised by what you learn.