Computing technology and specifically the internet has allowed access to unprecedented amounts of information. It has created enormous quantities of new data about how people engage with the world using that technology. As a result, a fully connected, unfiltered technology user can today have much of the information they see determined by their response to information they saw in the past.
One can argue whether that’s good or bad, but the data are out there and they are going to be used. Privacy is an important concern, but there are more present risks for businesses that leaders should ensure they address. Directors and managers are now able to access huge troves of data, and they are employing an ever-growing number of analysts to help them manage it. The U.S. Bureau of Labor Statistics has found that “statistician” is among the fastest growing jobs, and in 2012 the Harvard Business Review called it “the sexiest job of the 21st Century.”
But many of the analysts I’ve spoken to, particularly in traditional businesses (as opposed to start-ups or high-tech), say few of their managers have the training to understand data or interpret it effectively. Often, analysts are tasked with providing information they know is going to be used incorrectly, or to find data that just isn’t there. One analyst, for example, told me her boss will often ask her to find data that supports the manager’s arguments about his strategic decisions. “It’s crazy,” she says, “we have all this data that clearly shows what we should be doing, but he doesn’t want to do that, so he ignores the data. I have to create new metrics that show what he wants to show.”
This is a significant challenge for small- to medium-sized businesses. Misusing data can create as serious a competitive disadvantage as not using data at all. A manager who focuses on data to prove that what they think is right misses opportunities to actually be right. Let’s imagine a manager who believes that Facebook advertising is the best way to market a new line of shoes. He invests resources and launches a campaign. He knows this is going to work, so he asks for reports that show likes, shares, and clicks on the ads, and the data confirm his expectations. After a month, sales are great for three products but not so great for three others. The company decides to pull the three that didn’t sell well and puts the resources into more marketing for the three that did. The campaign is declared a success.
Now consider a manager who, like the first, believes social media is the best way to market the shoes and invests the resources in launching the campaign. She thinks it’s going to work, but she’s willing to accept she might be wrong, so she asks for reports that include all the data, along with an analysis of any discernible patterns. Soon after the launch, the data show that three of the shoes aren’t selling well, but also that most of the Facebook users who engage with ads for those shoes are under 25 years old. Recognizing that the price may be a barrier for these younger consumers, the company adjusts the price and soon the sales for these shoes match the levels of the others. This campaign has also been declared a success, but it generated almost twice the revenue as the other success.
And therein lies the true risk of managers without data skills: They can go along for months, even years, thinking they are doing a great job. They can declare success after success, and the whole company can think it’s doing really well while revenue or market share or some other critical success indicator stagnates. When the numbers start to decline, as inevitably they will, everyone is perplexed. The metrics they watch look great, so why is the business doing poorly?
Sometimes, people find the right answer: We’re looking at the wrong numbers! More often, people start finger-pointing and blaming. Meanwhile, the competitors who arelooking at the right numbers keep winning.
As Sam Altman, president of the startup incubator Y Combinator has said, “It really is true, the company will build whatever the CEO decides to measure.” It’s true for startups, but it’s also true for any organization, from non-profits to hundred-year old corporations. When directors and managers don’t understand the value of data, and how they should be used, they miss the opportunities that their more successful competitors will find.
There’s a rather simple solution to the problem, however. Anyone in the organization who has a data analyst as a direct report, who looks at data more than once a month to make key decisions, or who presents data internally or externally, should get training in statistics and analytics. Giving your staff a solid understanding of data analysis will improve productivity, increase efficiency, and maximize opportunities for accurate decision-making.