Business Forecasts: Cloudy with a Chance of Futility

The Illusion of Accurate Business Forecasts

Nobel Prize-winning economist Ken Arrow started his career as a weather officer in the US Army Air Forces during World War II. He worked with a group responsible for preparing long-range weather forecasts for military leaders. As a trained statistician, he began to wonder if the forecasts were accurate.

After examining the old forecasts, he determined that the one-month predictions were no better than random chance. Based on this conclusion, Ken sent a message to the commanding general asking to discontinue the practice. Here’s the response he received:

“The Commanding General is well aware that the forecasts are no good. However, he needs them for planning purposes.”

Like the general, CEOs need forecasts, but many are under the delusion that their current methods are valid. Every CEO wants to be rational by using data to run the business and make decisions. The problem is that data is not always helpful in predicting what is likely to happen in the future.

The Data Challenge

By definition, data is historical. It is a backward look at what has happened. I have seen many CEOs who obsess over the data but never develop a system to turn it into a forecast. Other CEOs who are flush with data may be overconfident in their ability to calculate the future of everything.

In addition, some CEOs are too rooted in the past. They only ask: “How well did we do?” not “How well did we perform against our predictions?” The best ones ask: “How good are our forecasts?”

Predictive Metrics Facilitate Good Forecasts

Setting up predictive metrics is a critical first step. However, most metrics reflect past performance. Revenue, for instance, shows how many deals the sales team closed or how well frontline staff pitched a new service—last quarter. It provides no information about what might happen next quarter.

The ability to predict future business performance is one characteristic of a good metric. For example, the best predictive metric for sales in my opinion is the accuracy of revenue forecasts.

Accurate revenue predictions measure how well the sales team understands the sales process and can use it to predictably maximize revenue. For instance, at one of my former companies our final sales numbers were almost always within 5 percent of what reps had forecast each quarter. Predicting the future is hard, but over time the sales team developed a process that allowed them to predict new license revenue accurately more than 90 percent of the time.

This excellence in forecasting gave me a crystal ball of sorts to understand how to lead the company into the future—and led to 31 consecutive quarters of double-digit revenue growth.

Collect Predictive Metrics from All Employees

CEOs need to collect forward-looking, relevant information from every department—not just sales. Very few CEOs require this, but those who do grow their own predictive capabilities, along with their employees’. These CEOs ask their executives, managers, and individual contributors to predict key outcomes at the beginning of each quarter. They then check in regularly with people: Is the forecast still accurate? What’s the likelihood we will meet the target? And then, at the end of the quarter, they—like Ken Arrow—compare actual performance to forecasted performance to ensure the organization is on track.

Training the organization to make good predictions can give CEOs a huge competitive advantage—you’re literally one step ahead in overseeing the business’s performance. No one’s invented a working crystal ball yet, but until that day, a predictive and predictable workforce is the closest a CEO can get.