What is a Leading Indicator?

A leading indicator is like a warning light on your car…

It gives you a heads up when something isn’t working quite right. Perhaps the check engine light means that you need to see a mechanic before your car breaks down. Or maybe a sensor just malfunctioned, and the engine is fine. In the same way, leading indicators direct your attention to a potential problem or opportunity before it happens. But they aren’t always reliable.

A leading indicator is a measurement that provides insight into how another piece of information is likely to turn out. There are many types of indicators in business, finance, and economics. Some act as warning signs — which managers, traders, and policymakers can use to make decisions. These leading indicators provide useful insight into what is likely to happen in the near future.

You can think of leading indicators as hints at what the future might look like before the whole picture is revealed. For example, economists measure a recession as two or more consecutive quarters of declining gross domestic product (GDP) — which is the value of everything made within a country’s borders during the accounting period. But it takes a long time to compile that economic data. In many circumstances, an economy might be out of a recession before the data identifies that there even was one.

This delay in information means that policymakers can’t implement fiscal policy (adjusting tax rates and government spending levels) or monetary policy (altering the interest rate) fast enough to be effective. Instead, they might rely on leading indicators to spot economic trends and to better time interventions. Since those leading economic indicators provide a glimpse at what the official data will look like when it’s released several months later, it can allow more effective policy actions. Some examples of these leading economic indicators include the yield curve, stock market volatility, jobless claims, the consumer confidence index, the purchasing managers index, and the durable goods report.

Any piece of information can be an indicator of any other data with which it generally correlates. Of course, correlations don’t anyways imply causality. Variables can move together without one causing the other to move. But all correlated data falls into one of three categories as they relate to one another.

A leading indicator means that one variable will move before another. For example, new housing starts can be a leading indicator of home sales. And applications for building permits can be a leading indicator of new homes starts. If contractors don’t believe there will be enough buyers, they won’t build as many new homes. So, looking at how many new homes contractors are planning to build can be a good leading indicator of the direction the housing market is heading.

A lagging indicator means that the information comes in after the fact. It confirms that something did, in fact, happen. Because collecting information is difficult and time-consuming, lagging indicators don’t make for useful policy tools. But these data are more reliable than other forms of information. Lagging indicators help determine how things unfolded, and they provide a better understanding of what happened in the past. An example of a lagging indicator is the unemployment rate. The official data from the Bureau of Labor Statistics comes out on a one-month lag. So, by the time the data is available, it might be too late to act on it. It’s a lagging indicator of the health of the labor market.

A coincident indicator means the information is available and relevant in real-time. It’s data that doesn’t point to where things are heading or what happened in the past. Instead, it’s data that explains what is going on right now. An example would be wage data, reported as payroll occurs. The wage data would show the amount of money households are receiving, which is a coincident indicator of the health of the economy.

Investors are typically interested in the direction that a security’s value will move. Any leading indicator that might hint at a company’s growth is essential for investors. If an investor knew that a company’s stock price was going to go up, buying that stock ahead of time would be profitable. In theory, a company’s stock price should reflect its intrinsic value (what the company is worth based on its revenues, expenses, assets, and debts). That is, the stock’s price should reflect the information on the company’s financial statements.

But if investors can use other information to predict what those financial statements will say, they can buy or sell the stock ahead of time. That’s why investors might want to pay attention to leading indicators. For example, a falling number of initial unemployment insurance claims released by the U.S. Department of Labor might suggest that the economy is growing. The positive state of the economy might suggest a company’s sales will increase, which should result in a rising stock price. There are many ‘parts’ that have to go just right to have this scenario play out as expected so investors have to understand the risks.

Most businesses use key performance indicators (KPIs) to keep tabs on how well their business is running. KPIs can be anything from the average customer wait time to the percentage of callers placed on hold. Many of these KPIs are leading indicators of sales and profits. One KPI many businesses pay a lot of attention to is customer satisfaction survey results.

Excellent customer satisfaction results in repeat customers and good word-of-mouth advertising — both of which reduce customer acquisition costs and increase future revenues. Poor customer service has the opposite effect. So, customer service surveys are a valuable leading indicator for business, which allows managers to address problems before waiting for the sales numbers to drop.

Setting leading indicators allows managers to get a preview of how the financial statements could look. It helps them find problems before they get out of control. And it provides them with the potential to improve profits without significant overhauls to processes or personnel.

For example, a business might set the percentage of callers placed on hold as a leading indicator. Because some callers will hang up when put on hold, a higher rate might indicate lost sales revenue. A manager could see that leading indicator as a problem to address. They might bring on more customer service representatives during the times of high hold rates. Doing so could increase sales by more than the cost of labor, thereby improving profits.

But one must be careful not to put too much focus on addressing the leading indicator rather than the problem it highlights. For instance, a manager that gets penalized for a high hold rate might opt to stop answering the phone rather than put callers on hold. That solves the wrong problem.

To set a leading indicator in business, you need to start with data. If you don’t know what a good result looks like, you can’t recognize it when it happens. For example, measuring the average customer purchase value might be a good key performance indicator (KPI). A low average sales value might imply that the sales staff needs training. But is an average sale of $34 good or bad?

Without knowing what normal looks like, it’s impossible to interpret the result of a measurement. Plus, there could be some unusually low outlier that skews the numbers. So, teaching managers how to understand KPIs as leading indicators is necessary.

Finally, it’s essential to know what desired outcome you are trying to achieve. Improving a KPI on its own might not be a profitable strategy. For example, dividing total sales by the amount spent on labor is called the labor yield. If a manager’s bonus is tied to improving labor yield, it might encourage them to overwork their employees. In this case, improving the KPI (labor yield) could result in poor customer service, lousy employee morale, and lower profits.

Setting a leading indicator is probably going to work out better if you focus on the critical outputs. For example, increasing profits is a common goal of a business. Then, set the KPIs to measure the things that improve profitability. That way, managers don’t get focused on cultivating better leading indicator outcomes rather than using them to make decisions about the bottom line.