Understanding Seasonality
Seasonality refers to periodic fluctuations in certain business areas and cycles that occur regularly based on a particular season. A season may refer to a calendar season such as summer or winter, or to a commercial season such as the holiday season.
Companies that understand the seasonality of their businesses can predict and time inventories, staffing, and other decisions to coincide with expected seasonal activities, thereby reducing costs and increasing revenue.
It is important to consider the effects of seasonality when analyzing stocks from a fundamental point of view because it can have a big impact on an investor’s profits and portfolio. A business that experiences higher sales during certain seasons may appear to make significant gains during peak seasons and significant losses during off-peak seasons. If this is not taken into consideration, an investor may choose to buy or sell securities based on the activity at hand without accounting for the seasonal change that subsequently occurs as part of the company’s seasonal business cycle.
Seasonality is also important to consider when tracking certain economic data. Economic growth can be affected by different seasonal factors including the weather and the holidays. Economists can get a better picture of how an economy is moving when they adjust their analyses based on these factors. For example, roughly two-thirds of U.S. gross domestic product (GDP) is made up of consumer spending—which is a seasonal measure. The more consumers spend, the more the economy grows. Conversely, when they cut back on their purse strings, the economy will shrink. If this seasonality was not taken into account, economists would not have a clear picture of how the economy is truly moving. Seasonality also affects industries called seasonal industries, which typically make most of their money during predictable parts of the calendar year.
Examples of Seasonality
Seasonality is apparent in many different aspects of daily life and business operations. Here are some notable examples:
If you live in a climate with cold winters and warm summers, your heating costs likely rise in the winter and fall in the summer. You expect the seasonality of your heating costs to recur reasonably every year around the same time.
Similarly, a company that sells sunscreen and tanning products within the United States sees sales jump up in the summer as demand for their products increases. On the other hand, the company will likely see a significant drop in the winter.
Another area affected by seasonality is retail sales. Retail sales measure consumer spending and demand and are reported every month by the U.S. Census Bureau. Data fluctuates at certain times of the year, primarily during the holiday shopping season. This period falls into the fourth quarter of the year—between October and December. Many retailers experience seasonal retail sales, seeing a big jump in consumer spending around the holiday season.
Special Considerations
Seasonality and Temporary Workers
Large retailers may hire temporary workers to respond to higher consumer demand associated with the holiday season. For instance, a large e-retailer might hire approximately 100,000 employees to cope with increased activity in stores. Similarly, major retail chains may hire thousands more to handle the same period. These decisions are made by examining traffic patterns from previous holiday seasons and predicting what to expect in the coming season. Once the season is over, many temporary employees are let go based on post-season traffic expectations.
Adjusting Data for Seasonality
A lot of data is affected by the time of the year, and adjusting for the seasonality means that more accurate relative comparisons can be drawn between different time periods. Adjusting data for seasonality evens out periodic swings in statistics or movements in supply and demand related to changing seasons. By using a tool known as the Seasonally Adjusted Annual Rate (SAAR), seasonal variations in the data can be removed.
For example, homes tend to sell more quickly and at higher prices in the summer than in the winter. As a result, if a person compares summer real estate sales prices to median prices from the previous year, he may get a false impression that prices are rising. However, if he adjusts the initial data based on the season, he can see whether values are truly rising or just momentarily increasing due to warm weather.
Related Terms: cyclical effects, seasonal industries, retail sales.
