What is "seasonality"

n. Variation with the seasons

In statistics, time series data is data collected at regular intervals. When there are patterns that repeat over known, fixed periods of time within the data set, such patterns are known as seasonality, seasonal variation, periodic variation, or periodic fluctuations. This variation can be either regular or semi-regular.

Seasonality may be caused by various factors, such as weather, vacation, and holidays and usually consists of periodic, repetitive, and generally regular and predictable patterns in the levels of a time series. Seasonality can repeat on a weekly, monthly or quarterly basis, these periods of time are structured and occur in a length of time less than a year. Seasonal fluctuations in a time series can be contrasted with cyclical patterns. The latter occurs when the data exhibits rises and falls that are not of a fixed period. These fluctuations are usually due to economic conditions and are often related to the "business cycle." The fixed period of time usually extends beyond a single year and the fluctuations are usually of at least two year and do not repeat over fixed periods of time.

Organizations facing seasonal variations, such as ice-cream vendors, are often interested in knowing their performance relative to the normal seasonal variation. Seasonal variations in the labor market can be attributed to the entrance of school leavers into the job market; as they aim to contribute to the workforce during their vacations, or upon the completion of their schooling. These regular changes are of less interest to those who study employment data than the variations that occur due to the underlying state of the economy. Where their focus is on how unemployment in the workforce has changed, despite the impact of the regular seasonal variations.

It is necessary for organizations to identify and measure seasonal variations within their market to help them plan for the future. This can prepare them for the temporary increases or decreases in labor requirements and inventory as demand for their product or service fluctuates over certain periods. This may require training, periodic maintenance, and so forth that can be organized in advance. Apart from these considerations, the organizations need to know if variation they have experienced have been more or less than the expected amount, beyond what the usual seasonal variations account for.