How Seasonal Forecasts Can Influence Your Business

Seasonality is a time series feature in which data experiences predictable variations that repeat every calendar year. Seasonal patterns are defined as predictable fluctuations that recur over a period of one year.

In a business context, seasonality refers to predictable commerce changes that occur based on a particular season. Seasons are either commercial or calendar-based. While the holiday season is classified as a commercial season, the winter season is considered a calendar season.

Most markets and industries experience seasonal variations such as rising housing costs in summer or increased retail sales during the holiday season. Businesses with the most intense seasonal variations may choose to close their doors during slower months or find innovative ways to boost short term sales during slower seasons.

There are various significant benefits and consequences of owning a seasonal business. Seasonal businesses can offer business owners invaluable additional time to develop their systems, processes, procedures, and budgets.

The offtime provided to seasonal business workers can decrease burnout and keep their engagement levels high. For employees with a limited schedule, such as a college student, these seasonal roles can be considered ideal.

Once you've formed an outstanding team of professionals for your seasonal business, your hiring process will likely be much more time-efficient and cost-effective. Additionally, a great work environment can lead to personal referrals from your existing employees to their own job-seeking network, further expanding your candidate talent pool.

Seasonal businesses often have a narrower customer base, a benefit for marketing and outreach initiatives. For example, a summer camp could start marketing directives during the winter months through discounted pre-registration offers at local schools.

The consequences of seasonal businesses include unexpected seasonal variations in weather patterns. An unforeseen weather event can be catastrophic to even the best-laid business plans.

Pain points including shipping delays and inappropriate inventory levels can be avoided by obtaining weather data in advance. While minimizing risks, make sure to consider that while seasonal work offers employees many benefits, your employee turnover rate may be higher than other businesses due to the instability and scarcity of available shifts.

The capital required to start up a seasonal business can be difficult to gather and there are often many large upfront investments necessary. However, with the right team, dedication, and proper management, a seasonal business can be a great investment.

When used correctly a seasonality forecast can decrease business costs and increase bottom-line profitability. Predicted seasonal variation can inform business decisions ranging from inventory levels to staff hiring initiatives.

Seasonality forecasting methods can assist business professionals with stock and economic trend analysis. For example, retail sales are generally affected by seasonality. If the monthly data of a retail operation is evaluated without the context of seasonal variations, a business can easily assume they are more profitable than they actually are.

Seasonal forecasting provides businesses with critical data to assist with preparing for upcoming business operations. There are several important forecasting terms that business professionals should be familiar with, including

• Seasonal indices- Seasonal indices are the plural form of a seasonal index and are measurements of a particular season cycle in comparison with the average seasonal cycle.
  
• Moving averages- A moving average evaluates subsets of data to find a consistently updated average.
  
• Exponential smoothing- Weighted averages of past historical data, with older data decreasing in weight. Without a clear data pattern available, exponential smoothing can be used to forecast sales.
  
• Time series- Time series data is collected over different points of time. A time series with a clear seasonal pattern can use moving averages and historical data for forecasting.
• Holt Winters method- The Holt Winters method, also known as triple exponential smoothing, is a time series behavior model. The Holt Winters method may be used to forecast time series data with trend and seasonality variations.
  
  Once you understand the common terminology used in seasonal forecasting you can develop a unique forecasting method for your business. Forecasting using historical data that analyzes seasonal patterns and time series data can provide a more comprehensive view of potential future profitability and success.