Any company that wants to remain competitive in the retail industry must be able to anticipate and adapt to seasonal trends. They need to be able to predict foot traffic and potential sales volumes and how many employees they will need to staff to accommodate those predictions. This foresight allows businesses to plan their staffing needs and inventory more effectively.

The benefits are tangible—better customer satisfaction due to staff availability and efficiency. But there’s a catch: seasonal demand forecasting isn’t always as straightforward as regular demand forecasting. Outside factors like weather, promotions, or local holiday events play a big part in sales during the holiday season.

Seasonal Demand Forecasting: Key Points

• Seasonal demand forecasting enables businesses to predict sales volumes better, resulting in more accurate plans and staff requirements accordingly, preventing overstaffing or understaffing.
• Manual forecasting methods such as spreadsheets may work when you have a single location or even a couple of locations. However, they can’t handle the scale and complexity of an organization with numerous locations or omnichannel operations where each location has its own characteristics such as items for sale, traffic patterns, channels like drive-up, buy online, pick-up in-store, or geographic considerations like proximity to local attractions. Manual methods also make it almost impossible to add external data that can impact demand, like local events or weather.
• Advanced workforce management software like Legion WFM utilizes predictive analysis tools that automate the seasonal demand forecasting process, including analyzing historical data, ongoing operational data, and external data such as local events and weather to provide precise forecasts.

Understanding Seasonal Demand Forecasting

Seasonal demand forecasting is how businesses predict customer needs based on seasonal trends and patterns from past seasons. If you can understand current consumer trends, seasonal demand forecasting can help you anticipate customer needs and detect any potential changes in their behavior.

This method goes beyond regular demand prediction in that it focuses on periodic fluctuations caused by factors like holidays, local season events, and weather changes. For example, the first winter storm in areas with cooler temperatures could cause an increase in foot traffic as consumers purchase snow-clearing supplies for their homes or warm clothing. The summer months may have different spikes and demand drivers.

Factors Influencing Seasonal Demand

Several elements can shape seasonal demand. Let’s first look at weather patterns. Rain or shine, heatwave or snowfall—all these impact what customers buy, when they buy, and through which channel.

Special events also play their part. Think about the shopping spree during the holiday season, outdoor holiday events, or the back-to-school rush every fall. Because these events happen every year, AI-driven demand forecasting solutions can help retailers precisely predict the impact of these events on demand.

The economy can also affect how much (or little) and where people shop, which could mean that you see more fluctuations in traffic or sales.

Keeping these variables in mind as you conduct your demand forecast will help you be as accurate as possible to make the best business decisions.

Challenges in Seasonal Demand Forecasting

The path to accurate seasonal demand forecasting isn’t always smooth. One hurdle businesses often face is the availability and accuracy of historical data. Without a rich bank of past information, making reliable forecasts can be tricky.
We also now live in a world of ever-changing trends. Rapid shifts in consumer behavior or unexpected market events can throw off predictions, leading to stockouts or excess inventory.

Unforeseen circumstances such as weather changes or global crises can add a layer of complexity, making it difficult to predict accurate seasonal demand forecasts.

Manually forecasting is particularly challenging when forecasting for many locations in different regions of the country, as they are all subjected to different demand patterns. Retailers with omnichannel operations who lack modern forecasting tools often don’t know which channels are surging or not on any given day and can’t react quickly enough to changes. And discrepancies often lead to lost revenue, lower productivity, higher payroll costs, and employee attrition.

So what’s the solution? In modern times, AI-powered technology is the way through these roadblocks. Businesses can navigate seasonal demand forecasts much easier with the flexibility and adaptability of automated technology.

Simplify Seasonal Demand Forecasts With AI-Powered Technology

AI-powered technology is designed to process large amounts of data and identify patterns that could be missed when initially analyzed, simplifying the forecasting process.

AI helps ensure your forecasts are accurate and timely, so you no longer need to worry about manually sifting through past sales records or trying to keep up with current trends. Automated WFM solutions that leverage AI can understand and incorporate the impact of demand drivers and future events such as weather or holidays, so you don’t have to run complex calculations, pay high data fees, or use manual processes. And you can integrate your unique staffing policies and local laws. Demand forecasting ensures you know exactly what type of labor you need every hour of every week.

For example, Legion WFM’s Demand Forecasting product is fine-tuned to predict your business’s seasonal demands accurately by using customized advanced machine learning algorithms that continually improve and learn from your data. Legion factors in your unique labor model and staffing policies and forecasts business demand in dollars, transactions, foot traffic, or other variants. Legion Demand Forecasting automatically delivers accurate forecasts at several levels—channel, location, or SKU—in 15-minute increments.

As new data is available throughout the week, labor is recomputed so you can compare an improved forecast and labor plan to what was previously published. You can adapt and react quickly to business changes by continuously re-forecasting and regenerating labor guidance. And, with Legion, forecast editing can be done at a manager level or centrally to combine human judgment with Legion’s AI.

Take the guesswork out of planning for high-demand periods and improve business agility, accuracy, and labor efficiency—simultaneously.

Future Trends in Seasonal Demand Forecasting

Seasonal demand forecasting requires smarter, faster solutions, with AI and machine learning that can process large volumes of data quickly and continuously learn and improve.

Intelligent, automated WFM solutions help predict consumer behavior and allow you to react to changes almost instantly. For instance, if a sudden weather change impacts demand for certain products, AI-driven systems can automatically adjust forecasts on the fly.

Real-time data also enables businesses to adapt to shifting conditions promptly—from product popularity shifts due to viral social media posts to unexpected events like concerts or festivals nearby.

This evolution makes it easier for managers and business owners using platforms like Legion WFM by providing precise insights into their business’s seasonal demands.

Drive Success With Seasonal Demand Forecasting

Seasonal demand forecasting comes down to science, not guesswork. You must be able to understand the patterns, trends, and influences that shape customer behavior to create an accurate forecast.

Legion WFM takes the auto-generated, highly accurate demand forecasts and creates an optimal labor plan automatically—no more mapping between labor models used by finance for forecasting and operations for scheduling. With no manual steps or “lost in translation” data issues, Legion creates an optimized labor plan for your business—no matter the season.

Schedule a demo to learn more about Legion WFM.