Forecasting Seasonal Demand With Machine Learning Tools

According to data from the National Retail Federation (NRF), holiday shoppers in the United States spent a record high of $964.4 billion during the 2023 holiday season. That’s a 3.8% increase from 2022, when spending grew to $929.5 billion — and that means companies at all levels of the supply chain need to step up their seasonal forecasting game if they want to stay competitive.

Seasonal profile adjustment is a vital yet often overlooked part of forecasting seasonal demand. Are your organization’s forecasting models keeping up? For most companies competing in today’s chaotic supply chain, it’s prime time to look into machine learning tools.

What Is Machine Learning?

Machine learning (ML) is a subset of artificial intelligence (AI) that uses algorithms, historical data and new inputs to make a program more accurate over time. Essentially, ML allows a computer program to “learn” from previous cycles and produce better outputs based on the feedback it receives.

For example, the developers at Blue Ridge Global have incorporated ML capabilities into our Demand Planning software to enable more accurate predictions. Whether you need to account for hundreds or thousands of different SKUs, our automated platform updates in real time to optimize seasonal demand forecasts and improve supply chain visibility.

How Machine Learning Enhances Seasonal Supply Chain Management

To manage inventory effectively, you first need to marry the optimal forecasting and replenishment optimization strategy with each SKU, which requires a more advanced seasonal demand forecasting approach.

Leveraging machine learning techniques can help identify seasonal items more easily, generate more accurate forecasts and gain an edge over competitors still struggling with elementary demand models. Here’s how:

• Predictive analytics: ML algorithms can analyze historical and present data to accurately predict future trends, aiding both manufacturers and distributors in demand forecasting for seasonal products.
• Process improvements: An ML algorithm can uncover areas for improvement within your supply chain, giving your company the information you need to improve operations in time to meet seasonal demand spikes.
• Risk management: Any supply chain disruption can destabilize operations and cause you to fall behind during demand peaks. ML’s predictive analytics capabilities can help you anticipate issues before they appear, creating a more resilient supply chain and improving your ability to keep up with seasonal changes.

4 Must-Haves for Accurate Seasonal Demand Forecasting

To master seasonal profile management, keep these four key areas in mind:

1. Determining which items to adjust. Do you know every SKU that should have a seasonal profile? The right demand classification techniques can help you understand how sales are likely to fluctuate across a wide variety of demand behaviors. Using probabilistic forecasting and advanced supply chain analytics, you can create an accurate seasonal forecasting model for each item — even the most challenging ones.
2. Finding the right model. Many businesses rely on a classic exponential smoothing model to predict demand, which smooths sales activity throughout the year into a holistic forecast. But what happens when an item has no available data for five or six months out of the year? More advanced forecasting techniques, such as aggregating sales according to higher-level characteristics, will help you arrive at the most accurate possible results for SKUs with intermittent demand.
3. Measuring accuracy. How confident are you that your seasonal forecasts are actually correct? ML-enabled tools can help businesses remove the guesswork from seasonal adjustment. Using pattern-matching algorithms, these tools help ensure that seasonal adjustments will actually improve accuracy before making the change.
4. Automating forecasts. The average distributor has thousands of SKUs, which makes it all but impossible to manually create forecasts for each seasonal product. Beyond improving accuracy, inventory forecasting tools can deliver big efficiency improvements by producing product-level forecasts with no need for user intervention.

How to Improve Seasonal Forecast Accuracy

As supply chain management technology continues to evolve, emerging techniques like unsupervised machine learning can help you improve accuracy even further. Using near human-level intelligence, these tools can automatically identify trends like seasonal pattern clustering and push daily alerts so you can quickly adapt and adjust inventory levels faster and with a higher degree of accuracy than ever before possible.

Forecasting seasonal demand with the help of AI and ML algorithms makes it easier to minimize manufacturing, distribution and warehousing costs without running into stock issues during peak season. Some other useful tips for seasonal forecasting include:

• Get familiar with seasonal products: Demand for seasonal stock typically spikes and dips at the same times every year, so flagging specific SKUs that experience seasonality can help you stay more organized. It can also help your ML algorithm better predict changes in demand as the season approaches.
• Understand what’s driving demand: Sometimes, seasonality isn’t the main cause of demand spikes — even those that happen regularly. Other factors, like especially effective marketing campaigns or industry-specific changes, can impact how much of a certain product you sell over a period.
• Pinpoint the root cause: Unlike fluctuations caused by cyclical effects like economic issues and international tensions, seasonal demand is regular and predictable. An ML-equipped software program can analyze sales data in real time to help you differentiate between cyclical disruptions and seasonality, which is important for effective preparation.

Improve Your Seasonal Forecasts With Blue Ridge Global

Think you might need to explore advanced seasonal forecasting tools? Blue Ridge Global has the solutions for you.

Our Demand Planning software uses AI and ML to improve your supply chain’s agility with end-to-end visibility, accurate forecasting models and user-friendly features. You can use our tools to enhance demand prediction for all your products across geographical locations, including seasonal ones. Plus, our LifeLine Support team is here to help walk you through roadblocks any time you need assistance.

See how Blue Ridge can help your company become supply chain invincible. Request your live demo today.