​​3 Proven Strategies to Avoid Excess Inventory in January

All retailers understand that starting the new year overstocked with stale merchandise can cause real financial stress. However, almost 60% of retailers still face excess inventory problems after the holidays (KPMG).

The industry even has a name for it: “the holiday inventory hangover”. Driven by slow-moving products and unpredictable post-holiday demand, excess inventory is most addressed through increased clearance sales and cutting receipts in January.

Intelligent inventory management is imperative to avoiding the negative financial impact of unsold stock. Here are three strategies to help you optimize your business’ inventory management as you move from the holiday season and into the new year.

Strategy 1: Leveraging Pre-Holiday Promotions to Balance Inventory Levels and Minimize Tax Liability 

Running early promotions before the peak holiday season can help clear stock, avoid the January surplus, and minimize your tax liability for 2024. Such targeted promotions include limited-time discounts, bundles, or early-bird specials aimed at customer segments to create urgency and move inventory quickly. Clearance sales between Thanksgiving and Christmas can also attract new consumers seeking out promotions, while moving forward slow-moving products before the new year.

Most importantly, use your sales data to forecast demand based on previous trends for more precise inventory planning. This can help determine which products perform well before holidays and which tend to linger, so that you can adjust promotions accordingly to target high-demand items and sell off slow-moving stock.

Strategy 2: Collaborating with Suppliers for Flexible Ordering to Mitigate Overstock Risks

retail stock management

Working with suppliers to arrange for flexible agreements can make the difference in mitigating overstock risks. To have full visibility over these needs and put effective solutions in place, retailers must have an effective inventory management system that creates real-time visibility over stocks.


Flexible ordering systems with adaptable delivery schedules will enable you to regulate stock levels after peak sales periods. For instance, when ordering seasonal products, having the possibility to reduce or delay shipments post-holiday can prevent unnecessary stock buildup.


Also collaborate on reducing lead times in January to have smaller, more frequent shipments, that allow for incremental order adjustments based on sales patterns. Following a Just-In-Time (JIT) approach to inventory management, will allow for your business to maintain leaner inventories without risking overstocking or stockouts.

Strategy 3: Using Inventory Forecasting Software to Predict Holiday Demand Accurately

Inventory forecasting software helps you take the guesswork out of ordering so you can accurately predict demand during the holiday season based on historical data.

Retailers of all sizes can integrate predictive analytics to optimize stock by seamlessly integrating it with their point-of-sale (POS) system for real-time tracking and monitoring of successful merchandise. Simultaneously, it can also help to identify which products are likely to remain stagnant after the holidays.

The Takeaway

To avoid excess inventory in January, retailers should combine these strategies for the most effective results. Leveraging data using Inventory Forecasting Software is key to maximize inventory efficiency and to guide sales strategies such as pre-holiday promotions and flexible ordering. In fact, the numbers speak for themselves: investing in an efficient IMS system was one of the top three investment priorities for retailers in 2024 to balance inventory levels and unleash capital for the next year.

To find out how Management One can support retailers in optimizing inventory planning with specialized tools in demand and sales forecasting, get a free consultation here.

Previous
Previous

​​5 Proven Markdown Strategies to Maximize Profit This Season

Next
Next

Retail Merchandising Trends: The Shift Towards Data-Driven Inventory Planning