A Complete Guide to Retail Allocation

Retail planning is a data-driven strategy implemented to meet consumer demand and maximize ROI by delivering appropriate products to different channels at the optimal price, while reducing the need for discounting and optimizing product margins.   

Otherwise known as merchandise allocation, retail allocation is an in-season process in the retail planning cycle that aims to allocate the right products to the right stores or channels in the right quantities at the right time. The overarching goal is to optimize inventory allocation to meet customer demand and minimize excess inventory and stockouts to maximize profitability. 

This is a challenging task. To make informed merchandise allocation decisions, retailers analyze sales data, market trends and other factors that may influence demand. Advanced analytics enable them to forecast demand accurately and allocate inventory accordingly. 

However, making retail planning and allocation decisions solely based on historical sales data may not be enough. Retailers need to consider additional factors, such as store size, location and customer demographics. 

Inventory allocation is the scrutinous process of assigning individual item quantities to each channel based on historical data. Ensuring the exact product types match your customers’ exact needs. Allocators have to balance many competing demands, data inputs and responsibilities to optimize inventory management. Their biggest challenges include: 

Allocators must work with enormous volumes of complex data, including historical sales data, inventory levels, store performance metrics and market trends. This data can be difficult to manage and analyze, particularly for retailers with a large number of stores and channels or those operating in diverse geographic regions. Traditional tools such as spreadsheets and legacy reporting solutions do not adequately support the modern retail landscape, making the process all the more challenging. 

Each store location has unique customer demand patterns. Allocators must identify these and adjust their decisions accordingly. This requires a lot of data combined with a deep understanding of local market conditions, customer preferences and the competitive landscape. 

Allocators must balance the need to maintain optimal inventory levels with the risk of overstocking or stockouts. Inventory allocation requires careful planning and forecasting, as well as the ability to adjust decisions quickly based on changes in demand or market conditions. 

Replenishment teams and allocators need to work closely together to rapidly adjust decisions and ensure that inventory is restocked in a timely and efficient manner. Careful monitoring of inventory levels and lead times is crucial to optimize stock availability. 

Allocators must work closely with a range of stakeholders, including store managers, merchandising teams and suppliers. Effective communication and collaboration ensure that everyone is aligned on retail planning and allocation decisions. 

Poor initial retail allocation can lead to a range of negative consequences, including: 

If a store’s inventory allocation is not sufficient to meet customer demand, it can lead to stockouts and damage customer satisfaction and loyalty. Customers may choose to shop elsewhere if they cannot find the products that they want. 

On the other hand, the allocation of too much inventory leads to overstocking. This ties up capital and reduces profitability, as excess inventory may need to be marked down or even thrown away if it does not sell before it becomes obsolete. 

If customers can’t find the products they want in store, sales are lost. This results in lower revenues and reduced profitability for the retailer.

If inventory is not allocated appropriately, it can lead to reduced inventory turnover rates. Inventory sits on store shelves for longer periods of time, tying up capital and reducing the retailer’s ability to introduce new products or respond quickly to changing market conditions. 

Incorrect retail planning and allocation decisions can lead to increased costs, including the cost of carrying excess inventory, expedited shipping costs for restocking and the cost of markdowns to clear out excess inventory. 

To minimize these risks, retailers must invest in retail allocation software to develop effective inventory management processes, including data-driven allocation and replenishment decisions. 

Retail planning solutions such as Centric Planning™ empower retailers to forecast demand, optimize inventory levels and product assortments, and manage their supply chain more efficiently. They can also provide real-time insights into sales performance, inventory levels and product mix across store locations, enabling retailers to make data-driven decisions and improve overall profitability.  

Manual inventory allocation for retailers with lots of SKUs and/or stores and channels is time-consuming and fraught with errors. Retail allocation software with AI-powered forecasting optimizes retail planning and allocation to ensure: 

A planning and forecasting solution uses historical sales data and market trends to accurately forecast future demand for each product and store location. Retailers are able to allocate inventory more efficiently, reducing the risk of stockouts or excess inventory. 

By accurately forecasting demand, a planning solution enables retailers to optimize inventory levels, reducing the amount of excess inventory they need to carry. This can increase inventory turnover, reduce carrying costs and improve cash flow. 

Cluster-based allocation is a retail allocation strategy that involves grouping stores based on factors such as geographic location, store size, customer demographics and sales performance. Advanced clustering capabilities make it easier to identify which products are popular in which locations and adjust product offerings accordingly in the assortment plan. Retailers improve their product mix, reduce excess inventory and increase sales. 

By optimizing allocation and replenishment, retailers can manage their supply chain more effectively. This can reduce transportation costs, improve delivery times and increase customer satisfaction.

When products are better allocated and aligned to where consumers expect to find them, it means there is less transfer between stores. A reduction in product movement is a reduction in pollution and when you’re talking about huge retailers this small saving can quickly become significant.   

A planning and forecasting solution can increase sales and profitability by optimizing inventory availability, improving product assortments and reducing stockouts and transfers. This can be particularly important in highly competitive retail markets where even small improvements in efficiency lead to significant gains. 

When evaluating retail allocation software, allocators should consider a high-performance end-to-end solution that drives decision-making from a single source of the truth for enhanced visibility and faster time to result.  

Although retailers would first and foremost invest in a planning solution to reduce excess end-of-season stock and increase the chances of selling more products at full price; sustainability is an attractive and very important secondary benefit, and a welcome addition to any other sustainability initiatives a business is undertaking.    

Allocation and replenishment in retail can be challenging processes for brands and retailers, and mistakes or poorly informed decisions can have a major impact on profitability and customer satisfaction. Managing the allocation process manually is arduous and complex for retailers with many SKUs, stores and channels, resulting in disconnected teams and huge margins for error. 

By leveraging a powerful, intuitive AI-driven retail planning and forecasting solution, retailers can overcome these challenges and benefit from accurate allocation and replenishment decisions, enhanced inventory visibility, improved collaboration, increased forecasting accuracy, greater profitability and better customer satisfaction.