Effective Allocation Management: Key Strategies for Retail Success 

Knowing what to buy is only half the battle for retailers – determining how to distribute purchased inventory across locations and channels makes all the difference in sales, margins, and customer satisfaction. Allocation management, a part of merchandise or inventory planning, is the strategic distribution of stock to match supply with consumer demand. With the rise of omnichannel retail, allocation has become more complex but even more critical to get right. This article will examine best practices in allocation to help retailers maximize inventory utilization and avoid lost sales.

The Need for Smart Allocation 

Allocation management exists because no retailer has unlimited shelf space or resources. Inventory must be distributed across locations, channels, and periods based on careful planning. Key drivers of allocation include optimizing sales and margin potential at each store while minimizing markdowns and stockouts. If a product sells out too quickly at one location but sits ignored on shelves elsewhere, the retailer loses potential profit. Effective allocation matches supply to consumer demand to avoid lost sales opportunities.

With omnichannel retail, allocation complexity has increased exponentially. Inventory can no longer be viewed at the total company level but must be broken down by channel. Allocation practices will differ for brick-and-mortar stores versus e-commerce fulfillment centers. Within each channel, allocation must match projected demand at the store level based on past sales, demographics, seasonality, events, and new product launches. Misallocation costs retailers millions in lost sales and margin each year.

Top Allocation Strategies

There are several proven strategies retailers utilize to optimize inventory allocation:

• Demand-based allocation uses past sales data, forecasting, and consumer insights to match supply to expected demand. Locations expected to have higher sales for a particular product category or specific SKU will receive a larger allocation. Demand-based allocation helps reduce missed sales opportunities.

• Market-based allocation segments stores into tiers based on sales volume. Top tier or “A” stores receive the most depth of inventory for faster-turning and high-demand products. Lower tier stores will carry less depth or variety. This helps allocate to where products have the highest sales potential.
  
• Space-based allocation determines allocations based on available shelf space and visual plans for each product category and store. Space allocation must align with corporate directives on visual merchandising and planograms. Space-based allocation ensures stores have the right amount of inventory that can be displayed properly.
  
• Inventory turn-based allocation analyzes how quickly inventory turns over by category, store, or channel. Faster inventory turns suggest high consumer demand, indicating a need for greater allocation. Slower turns suggest supply outpaces demand and may justify reducing allocation for those SKUs at underperforming locations. This metric helps identify and correct allocation mismatches over time.
  
• Stock-to-sales ratio allocation establishes target stock-to-sales ratios by product, Store A vs B volume tiers, or across channels. Stock-to-sales measures the relationship of inventory on hand to sales to gauge weeks of supply. Higher ratios indicate excessive stock that could be reallocated. Lower ratios suggest lost sales opportunities. Maintaining the right stock-to-sales balance informs allocation plans.
  
• Lead time-based allocation considers production, shipping, and distribution lead times when making allocation decisions to avoid out-of-stocks. For products with long lead times, retailers may place larger upfront allocations and reorder less frequently. For fast-turning items, more frequent reorders in smaller batches may be preferable. Factoring in lead time constraints ensures allocation plans are executable within the supply chain.

Omnichannel Allocation Approaches 

Traditional store-level allocation is not enough in an omnichannel environment. Fulfillment centers require their own allocation plans based on online demand. Retailers can utilize several techniques to optimize multichannel inventory deployment:

• Separate online and offline allocation plans tuned to each channel’s sales patterns, demand forecasting, and performance goals. This traditional approach provides the most flexibility.

• Integrated planning which allows inventory sharing across channels while still optimized at the channel level. This allows stores and DCs to pull inventory as needed.
  
• Ship-from-store capabilities that unlock store inventory for online order fulfillment. This provides more real-time flexibility to meet digital demand.

• Buy online, pick up in-store (BOPIS) syncs store and online inventory so omnichannel consumers can seamlessly complete purchases.
  
• AI-powered inventory planning software that dynamically shifts inventory in real-time based on channel demand signals to rebalance omnichannel allocation. AI represents the next generation of allocation.

AI-Driven Allocation Management

In recent years, retailers have increasingly adopted AI-powered inventory planning tools like OmniThink.AI and algorithms to enhance allocation. AI looks beyond historical data to detect real-time demand signals across channels. Incorporating AI recommendations allows for:

– More frequent and automated allocation planning and updates versus manual processes. This provides quicker reactions to demand changes.

– Granular, hyperlocal demand modeling beyond store tiers or clusters. AI assessment at the store level improves precision.

– Ability to instantly incorporate new demand drivers like weather, competitor actions, events, traffic, or social media trends. AI allocation stays ahead of changes.

– Continuous forecast updates to replace traditional periodic cycles. AI enables dynamic forecasting.

– Optimal reorder point identification while considering supply factors like lead time and transportation costs. AI balances service level goals with efficiency.  

– Automated order generation and dispatching based on machine learning-driven recommendations. AI removes previous manual constraints.

– Seamless visibility and movement of inventory across channels to rebalance omnichannel allocation in real-time. AI facilitates a singular view of inventory.

Adopting AI facilitates rapid, hyper-targeted, responsive allocation optimization for today’s complex omnichannel environment. With AI, retailers can make each item available to the right consumer, at the right place, at the right time.

In Summary

Allocation management remains both an art and science that directly impacts retail success. Following best practices around demand, inventory, and space planning while incorporating AI enhancements enables retailers to keep pace with omnichannel change. The strategies outlined provide a blueprint for effective allocation to maximize sales and margin while delivering the seamless shopping experience modern consumers expect. Efficient allocation improves the bottom line – when goods end up in the right place at the right time, everybody wins.