Maximizing Full Price Sales Potential Through Allocation Strategies

Maximizing the full price sales potential of an assortment is the goal of every planner and allocator. The benefits are numerous, from improved cash flow, increased open-to-buy, increased margin, all the way down to consumer perception of the brand and avoiding customers being trained to show the markdown. The goal is clear, but getting there is harder than expected and has some difficult challenges to overcome.

While building the right assortment and buying an appropriate amount of inventory is the starting point on the journey to improve full price sell-through, the execution of that assortment plan through the allocation process deserves just as much attention. Afterall, a poorly executed plan is no plan at all.

In this article, we discuss allocation strategies to maximize full price sales potential and what allocators need to consider, to make this happen.

Develop a strategy

Developing an allocation strategy will answer key questions about how the distribution of product will materialize and form the basis for measurement of success and adjustments to the strategy as required. An allocation strategy should answer some key questions.

• What - Deciding what product should be allocated is typically pre-determined based on what has been bought in the assortment process but allocators in collaboration with planners may need to make changes based on trends and constraints that occur in the supply chain from time to time.
• Where - Determining where the product will be offered is often decided as part of a localization exercise using clustering in the assortment planning process. Allocators however should identify gaps in the stores at a tactical level and be able to change the locations a product will appear in based on the latest trends and insights from their allocation solution.
• When - Defining the ideal launch and exit date of a product provides the basis for measurement of performance over time. Modern allocations solutions allow for these dates to be easily shifted as trends change and the impact of the shift to be evaluated in real time.
• How Much - How much to allocate can be determined in a number of ways. Allocating to a demand forecast will yield the best results when compared to traditional push strategies.
• Constraints - With every allocation strategy, there are certain constraints that need to be considered including inventory availability, presentation standards and others.

Setting a strategy allows allocators to measure the actual performance of the product and adjust the strategy or employ AI/ML solutions to adjust the strategy automatically.

Allocate Demand, Not Inventory

This may not be an intuitive strategy at first, but allocating demand allows the allocator to focus on how much they expect the product to sell while their inventory optimization engine will determine the optimal distribution of inventory to meet the demand in the right place, at the right time and account for all the inventory and supply chain constraints, automatically.

To allocate demand, you will need to develop an initial model for how a product will sell, this could include the following

• Utilize an existing demand forecast for core products or estimate a rate of sale through data analytics for new products.
• Determine the shape of the demand through analyzing seasonality and promotional impacts on the product in question
• Spread the demand to a location level by analyzing the relative productivity of similar products in the locations historically.
• Account for product sizing by calculating the size spread at a location level to understand the unique characteristics of sales by size by location.

Calculating a location/sku level demand forecast by modeling the steps above, provides the basis on which to quickly adjust to the latest trends and account for any expected dips or spikes in the future demand.

Allocate to Demand

Now that you have established a demand forecast, allocating the ideal inventory to meet the demand is the next step in maximizing full price sell-through. Not only does it form the basis for an initial allocation but can form a projection of the expected future distribution of inventory through to the end of the expected life of the product. This approach offers a number of key benefits

• By allocating to demand, lead time and other constraints can be used to postpone the distribution of stock for as long as possible to get the best read on where the stock is most likely to sell.
• Demand based allocation projects the need to promotions and seasonal variation ensuring stock is in place ahead of a promotion and reduced in advance of an expected dip in demand
• Allocating to demand allows for the optimization of limited source inventory. Demand becomes the primary deciding factor on which store should get a share of the limited inventory.

Allocating to demand ensures the right product is in the right place at the right time maximizing the potential to sell through the greatest quantity of inventory at full price.

Understand Realities

While a demand driven allocation solution will provide an optimal solution, there are realities of supply chain constraints and store requirements that may not be optimal.

• Presentation standards are important for any retailer to make their stores appealing to customers, this may not always be the optimal allocation of inventory but having a presentation standard can provide stores with the potential to sell regardless of the expected demand.
• Pack allocation is efficient but can end in sending more or less stock to a store than is absolutely required. Optimizing to minimize the overage or underage of a pack allocation by defining the right packs and filling in with singles can minimize this impact
• Lead time and schedules affect the amount of inventory that is sent to a store, ideally a store would be able to replenish daily or hourly but the reality is that there are costs involved in shipping frequency and finding the best balance of sending enough stock to account for cost effective delivery schedules is an important tradeoff to make.

The realities of allocating products will result in a less perfect outcome but understanding and planning to minimize those impacts is key.

Measure, measure, measure

The act of measuring the performance of your allocations does not have to rest on the shoulders of the allocator. Instead, utilizing advanced AI/ML solutions to re-trend the demand plans and measure the probability of sparse intermittent demand at the location/sku level can free up the allocator to focus on the big picture and adjust strategies where needed to change the trajectory of an affected product.

• Re-trend of the demand forecast is incredibly important and any solution from a simple exponential smoothing to the most advanced deep learning engine will improve the potential to put the right product in the right place.
• Reporting on exceptions and associating actions to each exception is important for allocators. Excess inventory in stores, for instance, can be redistributed before the need for a markdown with the potential for a lower margin impact. 
• Roll up and compare your allocations to the assortment and merchandise plans to confirm the execution of those plans aligns with the targets. This process is made much easier if your allocation approach is demand based and provides a projection into the future.

Measuring the performance of your allocation strategy is key to success in maximizing full price sell-through as it offers early warning on potential issues and allows for corrections before markdowns are required.

Conclusion

Together, these strategies provide the best opportunity for retailers to improve their full price sales potential. Setting a strategy, allocating to demand, understanding and accounting for the reality of constraining factors and measuring the performance of the allocation plan are the cornerstone strategies in a successful allocation solution.

In reality, these strategies are difficult to execute in traditional excel spreadsheets but the benefit of improved margin, decreased inventory and happy customers surely outweigh the cost of investing in available technology to help.

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