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Boost Sales and Profitability through Automated, Store-Specific Planogram Optimization

Mar 16, 2021 7 min

When managing a category across hundreds or thousands of store locations and a diverse set of customers, how can you get the benefits of central planning while also adapting to store-specific needs—without defaulting to planning based on averages? 

The answer is store-specific planograms, which can enable variations in assortment, inventory, and space allocation to meet each store’s needs. 

“But wait,” I hear you cry. “The creation of hundreds or even thousands of store-specific planograms is an impossible task!” 

This is true, and it is the reason that automation is the other necessary component in this process. With automation, central planning teams can create a high volume of accurate planograms that are adapted to store needs. These localized planograms have multiple benefits, including decreasing out-of-stocks and overstocks, reducing inventory costs, and improving operational efficiency in stores—replenishment, for example.  

In this whitepaper, we’ll dive further into automated store-specific planogram optimization and the benefits this type of localized planning strategy can facilitate in all areas of a retail business.

Why Do Averages-Based Planograms Fail? 

From large chains to small, retailers know that stores of the same size and in the same cluster (i.e. stores with similar demand patterns) can vary dramatically in sales density. Thus, using averages to plan means that you are never truly meeting the needs of a particular store and its customer base because every planogram is sub-optimal, leading to missed sales through assortment gaps and stock-outs that can have much wider ramifications. 

When a planogram is based on an average, implementation compliance is poor.

When a planogram is based on an average, implementation compliance is poor. Each store will make alterations to accommodate the mismatch between the planogram and the actual space, which means planned facings may not be implemented, leading to stock-outs while inventory sits in the back room rather than on the shelf. At the opposite end of the spectrum, too much space leads to a planogram being over-faced, resulting in poor-looking displays or low stock turns. 

Even when the space matches up, a reliance on averages for planogramming means that overstocks or understocks will occur far more frequently than they would with store-optimized planograms. It is crucial to reduce these inefficiencies and ensure that inventory is adjusted to accurately fit and fill each space based on customer demand, as this dynamic can vary even within a very small geographical area. 

For example, imagine two similarly sized stores located within blocks of one another. Store 1 has very high breakfast cereal sales in relation to space, while Store 2 has a lower sales-to-space ratio for the category. 

As shown in Figure 1, the required inventory to meet the demand for cereal is different in each store. The retailer needs to ensure that cereal out-of-stocks are reduced in Store 1 while at the same time avoiding overstock in Store 2. However, because both stores are using the same average-based planogram, this becomes a complicated process.

Figure 1: Both Store 1 and Store 2 carry the same cereal assortment in the same planogram. Store 1 is understocked in several areas (highlighted in red). Store 2 follows the national average across the chain, so most of its stock levels meet demand properly (highlighted in blue), but it also has a few overstocks (highlighted in green).

Planogram Optimization Can Reduce Costs and Increase Sales

All retailers know that the costliest inventory is inventory that isn’t turning because it accumulates costs and capital interest without generating profits through sales. Centrally designed planograms encourage excessive stock of many lines because they do not consider the local demand. 

When planograms reflect the forecasted local demand, batch size and delivery schedule efficiencies throughout the supply chain can be maximized. This can then lead to increased stock turns. In fact, food retailers can see up to 3% increase in sales with store-level planograms.

With local planograms, retailers often see an immediate 2-10% reduction in stock, depending on the format size and limiting factors on the optimization. For example, the smallest convenience-store formats, where almost all products have only one facing, experience minimal impact, while larger format stores, which have more space to play with, tend to see the largest falls in inventory value.

Even fresh products benefit from this localized approach. No retailer wants to have their presentation looking sparse, but filling shelves with slow-to-sell pre-packed meat or cold cuts is not good business and can lead to waste. Optimizing shelf space for goods at risk of spoilage for a particular store can results in a drop in waste of up to 10%.

Therefore, optimizing planograms at the store level can drive costs down and increase sales by:

  1. Reducing handling costs. One-touch replenishment increases efficiency in stores and the upstream supply chain.
  2. Decreasing inventory-related costs, such as inventory carrying cost and wastage.
  3. Improving shelf availability. Fitting space to demand reduces restocking as well as lost sales from errors or late restocking. Customers cannot buy items if they are in the stock room rather than on display.
  4. Improving item placement. When best-selling items have more space and are placed in an optimal location, it is easier for customers to buy them.  

It should be stressed that store-level planogramming and stock optimization can be carried out both with a completely centralized assortment as well as with any cluster or store-specific assortment. The idea is simply to optimize the shelf space for each product in each store based on its sales volume, margin contribution, pack size, and delivery frequency. 

Improve Efficiency in Store Replenishment and the Upstream Supply Chain

The greatest efficiency gains from locally optimized planograms are made by optimizing store shelving and subsequently reducing in-store handling through a one-touch replenishment model. When shelf space is configured accurately to incoming stock, each replenishment delivery can be stacked immediately on display units, achieving one-way inventory. 

As a result, costs are lowered because:

  • Staff don’t have to take excess stock to the back room after filling shelves to capacity.
  • Staff can use the back room more efficiently because it won’t be overfilled with unnecessary inventory.
  • Staff don’t need to restock fast-selling products as frequently.

The impact of store-level planogramming on food retailers’ costs can be significant. The physical handling of stock often accounts for as much as 30% of store labor costs—it is the largest labor-related expense after checkout staffing. Planograms created for individual stores can lead to a 5-10% reduction in the labor costs associated with shelf replenishment. 

Automating Store-Level Planogram Optimization Saves Valuable Planning Time

Store-level planogram optimization seems like a no-brainer. Higher sales margins with lower costs—what’s not to like? The biggest factor holding retailers back is the perception that creating and optimizing planograms is challenging and time consuming. Implementation projects are often anticipated to be long and drawn out, with uncertain outcomes and high costs.

Consider a retailer with 1,000 stores, each with five planograms that must be updated weekly due to product switches or category reviews. If one planner builds ten planograms a day, the retailer would need 100 planners to handle these tasks in an average week. The retailer must also manage the ongoing training required to ensure that the planning team keeps on top of its game.

By automating planogram optimization, users can configure any parameters and apply them en masse to many thousands of planograms.

All of this work is just not feasible for most retailers. However, automation can solve many of these issues, relieve planner concerns, lighten the planning team’s load, and remove the barriers to implementation of store-specific planogramming. By automating planogram optimization, users can configure any parameters and apply them en masse to many thousands of planograms. This means that the retailer will not incur an additional cost for adjusting a planogram’s inventory to reflect layout and local consumer preferences—and, in fact, they will save money. 

Moreover, today’s technology and automation can radically reduce the labor involved in store-level optimization. This means that costs are reduced further while planners have the room to reallocate their time to more value-adding tasks. 

Even the maintenance of planograms can be aided with the use of automation in the category management process. For example, large grocers typically carry out a major category review every 12-26 weeks, while weekly reviews are used for minor changes, such as product introductions and ramp-downs. With automated planogram creation, the time and cost barriers to category management at the store level can be more or less eliminated.

Until recently, there simply wasn’t software that was capable of being configured to build and optimize accurate store-level planograms automatically. Now, there are technologically advanced solutions that allow for this automation so that planograms can be created based on a retailer’s merchandising guidelines and each store’s demand profile. Such automated planograms, tailored to the needs of individual stores based on localized forecasts, are highly accurate and extremely effective. 

Let’s return to the earlier example of Stores 1 and 2. By introducing automated planograms that have been individually optimized for each store, overstocks and out-of-stocks of cereals have been all but eliminated, as shown in Figure 2. The space for cereal in both stores has been adjusted to fit more accurately, while the replenishment of cereal has been tailored for each to ensure that the deliveries fit the shelf. 

By implementing automation to create store-specific planograms, the central planning team would be able to reduce the time they used to spend on manual work by up to quarter, based on RELEX’s experience with retail customers. In fact, the automation makes it possible for the team to save this time even though the number of planograms they had to manage increased.

Figure 2: Store 1 and Store 2 with store-specific planograms for cereal in place. By implementing localized planograms, Store 1 and Store 2 have nearly eliminated overstocks and out-of-stocks of cereal. Each store is now optimized for its unique demand pattern (highlighted in blue).

Quickly Reap the Benefits of Localized Planogram Optimization

A quick and painless way to measure the benefits for a retail operation is to run a pilot of localized planograms in a selected subset of stores. Typically, the pilot will highlight that the benefits of such a strategy outweigh the effort and expense of implementation so heavily that the business case is irresistible. For example, East of England Co-operative Society, which is the UK’s fourth-largest consumer cooperative, was able to increase availability by 5% with store-specific planograms.

Based on RELEX’s experience with our clients, we have seen that automated, store-specific planogramming can increase sales by up to 3% and decrease waste by up to 10%. Implementation of automated and localized planograms is low risk and low cost with high potential for benefits that deliver rapid results. So, what are you waiting for?

Written by

Sam Welton

Product Strategy and Management Lead