The Subtle Art (and Science) to Successful Retail Allocation

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Knowing how and where to allocate products to the right stores can make or break a retailer. We live in a consumer-centered world. For better or worse, thanks to companies like Amazon, customer delivery expectations have changed so that they expect to get what they want and when they want it at the single click of a button. Often, this product can arrive on their doorstep the very next day.

Not wanting to be left in the dust, many brick-and-mortar stores are utilizing tools enhanced with artificial intelligence to master the subtle art of retail allocation. In today’s retail landscape, companies who do not utilize advanced analytics to allocate their products will be left behind or even fail completely. 

The Subtle Art to Retail Allocation Relies on Data 

Without the use of advanced analytics, allocation is cumbersome. Many retail allocators rely on legacy systems and Excel-based spreadsheets, making their job incredibly difficult to deliver accurate and effective store allocations. This is because, in most cases, you’re not doing this for just one product in one location. You’re trying to understand how to best assort thousands of products across hundreds of stores.  

When you add advanced analytics to the mix, allocation becomes a lot easier. This type of predictive technology is key to enabling more informed inventory decisions by providing insights at a granular level, where various components – including product attribute need — can be taken into account. These tools bring about a number of benefits, including improved allocations to increase sell-through and significant time-savings for allocation professionals.  

The Method Behind the Science

There was a method and science to how the painter, Bob Ross, expertly crafted his paintings with diligence and precision. If you look closely at his works of art, you’ll notice the broad strokes and care that went into making those little trees and clouds on the canvas so happy. 

This couldn’t be truer than when we talk about using sparse retail data, combined with advanced analytics, to inform precise, accurate inventory decisions throughout the allocation process. By introducing science to the art of retail, advanced analytics tools can provide a more accurate method for delivering allocations that reflect true store-level demand. In the end, retailers can ensure stores are kept in stock with respect to their ability to sell merchandise.  

How Lucky Brand Mastered the Art (and Science) to Successful Retail Allocation

The subtle art to successful store allocation is far from simple. In fact, a recent U.S. retailer survey estimated inventory misjudgments, including misallocating inventory, account for more than half (53%) of unplanned markdown costs. This issue has prompted retailers, like Lucky Brand, to search for ways to infuse intelligence into their allocation systems and processes. In fact, Mike Relich, COO of Lucky Brand, highlights the fine balance between the art and science of allocation at NRF earlier this year:

 

In our consumer-centered world, knowing how and where to allocate your products to the right stores can make or break a retailer. Utilizing advanced analytics to successfully master the subtle art of retail allocation will ensure your stores stay “happy little trees.”

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Topics: data overload, allocation, artificial intelligence, inventory optimization, ecommerce, brick-and-mortar retail, data, cross-channel demand, advanced analytics, technology adoption, customer preference, accuracy, demand prediction, markdowns

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