The Challenges of Sequential Allocation

merchandise-store-shelves-hangersIt’s almost that time of the year – Amazon Prime Day’s a-looming. The midsummer, Black Friday equivalent and annual reminder to retailers of one of the most wildly successful loyalty campaigns ever created. 

This four-year-old online shopping “holiday” is also a clear reminder to retailers of this:

It’s time to step up your game.

Beyond the Prime Day phenomenon, Amazon’s success stems from understanding what their customers want. 

In essence, understanding what your customer wants means the ability to offer the right product in the right place at the right time: the ultimate challenge retailers face today.

Perhaps not surprisingly, a huge part of this challenge can be traced back to a retailer’s allocations. You can have the best assortment plan in place, the perfect quantities purchased—and yet, you continue to see unsold product, day after day, that should have sold well at store A or out-of-stock situations at the supposedly-low-demand store D.

It’s not easy to know ahead of time that you should have stocked 30 more pairs of faux fur slide sandals in a size seven at Houston’s Galleria store. While hindsight’s 20/20, it’s also freakin’ costly. 

Here are some of biggest allocation challenges retailers need to quash ASAP:

Challenge #1: Too Many Variables to Consider

Retailers are flapping their arms, gasping for air, straight up drowning in data. 

As such, when it comes to time to prioritize what goes where there are just way too many variables to consider. Merchants have to consider hundreds of store locations, countless SKUs, space/presentation constraints, plus the inventory already in stores—you can see how prioritizing objectives can easily get overwhelming.  

How merchants gain valuable, and most importantly, accurate insights from such a vast pool of information without advanced technology is beyond me; it’s just not humanly possible.

Additionally, the sheer fact that most retailers approach allocations sequentially—that is, allocating purchase orders one at a time as they come in, instead of balancing all purchase orders at once—is indisputably prone to error.

Why is this? 

Because the costs vs. benefits merchants evaluate to make their allocation decisions isn’t considering all the potential plays at hand. Instead, they’re making below-average allocation decisions as each purchase order (PO) comes in, without considering the fact that maybe the faux fur slide sandal in a size seven had an unseen demand at the Houston Galleria store –whose allocations were already filled prior to this PO entering the system.  

Challenge #2: Time Consuming

The approach allocators use to make these decisions is far from simple. Consequently, it’s also really time-consuming.

Considering today’s demand for more agile, responsive business models, time is money. 

The traditional approach attempts to distribute PO’s proportionally across stores with the goal to get inventory in and out quickly—yet, it’s ineffective, inaccurate, and really slow from a business process standpoint.

Using advanced analytics tools to simultaneously consider and optimize hundreds of PO’s can actually save merchants significant time that can be spent on really important things like, oh strategy, rather than on tedious grunt-work.

Believe it or not, advanced analytics technology can shrink the traditional allocation approach from one week of work down to one hour.

Challenge #3: Top-Down vs. Bottom-Up Approach 

Lastly, typical allocation usually takes a top-down approach–i.e., using your merchandise financial plan to drive decisions for what goes where. 

The biggest drawback to this approach is that it overlooks one huge aspect of your business: what your customers want.

As if allocators needed another data point to consider, taking into account consumer demand definitely trumps all other factors. While it might seem painfully obvious to take into account consumer demand when it comes time to make important allocation decisions, it’s really the underlying issue retailers face today across all aspects of their business.

That being said, the allocation process is no exception.

All merchandising decisions need to account for customer demand at the store location level. It’s that simple. Advanced analytics tools just make it possible for merchants to put this into practice. 

It’s Time to Step Up Your Game 

If you’re tired of end-of-season markdowns killing margins or missing sales opportunities because of reoccurring out-of-stock situations year over year, it’s time to make a change.

Take advantage of the tools available now to really understand who your customers are and what they want. Once you understand this, once you gain actionable insights from this valuable information, then and only then will you make better decisions throughout every facet of the retail business – and that Houston Galleria store will be stocked to a tee with whatever type of slide sandal your customers want.

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Topics: allocation, localization, advanced analytics, customer preference

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