Optimize Omnichannel Fulfillment for the Holiday Season

holiday-gift-delivery-1We’re just a quick block and jingle bell ring away from the holiday season — a high stakes, strategically coordinated shopping season retailers strive to perfect each and every year. 

At this point, inventory assortment plans and buys have been squared away.

However, once the frantic shopping frenzy ensues, the scale of orders coming through (from any and all channels) becomes increasingly difficult to manage. When an e-commerce purchase is made, retailers are bending over backwards to meet customer expectations even at the expense of a more profitable sale.

“[O]nline sales are growing at a respectable rate for many omnichannel retailers in large part because they continue to bear nearly all the associated costs of attracting and accommodating online shoppers, while their store-based sales often languish.” - WWD

FTI Consulting forecasts U.S. online retail sales will reach $525 billion by the end of 2018, which represents a 15.9 percent gain over 2017. As retailers muster every last bit of strength they have to finish off this marathon of a year, it’s evident there is room to improve online fulfillment to ensure you’re not sacrificing margins and sales in other areas (while also meeting consumer delivery expectations).

With machine learning and advanced analytics, the chance to level up your omnichannel fulfillment strategy is low-hanging fruit for the holiday rush – a huge opportunity pounding loud and clear on your door. 

The biggest holiday order fulfillment challenges in retail 

The larger forces driving fulfillment challenges today are beyond our control. Consumers want what consumers want — even more so during the holiday shopping season. If this means quick and free delivery, then someone will deliver on these expectations.

In fact, 83% of consumers have chosen not to purchase a product because of shipping costs:  

 (Source: IBM 2016 Consumer Expectations Study)

Additionally, 77% of consumers will buy from a retailer who offers free shipping versus one who doesn’t, even if they have never ordered from them before. 

“Now is the time to plan for 2018’s peak shopping days. 2017 was the first time since the inception of our study five years ago that almost a third of retailers opted not to provide a guaranteed shipping date to consumers. While that may have helped them not disappoint, it may also have driven customers to another retailer who could predict a delivery date with greater accuracy. Which retailer do you want to be?” - Accenture

The point is this:

The endless treadmill of choices (enabled by e-commerce) levels the playing field to any retailer who can deliver exactly what a shopper wants when they want. 

Customers expect everything in stock, all the time, regardless of channel. However, from a retailer’s perspective this means managing multiple sources of demand with multiple ways to get products to customers (i.e, ship-from-store, BOPIS, etc.), resulting in: 

  • Enormous strains on inventories and demand forecasting
  • Excess inventory costs and unnecessary markdowns 

What can we do differently today to protect our margins in the face of consumers’ incredibly difficult-to-meet expectations?

Is ship-from-store working to your advantage? 

Clearly, the biggest differentiator among most traditional retailers is their brick-and-mortar stores. Much like Amazon owns the delivery game with its vast distribution network, retailers can leverage their storefronts to fulfill online orders.

The most obvious advantage? 

Store location puts you much closer to the customer. 

But… 

  • Do you know the forward-looking demand for a particular store?
  • Does the store have the right inventory to satisfy in-store and online demand?
  • Can the store successfully pick and pack? 

Each consideration factors into a successful omnichannel fulfillment strategy – and executing properly is not easy. How can we leverage our network of stores efficiently and profitably to ensure we deliver the holiday season as best we can?

Solving omnichannel fulfillment goals with advanced analytics

What does a successful omnichannel fulfillment strategy even look like?

You’re more than likely already doing some level of ‘optimization’ for online fulfillment; perhaps you incorporate a couple of decisions points (such as proximity, markdowns, or weather patterns) into a traditional order management system (OMS).

While your OMS system holds a vital role within the fulfillment process, it isn’t enough to get the job done alone. When an online purchase is made, the timely delivery of an order to a customer relies on a shortsighted, rules-based approach.

However, this approach is totally flawed. The variables you want to optimize often compete with one another. For example, how can you maximize inventory turn if you’re fulfilling orders from a store likely to sell out because the OMS is targeting proximity to the customer?

Consequently, you’re sacrificing an opportunity for a full price sale in-store at the expense of an OMS recommendation. 

What if you could ensure you were making the most out of your inventory available in-store?

“Ultimately, consumer preferences, product characteristics and geographic context need to be analyzed granularly and in real-time to enable dynamic fulfillment decisions at the single-order level.” - Accenture

With advanced analytics, you can drive predictive insights on localized customer demand into your current OMS decision-making to process orders in real-time while dynamically balancing numerous variables at once.

In fact, retailers like the ALDO Group benefit tremendously from advanced analytics tools, seeing as much as a 6X ROI through improved omnichannel fulfillment

The inevitable surge of online orders and holiday foot traffic will make it even more challenging for retailers to efficiently fulfill orders in the upcoming months, so it's best to get ahead of the game with advanced analytics to exceed customer expectations while improving margins. 

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Topics: order fulfillment, fulfillment optimization, cross-channel demand, demand prediction, customer preference, advanced analytics, holiday shopping, ecommerce, holidays

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