The state of order fulfillment is so far beyond what retailers could have imagined just a few decades ago. In the era of ‘see now, want now’ brands have no choice but to conform to industry expectations around quick and free delivery. Despite a shift towards one-hour, same-day, or, at most, two-day delivery, retailers still struggle to get fulfillment right, leaving money right smack in the middle of the table. Here’s why retailers continue to battle for profits from efficient order fulfillment:
Consumers Are REALLY Spoiled
We’re spoiled. Really really spoiled. There is no waiting in today’s consumer society – immediate gratification is the only certainty, especially among younger generations accustomed to the ‘always on’ connected environment (enabled by technology + social media) and Amazon-inspired shopping experiences:
“Consumer demand for free shipping and shorter order fulfillment lead times is pressuring retailers to continually improve fulfillment performance while redesigning their inventory placement strategies.” – Tom Enright, VP at Gartner
The fast-free-anywhere (anywhere = omnichannel) delivery model is undoubtedly giving retailers a run for their money. Meeting this expectation is an undertaking no legacy retail business model was prepared to handle, and, as a result, have triggered costly investments into transforming existing structures to meet consumer desires.
Your OMS Can Only Do So Much
In addition to market demands, the tools retailers traditionally rely on also present a major roadblock. To meet customer delivery expectations, many order management systems (OMS) retailers use for online transactions rely on one or two decision points to make the ‘best case’ fulfillment decision.
But this comes at a cost.
The minute you throw in more variables, you know it’s at the expense of another – leaving *lots* of gross margin on the table. While your OMS plays a vital role in the order fulfillment process (like managing orders at scale & throughput), the rules-based, optimization side of things could use a little help to ensure the most profitable outcome:
“The enterprise order management solution needs to be smart enough to optimize the shipping for the greatest margin/sales opportunity.” – Supply Chain Dive
Retailers are infusing advanced analytics into their order management processes and seeing as much as a 7-figure return within just a few months (more on that at the end of this blog).
Other Variables Add Up 💸
A recent HRC survey polled C-level retail execs on the challenges of online retail execution, and you know what they said? Nearly 70% of execs polled said they are “not optimizing their customer order systems to prioritize filling the entire order from one location, causing split shipments and increasing freight costs.”
This ties back to the inefficiencies of your traditional OMS – which is at the core of the problem. However, we can’t ignore the operational and logistical issues that emerge as retailers try to fulfill online orders in an omnichannel environment where inventory inaccuracies, store transfers, and transportation costs all come into play.
All the extra costs tied to not fulfilling the right product from the right place add up. We recently interviewed Marc Chretien, the Sr. Director of eCommerce at the ALDO Group, who shared how anticipating demand better can help mitigate these costs:
“The better I can predict the right demand in the right store, the better chance I have of making the best fulfillment decision. Then I can protect the 'hot' stuff in the 'hot' stores, and I can move out the 'cold' stuff in the 'cold' stores —allowing you to get more conversions or margin out of every transaction.” - Marc Chretien, Sr. Director of eCommerce at the ALDO Group
Fine-tuning inventory decisions for fulfillment in the omni-channel age is where retailers can improve margins and still provide delivery offerings consumers want.
A Case for Adding AI to Your OMS
How exactly can retailers fine-tune inventory decisions around fulfillment? How can you ensure you're making the most out of every e-commerce delivery? One approach is by infusing your existing OMS with predictive analytics powered by machine learning and artificial intelligence.
Going back to the HRC survey I referenced earlier, most retailers still struggle to figure out how to integrate predictive analytics into their operational processes. While only 14% of respondents claimed to be using predictive analytics, Gartner expects global retail technology spending to reach $203.6B by 2019 as customer expectations and competition force retailers to evolve and invest heavily in digital business transformation.
Major brands like ALDO and Lucky Brand are seeing up to 6X ROI improving omni-channel fulfillment by more accurately predicting customer demand (in real-time) to determine the best fulfillment scenario. The results are crystal clear: an increase in gross margins through improved inventory turns, speed to customer, and decreased split shipments — all while reducing shipping costs. Stop losing money on delivery and see how AI can impact your margin on order fulfillment.