How integrated supply chains and data drive profitability

For over a decade, retail strategy separated physical stores from digital storefronts, operating e-commerce as an isolated sales channel with its own targets, inventory allocations, and operational teams. Marketing spent heavily on paid customer acquisition, while fulfillment teams operated downstream, managing order delivery and returns as purely transactional functions.

In modern retail, that siloed operational model severely damages profitability.

When a customer engages with a brand, they do not distinguish between online and offline channels; they perceive a single brand promise. When stock availability breaks down, delivery communication fails, or physical stores refuse online returns, the customer relationship deteriorates regardless of how effective the digital marketing campaign was.

Having built and scaled enterprise e-commerce platforms from the ground up—scaling digital revenue at PUMA South Africa to over R100 million before taking on global retail data roles and now leading regional strategy as Head of Ecommerce (Southern Hemisphere) at G-STAR—Christopher Baird champions a connected approach to commercial execution. Baird contends that long-term digital profitability relies on operational alignment across merchandising, supply chain logistics, and unified customer data.

“There are multiple customer conversions that happen when somebody makes an emotional connection with your brand—it is not simply a successful checkout,” explains Christopher Baird, Head of Ecommerce (Southern Hemisphere) at G-STAR. “When marketing and content do what they do best- showcasing your product at the right price, do you have efficient sizes available, let alone stock? It is often a disappointing experience if not.”

The Full Customer Journey: From Initial Engagement to the Doorstep

Winning a customer’s initial click is only the first step in a complex fulfillment sequence. A transaction is incomplete until the product is physically handed over at the doorstep and verified by the customer.

Operational breakdowns across size availability, inventory distribution, or last-mile courier delivery directly undo the investments made in digital marketing and customer acquisition.

“Same goes for paid marketing—a click-through resulting in little to no sizes available,” Baird observes. “Then once that emotional connection and purchase is in fact made, we fall short with poor delivery communication flow. Or worse, the very last touchpoint of your brand, the courier driver, delivers a bad experience. That is the last thing a customer will remember.”

Ensuring operational alignment across every touchpoint protects both customer lifetime value and bottom-line margins.

“The journey starts from interest, through engagement and conversion, but only really finishes the race once your beloved product is handed over to the customer on their doorstep,” Baird notes. “It needs to be seamless and effortless. Let’s not get started on returns. This is where online businesses fail, fast.”

Eliminating Channel Silos: Why Physical and Digital Must Converge

Treating online storefronts and physical retail locations as competing business units creates unnecessary friction for shoppers while inflating operational costs.

Customers expect a unified brand experience where physical stores support digital transactions and digital platforms drive store discovery. Restricting cross-channel capabilities—such as refusing in-store returns for online purchases—creates friction that directly undermines customer retention.

“This kills your brand,” Baird emphasizes. “A customer doesn’t see two channels; they see one brand, one store. Systems need to talk seamlessly. Any remote barrier for engagement for a customer between online and offline needs to be removed, especially returns. Not allowing online orders to be returned in your owned and operated physical store is madness.”

Connecting store inventory and physical networks allows retailers to turn physical locations into fulfillment and returns hubs, reducing last-mile shipping costs while increasing footfall for brick-and-mortar stores.

Unifying Customer Data: Building a Golden Record Architecture

Retail organizations frequently collect vast volumes of consumer data across POS terminals, digital storefronts, and loyalty programs. However, without an integrated data architecture, disjointed data leads to misaligned merchandising decisions, channel cannibalization, and wasted media spend.

Building a “golden record” architecture enables retailers to align pricing across channels, optimize size curves, and tailor merchandising strategies to regional market demands.

“Whether you’re starting or growing a mature business, ask yourself: what system architecture do you have, or are you willing to invest in, that builds on a true golden record design for every customer touchpoint and respective attribute with your brand?” Baird advises. “Failing this, you’re uploading great product, allocating a presumed healthy size curve at best, spending a fair penny on paid media, and hoping it sells.”

Data integration prevents cross-channel cannibalization while ensuring product assortments match local customer demand across owned stores and wholesale partners.

“What product do you have in the market elsewhere, physical or online? Does your own direct-to-consumer channel have a clear merchandising strategy? What differentiators are there, are you cannibalizing across channels, and are price points aligned in the market?” Baird highlights. “What is the experience a customer has with your brand, whether on your own store or key accounts? Your data should be driving this strategy.”

Unlocking Return Insights and Applying AI for Relevance

While returns are traditionally treated as a supply chain cost center, return data offers valuable insights into product fit, quality, and customer expectations.

Analyzing why returns occur allows retailers to identify discrepancies between product representation online and physical execution, reducing future return rates and protecting gross margins.

“Retailers often have too much data, but not enough connected data, often measuring what happened rather than understanding why it happened,” Baird points out. “Returns are probably one of the most underused sources of customer insight. They tell you where the promise made by merchandising and content differs from the reality experienced by the customer.”

Similarly, as artificial intelligence tools become integrated into retail operations, predictive models require structured, high-quality data foundations to deliver commercial value. Rather than personalizing every touchpoint for the sake of automation, retailers should deploy technology to remove friction and increase relevance.

“AI is only as good as the customer data, product data, inventory data, and behavioral signals sitting underneath it,” Baird concludes. “If the underlying data is wrong, AI simply automates bad decisions at scale. The objective shouldn’t be to make retail more automated; it should be to make it more relevant. Don’t personalize everything. Sometimes the best customer experience is simply getting out of the customer’s way.”