As supply chains become smarter and increasingly leverage insights to serve customers in new ways, the old transactional models are no longer sufficient.
Gartner notes that 65% of purchasing now begins with a search. Rather than focusing solely on attracting customers at the point of sale, retailers should consider capturing attention at the point of search. Abandoned shopping carts result in lost sales, often influenced by shipping and return policies. This presents an opportunity to directly impact revenue and sales by offering more compelling options to convert abandoned carts into completed purchases.
Amazon’s adoption of one- to two-day delivery has put pressure on retailers hoping to protect their margins. However, rapid fulfillment—which delights general consumers—may not always be necessary. Both B2C and B2B customers often make purchase decisions without considering next-day delivery. Flexibility in pricing, delivery times, and final-mile fulfillment can create new value. For example, if your wife’s birthday is next month, you don’t need the gift delivered the next day—you might prefer it to arrive on a specific day to create a memorable experience. Retailers who understand this and offer diverse purchase and delivery options can more easily win the sale.
Access to customer data and point-of-sale (POS) system data is crucial for identifying attractive options and determining which offers should be presented to customers during their search. On the back-end, this requires managing complex data flows: retailers need to know the status of all inventory ready for fulfillment. With this information, they can begin analyzing and predicting delivery times based on customer location, inventory levels, order details, carrier capabilities, and scenario simulations. Retailers can optimize inventory and delivery routes to meet customer demand at the point of search, offering personalized options that engage customers while minimizing costs and operational burdens. This strategy shifts the focus from rapid delivery to precise fulfillment based on customer needs, leveraging supply chain data and insights.
Each company in the supply chain tends to operate its own enterprise systems, making cross-business visibility and collaboration challenging. Standalone systems—such as ERP, TMS, and WMS—create silos and barriers that hinder data flow and visibility. Traditional methods, like portals for suppliers and partners to exchange documents, enabled commerce but often caused data delays and limited true visibility. Companies often compensated by pre-stocking inventory at key locations, but in today’s supply chains, which aim to reduce inventory and optimize stock levels, this approach creates a dead end.
The vision of adjusting inventory and transportation to deliver personalized customer offers using predictive intelligence is not achievable with legacy, enterprise-centric systems. Traditional centralized distribution networks were designed for past environments, but today’s supply chains must operate as a connected network, customer-centric at their core.
To achieve this vision, partners must be connected in a single network—everyone using the same system, interacting and working from the same data set. No duplicate data or transfers between systems. Everyone sees the same dataset. AI and machine learning offer opportunities to enhance operations, but their value is limited without high-quality, reliable data. A carefully curated and accurate data network becomes the digital foundation for predictive and prescriptive analytics.
In a single-instance network, every node in the supply chain has visibility, connectivity, and collaboration capabilities. When AI and machine learning are applied, analyses—such as predicting delivery times—can be applied to each node. With this in place, new opportunities arise for multi-option customer service based on trusted data. When these analytics are reliable enough for retailers to confidently craft offers for customers, the supply chain becomes a competitive advantage, generating new revenue streams. Through accurate, connected data networks visible to all partners, a digital foundation is established that accelerates innovation, adapts to customers, and embodies the essence of a customer-centric supply chain.
