Modernizing the Retail Supply Chain with AI For Resilience and End-To-End Optimization

The retail industry seems to exist now in an unending shockwave of change, as the effects of COVID, geopolitical forces, and an inscrutable economy continue to rattle the markets. First, the pandemic accelerated retailers’ ecommerce transformation. Then, pandemic missteps compelled retailers to rethink legacy supply chain processes and systems. From scrambling to get supply to consumers during lockdowns to recent over-inventorying on the heels of COVID and inflation, retail leaders are now prioritizing supply chain visibility, building resilience against disruptive forces, and keeping costs under control. This overdue digital transformation of the retail supply chain includes the adoption of machine learning and artificial intelligence technologies, which are helping retailers use data in a streamlined way for end-to-end optimization of the product journey, from the supplier to the consumer.

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Staying Ahead of Fluctuating Consumer Demand in Retail Supply Chain

Wildly shifting consumer demand has plagued retailers over the past few years.

McKinsey’s 2022 supply chain survey revealed that demand planning was the #1 priority for digitization among global leaders, among which 80% intend to or are already leveraging AI/ML for planning. Supply chain executives need technology to minimize excess inventory and stock outs, predict demand for new products, and factor in local market conditions. AI can synthesize insights from massive amounts of data, from weather and perishable items to historical data and promotions, to prevent waste and inefficiencies and keep pace with unpredictable external factors, leading to a more accurate picture of future demand. If a brand doesn’t have the product when demand spikes or the product is delivered late, revenue is lost, and customer experience suffers. Further, the speed of AI solutions makes it possible to deftly course-correct based on sudden market disruptions.

AI-Optimized Inventory for Accurate Availability and On-Time Delivery

Seventy per cent of global supply chain leaders are planning to change their inventory management strategies in late 2022 into 2023. Retail leaders need to optimize inventory by determining the right stock levels without negatively impacting customer service, while generating supply chain cost savings. Whether facing a supply crunch or selling with excess stock, a lack of visibility into inventory data will lead to customer experience failures.

Retailers that fail to get closer to a demand-supply balance using manual processes will continue to experience expensive spoilage and out of stock scenarios, as well as profit margin losses and customer frustration. Many big retailers such as Target saw profits fall 90% in Q2, now having to cancel orders and reduce prices to move excess inventory. AI solutions can increase visibility into inventories, reduce inventory holding costs, reduce non-moving inventory, trim fulfillment costs and transit times. Best of all, they keep the customers happy with accurate availability and on-time delivery.

Automated and intelligent inventory management is critical for making the supply chain more agile and responsive to change.

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Reduce Supply Chain Impacts With Interconnected AI and End-To-End Approach

Demand planning and inventory management are symbiotic functions wholly reliant on each other’s precision. AI/ML solutions are available for inventory management, demand planning, capacity planning, logistics – every step of the supply chain. While specialized AI applications can provide valuable data-driven insights to create efficiencies at every link in the chain, interconnected technologies that talk to each other across the supply chain can capitalize on the entire workflow and aggregate mountains of data. This more holistic approach yields actionable insights from across the chain, which, when compiled, can power intelligent decision-making in alignment with overarching business objectives.

McKinsey found that supply chain leaders who increased their end-to-end visibility in this manner were twice as likely to report no challenges from 2022’s supply chain impacts.

Taking it a step further, if brands can find ways to share supply chain information between vendors and other partners, they can create unprecedented optimization. If Target can predict a rise in its customers’ demand for, say, skateboards, they can communicate with their supplier, thus avoiding a potential shortage and lost revenue.

Retailers Can Get Ahead of the Competition Still Using Legacy Processes

Since most businesses are still relying on manual methods to monitor supply chains, retailers that leverage AI technology to optimize supply chains will gain significant differentiation against the competition. Retailers are moving toward data and automation to build resilience in the face of numerous challenges, including workforce shortages, changing geopolitical dynamics, a recession, new regulations, and lingering supply chain bottlenecks.

Retail supply chain leaders can take control of their own destinies by using AI/ML to reimagine the product journey, tracking assets, and monitoring their locations in real-time, optimizing routes for faster last mile deliveries, planning the workforce in warehouses, and more. Poised to move from being disrupted to the disruptors, retailers are using AI to become more assured in the face of uncertainty, taking data-driven decision-making to a new level to drive intelligent outcomes and future-proof operations.