In light of market volatility, increasing complexity and rapidly changing buyer habits, brands and retailers must build a resilient supply chain to weather future disruptions and shifts. Leveraging artificial intelligence (AI) to harness the power of data is imperative to long-term success.
AI is ubiquitous. According to Gartner, more than 80% of new supply chain management technology applications will use AI and data science in some way by 2025. Those who don’t invest now risk falling behind.
By implementing digital technology, organizations gain better risk management, improved efficiency and customer experience, increased visibility and enhanced collaboration. According to McKinsey, early adopters have achieved:
- 15% savings in logistics costs.
- 35% increase in inventory levels
- 65% increase in service levels
Let’s explore how AI transforms the supply chain.
Inventory Management
While an integral supply chain component, inventory is incredibly complicated to manage. AI can ease challenges in several ways.
Demand forecasting. Retailers spend an estimated $1 trillion every year on stockouts. However, overstocking carries many of its own costs and is not a viable alternative. AI can reduce inventory conundrums by enabling more accurate demand forecasts.
AI-powered inventory management systems analyze data gathered from many sources to anticipate consumer demand, optimize stock levels and identify potential stockouts or overstock situations. The technology also recognizes inventory data patterns and trends humans may miss, such as seasonal demand or unexpected spikes.
Inventory tracking. AI improves inventory tracking accuracy by monitoring real-time inventory levels, locations and movement throughout the supply chain. For example, a supply chain software platform may use RFID (radio-frequency identification) tags and sensors to follow inventory progress from warehouse arrival and sorting to packaging and shipping.
Integrating supply chain software into other platforms like sales channels and order management systems gives decision-makers a holistic view of inventory across the entire supply chain, from raw materials to customer delivery. This information helps businesses make strategic decisions about procurement, production and shipping. The data also identifies system bottlenecks, such as a slow supplier or an inefficient warehouse.
Automation. AI can automate many repetitive manual tasks involved in tracking and processing stock, increasing efficiency, reducing errors and allowing humans to address more strategic priorities. Task automation especially benefits small businesses, 43% of which lack any tracking or rely solely on manual tracking.
Automation also extends to warehouse robotics. Combining AI integrations, improved sensors and response capabilities, and warehouse management system (WMS) software allows robots to operate autonomously. AI analyzes sensor-collected data to enable robots to make decisions about tracking, transporting and delivery based on their environment and operational needs. AI-powered robots can increase speed, accuracy and safety in warehouse operations, saving money and enhancing productivity.
Returns. While increased online shopping means more returns, data provides a roadmap for navigating those reverse logistics. AI helps you analyze customer data, such as reviews, reason codes and purchase histories, to predict returns and identify root issues. Understanding whether the return was a one-time buyer preference or a problem with the product informs the changes required to address customer concerns and meet their needs more effectively.
More Data for Better Business Decisions
To achieve predictability in the face of a rapidly transforming supply chain, businesses need full visibility into product journeys. Integrating technologies and systems enables data-sharing among key players, including:
- Manufacturers
- Brands and retailers
- Third-party logistics providers
- Shipping carriers
In a non-integrated supply chain, these businesses operate in isolation, providing little (if any) visibility into their contributions to the product journey. The blindspots inhibit informed decision-making.
By integrating systems, businesses gain transparency, enabling them to streamline their supply chain. The simplification results in increased flexibility, reduced operating costs, improved productivity and the ability to scale. AI enhances integration’s benefits with comprehensive data analysis. The technology flags potential risks and offers mitigation recommendations.
Consolidating all real-time supply chain data into a single platform provides quick and easy access and empowers all partners to make quick, informed decisions benefitting every part of the chain. American Eagle is a prime example of successful integration. The company works with more than 100 partners—including other retailers, carriers and tech companies—to consolidate packages and reduce shipping time to stores by 80%.
It’s been repeated endlessly, but it’s true — AI is the future of supply chain management technology. Retailers and brands investing in data and AI today will rise to the top because they’ve positioned themselves to provide a superior customer experience at a lower cost.
