To tackle the complexities of modern supply chains, businesses are prioritizing agility, resiliency and sustainability, as they navigate rising transportation and freight costs, complexities in demand forecasting, and gaps in visibility. 

Following are five megatrends that are currently at play across the supply chain ecosystem.

Green and circular supply chains. The importance of environmental compliance is driving the adoption of green supply chains, with sustainability an integral component. Enterprises are shifting to circular supply chains with increasingly distributed and interconnected networks of players, along with multidirectional flows of information, goods and money.

Reverse logistics. The prevalence of business-to-consumer deliveries emphasizes the need for logistics that involve managing returns and buying surplus goods and materials. The backward movement of goods from customers to sellers or manufacturers requires well-designed supply chains that are responsive to disruptions.

Micro supply chains, micro-warehousing and fulfillment. To accommodate the growing diversity and complexity of consumer demands, including the need for customization, businesses must deliver value without impacting costs. Micro supply chains are agile, small and decentralized operating models that optimize delivery systems and reduce the costs associated with the complexity and variety of products.

Visibility, traceability and location intelligence. Data is the critical component of supply chain operations. Visibility across a supply chain requires real-time insights on materials, orders, suppliers and products, to improve planning at a granular level, ensure efficiency, reduce disruptions and be able to make time-sensitive decisions.

Deglobalization of supply chains. Excessive concentration in certain markets and port congestions are leading to a drastic increase in inventory levels globally. To navigate this challenge and to build a resilient, long-term supply chain strategy, enterprises are considering the deglobalization of supply chains.  

Businesses have achieved varied levels of digital maturity with the application of innovative technologies such as artificial intelligence, machine learning, natural language processing, deep learning and computer vision. They’re using those tools to forecast orders, achieve end-to-end inventory visibility, and improve the reverse logistics experience. AI and ML-integrated models analyze both structured and unstructured data to streamline inventory and logistics management, warehousing, distribution and monitoring.

Recent developments in smart supply chains have driven innovation in predictive analytics, ML and computer vision. Service providers are investing in analytics to use data for improved planning and operations, and apply advanced algorithms in tandem with AI and ML-powered models across the supply chain. Over the years, providers have developed deep domain expertise that helps them spearhead evaluation scenarios to identify optimal operational metrics, and define micro-level segmentation to analyze and predict demand. 

Innovations by leading analytics service providers include the following:

Next-generation control towers. Cognitive technologies such as AI, ML and intelligent automation have evolved supply chain control towers over the years to provide end-to-end visibility across every aspect of supply chain and logistics operations, mitigating inaccuracies caused by data silos. A comprehensive control tower strategy brings superior advantages in operational efficiencies and customer experience.

GenAI in supplier risk management. Service providers are drawing on the capabilities of generative AI to analyze diverse datasets such as historical information, market conditions, weather patterns and geopolitical events. Upon detecting possible risks within the supply chain, GenAI can rapidly generate insights, simulate scenarios to develop mitigation strategies, and assess and manage supplier risks.

Analytics-led cost optimization. Service providers are utilizing the large volumes of data generated by supply chains to identify patterns, glean insights and optimize operations budgets. They use a combination of prescriptive and predictive analytics to simulate scenarios for network optimization and improved cost efficiency.

Real-time monitoring through digital twins. Digital “mirrors” of entire supply chain networks continuously collect data from internet-of-things sensors and other sources. Embedded advanced analytics and AI enable more accurate and dynamic forecasting across inventory, contingency planning, distribution and logistics.

Scenario planning for demand sensing and forecasting. Real-time data and the use of advanced analytics are precursors to identifying and forecasting demand. Service providers monitor up-to-date information on changes in consumer behavior, weather patterns and economic conditions. They can generate “what-if” scenarios on future demand requirements and supply chain disruptions for contingency planning.

Geo-data analytics and route optimization. Service providers have invested in location analytics and intelligence to improve carrier networks, locate customers and analyze and understand the most popular products, services or stores in a particular area. This also enables businesses to plan and optimize routes, delivery times and locations. Last-mile delivery focus and route optimization algorithms reduce delivery costs and improve the customer experience.

AI-enabled inventory optimization. AI and ML models analyze large volumes of data, identify trends and patterns, and bring multidimensional intelligence to inventory management. Real-time inventory tracking is enabling enterprises to keep a check on their inventory and adjust as needed to prevent overstocking or understocking.

Businesses should consider whether they have the time, budget and talent to build and run the technology tools needed to achieve these outcomes. Many will find it makes sense to partner with one or more specialized supply chain ecosystem providers. Before turning to the outside, however, they should consider working with a third-party adviser to determine their business objectives, and align them with the right operating model and partner network to deliver desired outcomes. 

Saravanan M S is research specialist, and Gowtham Kumar Sampath is assistant director and principal analyst, with ISG.