In the ever-evolving omnichannel landscape, consumers seamlessly transition among online and offline channels, requiring retailers to provide a unified experience across channels. Having re-engineered their supply chains to meet this challenge, retailers are now deploying artificial intelligence (AI) to take omnichannel retailing to the next level.

A recent survey conducted by the Omnichannel Supply Chain Lab examined where AI-driven innovations are having the most impact on omnichannel fulfillment. Not surprisingly, respondents ranked demand forecasting as the top domain affected by AI, followed by customer experience, customer service and chatbots, and inventory management. However, AI has a critically important role to play in transforming all the areas ranked, such as warehousing and returns management. Let’s delve into these different roles.

Read more in Supply Chain Xchange.

Recently, a panel of experts convened to discuss the convergence of AI and supply chains as part of Fast Company and Inc.’s AI Bootcamp series, in partnership with SAP, a leader in resource planning software series. The conversation explored AI’s potential for building more robust supply chains, as well as the challenges companies need to consider as they lean on technology to maximize efficiency and procurement efforts. Here are four takeaways from that conversation.

“One of the most common reasons I have seen companies fail when implementing disruptive technologies like AI is when they are rushing, with a lack of clear vision,” says Dr. Eva Ponce.

Highlighted in MIT News with the full story in Fast Company.

Based on our research of omnichannel supply chains, including an online survey conducted in partnership with DC Velocity, we have identified six omnichannel fulfillment challenges that companies must address in order to be successful in today’s continually changing retail space. The answer in many cases, we believe, will involve adopting innovative technology and processes.

Read more in Supply Chain Quarterly.

As the pandemic receded and consumers began to return to stores, the retail landscape once again shifted, presenting supply chain professionals with a whole new set of challenges.

Read more in DC Velocity.

• Different e-fulfillment strategies significantly alter the composition of e-fulfillment costs.
• The cost of e-fulfillment activities is poorly controlled except for the last-mile and picking.
• Most OC retailers don’t know the cost of fulfilling a specific online order (cost-to-serve).
• Accurate e-fulfillment cost data is correlated with using online-dedicated fulfillment centers (FCs).
• OC retailers change e-fulfillment strategies without knowing the true costs.

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A large U.S. foodservice distribution company, aims to minimize the overall cost for the supply chain network, including omnichannel fulfillment options. We built an MINLP model to simultaneously optimize network design and inventory positioning. Our results demonstrate potential cost reductions of 3–9% in transportation, 2–8% in warehouse handling, up to 50% in inventory costs, and nine times greater efficiency than Gurobi.

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This paper proposes a mixed integer program (MIP) for the network design problem of a parcel carrier that manages online orders from omnichannel retailers. The network includes several types of facilities, such as city distribution centers, intermediary depots, parcel offices, as well as collect channel points, such as automated parcel stations (APS), stores or kiosks. The model formulation takes into account the influence of these collection points on consumer choice and the maximum distance customers are willing to walk to reach them. Realistic transportation costs are also considered, including detailed long haul costs and delivery costs in an area… Finally, we use the model to discuss the network design of a Spanish parcel carrier operating in Madrid.

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The warehouse of the future represents a paradigm shift in warehouse design and operation. It is the industry’s response to the burgeoning growth of e-commerce, worldwide supply chain disruptions including warehouse labor shortages in developed markets, and increasing awareness of the significant volume of greenhouse gas (GHG) emissions emitted by warehouses.

In this white paper, we detail the concept and fundamental characteristics of the warehouse of the future: a shift toward a highly automated, interconnected system that leverages automation and digitalization to enhance precision, flexibility, and efficiency to adapt to changing market and supply chain trends, while integrating environmental sustainability alongside technological innovation. This concept signifies a forward-thinking model that aligns operational efficiency with a sustainable approach to warehousing, that is pivotal to the evolution of contemporary supply chains.

Currently, we are exploring potential vulnerabilities in highly automated warehouses. The complex nature of new warehouse technologies, such as digital twins, drones, or collaborative robots, obscures potential weaknesses and since these systems are often interconnected, a disruption in a single facility could impact the entire supply chain, leading to significant losses in productivity and profits. Our goal is to identify potential vulnerabilities in emerging warehouse technologies and data management through cutting-edge research.

The warehousing industry is a significant source of greenhouse gas (GHG) emissions contributing to the climate change that is being witnessed by the world in the past few years. In response to that, our capstone sponsor Maersk tasked us with identifying actionable steps to reduce GHG emissions at the warehouse level. We evaluated 13 technologies to reduce GHG emissions and conducted an in-depth review of seven of them. Our methodology assessed the environmental and economic impacts of implementing these technologies. The project was concluded with a framework for evaluating different sustainable solutions in an integrated way.

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Omnichannel supply chains in the retail industry have evolved rapidly over recent years in response to shifting consumer demands. At the same time, the shift toward circular economies is gaining momentum as countries and companies set increasingly ambitious sustainability goals. How can omnichannel support the development of circular supply chains?

One way is to create reverse flow channels that collect returned products and packaging for recycling and reuse. The retail industry is actively developing these reverse supply chains, and one of the challenges they face is how to measure the impact of reuse strategies on omnichannel operations.

Learn more about our recent research with a large, multinational retail company in the Supply Chain Management Review.

Circular supply chains comprise the industrial production and supply chain systems used by companies to eliminate waste and recover value in products and materials. There are a variety of circular strategies including recycling in waste management, returns and repair in consumer-facing industries, and reusable packaging in supply chains. Successful implementation and management of these circular strategies requires the ability to measure and report on progress across different functions and processes. In this paper, we propose a new set of metrics to measure the performance of reusing items in a circular supply chain. We then demonstrate the use of the proposed metrics through a case study with an omnichannel retail company. This new set of metrics provides companies with a tool to measure and report on progress toward a circular economy. It also suggests future avenues for research to assess the economic, environmental, and social dimensions of sustainability.

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