It's all too easy for logistics leaders to get caught up in the day-to-day demands of running a supply chain. With pressure to meet short-term demands and deal with immediate challenges, it can be tempting to put off investing in new technologies and processes that could improve big-picture supply chain strategy and drive long-term business goals.
But in today's shipping landscape, staying ahead of the curve is more important than ever. By focusing on technological innovation, logistics leaders can become supply chain innovators, ensuring that their supply chain innovations are preparing them for the future and helping them stay competitive and adaptable in the face of short-term disruption.
Three technological innovations are poised to transform supply chain management and improve efficiency: collaborative mobile robots, edge ecosystems, and embedded artificial intelligence (AI) analytics. With the help of these cutting-edge digital technologies, supply chain leaders can automate routine tasks, gain real-time visibility into their operations, and make more informed decisions, leading to a more efficient and cost-effective supply chain. Let's take a closer look at how these innovations are set to revolutionize the way we manage our supply chains.
Collaborative Mobile Robots
Collaborative mobile robots (CMRs) are robotic devices designed to work alongside humans in the warehouse. Traditional automation solutions are difficult to configure and require significant resources to install, but CMRs are typically smaller, more flexible, and easier to move around the warehouse floor. Their ability to maneuver freely and interact with their environment benefits businesses who wish to quickly scale up or down their use of CMRs depending on their needs.
In a warehouse setting, for example, a CMR could be used to assist workers with tasks such as picking up, moving, and packing heavy items. With the help of sensors and cameras to navigate the warehouse, the CMR can use its gripper arm to grab the items and place them in the appropriate location or container. Practically, this means that when a customer orders an item, the CMR is able to pick up the item from its storage area and transport it to the packing station—a task that would otherwise take a considerable amount of time to complete manually.
The collaborative nature of this supply chain innovation can go a long way in assuaging major logistics companies nervous about large-scale automation replacing their human workforce. CMRs can be used to augment rather than replace human workers, allowing workers to focus on more complex tasks, while letting the robots handle the more repetitive, time-consuming, and even dangerous tasks, such as managing hazardous materials, operating in extreme temperatures, and performing precision assembly operations.
Edge ecosystems are networks of connected devices and applications that sit closer to the source of data collection—the edges of enterprises—instead of in far-off cloud or centralized data centers. In a warehouse, edge ecosystems might comprise sensors, processors, and software that monitor the performance of different parts of the supply chain. Their proximity to the action offers executives faster, more reliable, and more secure data processing and storage.
Because the data is collected and processed closer to its source, edge ecosystems can improve supply chain visibility and traceability, all while reducing the latency in data transfer. On the other hand, data collected and transferred through a remote server can lead to delays that make it difficult to track supply chain processes in real-time. And if there’s one thing no company wants, it's delays that impede immediate visibility into the flow of goods.
By connecting devices, data, applications, and services together—right at the source of the supply chain activity—edge computing can help companies create a powerful, distributed platform that can process data faster, provide reliable access to data from any location, and enable AI-driven solutions.
Embedded AI Analytics
Embedded AI analytics provides real-time reporting, interactive data visualization, and advanced analytics capabilities directly on an accessible digital platform, allowing businesses to evaluate their supply chain performance in real-time and make quick changes to improve customer satisfaction.
The advantage here is two-fold: The AI component of the offering—underpinned by predictive technologies—enables leaders to optimize shipping routes, predict demand and supply, and achieve more accurate demand forecasting. The embedded component ensures that data is always accessible to decision makers, and that the predictive horsepower can be applied to the data in real-time, allowing for an agile supply chain that's responsive to consumer demands.
Before the advent of embedded AI analytics, business leaders were required to access and interpret data from multiple sources and in multiple formats. In addition to being time consuming, it often required a specialized skillset to understand and apply that data in meaningful ways, leaving many business leaders overwhelmed by the sheer amount of information available and unable to effectively leverage it to optimize their supply chain and reduce costs. An embedded approach ensures all data is collected, organized, and readily available to decision makers on a single platform, allowing for improved decision making and a more responsive supply chain.
Unlock Your Supply Chain's Potential
Ultimately, the stakes are high for logistics leaders who hope to survive and thrive in the coming years. Technologies like collaborative mobile robots, edge ecosystems, and embedded AI analytics can help logistics leaders become more agile, allowing them to handle more efficient, cost-effective, and secure supply chain management processes. With the help of these cutting-edge digital technologies, companies can stay ahead of the competition and protect their long-term business objectives. So, don't delay—start incorporating these technologies into your supply chain innovation planning today.