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In previous decades, supply chain managers focused on managing the flow of materials and resources through different processes as they became finished products and were ultimately delivered to the end customer. These past eras of stability and predictability have recently given way to a new emphasis on increased risks, regulatory changes, and economic, societal, and geopolitical shocks. Initially, managers did not have the tools and information necessary to respond adequately to sudden disruptions. As a result, global supply chain networks continue to undergo digital transformation to overcome these new challenges, implementing asset tracking solutions and adopting Industry 4.0 technology, including artificial intelligence ( AI), machine learning (ML) and the Internet of Things (IoT). .
Digital Transformation in the Supply Chain
Broadly speaking, digital transformation describes the process of fundamentally changing the way a business operates by integrating digital technologies into all areas of the business. When it comes to supply chain, digital transformation is similar in that it involves inserting digital capabilities into all aspects of the supply chain to improve everything from customer service and productivity to collaboration and decision-making between departments.
Historically, there was no urgent need for digital transformation; similarly, businesses took for granted the logistical links connecting different parts of global supply chains. Predictable costs and performance across all standard modes of transportation (sea, air, rail and truck) meant companies could confidently build geographically distributed supply chains by leveraging the cost or scale advantages of Asian manufacturing. However, the pandemic, new regulations and incidents, such as the closure of the Suez Canal, have called into question the validity of these assumptions, highlighting the need for digital capabilities to respond quickly to emerging issues with timely information. real – especially when great distances are traveled. implied.
By implementing technologies such as sensors and IoT devices throughout the supply chain and connecting them to an IoT device management platform, managers have access to real-time information. These IoT solutions enable supply chain managers to assess product health, respond quickly to disruptions, and detect inefficiencies. Although critical information may be readily available to supply chain managers, this information sometimes does not always appear in an easily digestible form for key personnel to make critical decisions in a timely manner. This is where introducing AI and ML into any logistics system allows patterns to be quickly identified as soon as a problem arises.
Businesses can use AI to improve their decision-making, making their supply chains more flexible to changes, which is particularly relevant given today’s highly volatile and disruptive environment. And by enabling AI to streamline the process of collecting and analyzing relevant historical and current data, businesses can improve supply chain visibility and responsiveness. A company in the shipping and shipping industry leveraged ML to solve the inventory management conundrum by applying ML to existing historical data to create more robust and reliable base probability forecasts that model with clarify the different phenomena that shape demand. With ML, this company has also reduced waste through better inventory optimization, meaning fewer out-of-stocks and instances of excess inventory.
Real-time asset tracking
A central part of ongoing efforts to integrate digital capabilities throughout supply chains is asset tracking, or how a the company tracks its physical assets by equipping them with technology solutions such as GPS trackers, barcode readers or radio frequency identification (RFID). These asset tracking solutions – installed inside trucks, shipping containers or the asset itself – provide managers with greater supply chain viability. And by adding AI, ML, and IoT to the mix of asset tracking technologies, businesses can accurately forecast demand for more efficient inventory management, thereby reducing emissions and waste.
At the same time, implementing AI, ML, and IoT-based asset tracking solutions in the supply chain can help businesses reduce costs. Search for McKinsey found that early adopters who successfully implemented AI-driven supply chain management saw inventory costs improved by 35% and logistics costs by 15%. AI is also a key tool in automation that can help minimize errors and delaysenabling organizations to reduce costs associated with loss of supply. Additionally, AI and ML-based solutions can automate repetitive warehousing-related tasks, allowing supply chain personnel to focus on higher-value work.
Another considerable challenge that often generates expenses in the supply chain is that of damaged, destroyed or deteriorated inventory and assets, particularly during the transport of fragile materials. However, by using AI-based sensors to track individual shipments, supply chain managers can gain real-time visibility into environmental situations surrounding their assets; Additionally, if conditions inside a truck or unused shipping container in a warehouse approach dangerous limits, AI sensors will send alerts. With this data, managers can improve the security of their assets while reducing losses and misdirected shipments. They can even instruct their AI-based solutions to autonomously order new materials if supply reaches specified levels. Additionally, GPS asset tracking reduces theft via geofences: if an asset moves outside of its defined parameters (like the boundaries of a warehouse), a notification will be triggered.
Prepare accordingly for the new era
Managing your supply chain in this new era of increasing compliance costs and frequent, global disruption means having the ability to overcome risks in near real time. Likewise, the need to focus on resilience and sustainability will require supply chain managers to reorient their supply chain maps to make them more flexible and more regional. Those who succeed in meeting these challenges will be the companies that succeed in promoting digital transformation, using techniques such as asset tracking while leveraging AI, ML and IoT technology solutions to reduce costs. costs and improve decision-making with real-time data.