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It's Looking Digital for the 2023 Supply Chain

作者： Hailey Lynne McKeefry 2023-01-20

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As we begin the new year, we can reflect upon those many seemingly insurmountable supply chain challenges, but the path forward will have its own challenges, as well as ever-increasing complexity. Technology solutions to improve the supply chain and abstract us from its complexity abound, and the coming year will have most organizations investing in ways to increase agility, improve transparency, and enhance security.

At the same time, the industry is rife with platforms, technologies, and applications that promise to bring supply chain functioning to excellence. In the next couple of years, there will be a market shakeout that will cull the herd to proven solutions that have had solid adoption. (Sadly, we all know that the best technologies do not always win, but that’s a discussion for another day.)

The Association for Supply Chain Management (ASCM) identifies data, advanced analytics, and automation as the key pillars of the supply chain,¹ all of which depend on the selection of the right supporting technologies to achieve. As I discussed in my last piece, “2023: Applying Supply Chain Wisdom & Expertise”, cloud-based strategies will take the lead in the supply chain because they allow a strong security stance while still enabling collaboration. There are some other ways, though, to slice the technology pie in order to think about prioritizing technology adoption in smart and effective ways.

Figure 1: At least half of the top trends identified by ASCM are related to supply chain technology—it’s going to be the year for smartening up the supply chain. (Image source: ASCM)

Big data & analytics

The key to business success is not having data but rather using data. Unless data is translated into actionable decisions, it’s truly useless in the supply chain. That reality will drive organizations toward the adoption of big data & analytics to capture the enhanced visibility, synchronized planning, agility, and profitability that solutions support.

Right now, most organizations have somewhat blurred supply chain visibility. In a recent year-end global supply chain report I saw from Interos, between a quarter and a third of organizations say that they only have confidence in their ability to know about a supply chain disruption in anything but their first tier of suppliers. Further, they predict more disruptions and a larger number of suppliers in each supply chain—the need to sort and understand data will be more important than ever.

Big data and analytics are the technology duo that helps supply chain pros cut through the data overload toward understanding, insight, and its optimal application. Supply chain pros need to focus on gaining technical expertise to understand the scope of the data in their organization and to establish a structure within which to collect and evaluate that data. For example, real-time data insights, as well as data from both internal sources (across the organization, from various systems, as well as data provided by partner systems) and external public sources (media and entertainment data, weather data, sensor data, etc.) are needed. By applying analytical tools, organizations can translate raw data into decisions.

Digital supply chains

Traveling hand-in-hand with big data is the implementation of the digital supply chain. Traditional supply chains are linear—one step at a time—and a misstep at any point causes delays. In a digital supply chain the systems are integrated to take structured and unstructured data to share bidirectionally between an OEM and its suppliers. By creating full visibility amongst all stakeholders, problems can be identified and resolved in real-time. A number of supporting technologies are needed to create a digital supply chain—including sensors that collect and send data, digital twins to provide a virtual model of the supply chain, and shared interfaces between the involved organizations.

Artificial intelligence (AI) & machine learning (ML)

Using AI and ML techniques, computer and robotic systems can seemingly simulate human intelligence processes to carry out tasks normally done by humans (that means manual jobs can be automated). In the supply chain, this can translate into demand-forecasting tasks that map transportation routes or identify available stock. ML (a subset of AI) allows systems to teach themselves over time based on trends and provide predictions or other insights by spotting anomalies. ML and AI can also help inventory management, supplier management, and other tasks by using algorithms to respond to changing market situations and fluctuating demand.

Robotics

Robots are quickly moving beyond the stuff of science fiction. In fact, collaborative robots—or cobots—help address some key supply chain challenges, including labor shortages, demand surges, and supply disruption. Allied Market Research puts the global logistics robot industry at $6.3 billion and predicts a market of $27.8 billion by 2031 (an annual growth rate of over 16%)³. In a warehouse, robots can enhance safety and reduce costs by improving workflow. In many instances, they can take over repetitive and boring tasks to free up humans for tasks that require their attention.

Data security & cybersecurity

Finally, because we understand that the supply chain is a strategic asset for any organization, protecting that asset will be a critical task going forward. Collaboration means that organizations can also expose each other to bad actors and data breaches. Increasingly, the organization’s IT, supply chain, and procurement functions will have to work together to identify and address vulnerabilities in the supply chain. A variety of security protocols, including firewalls, anti-hacking technologies, and redundancy will be key investments. In the case of cyber threats, organizations require close cooperation between IT security, supply chain, and procurement managers to identify and plug vulnerabilities in suppliers with access to their systems and networks.

Just about every supply chain technology is expected to explode over the next few years, but for OEMs, it will take careful planning to align with the technologies and vendors that can meet their supply chain needs over the long haul.