Interlinked mechanics strengthen supply chain

We delve into the main challenges plaguing the supply chain industry and see how this year’s trends could help to address these problems.

“Our global supply chains are stressed and under pressure, not only because of material shortfalls and shipping delays, but also due to labour shortages in key sectors,” writes Joe McKendrick in his Harvard Business Review piece, “How to Address the Supply-Chain Staffing Crisis”.

It comes as no surprise that 54% of supply chain and logistics leaders are focused on automating non-value-added and repetitive tasks with technology to improve worker productivity in the face of the notable workforce shortages.

A total of 1,000 supply chain and logistics decision-makers across three sectors (manufacturing, distribution, and retail; carriers; and logistics service providers) were surveyed late last year in the study “What are Companies Doing to Survive the Supply Chain and Logistics Workforce Challenge?” The survey was conducted by Canadian tech multinational Descartes – specialists in logistics and supply chain management software, and cloud-based services for logistics businesses – and London-based market research agency Sapio Research.

The goal was to understand supply chain and logistics organisations’ efforts to improve worker productivity, attract and retain employees, and find alternate labour sources to mitigate current and future workforce challenges. Respondents came from nine European countries, Canada, and the US, and all held owner, c-suite, director, or manager-level positions in their respective organisations. 

To help drive productivity gains for labour workers, the top technology choices in the study were delivery route optimisation (54%) and driver mobile productivity (45%) solutions. For knowledge workers, the top technology choice was real-time shipment tracking (53%). 

In addition to making technology investments to help combat supply chain and logistics workforce shortages, companies are also adapting their recruitment and retention strategies and tactics. According to the study, hiring labourers (such as warehouse workers and drivers) and knowledge workers (planners, managers, and analysts) were the areas most altered to address workforce availability challenges (54%).

Study findings also revealed that the top strategies for attracting workers were work time flexibility (35%) and latest technology adoption (34%), while the top strategies for retaining workers were on-the-job training and education compensation (35%), and higher pay (34%).

“The workforce problem is pervasive, and the study confirms that most supply chain and logistics organisations have made changes to their operational, technology, recruitment, and retention strategies to help combat the issue,” notes Chris Jones, executive vice president of industry and service at Descartes. “Based on the results of the study, we believe that employers should continue to invest and evolve to get the most they can from their existing resources and focus on more than money to hire and retain a capable workforce.” 

In light of this, it’s easy to see why the interplay between humans and machines is a key theme driving multiple trends in the supply chain sector. “This year’s trends are driven by themes that encourage supply chain technology leaders to ensure their foundation can support both past and future investments, while also looking ahead for new differentiation opportunities,” explains Christian Titze, research vice president at the Supply Chain Practice division of Gartner, a US research and consulting firm.

Gartner highlights two broad themes driving supply chain technology trends: (1) the need for supply chain leaders to leverage emerging technologies to control and protect their businesses, and (2) new opportunities for competitive differentiation through the complementary integration of humans and machines.

With these influences in mind, the top eight strategic supply chain technology trends for 2024 are:

Cyber extortion  

Cybercriminals are extremely proficient at executing successful ransomware attacks to extort funds from supply chain organisations. It is highly likely that they will utilise the power of AI to generate advanced attack tools, making attacks even more effective. Supply chain technology leaders should collaborate with IT leadership to confirm that ransomware attack scenarios are included in corporate risk management processes and develop a detailed ransomware incident response playbook. 

Supply chain data governance

The emergence of powerful tools for advanced analytics and AI techniques is massively scaling the capabilities for cross-functional visibility, scenario modelling, and decision automation. As those technologies are increasingly adopted, the importance of maintaining a high level of data quality and a strict governance process is becoming business mission critical.

End-to-end sustainable supply chains

Sustainability-related legislation is growing globally and driving a shift from voluntary to regulatory compliance. As a result, sustainability data accuracy needs to be uplifted from simple indicators to investment grade data in order to meet stakeholder requirements, while also driving internal decision making.

AI-enabled vision systems

These novel hyper-automation solutions combine industrial 3D cameras, computer vision software, and advanced AI pattern recognition technologies. They can autonomously capture, interpret, and make inferences based on the unstructured images the vision systems see in real time.

Augmented connected workforce 

Augmented connected workforce (ACWF) initiatives reduce the time required after onboarding for an employee to become fully productive and improve their decision making. ACWF is a strategy to optimise the value derived from a human worker by establishing a connected system that optimises the use of intelligent technology, workforce analytics, and skills augmentation. It treats these capabilities as a unified, cohesive strategy to accelerate and scale talent. 

Composite AI

Composite AI is the combined application of multiple AI techniques to improve the efficiency and accuracy of learning. In this way composite AI broadens the level of knowledge representation and ultimately solves a variety of business problems that drive supply chain performance improvements. Depending on the context of a specific use case, different AI techniques (or more often a combination of techniques) will make more sense than relying on a “one-size-fits-all” approach. 

Next-generation humanoid working robots

Next-generation humanoid robots combine sensory awareness with mobile manipulation and dynamic locomotion to perform productive work that was previously reserved for people. Humanoid robots will typically imitate the human body by having a head with sensors and cameras for sensing their environment; a body that houses the power and mechanical components; arms and hands/grippers for grasping, manipulating, and carrying items; and legs for dynamic motion. 

Machine customers

Machine customers are nonhuman economic actors that autonomously obtain goods or services in exchange for payment. Examples include IoT-connected devices or assets that place orders independently of a human command, intelligent replenishment algorithms that maintain the availability of consumables, and intelligent assistants that suggest deals to consumers.

“These technology trends are not isolated, but rather interconnected and mutually reinforcing,” says Dwight Klappich, analyst vice president and fellow in the Gartner Supply Chain Practice. “Their importance will differ not only by organisational maturity, but also by industry, business needs, and previously devised strategic plans. Innovative supply chain leaders will connect strategies and investments between multiple trends to help deliver on their mission-critical goals this year.”