Supply chain management is a challenging field owing to the interactions among multiple players like consumers, suppliers, manufacturers, and logistics. Successful business operations rely on the execution of successful supply chain management (Dash et al., 2019). At the same time, changes in business practices, like just-in-time delivery, environmental issues like climate disasters, and globalization present significant challenges that may constrain supply chain management processes. In recent years, the introduction of new digital technologies has changed the supply chain environment. Breakthroughs in autonomous capabilities, AI, blockchain, and the internet of things have resulted in changes in all supply chain processes. The innovations occurring in the fourth industrial revolution blur the lines between the biological, physical, and digital spheres (Calatayud et al., 2018). Information that previously relied on human beings will be machine-generated, resulting in significant gains in accuracy and speed. The future supply chain will be predictive and autonomous, enabling higher performance despite an increase in uncertainties and risks.
Artificial Intelligence, AI
Artificial intelligence refers to machines’ capability to imitate human capabilities and communicate with humans. AI results in more efficient problem solving since the technology takes less time, is more accurate and can take in more inputs (Toorajipour et al., 2021). AI application spans various fields, including supply chain management. It enhances firms’ functionality, increasing their competitive advantage in the industry. AI-enabled machines in the modern environment can gather information from the environmental surroundings, relying on probability and logic to select the highest actions with the highest chance of success. One of the uses of AI in SCM is to boost value creation. AI-assisted projections allow businesses to achieve almost 100% precision in forecasting customer demand, optimize the research and development to achieve higher production at lower costs, and enhance customer satisfaction (Dash et al., 2019). These value creation areas are critical in attaining a competitive advantage in any industry.
AI achieves better forecasting, equipping companies with the capabilities to effectively balance supply and demand. Businesses relying on AI to forecast consumer demands only stock the desired products, minimizing waste and meeting customer demands (Dash et al., 2019). Additionally, information about sales trends enables businesses to stock products that will soon be popular, such that they do not lose customers due to product unavailability. AI also boosts production processes through several mechanisms, including improving reliability and quality, optimizing processes and assets, and designing the best teams comprising of machines and people (Toorajipour et al., 2021). AI-enhanced robots are more efficient in recognizing empty shelf space, resulting in increased speed in picking objects. Improvements in deep learning empower robots with the ability to recognize and pick objects regardless of their position. AI is also applied in logistics, increasing the effectiveness of delivery processes by integrating obstacles in the delivery route.
Another supply chain application of AI is promotion and pricing. AI tools are applied in News websites to increase traffic from information consumers. Further, AI-supported activities are numerous in digital content creation, including website optimization, programmatic buying, outbound e-mail marketing, and search engine optimization (Dash et al., 2019). AI applications analyze data regarding consumer behavior, including the most suitable times in the week to contact consumers, where the consumers’ interests lie, and the best frequency for the contact between companies and consumers. Other consumer information allows businesses to optimize promotional strategies by advertising a brand to the most effective audience depending on demographic factors (Dash et al., 2019). AI also enhances the user experience. The technology achieves this by creating tailored, more convenient, and richer experiences for users, such as in shopping. The future of AI in these processes will comprise higher adoption rates and overcoming technical difficulties associated with the technology.
Smart manufacturing is another application of AI that enables companies to produce products with fewer errors. The technology enhances engineering efficiency, optimizing product development cycles such that companies produce more products within a shorter period (Toorajipour et al., 2021). Moreover, the automation of risky activities results in safer manufacturing environments. Intelligence manufacturing is the phenomenon where machines are linked to human beings. The two parties collaboration in the most effective way with minimal or no supervision to optimize the manufacturing process. Dash et al. (2019) reported the intelligence manufacturing process at Siemens, where programmable logic circuits are operated and controlled by employees in a virtual factory that replicates the physical factory. Communication among the machines allows them to identify and correct errors in products, while machines and products communicate via barcodes during the manufacturing process. AI also results in better accountability in all parts of the supply chain while providing transparency regarding performance, downtime, and availability of supplier machines.
Autonomous Capabilities
Technological advances suggest that supply chain management in the future will be characterized by autonomous capabilities with significant improvements in performance. Supply chain management is growing increasingly complex in the context of more firm interconnectedness, increasing internalization, the need for higher process speeds, and higher demand volatility (Calatayud et al., 2018). The autonomous supply chain process will have the capacity to analyze quintillion data bytes to continuously monitor performance, forecast risks, and take preventive actions before the risks occur. Moreover, autonomous systems will have the capacity to learn from past decisions, increasing the effectiveness and efficiency of future decision-making. In this regard, an autonomous supply chain will result in higher levels of supply chain agility and flexibility. An autonomous supply chain requires higher interconnectivity between physical objects and cyber systems, which is facilitated by the internet of things. Catalayud et al. (2018) contended that IoT facilitates such interconnectivity through internet-based applications, short-and-long range networks, and the deployment of sensors.
Enhancing supply chain agility is among the primary advantages of autonomous supply chains. Higher agility will allow supply chains to respond faster to market demand, which is necessary for mass product customization (Catalayud et al., 2018). Agility will also result in better replenishing lead times and product demand predictability. Currently, companies use either a lean or an agile supply chain management approach to increase efficiency. However, an autonomous supply chain will optimize the two processes to create more effective and efficient processes. Additionally, the innovation will impact supply chain risk. Increased volatility results in higher supply chain risk, which can reduce a company’s competitive advantage. Self-thinking supply chains will have the capacity to sense risk and respond to prevent it from materializing or reducing its impact. The confluence of new materials, new processes like synthetic biology, and digital technologies is spearheading a production revolution that is changing the nature of manufactured products.
The digital revolution has also impacted production capabilities. For instance, direct digital manufacturing allows companies to directly produce products from CAD files, eliminating tooling investments and time-lag and reducing production lot sizes (Catalayud et al., 2018). As a result, the economy is witnessing a transition from economies of scale to economies of scope. Autonomous supply chains will support additive manufacturing like 3D and 4D printing. Incorporating this change into mass customization will further increase the ‘maker movement,’ a situation in which the customer actively participates in the production process. Such developments will result in a speedy shift from consumers to prosumers. Autonomous supply chains will also result in more value addition on products while in transit (Catalayud et al., 2018). Such supply chains will also result in changing products to meet customer requirements, such as 3D printing more products while on transit to comply with changes in preferences or increased demands.
Blockchain
Blockchain is a form of distributed ledger technology comprising a list of time-stamped records linked through cryptography. The technology can radically change how businesses operate as it provides a secure and immutable channel of information transfer (Chang & Chen, 2020). One application of the technology in supply chain management is the improvement in traceability and transparency. Examples of points of concern that would benefit from better transparency and traceability include over-centralized business operations, process hand-offs, and critical intermediaries. In a blockchain platform, every participating node maintains and validates records about transactions in the same ledger (Chang & Chen, 2020). Various stakeholders in a supply chain, including distributors, customers, manufacturers, suppliers, and shippers, would have access to transactional records and permission to monitor process flows. IN this regard, blockchain would enhance the efficiency of supply chains and eliminate the need for centralized authorities.
Real-time monitoring of activities would be a useful development in supply chain activities like logistics. Customers can monitor the progress in product development and logistics, ensuring that the production process meets all of the customer preferences. Blockchain will also increase disclosure in supply chain activities and result in higher accountability across players, mitigating business disputes (Saberi et al., 2018). Immutable features of the technology will eliminate the need for reconciling siloed databases, allowing stakeholders to reduce transaction risks and capture more value. As technological innovations increase, smart contracts will enhance process automation and provide real-time monitoring of service visibility. In this case, blockchain technology will address the trust issue among unfamiliar trading partners. Another advantage of blockchain is a reduction in processing paper-based documents, as it will enable authenticity verification through encrypted digital signatures (Chang & Chen, 2020). This feature will also benefit businesses as they will reduce costs associated with tracking proof of authenticity.
The incorporation of blockchain in supply chain activities will also result in greater stakeholder collaboration and involvement. Dispersed parties present a critical problem of efficient collaboration (Chang & Chen, 2020). The technology will enable large-scale stakeholder collaboration regardless of location due to the higher security levels. Businesses will be more adept at realizing strategic objectives after incorporating blockchain in supply chain activities. Saberi et al. (2018) report that the type of benefits that businesses will get from blockchain technology will depend on the type of blockchain incorporated into the operational processes. Nonetheless, firms will be able to incorporate a new business model comprising different disintermediation levels, allowing for better privacy, security, and transparency. Increased efficiency in financial operations will also result in lower transaction costs due to a synchronized ledger.
The future supply chain will also witness the digitization of intelligence rights and physical properties (Chang & Chen, 2020). This will be feasible owing to the technology’s capability to improve security from cyber-attacks and malicious tampering. However, Saberi et al. (2018) affirmed that the application of blockchain in supply chain activities is still open to development and interpretation. Supply chain networks based on blockchain may require permissioned, closed, and private blockchain with limited yet multiple players. Blockchain-based supply chain networks are characterized by four main elements, some of which are absent in traditional supply chain management. These include standard organizations that define standard schemes, registrars that give identities to network actors, certifiers, who certify actors for supply chain participation, and actors, such as retailers, suppliers, manufacturers, and customers (Saberi et al., 2018). A disruptive feature that would result from blockchain is the elimination of financial intermediaries like stock exchanges and payment networks, which will minimize financial flows’ inefficiencies.
Internet of Things, IoT
IoT revolutionizes supply chain communication by enabling new levels of adaptability, agility, and visibility to address supply chain management challenges. Technologies that facilitate IoT comprise a data collection layer, a transmission layer, a service layer, and an interface layer (Ben-Daya et al., 2017). These features allow the technology to accomplish various activities. Logistics processes in supply chain management would benefit from monitoring, location tracking, tracing, optimization, and real-time responsiveness. Cyber-physical systems based on the technology can connect the cyber and physical world, integrating analog hardware and cloud-based manufacturing capabilities. IoT is beneficial in reverse supply chain management and reverse logistics, which are critical competencies in the field (Garrido-Hidalgo et al., 2019). The technology provides an extensive communication network, significantly minimizes energy consumption, and enhances process-oriented performance. Congruent with the fourth industrial revolution IoT is characterized by high flexibility, transparency, and real-time flow of information.
Ben-Daya et al. (2017) affirmed that short-range communication capabilities of IoT will facilitate the identification of returned products, a key aspect in reverse logistics. Product identification will be accompanied by the reason for return and other essential product features. The information will be conducted in RFID tags placed on products before dispatch to customers, such that should customers need to return a product, the process is optimized. Introducing an actuator system in the process would allow reusable products to be taken back into containers while faulty products pass through for re-processing or waste management (Garrido-Hidalgo et al., 2019). The third aspect in an IoT-enabled reverse supply chain system is a classification feature. This stage collects information regarding products and passes it through a quality control test to assess the suitability for product reuse. In so doing, the technology will enable firms to meet circular economy objectives by reducing and reusing wastes.
Another aspect of IoT-enabled systems is smart containers. The containers have microcontroller platforms that enable them to gather context information and update inventory (Garrido-Hidalgo et al., 2019). Aside from reverse SCM, IoT will also result in the optimization of other supply chain operations. For instance, the technology will enable real-time monitoring of products’ and raw materials’ storage conditions. Factors like humidity, temperature, and light intensity need to be at optimal levels for sensitive goods (Ben-Daya et al., 2017). Information about changes in environmental factors will allow companies to implement corrective measures that mitigate risks and increase the viability of products or raw materials. Additionally, the technology will streamline goods’ movement by identifying potential obstacles that would interfere with the transit process. Consequently, customers and manufacturers will receive goods within shorter timeframes owing to the increased process efficiency. While some of these processes are possible without IoT, the significant reduction of errors will impart companies with a considerable competitive advantage in various industries.
Conclusion
Supply chain management in the future will have exceptional capabilities that will allow companies to mitigate risks, enhance efficiency, and correctly predict future opportunities and challenges. Innovations relating to autonomous capabilities, artificial intelligence, AI, and IoT will equip firms with capabilities to mitigate several challenges in supply chain management. Logistic challenges, trust between unfamiliar trade partners, and tracking and tracing products will be more efficient with the integration of these technologies into supply chain management. While the integration process is bound to face several technical and infrastructural challenges, the connectivity of information systems will increase significantly. Higher connectivity will enable developing countries to take up more active roles in global supply chains, closing the digital divide. Self-thinking supply chains will improve performances and logistical processes, resulting in more efficient global trade.
References
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: a literature review. International Journal of Production Research, 57(15-16), 4719-4742. https://doi.org/10.1080/00207543.2017.1402140.
Calatayud, A., Mangan, J., & Christopher, M. (2018). The self-thinking supply chain. Supply Chain Management: An International Journal. https://doi.org/10.1108/SCM-03-2018-0136.
Chang, S. E., & Chen, Y. (2020). When blockchain meets supply chain: A systematic literature review on current development and potential applications. IEEE Access, 8, 62478-62494. 10.1109/ACCESS.2020.2983601.
Dash, R., McMurtrey, M., Rebman, C., & Kar, U. K. (2019). Application of artificial intelligence in automation of supply chain management. Journal of Strategic Innovation and Sustainability, 14(3), 43-53. https://www.researchgate.net/profile/Upendra-Kar/publication/334749440_Application_of_Artificial_Intelligence_in_Automation_of_Supply_Chain_Management/links/5d7026aa4585151ee49e45da/Application-of-Artificial-Intelligence-in-Automation-of-Supply-Chain-Management.pdf.
Garrido-Hidalgo, C., Olivares, T., Ramirez, F. J., & Roda-Sanchez, L. (2019). An end-to-end internet of things solution for reverse supply chain management in industry 4.0. Computers in Industry, 112, 103127. https://doi.org/10.1016/j.compind.2019.103127.
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117-2135. https://doi.org/10.1080/00207543.2018.1533261.
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