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7 Critical Supply Chain Technology Innovations Reshaping Financial Auditing in 2024
7 Critical Supply Chain Technology Innovations Reshaping Financial Auditing in 2024 - Blockchain Networks Enable Real Time Transaction Verification Across Global Supply Networks
Blockchain's distributed ledger technology is transforming how transactions are validated across global supply networks. This real-time verification capability provides a level of transparency and visibility that wasn't possible before, allowing businesses to see exactly where products and materials are at any given moment. One of the key features is the use of smart contracts, which automatically trigger pre-defined actions in response to specific events within the supply chain. This allows for faster responses to disruptions and potential problems.
Furthermore, blockchain can streamline numerous operational processes, potentially reducing the administrative burdens associated with managing complex global supply chains. The rise of blockchain in supply chain management has accelerated in response to events such as the pandemic, which brought the vulnerabilities and complexities of these systems into sharp focus.
While blockchain offers clear potential, its success is dependent on user adoption. Companies need careful planning to ensure a smooth integration, including clearly defined digital tagging and tracking procedures. Combining blockchain with technologies like IoT can potentially unlock even greater efficiency and data management capabilities. But it is important to acknowledge the difficulties in adopting it, such as users needing to change existing practices in order to gain the benefits. Ultimately, blockchain has the capacity to address some long-standing issues within global supply chains, including challenges related to traceability and collaborative decision-making.
Blockchain networks offer a compelling approach to supply chain management by facilitating real-time verification of transactions across the globe. Essentially, each participant in the chain can view the same, tamper-proof record of every transaction. This is achieved through a unique linking of each transaction to the previous one, creating a chain that's hard to alter. This kind of real-time transparency can be quite useful in pinpointing fraudulent activities promptly, hopefully minimizing financial losses for businesses.
However, the specifics of how the blockchain operates can impact its usefulness in a fast-paced supply chain. Different blockchains use varied approaches to achieve consensus, with trade-offs in energy usage and transaction speed. We still need to understand how these mechanics interact with the real-world demands of managing a supply chain efficiently.
The ability of the chain to record the movement of goods in real-time opens up opportunities for insightful supply chain mapping. Businesses can track a product's journey throughout the supply network, which could lead to better decision making.
We also see the potential for smart contracts within these systems. Smart contracts are pre-programmed agreements that automate actions based on predefined conditions. This could lead to streamlining of various supply chain tasks and reduce the chance of human error, theoretically leading to less administration overhead.
Having a shared ledger that's accessible to all players in the supply chain could do a lot to clear up the mess of having differing records across the chain. This would eliminate discrepancies, especially when working across companies in different countries or regions, and potentially save time that would otherwise be spent reconciling conflicting records.
Supply chain financing could also be impacted. By linking financing options directly to digital assets tracked on the chain, we could potentially improve cash flow management and make capital more accessible in this area. Additionally, the potential to sidestep some of the bottlenecks inherent in global banking due to traditional systems could expedite international trade.
We see various industries, from food and beverages to pharmaceuticals, experimenting with blockchain for enhanced product tracing. This is driven by a need to comply with regulations and also to offer customers greater transparency on the journey of the products they buy. But of course, this raises questions about how these systems will change the current landscape of these sectors.
7 Critical Supply Chain Technology Innovations Reshaping Financial Auditing in 2024 - Machine Learning Algorithms Detect Supply Chain Payment Fraud Within Minutes
Machine learning is increasingly being used to identify fraudulent payments within supply chains. These algorithms can quickly scan transaction data to spot unusual patterns and potentially fraudulent activity, such as inflated supplier invoices or forged checks, in a matter of minutes. This rapid detection capability can help businesses significantly reduce financial losses.
Supervised machine learning approaches appear to be effective in spotting various types of fraudulent behavior. By identifying and analyzing historical data, these systems can learn to distinguish between legitimate and fraudulent payments, allowing for intervention before significant financial damage occurs. Moreover, combining machine learning with other analytical tools enhances the effectiveness of the fraud detection process.
As the supply chain landscape becomes more complex, particularly in 2024, the use of machine learning to detect and deter fraud is likely to become even more important. Organizations will need to adapt to a constantly evolving set of threats and the ability to quickly identify fraud is increasingly critical. However, it's important to note that while these technologies show promise, they are not a silver bullet. Businesses will still need to carefully manage their supply chains and have appropriate controls in place to mitigate risk. The reliance on machine learning does not negate the need for human oversight and a healthy dose of skepticism when it comes to financial transactions.
The use of machine learning (ML) in supply chain fraud detection is a fascinating area. These algorithms can analyze huge amounts of data, such as payment records and invoices, incredibly quickly. For example, they can potentially sift through thousands of invoices within minutes, a stark contrast to the more time-consuming traditional methods. This speed is invaluable for auditing, offering the potential to drastically shorten the audit cycle.
These algorithms are especially good at identifying anomalies, patterns that diverge from what's considered normal. This helps them spot irregularities that might easily be missed by human auditors. Consequently, we might see improvements in fraud detection accuracy. Interestingly, some ML models are capable of learning as they process new data. This adaptive characteristic is crucial since fraud techniques often change, and these models can potentially adapt without needing constant human intervention.
While many studies focus on things like financial statement and tax fraud, there's also a focus on fraud in the supply chain itself. For instance, the use of AI to catch things like forged checks or suppliers attempting to inflate prices. This has real implications for things like payment processing, where it's critical to identify potentially fraudulent transactions quickly, such as unauthorized credit card usage, to minimize risks for both businesses and consumers.
One particularly interesting application is the use of artificial neural networks (ANNs) to classify credit card transactions. Essentially, researchers are training these networks to accurately identify fraudulent transactions, a task that traditionally can be quite challenging for humans. This approach relies on being able to differentiate between legitimate and suspicious activity based on a wide variety of transaction features.
However, as with many AI applications, there's a trade-off. It's important to look closely at the rate of false positives. It's easy to imagine a scenario where a system flags many legitimate transactions as fraudulent, which would be quite disruptive. Thankfully, more sophisticated ML models are reducing these issues, which is crucial for maintaining confidence in the technology.
ML models can also incorporate other tools and insights. For example, combining knowledge-based rules with fraud detection systems can create a more robust verification process, helping to differentiate between genuine and fraudulent activities.
Beyond simply improving individual fraud detection methods, ML gives financial institutions and policymakers more visibility into how fraud happens and how to develop better strategies to address it. It's worth remembering that ML is still in its early stages for some of these applications, and its full impact on supply chain and financial auditing is still unfolding.
There are also broader implications beyond just auditing. For example, ML can potentially lead to better allocation of human resources within the audit process, shifting people to tasks that require more strategic thinking instead of tedious, repetitive tasks.
Finally, it's essential to consider the ethical implications of using ML for fraud detection. Questions about data privacy and the security of algorithms used need to be carefully addressed. While the speed and accuracy of ML offer a potentially potent tool against fraud, there's always a need to balance the benefits with the potential risks of unintended consequences. This balancing act is key to successful implementation. The emergence of these ML technologies is certainly one of the big shifts in the field of financial auditing and risk management for 2024 and beyond.
7 Critical Supply Chain Technology Innovations Reshaping Financial Auditing in 2024 - IoT Sensors Track Physical Assets Through Every Stage of The Supply Process
IoT sensors are transforming how businesses monitor the movement and condition of physical assets across the entire supply chain. These sensors, using technologies like GPS, NFC, and RFID tags, provide real-time location and status information at every stage. This continuous stream of data creates unprecedented visibility into the supply process, allowing businesses to be more responsive to potential problems. By sharing this data, companies can also work together more effectively, creating a more dynamic and collaborative supply chain.
Furthermore, the data generated by these sensors can be used to automate tasks and improve operational efficiency. This data can also inform decisions aimed at increasing the sustainability of the supply chain. A practical example is Remote Container Management systems that use IoT to track and manage refrigerated shipping containers, improving the quality and safety of goods that require temperature control. This demonstrates how IoT can be practically applied to improve supply chain practices.
The widespread use of IoT in the supply chain marks a significant shift away from the more traditional methods of monitoring physical assets. It emphasizes the value of data in managing a complex network of transactions, suppliers, and customers. It will be interesting to see how this reliance on sensor data changes how supply chains are managed in the future.
The Internet of Things (IoT) is increasingly being used to track physical assets throughout the supply chain, a development that's gaining attention from researchers and engineers like myself. It's intriguing how devices equipped with sensors like GPS, NFC, and RFID tags are being incorporated into supply chains to monitor the location and condition of goods at every stage, from production to delivery.
One of the primary aspects that stands out is the continuous stream of data these sensors produce. The sheer volume of data generated can be significant, sometimes reaching hundreds of thousands of data points per minute. This constant flow provides a level of granularity previously unseen in supply chain operations, enabling us to gain a much better understanding of what's happening with physical assets.
The ability to track the physical location of goods in real-time is also useful. Think about the implications for logistics – businesses can keep a much closer eye on where their inventory is at any given time. This has the potential to streamline things like delivery scheduling and improve the overall flow of goods through the chain.
Beyond simply location, many of these sensors can gather data on environmental conditions. Imagine the implications for things like pharmaceuticals or food, where temperature and humidity control are crucial. The ability to monitor these conditions in real-time and potentially predict issues before they happen could significantly reduce product spoilage and potentially save businesses a significant amount of money.
Of course, integrating all this data into existing systems isn't always straightforward. The potential benefits of connecting IoT sensor data with existing ERP and financial systems are interesting, with the goal being better-informed decisions. The ability to correlate operational efficiencies and financial data is appealing, but we need to figure out the best ways to implement such integration.
But it's important to consider that there are also challenges. For example, the security of these sensor networks raises important questions. Studies have shown that these systems can have more security vulnerabilities than traditional systems, meaning a good deal of effort will need to be devoted to making sure sensitive information is protected. It's a tradeoff, though. More visibility in the supply chain also makes it easier for bad actors to find weak points.
The evolving nature of IoT in supply chain management is also important to note. This isn't a static field. Ongoing research and development are essential to understand how these technologies can be best utilized. We're still learning how these vast amounts of data can be turned into practical and useful insights for auditors and managers.
The impact of IoT sensor data on auditing practices is also a big change. Auditors now have access to this up-to-the-minute data about the movement and condition of assets. This real-time data is a departure from the more traditional ways audits were conducted. It creates potential for more accurate financial reporting and a more efficient audit process. It remains to be seen how these changes will influence the overall auditing landscape in the years to come.
7 Critical Supply Chain Technology Innovations Reshaping Financial Auditing in 2024 - Digital Twins Map Financial Impact of Supply Chain Disruptions Before They Occur
Digital twins are a significant advancement in managing supply chains, allowing companies to anticipate and lessen the financial consequences of potential disruptions before they happen. These digital replicas of supply chains, built using data from sensors, the Internet of Things, and historical records, provide a way to simulate various situations. This can help companies foresee bottlenecks, refine their inventory management processes, and respond more quickly to issues. By modeling how local decisions can ripple through global operations, they can improve the overall strength and ability to adapt to changes within the supply chain. As more companies start using digital twins, we'll likely see them play a bigger role in how financial audits are done and how supply chains are kept secure.
However, the success of this technology relies heavily on how well it integrates with current company systems and how readily organizations can adopt these new approaches. It's not a simple plug-and-play solution; companies need to adjust their practices and procedures to maximize the benefits digital twins offer. The potential is there for a major shift in how supply chains operate, but achieving it requires careful planning and execution.
Digital twins are essentially highly detailed, virtual replicas of real-world supply chains. They are constructed by blending data from sensors, the Internet of Things (IoT) devices, and historical records to create a dynamic and interactive model. The aim is to allow organizations to run simulations and understand how changes in one part of the chain might impact others. Interestingly, some researchers are reporting that these digital twins can predict the financial impact of potential disruptions with a high degree of accuracy, sometimes achieving a 95% confidence level in their forecasts. This predictive ability stems from the capability of these systems to model a wide range of possible scenarios, making it possible to uncover potential vulnerabilities and to plan for unexpected disruptions.
It's intriguing to see how this approach can lead to better risk management. Companies experimenting with digital twins have reportedly managed to cut the financial losses associated with disruptions by roughly 30%. This significant reduction likely comes from the ability to run simulations ahead of time and identify the areas that might be most prone to problems. The technology allows you to ask "what if" questions, examining how different decisions or external factors (like weather or geopolitical events) might affect the supply chain.
The integration of IoT data is quite interesting in this context. Not only can you pinpoint the location of assets, but you can also get real-time information on factors like temperature and humidity. This detailed level of insight can lead to more timely financial decisions and a greater understanding of how the physical world intersects with operational efficiency and potential financial implications.
Another intriguing aspect of digital twins is that they can help speed up response times to disruptions. Organizations can leverage the predictive insights generated by these systems to react more quickly to issues, leading to faster decision-making. Some companies are even reporting a reduction in their decision-making process from days to hours. This ability to react rapidly can be critical for mitigating losses during unexpected crises.
Moreover, you can use digital twins to overlay historical data onto current conditions. This capability allows finance teams to better assess the probability of operational issues impacting cash flow and potentially influencing budgeting decisions. It's like having a historical context for a real-time view of the chain, a useful combination that can greatly aid in forecasting and decision making.
While some might worry about the cost, surprisingly some organizations have observed a relatively rapid return on their investment in digital twin technology. There are some who report being able to achieve a positive ROI within a year of implementation. This benefit may come from reduced downtime and better inventory management, both of which are crucial for maintaining profitability and cash flow.
The visualization tools embedded in digital twin platforms can be quite useful. They often provide a dashboard-like interface for observing potential disruptions and understanding their financial repercussions. This can encourage more interdepartmental collaboration and allow leaders to strategize effectively by having a common understanding of the issues and their potential impacts.
The integration of digital twins with machine learning algorithms could be significant as well. The ability to further enhance predictive capabilities by layering on AI and ML models could give an even more granular understanding of risk and opportunity. This improved understanding can aid in better planning for the future.
The benefits of digital twins aren't limited to a company's own internal operations. Businesses are starting to experiment with sharing simulated outcomes with their suppliers. This level of transparency and collaboration can ultimately improve the financial health of the entire supply chain network, something that's beneficial for all parties. It's a step toward more collaborative and resilient networks.
As this technology matures, it's becoming clearer that it offers a distinct competitive advantage. Companies who have mastered the use of digital twins are reportedly experiencing reductions in supply chain costs of up to 20%. This type of efficiency gain can have a major positive effect on a company's bottom line.
Despite the potential benefits, it is important to note that these are nascent technologies that still require ongoing development and careful consideration regarding integration into existing infrastructure and processes. It's a technology worth tracking and exploring, however, since the potential for improvements in supply chain management seems quite promising.
7 Critical Supply Chain Technology Innovations Reshaping Financial Auditing in 2024 - Smart Contracts Automate Purchase Order Matching and Payment Processing
Smart contracts are increasingly being used to automate parts of the supply chain, including the often-tedious processes of matching purchase orders and handling payments. The core idea is that these contracts are self-executing digital agreements that trigger actions only when certain criteria are met. This automation can streamline operations and slash costs associated with manual processes. Additionally, it can create greater transparency and trust between the various entities involved in a supply chain, especially when combined with the security features of blockchain technology. Blockchain can act as a secure ledger for tracking and tracing the movement of goods throughout the chain, adding another layer of confidence in the transactions.
However, implementing smart contracts successfully can be tricky. It requires a careful assessment of how they'll mesh with existing systems and processes. There's still a lot to learn about the long-term effects smart contracts will have on how supply chains function and how financial auditing is conducted. The potential is certainly there for significant change, but how it all plays out in the coming years will be interesting to observe.
Smart contracts are increasingly being explored within supply chains for their potential to streamline processes like purchase order matching and payment processing. The core idea is that these contracts, which are essentially self-executing agreements encoded in code, can automatically trigger actions based on predefined conditions.
For example, a smart contract could be designed to compare a purchase order against a corresponding invoice and goods receipt. If all three match, the contract could then automatically initiate payment to the supplier. This eliminates the need for manual intervention in these often tedious and error-prone processes, which can lead to greater efficiency. It is intriguing to consider how a 99% matching accuracy rate could potentially transform the current error rate. While it may be years before the technology becomes fully mature, there's a compelling argument for this approach to become more commonplace. We could see a situation where the speed of payments is drastically different, shifting from days to a mere fraction of a second.
However, there are some lingering concerns regarding this technology. It's important to recognize the reliance on oracles for external data input. In order to function correctly, these smart contracts often require data from the real world—things like confirming the delivery of goods, the quantity received, or changes in market prices. The accuracy and reliability of these oracles can become a key element in the entire process. The degree to which multiple oracles are used to verify each other will also be important to establish trust and accuracy. Furthermore, having various stakeholders within a supply chain agreeing to use and trust a shared system, such as a blockchain, presents challenges. There are legacy systems, existing contracts, and a certain level of comfort with established methods of operation. This creates a barrier to change that might need to be overcome before smart contracts are broadly adopted. Another aspect to consider is the inherent complexity of such systems. Smart contracts are encoded in code and are not easily understood by everyone.
Having said that, these automated agreements do provide a way to improve traceability throughout the supply chain, potentially reducing disputes and improving audit trails. They can handle a large number of transactions, and their parameters can be adjusted on the fly as the circumstances of the supply chain change. Moreover, some believe they can simplify legal compliance, perhaps by reducing the need to track and reconcile disparate regulatory requirements. The impact on businesses dealing in international trade could be significant, as smart contracts can potentially smooth out the inherent challenges in currency conversion and the complexities of navigating different regulatory environments.
But I think it is still too early to predict the full scope of this technology's impact. It's important to acknowledge that we're still in the relatively early stages of adoption. A great deal of work remains to explore the full potential of smart contracts and how they can be integrated into existing systems in a way that leads to clear and demonstrable value for the many parties in a complex global supply chain. The next few years will be fascinating for supply chain researchers and engineers.
7 Critical Supply Chain Technology Innovations Reshaping Financial Auditing in 2024 - Cloud Based Supply Chain Analytics Platforms Process Millions of Daily Transactions
Cloud-based supply chain analytics platforms are now handling an enormous volume of data, processing millions of transactions each day. These platforms rely on a range of sophisticated techniques, such as machine learning and big data analytics, to offer insights into aspects like predicting demand, keeping track of inventory, and maintaining visibility into supplier operations. By processing this immense amount of data, companies can make more informed decisions in a timely manner, reacting to unexpected disruptions more efficiently and optimizing their overall operations. The adoption of these platforms signals a move towards supply chain management that's driven by data, which in turn, leads to increased efficiency and helps manage the complex challenges in this area. However, depending on these sophisticated tools brings its own set of difficulties, specifically regarding maintaining the accuracy of the data and integrating them effectively with a company's existing systems. It's a powerful tool but not without potential pitfalls.
Cloud-based supply chain analytics platforms are processing millions of daily transactions, handling data at massive scales, sometimes exceeding petabytes. This enormous volume necessitates sophisticated data storage and processing, posing intriguing challenges for researchers like myself to ensure rapid access and analysis without sacrificing speed.
The real-time analytics capability of these platforms is notable. It's allowing businesses to react to disruptions almost instantaneously, which in turn leads to better efficiency and faster decision-making, reducing the financial consequences of disruptions. It's fascinating to see how quick responses to these events are leading to less disruptions.
Predictive analytics within these systems, powered by machine learning, are getting very good at anticipating supply chain disruptions. Some algorithms can forecast disruptions with incredible accuracy, as high as 95%. This ability to anticipate and potentially mitigate disruptions before they occur could lead to big changes in how organizations operate.
Another compelling aspect is cost-effectiveness. The shift to cloud-based solutions often reduces expenses significantly by eliminating the need for companies to maintain on-premises systems. We're seeing some reports indicating cost reductions of around 30%, which is a noticeable impact on organizations, especially those with intricate global supply chains.
The scalability and adaptability of these platforms are key. They allow companies to adjust their analytics resources according to their needs. This is crucial during fluctuating periods, when transaction volumes can change suddenly, offering the agility to respond to such variability.
These platforms are also capable of merging data from various sources, including the Internet of Things (IoT) devices, customer relationship management (CRM) systems, and enterprise resource planning (ERP) systems. This comprehensive view of the chain can help improve visibility and coordination across the supply network, with the goal of reducing friction and enhancing efficiency.
Security and compliance are important in such systems, and many cloud analytics solutions include advanced security protocols to safeguard sensitive data. This can lead to a streamlined compliance process, since cloud providers regularly update their security to address the constantly evolving threats in cyberspace.
Modern platforms focus on user experience, presenting intuitive interfaces so that even those without a strong technical background can understand and use the data. It is quite interesting to see how the accessibility of these systems are changing how businesses approach supply chain management.
Automated reporting can provide crucial insights into key performance indicators (KPIs) in real-time. This can lead to fewer manual tasks in data collection and analysis, freeing up resources for more strategic initiatives.
These platforms facilitate collaboration between departments and external partners by creating shared data spaces. This interconnectedness promotes more efficient sharing of information, which can improve the agility and response capabilities of the supply chain. This is leading to new ways to integrate organizations and manage global operations.
It's clear these technologies are transforming how we manage global supply chains. The scale of data involved, the speed of analysis, and the ability to anticipate issues are creating a fascinating shift in this field. It remains to be seen how the technology will continue to evolve and reshape how we approach these complex global systems in the future.
7 Critical Supply Chain Technology Innovations Reshaping Financial Auditing in 2024 - Advanced API Integration Links Previously Disconnected Supply Chain Systems
Advanced API integration is reshaping supply chains by connecting previously isolated systems. This newfound connectivity allows for real-time data sharing and facilitates a much more agile response to changes and disruptions. The ability to instantly update information across warehouses and other locations using protocols like REST APIs has the potential to vastly improve performance. This means smoother order fulfillment, faster invoice matching, and a more streamlined customs process—all contributing to a more efficient supply chain.
One of the key impacts of this is that it reduces the reliance on isolated, inflexible systems. By breaking down these operational silos, companies can improve cooperation and communication across the chain. This level of collaboration is crucial as supply chains become increasingly global and complex.
The shift toward an "API-first" approach signifies a future where software integration is simpler and more seamless. This design philosophy prioritizes exposing functionality through APIs to support interoperability across various supply chain software tools. While this could greatly enhance efficiency and communication within the supply chain, it is also forcing companies to assess if their current infrastructure can support these changes. Adopting such a comprehensive change often requires extensive revisions to existing systems and possibly changing established work processes. While the potential benefits are compelling, the effort needed to realize them shouldn't be underestimated.
Advanced API integration has become a vital force in modern supply chains, particularly in the context of 2024. It's fascinating how these APIs, essentially the connective tissue between different software systems, are now weaving together previously disconnected parts of the supply chain. It's not uncommon to find older, legacy systems that weren't designed to work together, creating data silos and operational bottlenecks. APIs are a way to get these systems to talk to each other, a development that has the potential to greatly improve operational efficiency and reduce errors in data sharing.
One of the most notable aspects of advanced API integration is the ability to synchronize data in real-time. Imagine a scenario where a retailer's online store instantly updates inventory levels based on a warehouse management system. This sort of instant synchronization, which is powered by REST APIs in many cases, is changing how supply chains react to demand fluctuations. Before this level of integration, it was more common to see a delay between when a product was sold and when the inventory system was updated. This lag in information flow could create issues if a company was unable to quickly restock a popular item. The advancements in API integration, in turn, is improving the responsiveness of supply chains to market demands.
Beyond data synchronization, advanced API integration is showing promise in simplifying complex processes. Take the example of order fulfillment: with APIs, the process of accepting an order, routing it to the appropriate warehouse, updating inventory, generating a shipping label, and tracking its movement can be a smoother and more efficient process. We also see automation potential in areas like invoice matching and even custom clearance, all of which can be helped by API integration. This degree of automation is an area where researchers and engineers are currently exploring the impact of automation on the various roles within these systems.
However, the ability to integrate across complex supply chain networks is not without its challenges. One aspect that's worth noting is the need to carefully consider the data security of systems that rely on API integration. While the benefits of improved communication and data sharing are numerous, there's also a need to maintain a high level of security in this interconnected world. Additionally, the complexity of integrating multiple API layers requires specialized expertise and sometimes a degree of standardization that isn't currently available in some sectors. The lack of standards can potentially slow down the adoption rate of certain types of API integration in some areas of the supply chain.
Despite these hurdles, the outlook for API integration in supply chains appears positive. Businesses who have invested in integrating their systems using APIs are reporting a variety of benefits, including improved agility, increased efficiency, and lower operational costs. The increased transparency that API integration provides can lead to better decision-making at all levels within a supply chain. Furthermore, it enhances the potential to expand the range of business partners a company interacts with, creating a more interconnected and globally connected network of companies. It's a fascinating development that continues to shape how supply chains function in a world that is becoming ever more interconnected. It is certain that as we go forward, we will likely see APIs become an increasingly important aspect of supply chain operations.
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