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The AI Revolution in Supply Chain Mapping

The AI Revolution in Supply Chain Mapping

Over 70% of CEOs state that artificial intelligence (AI) is delivering a strong ROI for their supply chain operations. Impacting everything from logistical efficiency to disruption prevention, AI has the potential to revolutionise how the modern supply chain operates.

Early adopters of artificial intelligence supply chains are already seeing a 15% decrease in the costs of logistics management and strategy planning. As artificial intelligence tools continue to develop, new use cases will arise. With these new aspects of AI functionality, business leaders will be able to use AI in several parts of the supply chain, enhancing it across the board.
Considering the vast number of benefits that AI can offer in the supply chain, it’s no wonder that, by 2025, 38% of supply chains will perceive AI as critical to the success of their business.

Artificial intelligence adoption rate in supply chain and manufacturing businesses worldwide in 2022 and 2025.

Source – Artificial intelligence adoption rate in supply chain and manufacturing businesses worldwide in 2022 and 2025.

Let’s discuss the AI revolution in supply chain mapping and demonstrate exactly how artificial intelligence is strengthening supply chain links around the globe. 

The Power of AI in Supply Chain Mapping

One of the reasons that artificial intelligence is having such a profound impact on supply chain mapping and operations is that it has numerous deployments. AI isn’t just one thing; on the contrary, it offers applications that can slot into various parts of a supply chain.

Here are just some of the most useful deployments and how supply chains are using them:

  • Predictive Analytics – Artificial intelligence tools are able to process large volumes of historical data, turning historic trends and patterns into potential future forecasts. Based on product demand, disruption frequency, and other historical data, AI tools can provide accurate predictions in future operations.
  • Real-Time Data Processing – Real-time data processing allows supply chains to turn the vast quantities of data they produce into actionable insights that vendors can use to optimise processes. By analysing data as it comes in, AI systems can help to improve responsiveness and decision-making throughout the supply chain. 
  • Route Optimisation – Another important aspect of monitoring the supply chain is tracing the movement of logistics vehicles as they move across the globe. With AI systems, real-time data processing can simulate transport journeys and determine the most cost-efficient and fastest route to take. This form of AI application helps enhance the supply chain while improving transparency regarding where goods are on the supply chain map at any given moment.
  • Intelligent Warehousing – AI-powered warehouses use AI technology to gather and analyse sensor data across warehouses. Armed with this information, AI systems can automate several of the most time-consuming aspects of warehouse management, like picking and packaging products, monitoring inventory levels, and generating reports about warehouse operations. Businesses can use this deployment of AI to get full visibility into each warehouse or vendor base of operations in their supply chain.

Perhaps one of the most powerful deployments of AI in supply chain mapping is enhanced decision-making. By processing huge qualities of data concurrently, AI models are able to create highly precise data-driven insights. Supply chain businesses can then extrapolate from these insights to support strategic decision-making.

When making decisions related to vendors and supply chain stability, companies used to have to rely on business intuition to drive them toward operational changes. Yet, with the rising availability of data, combined with AI tools to capture and process the needed volumes of information, organisations can now resort to data-backed strategies.

Instead of launching directives in the dark, supply chain businesses can use AI-enhanced decision-making to pilot their company toward more stable, effective choices.

Real-Time Visibility and Efficiency

Visibility is one of the leading factors that contributes to a secure supply chain. Without a comprehensive and granular understanding of supply chain logistics connections and the flow of products through partners, a business is unable to future-proof its supply chain.

In traditional supply chain networks, vendors and contractors have a limited view into the operations of their partners. Without the ability to process data in real-time, the majority of insight comes from reports that a company receives each month or quarter. 

With AI-driven visibility, businesses can collect and process data from numerous sources concurrently. For example, AI can process sensor data from warehouses and logistics trucks while also monitoring production lines. This holistic view of supply chain operations provides complete visibility into the supply chain.

Additionally, with this information, businesses can then use AI to conduct predictive analytics, achieving insight into potential future trends. Moving toward more transparent supply chain systems enhances everything from operational efficiency to compliance. As an organisation has direct visibility into the business practices of its partners, it can monitor for any processes that may violate regulatory frameworks like the CSDDD or the CSRD.

True visibility over the supply chain provides an enhanced and real-time perception of operations, yielding precise and comprehensive supply chain mapping.

Achieving Operational Efficiency with AI

Another deployment of AI that’s aiding in enhancing supply chain efficiency is automation. Robotic process automation (RPA) allows businesses to automate highly routine tasks. Typical tasks in the supply chain, like checking stock levels, packing boxes, or picking products off shelves, are all prime for automation. 

Any task that typically follows the same format is easy to perform with artificial intelligence. AI lends itself to mass RPA, minimising the need for manual interventions. Firstly, this enhances the efficiency of the supply chain, as tasks can be completed 24/7 without the need for human interaction. Secondly, this frees up hours of the day for human workers, allowing them to instead focus on higher-value tasks. 

By automating routine tasks and allowing human agents to focus on more pressing matters, AI helps to streamline every level of the supply chain. Key tasks across each segment of the supply chain are perfectly primed for automation. 

Predictive Analytics and Demand Forecasting

Predictive analytics and demand forecasting are two central parts of supply chain mapping. By collecting information about suppliers, worldwide demand, and changes in consumer habits, AI tools are able to provide accurate predictions about potential future client demands. With this insight, supply chain companies can better prepare for the future, preventing moments of excess inventory or stock buyouts. 

Traditional statistical algorithms can already conduct predictive analytics. Yet, the core value that AI delivers in this regard is that it is much more precise. Statistical algorithms can use past trends to forecast future predictions with a 77.45% accuracy. AI predictive analytics, on the other hand, can deliver a 94.56% accuracy when using the same data.

These figures will only become even further away as artificial intelligence tools continue to develop. As AI learns from its own mistakes and trains on large quantities of supply chain data, it will become even more precise and integral to supply chain mapping and prediction.

Source – Percentage Average Accuracy of Prediction Algorithms.

By leveraging predictive analytics and learning from historical and current data, AI can:

  • Identify Shifts in Consumer Demand: Identifying small changes in consumer demand will help your business alter its strategy ahead of time to optimise inventory ordering and management.
  • Locate Optimisation Opportunities: By monitoring the performance of your supply chain over time, predictive analytics and forecasting tools can simulate improvements and demonstrate how effective certain optimisations would be.
  • Refine Accuracy Over Time: AI tools are constantly improving, allowing them to provide more business value with higher precision as they learn from your company’s unique data. 

AI allows businesses to better prepare for the future while optimising current processes. 

AI and Risk Management in Supply Chains

Risk management in the supply chain is a vital pursuit, allowing businesses to prepare for potential disruptions and mitigate losses. Each year, disruptions in the supply chain cause over $184 million USD in damages on average. With that in mind, artificial intelligence has become a pertinent tool that’s shaping risk identification, management, and mitigation.

Artificial intelligence tools like Prewave’s Tier-N Monitoring use real-time data, historical insight, and public data to generate comprehensive visibility into suppliers around the world. By combining these sources of data, Prewave is able to achieve full 360-degree visibility into supply chain risk.

The platform gives each supplier a risk rating, with suppliers that are more likely to cause a future disruption getting a worse score. Based on this information, supply chain vendors are able to analyse their suppliers and then mitigate potential disruptions.

For example, if a business noticed that one of its suppliers had a significant risk profile, then it could start to distribute the materials or goods acquired from that supplier over many different companies. Taking action ahead of time then reduces the total risk that a company takes, allowing it to build up resilience. If that supplier were then to fail or be unable to deliver, the company already has backup contracts and suppliers ready to step in to sustain production.

By using real-time analysis and powerful predictive analytics technology, Prewave’s selection of AI services help to greatly improve risk management in supply chains.

Resilience in the Face of Disruptions: AI and Supply Chain Resilience

Another way that artificial intelligence in supply chain mapping helps to enhance operations is by providing solutions to live disruptions. Even with AI-driven risk management tools, there is still a chance that completely unforeseen disruptions disable your operations and cost your business money.

While precise AI risk management tools have made this scenario far less common, the chance is far from zero. To counter this and allow businesses to continue operations during disruptions, supply chain organisations are again turning to artificial intelligence.

AI can help enhance supply chain resilience by providing several options during disruptions:

  • Dynamic Adaptation – Based on disaster situations, AI systems can recommend changes that organisations can make to overcome these scenarios. Highly effective real-time processing will suggest the best course of action, helping to reduce the time taken to get back to a normal level of functionality.
  • Real-Time Optimisation – While human operators have specific shifts that they cover, AI tools can work around the clock. This flexibility, combined with the ability to process new data in real-time, allows AI systems to make micro-adjustments to supply chain mapping and operations. Whenever new scenarios arise, whether predicted or not, AI can then collate masses of information to find the most efficient way to proceed. Using this strategy of real-time optimisation and strategy shifts enables businesses to reach new heights of operational efficiency. 
  • Automatic Response Procedures – Every year, thousands of cyber attacks disable supply chain businesses, impeding their functioning and threatening their data. While developing an effective security posture is vital to prevent this, AI tools can also provide useful protection here. By developing AI protocols that automatically respond to cyber threats and signature incident markers, you can mobilise a cyber response in a fraction of the time. An automatic AI defence will ensure that your business is less exposed during a cyber attack, minimising damages and helping your business to get back up and running as quickly as possible. 

Artificial intelligence tools are actively creating a more stable, resilient supply chain system across the globe. The vast range of deployments all lend themselves to supply chain mapping, creating stronger transport links, more predictable systems, and stable levels of risk.

Embracing the Future with AI

Artificial intelligence tools actively integrate into nearly every aspect of supply chain mapping and management. These technological advancements help to shape the supply chain for the better, automatic tasks, enhancing operations, and improving the resilience of the modern supply chain.

Prewave offers leading AI-enhanced supply chain risk management software. With our systems, you can gain complete visibility of your supply chain, enhancing transparency and protecting your business from potential disruptions.

With real-time visibility into supply chain processes, Prewave improves your supply chain processes, allowing you to reach new levels of efficiency. 

Book a demo with Prewave or reach out to the team today to start building a more resilient and dynamic supply chain. 

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