Global supply chains are one of the most exciting and demanding topics of our time. Whether it's Covid, the Ukraine war or, most recently, the earthquake in Turkey, supply chain disruptions can have serious and long-lasting effects on the economy, society and supply chain management (SCM). This shows once again how complex and susceptible SCM is to disruptions — whether due to changing consumer demand, unforeseeable events, or social and economic crises.
A recent Accenture study talks about ”Supply chain disruptions could cost European economies around 920 billion euros of their GDP by 2023”. This figure is caused solely by a long-standing war. Experts expect a loss of 318 billion euros in 2022 and 602 billion euros in 2023. What happens if other crises (and these are inevitable) are added to this?
To counteract this, supply chains must virtually reinvent themselves. Modern supply chain management is about resistivity, relevancy (customer orientation and flexibility) and sustainability. To address these challenges, more and more companies are turning to artificial intelligence (AI) to manage their supply chains more effectively and efficiently. When used correctly, AI can do a lot — such as providing insights into consumer behavior, predicting future trends, automating processes, and increasing transparency across the entire supply chain network. By using AI, organizations can gain a competitive advantage while ensuring continuity of operations in times of crisis.
Let's look at some of these potentials and use cases.
Demand forecasting
So-called “predictive analytics for demand forecasting” is at the top of the list for AI in the supply chain. Predictive analytics in supply chain management is used to predict future consumer demand so that companies can better manage their resources and adjust their production accordingly. In addition, through the use of predictive analytics, companies can gain insights into customer behavior, predict market trends and prepare for changes in supply and demand situations.
Examples of predictive analyses include looking at historical sales data and analyzing consumers' buying behavior, as well as using machine learning algorithms to determine correlations between various factors that could have an impact on demand — this even goes so far that, for example, the weather or political events can also be calculated. Thanks to predictive analytics, organizations can make accurate forecasts and optimize their inventory, production, and fulfillment processes, which ultimately increases efficiency in all of these areas. Costs can also be reduced. For example, companies can use AI-driven automation tools to reduce manual labor costs associated with demand forecasting.
inventory management
Inventory management is another crucial component of success in logistics. Nowadays, this management is carried out in real time (i.e. real-time inventory management). Real-Time Inventory Management is an AI-driven technology that helps companies monitor their inventory in real time. This system uses technologies such as RFID tags, bar codes, sensors, and data analytics to collect and analyze data about inventory and movement so companies can make better decisions about their inventory. With real-time inventory management, companies can track the exact location of products, predict and proactively manage bottlenecks or excess inventory, reduce the costs associated with manual tracking — and thus improve the customer experience.
Examples of real-time inventory management include automatic replenishment systems that order replenishment when stocks are low, or smart shelves that monitor product availability. If you also combine real-time inventory management with predictive analytics, demand can be predicted, which further optimizes the ordering process and shortens delivery times.
Automating processes and procedures in the supply chain
Speaking of automating processes, automated logistics uses artificial intelligence to fully automate and optimize shipments and deliveries. Similar to inventory management within a warehouse, sensors and GPS tracking are used to track shipments, monitor shipment status and identify possible delays or problems with delivery. Thanks to automated logistics plus data analysis, companies can reduce the costs associated with manual work and improve customer satisfaction through shorter and reliable delivery times. Tracking and updates are also carried out here in real time.
This is made possible, for example, by intelligent containers that monitor temperature, humidity and other environmental conditions during transport, as well as automated systems that optimize the route for deliveries. Automated logistics is another key component of supply chain management, as it enables companies to track and manage their shipments more efficiently.
Supply chain transparency
When it comes to supply chain transparency, it is more than ever about human rights, environmental protection and sustainability. The latter point will not only increasingly important for consumers, but is the most important factor when it comes to ESG (Environmental Social Governance) performance. Based on this performance data, it is measured how Companies are attractive for investors. From the reputation Quite apart.
AI is helping improve these areas by giving companies more insights into their operations. By using AI-based solutions to analyze data from the supply chain, companies are able to identify areas of waste, inefficient processes, or underutilized resources. With these insights, organizations can optimize their supply chain processes, minimize waste, reduce energy consumption and emissions (CO2 footprint), and ensure responsible sourcing of materials.
AI can also help manage risk by identifying risks in the supply chain and developing strategies to mitigate them. For example, predictive analytics can be used to identify potential ESG issues such as labor or environmental violations by suppliers before they occur. Potential risks can be proactively identified and addressed to ensure that activities comply with ESG standards set by the organization and potential stakeholders and investors.
Optimization of delivery routes and faster delivery times
When automating the supply chain, we have already addressed the reduced delivery times and the overall optimization of the supply chain.
By using machine learning, customer demand can be predicted and the entire supply chain from production to shipping can be optimized. This optimization also allows problems to be identified and resolved more quickly — in the end, all of these measures have a positive effect on customer service and lower shipping costs overall.
Customer Experience 4.0
The improvements mentioned above have, of course, a strong positive effect on the customer experience overall. But it doesn't stop there — AI continues to enable companies to offer their customers another better experience through personalization. Predictive analyses are also used here. This makes it possible to anticipate needs so that tailor-made product recommendations and discounts can be sent to customers. Thanks to the collected data, automated chatbots can be used to provide personalized customer service — around the clock, of course. All of these solutions help and, above all, retain customers who get the most out of their online shopping experience — personalized and tailored to their needs.
And it goes even further. AI can then also be used to identify potential customer problems and develop strategies to solve them before they become a real problem. Here, too, predictive analytics can be used to identify abnormalities in customer behavior or to identify potential problems in the service before they occur. Artificial intelligence can Look deep into customer behavior and anticipate problems.
Brave new world? Complex times need complex answers and solutions, which is why it is our mission at Pacemaker to apply tools and technology to challenges in a timely manner. Supply chain and artificial intelligence are in our DNA, and we'll dive deeper into the subject matter in the following articles. We are looking forward to your input and a lively exchange!