Artificial intelligence in supply chain management helps improve efficiencies and reduce costs. Learn more details about how it helps your business.
Artificial intelligence (AI) is making the supply chain industry a more efficient and effective place to do business. While artificial intelligence in supply chain management has been around for many years, it is now beginning to take off in a big way. Why? Because AI can help determine the best options for streamlining and automating your processes.
It can also make your employees' jobs easier by handling the tedious tasks they would otherwise have to do themselves. And, perhaps most importantly, it can help keep costs down while improving efficiency and productivity.
Let's take a look at how artificial intelligence in supply chain management is redefining the space how you can leverage it.
As many as 64% of manufacturers are already using AI as part of their day-to-day operations. Here are various ways artificial intelligence in supply chain management is enabling efficiencies for businesses.
Artificial intelligence in supply chain management helps with demand forecasting through data-driven demand forecasting. It allows you to process large amounts of data and make accurate predictions. Data-driven demand forecasting refers to the process of predicting future demand for a product or service based on past sales and other relevant information. According to McKinsey, AI-driven demand forecasting reduces errors by 20-50%.
This forecasting method allows you to plan your production and marketing activities better. You can also determine how much inventory you need to keep on standby. AI can help with this process by using algorithms, machine learning models, and other techniques to gather historical data and use it to predict future trends in demand.
AI can also help with other aspects of data-driven demand forecasting, such as determining which factors affect demand most significantly. It will help you focus on those when making decisions about production or inventory levels.
It's no secret that automated quality control is a big deal in manufacturing. As you aim to get more and more efficient, you need to ensure the quality of your products doesn't suffer—even as production speeds up and labor costs go down.
Automated quality control is the use of software to analyze images and videos to check for quality, consistency, and defects. Visual recognition technology helps with automated quality control as it can automatically detect and alert with an image or a video when something is wrong.
For example, you may use visual recognition technology to check for defects in your manufacturing process. It might be able to tell you that one of your machines is defective if it sees that it's producing parts that look different from what they should look like. Visual recognition technology can also help with automated quality control by ensuring all products in production look the same.
Artificial intelligence in supply chain management helps with automated warehouse management by making it easier to track and plan inventory and predict trends. With the right software, you can use the data from your warehouse management system and combine it with other sources to get a better picture of what's happening in your warehouse.
You can see how much product has been moved from one location to another, how often certain items are ordered by customers and at what times of the year, and even which products sell best during certain months or seasons. This data is invaluable for planning inventory levels and making decisions about what kinds of products you should stock in your warehouse next time.
Artificial intelligence in supply chain management also helps automate warehouse management because it makes it easier for you to predict trends based on past performance.
For example, you may notice that sales of one type of product have been increasing steadily, but another type has remained flat or even decreased slightly over time. It could indicate there's been a change in customer preferences over time. This information will be helpful for future planning.
The real-time monitoring of cargo is a critical component of any supply chain. You need to know what's happening to your shipments and how long it takes them to move from one point to another. Real-time cargo monitoring also allows you to ensure they get handled correctly.
When a shipment needs tracking, you can tag it with an RFID tag or barcode. Anyone from anywhere in the world can then scan it with a computer or mobile device. You can receive alerts if anything unusual happens during transit.
For example, if the temperature in the container rises above or below certain levels or if the container stops moving for longer than expected. The information can help you better understand how your products behave outside of your own facilities and make adjustments accordingly.
Artificial intelligence in supply chain management can automatically analyze this data so that decisions about handling can be made quickly without any human intervention.
Text analytics uses data to predict trends and patterns, as well as help develop strategies based on those findings. Artificial intelligence in supply chain management can analyze everything from customer feedback to supplier performance. The information will allow you to understand what customers want, helping you improve your product or service offerings.
AI also helps analyze large amounts of data quickly, which means you can get an accurate picture of what's happening within your supply chains much sooner than you would otherwise without technology at your disposal. It gives you more time to respond if something goes wrong. You can also investigate further if there are any red flags raised during the analysis that need resolving.
Artificial intelligence in supply chain management can analyze data trends with the help of statistical methods, machine learning algorithms, and natural language processing techniques. It allows you to predict future sales based on past sales and trends. AI also helps you get a better idea of how your customers will react to price changes and offers. It ultimately helps make more informed decisions about pricing.
The most common way to use AI for price planning is through machine learning models. They analyze past data to predict what customers will want in the future. For example, if you sell office supplies, you might use an algorithm that looks at past sales data for office supplies and predict the best pricing for each item based on the results from that algorithm.
It helps you make better decisions about pricing than you could if you were guessing or trying out different prices one by one.
Artificial intelligence can help with production planning in the supply chain by using data analysis and machine learning. It can help you predict how many products will be needed and at what time you need them.
It is essential to note that production planning is one of the most time-consuming parts of supply chain management. It can end up taking hours if done manually. By automating this process with artificial intelligence, you can save money and increase the speed at which you respond to customer demand.
Artificial intelligence in supply chain management is a great way to improve supplier relationship management. It can help by improving the speed of communication between buyers and suppliers, which is beneficial because it allows both parties to be responsive and timely in their responses. Ultimately, it leads to better results in the long run.
AI also provides a platform for collaboration between buyers and suppliers, which helps ensure everyone involved in the process is on the same page and working together towards the same goals. Furthermore, automating tasks that would otherwise require human work or attention can help save time and money for both parties involved in the process.
Artificial intelligence in supply chain management systems can help improve sustainability in supply chains by providing insights into the environmental impact of a product's production and distribution.
As more businesses begin to recognize the value of sustainable practices, they are increasingly looking for ways to incorporate those practices into their supply chains. Supply chain managers can use AI to analyze their manufacturing processes and identify opportunities for improvement.
The data collected by AI can improve the efficiency of manufacturing processes, reduce waste, and increase resource conservation. AI can also analyze consumer demand and predict future trends in demand for products that have high levels of variability in production costs or availability.
Artificial intelligence in supply chain management also allows you to plan your production schedules better and ensure you have enough raw materials on hand when needed. It will not disrupt production flow due to shortages or delays in deliveries from suppliers or other causes related to quality control issues.
AI has been a boon to document processing automation in supply chains. It allows you to process documents more quickly and accurately, while also reducing the need for human intervention.
AI is particularly well-suited for tasks like image recognition and data analysis. It can help with time-consuming processes involved in document processing automation. For example, AI can quickly scan documents and determine whether they contain certain keywords or phrases.
Another way that AI helps with document processing automation is by analyzing large amounts of data and making predictions based on what it finds there. For example, you want to know which customers are likely to buy a certain product or service.
You can use AI to analyze past sales records and make predictions about which customers might actually buy something new from you in the future. It will also help you decide where you should focus your marketing efforts next quarter or year so that you do not waste time trying to sell products that aren't likely to sell well enough or at all.
Intelligent document processing (IDP) is a technology that helps automate the process of handling documents for your supply chain management process. IDP uses machine learning to identify and extract data from a range of documents, whether digital or physical. The extracted information can then be used to store or transfer information.
It makes IDP a convenient way to automate the data entry process. IDP also helps reduce errors in document processing by automatically identifying errors in scanned documents and correcting them before they are sent on their way. This technology is helpful for companies that need to handle large volumes of information since it can scale up or down as needed.
According to Gartner, RPA (robotic process automation) can help finance teams save up to 25,000 hours annually. Businesses that leverage IDP have a lot to gain and enable efficiencies while reducing operational costs. Since you can automate most of the document processing activity, you can instead make your team members on other crucial activities that can have a significant impact on your bottom line.
The use of IDP in supply chain businesses has increased much in recent years. Let’s consider the example of the DHL Supply Chain here. The €15 billion company has a huge finance department that deals with thousands of invoices annually. When implementing their RPA programme, they found invoice processing as one of the key activities that needed automation.
Complexities of the semi-structured documents and lack of intelligent document processing capabilities in their existing RPA systems were other factors that prompted the move. They understood their existing processes and created a system that can process invoices without human intervention. The system needed human intervention only when the text could not get matched.
The results are staggering enough to prove the capabilities of IDP. DHL Supply Chain could automate the processing of thousands of invoices from 124 vendors. The IDP platform also accurately extracted 98.9% of the English and Dutch characters. With significantly reduced errors and faster processing time, the team experienced higher productivity.
VisionERA is an advanced IDP platform with a 100% performance guarantee. It is a plug-and-play platform that can immediately process any document you like. VisionERA comes with a continuously learning mechanism, meaning that it will only improve with each document you process.
It comes with a proprietary AI technology without any dependency on third-party platforms. VisionERA automatically does the image pre-processing to prepare it for extraction. The extracted information further gets validated with a triangulation logic to ensure only the most accurate information gets passed through to the next steps.
Smart integrations with your business processes means you can export the data automatically to local and cloud databases and document depositories. The platform also offers outcome-based pricing to help you get started without any worries about making heavy initial investments. You pay only when you start getting the results and achieving your desired business objectives.
So, what are you waiting for? Get your free product demo today.