As industries develop and evolve, they become more complex and harder to manage. Supply chain management has always been a complicated process, but it's becoming even more difficult due to the digital transformation going on worldwide. Many companies and manufacturers operate from multiple locations and ensuring a constant flow of raw materials, product parts, and other ingredients is more complicated than ever before.
Managing a supply chain needs a different approach, so companies have started developing and adopting artificial intelligence solutions to streamline the process. Let's see how AI simplifies supply chain management and sets it up correctly.
These days, most corporations and enterprises operate on a global scale. Most product parts are assembled across various production plants, so ensuring that the entire supply chain works perfectly at all times is a must. The process involves multiple essential processes and functions, including production, procurement, marketing, sales, and logistics. Moreover, manufacturers also have to take care of product packaging, shipping, and many other details.
When you consider that manufacturers are always looking for ways to streamline supply chain functions and increase efficiency, new solutions are needed to cope with the rising market demands. But unfortunately, traditional methods don't work in a digital environment. Hence, manufacturers adopt or develop their own AI solutions with advanced features such as automation to optimize supply chain management, reduce industrial waste, and create a more resilient operation.
Modern problems require a modern solution. For example, supply chain management on a global scale is a complex process, even for an experienced manager. Humans can't keep up with so much data, so manufacturers started adopting AI-powered software solutions to analyze vast amounts of data and use automation to complete repetitive tasks.
Instead of dividing the supply chain into various silos, the AI can connect all processes into one centralized system to simplify supply chain management. The system can learn how the operation works to the minor details, and once it does, it can propose solutions that help increase efficiency. The process starts with data analytics, and it involves a lot of planning and monitoring. However, for everything to work as expected, companies have to overcome specific challenges down the road. The most common problems when optimizing supply chains are:
The truth is that there are many different AI solutions available at the moment. However, each of them is designed for a specific use or industry, so the next challenge is to find the ideal software for your operation.
If you Google AI for supply chain management, you'll get hundreds of solutions designed to help optimize supply chains and other business processes.
These solutions offer all kinds of features, including demand forecasting, business planning, automation, transparency, and many others. All of these solutions are built on prediction models and data analytics.
Once adopted, they first analyze large amounts of data to understand the causes and effects across the entire supply chain.
Companies that adopt this technology in the earliest stages have a 15% reduction in logistics costs, inventory improvements of about 35%, and a service improvement of 65%.
Compared to the competition that didn't adopt these technologies, their benefits can help companies get a significant competitive edge in the markets.
The adoption of new technologies is expensive and requires a complete rework of existing processes. Companies have to integrate real-time machine learning, inventory management, and all physical assets using the Internet of Things technology.
Once the adoption is done, the managers will track assets in real-time across the entire supply chain using the digital twin technology. That way, they can simulate outcomes and predict product demand with incredible accuracy.
That's why you must choose the right solution for your operation. As mentioned earlier, most AI-driven solutions are designed for specific business cases. Even if the shoe fits, you still have to ensure that the solution fits in with the overall organizational strategy of your company.
That approach will help you avoid various technical issues down the road and make the entire adoption process more manageable. Of course, even if everything aligns perfectly, you will still have to overcome various technological and human resource challenges to get things done correctly.
There is no easier way to say this - adopting and redefining supply chain management is not a simple task. In order to make the adoption process go as smoothly as possible, make sure you follow the essentials for successful digital transformation.
Here's a quick overview of the entire process:
The first and most crucial step in adopting AI-driven solutions is to identify and prioritize all processes where they provide the most value. That includes procurement, manufacturing, logistics, and even commercial operations. Then, try to see how the software helps in each area and identify the parts that provide the most value.
It would help if you defined the digital supply chain strategy that complements its overall strategy.
The software will underline the areas and processes it can improve, and your management should identify the organizational challenges that have to be made to improve performance in the future.
Depending on the system's complexity, you can approach supply chain management optimization from two different angles. You can either develop an in-house software solution by yourself, or you can get a third-party solution developed by someone else.
Generally speaking, it's always better to go with a third-party software solution designed for a specific process because it's more affordable and easier to adopt.
Many organizations combine various AI-powered solutions into one system to get the most benefits. Leading software solutions offer easy integration with other software and existing systems, so you don't have to worry about that.
The bottom line is - you have to pick the best approach for your company. With that said, keep in mind that developing an in-house solution is much more expensive, time-consuming, and risky.
Most companies don't have a lot of experience with software integration. Until recently, they used traditional methods, so they didn't have to worry about adopting enterprise-wide software solutions. However, once they find the best solution for their operation, companies have to closely follow the integration process to ensure that it doesn't exceed the budget and creates real value. Sadly only 1 out of 4 integrations goes down as planned.
You need a holistic approach to the process, and you have to find a way to integrate it across your entire operation. That's the only way to get the enterprise-wide value you can build on in the future. The end-to-end approach is the best choice because it's sustainable and provides long-term benefits.
Your internal company processes will change after adopting AI-powered supply chain management solutions. That requires a change of management and putting extra effort into employee training. The company culture changes as well, and it's up to you to find a way to present the changes to your employees.
Apart from providing your staff with extra training and education, you have to find a way to explain why the transformation is needed and how it helps secure a better future for the company.
Supply chain management has become more complex and challenging to manage than ever before. Luckily, with significant advancements in AI and computing power, companies today have access to flexible software solutions that help streamline the entire supply chain using real-world, real-time data.
The centralized approach increases visibility throughout the operation, allowing the AI to identify new opportunities and increase their ROI. The digital transformation requires a significant initial investment, but it's the only way you can secure a bright future for your company.