Let’s first talk about artificial intelligence. AI is the umbrella term encompassing machine learning (ML) and other natural language processing, computer vision and robotics. ML is a specific technique that allows machines to learn from data and improve their performance over time.
Now, the ability of machines to perform tasks typically associated with human intelligence or to learn from data without being explicitly programmed sounds truly amazing; examples here include self-driving cars, virtual assistants and even your spam filter. Even tonight’s TV recommendations from Netflix or your bank’s fraud detection both utilize ML. These are powerful tools that can be used to solve various problems. But, and this is the rub, they are still in their early stages of development. We have been using algorithms and mathematical modeling in supply chain software for years. AI has the potential to revolutionize the way we interact with data and the world around us.
So, back to my opening statement, are you ready for AI? If not, what should you consider doing next?
AI: Transforming the Supply Chain Landscape
Like it or not, the process of moving goods from point A to point B is now being transformed by smart algorithms and ML. Let's give some more context to our conversation. In McKinsey Digital’s June 2023 issue, their report, “The economic potential of generative AI: The next productivity frontier,” stated that generative AI is poised to unleash a new wave of productivity and could add the equivalent of $4.4 trillion to the world economy by 2040. To put that into perspective, the UK’s total GDP is $3.1 trillion—truly staggering numbers.
In Syncron’s research commissioned through Vanson Bourne, we surveyed 500 supply chain leaders. We found that if organizations could invest in desired operational improvements, they would expect an average 10.5% increase in organizational profits. Could AI-based applications like OpenAI, ChatGPT or Bard be responsible for delivering these profits in our supply chains?
Before getting too carried away, we must ask a simple question. Is AI going to be incredibly disruptive in the supply chain, and if so, how disruptive? From my perspective and personal involvement in my organization’s technology and roadmap, it’s a very simple answer: AI is transforming how businesses operate and manage their supply chains. AI can help optimize various aspects of the supply chain, such as demand forecasting, inventory management, logistics, procurement and customer service. AI can also enable new capabilities, such as predictive analytics, prescriptive actions and autonomous decision-making.
However, AI also poses significant challenges and risks for the supply chain. AI can disrupt existing processes, roles and relationships, requiring businesses to adapt and restructure their operations. AI can also create ethical, legal and social issues, such as data privacy, bias, accountability and transparency. AI can also increase supply chain vulnerability to cyberattacks, malfunctions and errors.
Therefore, businesses need to carefully assess the potential impacts of AI on their supply chain and prepare for the changes and uncertainties that AI will bring. They need to develop a clear vision and strategy for leveraging AI in their supply chain and aligning it with their goals and values. The question is, should I make fundamental technology changes to embrace AI or take a more cautious, step-by-step approach?
A Deeper Dive Into ML
At this point, let’s get past the hype cycle surrounding AI. Is AI just advanced ML? The answer is both yes and no. As we have already learned, AI is a broad term encompassing many different technologies, including ML. ML is a type of AI that allows computers to learn from data without being explicitly programmed.
Let’s ask Bard from Google what it thinks by prompting, “What is machine learning?”
Machine learning is a type of artificial intelligence (AI) that allows computers to learn without being explicitly programmed. Machine learning algorithms use data to learn how to perform tasks, such as classifying images, predicting outcomes, or detecting fraud.
There are two main types of machine learning: supervised learning and unsupervised learning. In supervised learning, the computer is given a set of labeled data, such as images with labels of what the objects in the images are. The computer then learns to associate the labels with the features of the images. In unsupervised learning, the computer is given a set of unlabeled data, and it learns to find patterns in the data without any prior knowledge.
Generative AI is a type of machine learning that can create new content. It does this by learning from a dataset of existing content and then using that knowledge to generate new content that is like the training data.
How ML Can Revolutionize Supply Chain Organizations
So, in a sense, AI is just advanced ML. However, it is a specific type of ML that has the potential to revolutionize many industries. Let’s look at some examples:
AI can be used to automate many of the tasks that are currently performed by humans in the supply chain, such as order processing, scheduling and inventory management. This can free human employees to focus on more complex tasks, like customer service and strategic planning.
AI can optimize supply chain processes, such as transportation, warehousing and production. This can lead to more efficient use of resources and lower costs.
AI can be used to make predictions about demand, supply and risk. This can help businesses to make better decisions about allocating resources and managing their supply chains.
AI can be used to personalize experiences for customers and suppliers by understanding their needs and preferences. This can help businesses to build stronger relationships with their customers and suppliers.
AI can be used to improve visibility into the supply chain by tracking shipments, monitoring inventory levels and identifying potential problems. This can help businesses to make better decisions and respond to challenges more quickly.
How Supply Chain Organizations Can Best Prepare for AI
Fortunately, there are steps supply chain organizations can take to get ready for the future of AI. Here’s how:
Understand the potential benefits of AI
Businesses need to understand the potential benefits of AI for the supply chain to be motivated to invest in it. These benefits include increased productivity, efficiency and visibility and the ability to make better decisions and mitigate risks.
Assess their current capabilities
Businesses need to assess their current capabilities in terms of data, technology and skills to determine how they can best adopt AI. They need to identify the areas where they are strong and where they need to improve.
Develop a roadmap
Businesses need to develop a roadmap for the adoption of AI. This roadmap should outline the steps they will take to implement AI, the resources they will need and the timeline for implementation.
Invest in the right technologies
Businesses need to invest in the right technologies to adopt AI. This includes investing in data analytics, ML and other AI-related technologies, but this doesn’t have to involve complete system upgrades with all the resultant costs. Look for complementary technologies that augment your current IT stack. This is a matter of evolution and not revolution.
Build the right skills
Businesses need to build the right skills to adopt AI. This includes training employees on how to use AI-related technologies and how to interpret AI-generated insights.
Partner with the right organizations
Businesses can partner with other organizations that are already using AI in the supply chain. This can help them to learn from the experiences of others and to avoid making the same mistakes. Choose a partner with a proven track record in delivering fiscal results utilizing AI technologies.
Don't try to implement AI across your entire supply chain all at once. Start with a small pilot project to test the waters and see how AI works in your context.
AI is a complex technology that takes time to implement and get it right. Don't expect to see results overnight.
AI is constantly evolving, so you must be flexible and willing to adapt your plans as needed.
Be open to feedback
Get feedback from your employees and other stakeholders as you implement AI. This feedback will help you to improve your AI initiatives and make them more successful.
Given the current industrial and financial climate, anything I can do to help my customers improve their resilience has got to be a top priority.
Resilience: The Key For Supply Chains Navigating Their AI Future
The ability to proactively identify risks, preempt crises and optimize decision-making has become imperative for service and supply chain leaders. Preempting risk is vital because it ensures operational continuity and minimizes the financial effects of disruptions. By identifying potential risks early on, organizations can take proactive steps to mitigate them, avoiding production delays, stockouts and customer dissatisfaction. Anticipating risks can also provide insights that empower leaders to design resilient, agile supply chains that adapt to future challenges with ease.
However, efficient, responsive supply chains require an intelligent infrastructure that differentiates these organizations from the competition and equips them with advanced data analytics, predictive capabilities, intelligent automation, cognitive computing, and optimization tools. According to McKinsey & Company, “successfully implementing AI-enabled supply-chain management has enabled early adopters to improve logistics costs by 15 percent, inventory levels by 35 percent and service levels by 65 percent, compared with slower-moving competitors.”
By harnessing the power of AI, service and supply chain organizations can enhance their ability to see around corners and identify risks on the horizon, make data-driven decisions, optimize operations and adapt to the new service economy and evolving supply chain challenges.
So, there you have it. AI is the future of supply chain management. And if you're not using it, you will be left behind. But don't worry, you're not alone. Most businesses are still in the early stages of adopting AI. But the sooner you start, the sooner you'll start reaping the benefits.
Here’s one final point I’ll leave with you. A few weeks ago, I attended a service conference in Switzerland and the topic of generative AI came up in our discussion. I was sitting next to a service executive from a large medical technology OEM, and he said something that stuck with me: “The biggest concern I have with new technology is not security. I’m more worried that we are not moving fast enough. We have never seen technology transform so rapidly, and it will be the great equalizer. I hope my organization is flexible enough to test new solutions and take on some risk.”