AI-Driven Flexibility: Shaping the Future of Supply Chain Operations
Key Takeaways
- Efficiency and productivity dominate traditional supply chain thinking. But what if we’re focusing on the wrong things? It’s not just about getting things done but also about choosing the right goals.
- The future of supply chain is flexibility and embracing inevitable change, rather than sticking to old processes that aren’t fit for purpose in an AI-driven era.
- Companies that welcome the power of AI can harness supply chains to achieve specific outcomes. Data fuels the engine of large language models (LLMs) and AI to drive business innovation.
Disruption is the unwritten rule for every industry, dictating how organizations think about technology, plan for the future, and do business. The supply chain industry is no exception.
Supply chain leaders often see automation as a way to reduce costs and enhance operational efficiency in a bid to combat this disruption. They’re not wrong. But why simply react to automation rather than viewing it as an opportunity?
Rather than focusing purely on productivity, companies can use technological change to think about what goals they want to achieve. Automation in supply chain can improve predictive capacities, workflows, and transparency. These forces converge to propel the supply chain industry forward.
Supply Chain: From Formal Discipline to AI-Powered Flexibility
Automation as a concept stems back to the Industrial Revolution. With mechanized manufacturing operations came both physical and process automation. Supply chain as a discipline came about in the 1980s and 1990s — as enterprises modernized with PCs, they also saw increased supply chain software and hardware solutions. The key objectives of warehouse and transportation management systems (WMS and TMS) were to boost operational efficiency, remove manual labor, and automate workflows.
Organizations are now investing early in advanced technology that wasn’t available a decade ago to improve traditionally capital-intensive automation processes. But it’s no longer enough to focus on trying to make specific processes efficient in some ten-year bet. Instead, companies should invest in the idea of flexibility. After all, if there’s anything we’ve learned in supply chain, it’s that we can count on change.
Traditional automation types don’t make as much sense anymore. On top of automation, the supply chain industry is now contending with AI and interoperability. Different automated systems connect and communicate with each other rather than remaining siloed.
The most valuable resource that we have as individuals and businesses is time — automation boils down to increasing predictability to save more of it. Then we can shift focus to more valuable ends, like innovation, business-building, or even leaving work on time.
This new wave of automation is about supply chain leaders making the industry an asset for business growth: to produce and achieve more. Going forward, boardrooms no longer see supply chain as a necessary evil — instead, it can be a prime differentiator and an opportunity to expand market share.
AI for Enhanced Supply Chain Efficiency and Goal-Creation
Four key supply chain domains can benefit from AI when increasing operational efficiency. Automation and efficiency initiatives continue in each domain:
- Inventory: As such a valuable resource asset, organizations need to be disciplined in its deployment. Businesses must calculate the correct inventory size based on forecasted demand. The more precise the forecast, the more accurate the size.
- Space: Organizations must identify what decisions and criteria they’re using with respect to warehouse and storage space. Intelligent algorithms based on patterns and profiles of inventory movements in and out of warehouses optimize those decisions.
- Labor: Labor task optimization isn’t just about prioritizing particular tasks but also about establishing the right resources for those tasks, such as machines or humans.
- Transportation: Technology can optimize asset usage for trucks and containers.
Ultimately, the aim of combining automation and intelligence seems to be higher productivity across the board. But we now have an era-defining opportunity to ask what business outcomes we want to achieve with the increased productivity. Efficiency is simply a means to an end, and at the heart of these changes is supply chain.
Powering the Humanity in Customer Service
Ten years ago, no one knew what supply chain was unless they worked in the industry. Now, supply chain is much more consumer-facing. And while our expectations and demands as consumers might have grown, we still like interacting with each other — not robots.
But that doesn’t mean we can’t use automation to improve customer service. Customers have to send back orders sometimes. It’s easy to stop there and celebrate the win that is a smooth returns process. But what if consumers could make the right purchases in the first place and skip the returns altogether?
If companies have data that can help produce better consumer outcomes, they should share that data with their customers. Targeted ads can be creepy now, but it’s easy to envision a future where we get comfortable with and perhaps even desire more of that transparency between companies and customers.
After all, we already expect consumer brands to proactively know what our expectations are, uniting manufacturers and retailers — via supply chain — to meet that demand. Modernized supply chain adjusts inventory and price: Greater precision increases convenience.
Streamlining Warehouse and Transportation Management
Consumers who heavily rely on supply chain efficiency aren’t the only winners with AI-driven automation. Businesses benefit from streamlined WMS and TMS as well. Be it physical or software-based automation, every player is looking for an edge.
Taking the Repetition Out of the Warehouse
Currently, warehouse management still rely too much on paper, email, and phones. Repeatable, manual tasks like these represent the next frontier of warehouse automation. The beauty of robotic process automation (RPA) is that original equipment manufacturers (OEMs) building enterprise supply chain software have a business arbitrage opportunity to improve their customers’ user experience. With RPA, OEMs are processing emails for their customers today, but tomorrow they’ll use electronic data interchange (EDI), and in the not-too-distant future, application programming interfaces (APIs).
Two strands of thought are at play here. The traditional focus on productivity and efficiency prioritizes data extraction, automated reports, publication, and data validation. These predictable, repeatable processes are low-hanging fruit for businesses to automate.
But the other side of the streamlining process encompasses what’s known as “quadrant two planning.” When everyone in a business is firefighting, they naturally deprioritize non-urgent but important tasks, even though these high-value tasks are what drive businesses forward.
Automation creates predictability. This newfound efficiency not only saves customers’ time but also drives value to help the business grow.
Get Ready for TMS Innovation
Automation is set to bring even more improvement and innovation to TMS than WMS. Warehouse execution systems (WES) demonstrate physicality: moving conveyors and inventory, as well as humans milling about. But this highlights the rigidity of WES versus TMS. While improvements in physical warehouses necessitate physical changes — like moving stock-keeping units (SKUs) from one location to another or adjusting travel paths — the process is more fluid for TMS.
AI enables more intelligent TMS-based decisions to be made via software-to-software communication that translates into change at a physical, WMS-based level downstream.
Both WMS and TMS are mature solutions evolving from configurable and rule-based to intelligent systems. Experts who decided how to automate a particular transportation or warehouse function are giving way to dynamic systems that adapt — often automatically — to changing business conditions in a competitive landscape. This is why businesses need to focus on agility and flexibility: No one knows exactly what the future holds. But when we look at the trajectory of our technology, we catch a glimpse.
AI as the Future of Supply Chain
Technological advancement has brought us two types of AI: Large language models (LLMs), like generative pre-trained transformers (GPTs) — that can be described as generalists — and purpose-built AIs for specific industries like finance or law.
But what unites all AIs is that they’re steadily becoming copilots and coworkers: integral parts of our teams. As those teams grow, will we develop a hiring process to sort for AI generalists and experts depending on specific business needs, like logistics?
Beyond excitement about new, emerging technology, organizations are investing because they’re expecting to reimagine what we do today for a better tomorrow. A focus on achieving outcomes over traditional, rules-based efficiency gets us closer to building the AI-driven future we want and need.
Are you interested in learning more about implementing test automation in your warehouse system implementation? Read our customer success stories, check out additional blog posts, or learn more about the Cycle platform.
This blog post was adapted from a live expert webinar with our partner, Netlogistik.
