This blog is a guest post from Paul Patin, Chief Technology Officer at Logistiview. He explains his personal journey from supply chain AI/ML skeptic to optimistic believer and how these technologies will radically transform supply chain planning and warehouse automation in the future.
I confess that I was once an AI and ML skeptic. I love technology. I love gadgets. I love efficiency. I even watch some sci-fi. I wanted to believe that a sentient machine Architect could someday oversee an optimized and balanced world based on artificial intelligence, machine learning, and self-healing algorithms. Over the last few years, Google has demoed ad-supported conversational AI and self-driving cars while Magic Leap released videos showing augmented reality wildlife floating in an office as if these products were in final pre-release development. But something about these demonstrations always nagged at me. I could see “behind the curtain”.
I confess that I was once an AI and ML skeptic. I love technology. I love gadgets. I love efficiency. But something always nagged at me. I could see “behind the curtain”.
As you may already suspect, an inconvenient truth is that many much-hyped AI and ML-based technologies cannot easily be applied to many micro-scale supply chain challenges – at least not in real-time. We are not incapable of writing the algorithms, but rather there is often insufficient data to derive statistically significant insights that drive automated action, or incomplete system integration needed to capture accurate and timely data about each step of an operation’s workflow. For example, accurate data capture inside many warehouses can be a challenge even when you have top of the line IT systems because of inconsistent Wi-Fi, paper-driven processes, and manually triggered process steps. Likely due to these day-to-day realities, supply chain is by-and-large a practical industry focused on “getting stuff done” and, as cool as consumer-facing technologies may look, enterprise (usually) favors pragmatic innovation that solves real challenges and produces clear results soon after implementation.
I got my start in consulting for enterprise warehouse systems right out of college. Consulting is a great profession – grueling but great. Few other jobs can throw you in the deep end as quickly with as much opportunity for growth and exposure to real world business realities. Over my career, I have designed and programmed hundreds of process optimizations, integrations, and customizations for dozens of companies across green screen, web, and mobile platforms. Everything I had built professionally was driven by semi-manual analysis and best practice (sometimes back-of-the-envelope) process engineering. But my future (and likely yours) will be largely built on proactive insights and automated actions delivered by AI and machine learning.
What has changed for me? I am still a practical technologist at heart, but after years of staged tech demos, endless R&D, and futurist seminars, several of these technologies now function outside of Silicon Valley’s controlled environments and are demonstrable in the real world. You are experiencing more and more of the tech in your own life, often without realizing it. You interact with these technologies every time you search the Internet, interact with a customer service system, or browse Facebook. When you order from popular e-commerce stores, your order may have been fulfilled with the help of collaborative robotics. The algorithms that drive major websites can detect patterns at massive scale that a human analyst might never find at all. While we do need to enforce strict privacy and data usage protections, these advances will make our supply chains more efficient, which will eventually increase standard of living for everyone.
What has changed for me? I am still a practical technologist at heart, but after years of staged tech demos, endless R&D, and futurist seminars, several of these technologies now function outside of Silicon Valley’s controlled environments and are demonstrable in the real world.
AI and ML can deliver insights you didn’t know you needed – and drive automated actions you don’t have the time or resources to do yourself. Think of automobile technologies like Lane Keep Assist and Tesla’s Autopilot. Can these systems smoothly and safely handle every exception scenario a human driver is capable of? Certainly not. But can these technologies make driving well-marked highway portions of road trips more efficient and less fatiguing? Yes.
Do we have self-driving semi-trucks or autonomous supply chains yet? Not quite, but I can certainly see it in the future. We now have devices smaller than your smart phone that can process computer vision and natural language speech algorithms on the edge, with or without access to the cloud. We have supply chain control tower and planning software that can predict disruptions and recommend solutions. We have warehouse management directed tasking that intelligently optimizes warehouse activity based on changing conditions on the floor. And we have collaborative robotics that can navigate around a warehouse autonomously, saving thousands of hours of human travel time.
This recent article from The Wall Street Journal says Gartner expects a double-digit increase in demand for robotic goods-to-person systems over the next three years alone and that half of the world’s global leading enterprises will have invested in real-time transportation visibility software by 2023. While it was already clear that software-driven automation powered by AI and ML was the next step in the evolution of supply chain management, COVID-19 instability is turning adoption into a necessity for many industries as remote work and social distancing exacerbate pre-existing inefficiencies and introduce new disruptions.
Perhaps you look at this tech and say, “if they don’t have autonomy, there’s no point in investing yet” or “our legacy systems are too old to get anything out of this”. The reality is that there are many achievable benefits now, even without replacing your legacy systems. For example, Logistiview has a standard integration capability that emulates the existing communication flow of telnet (green screen) devices, allowing us to seamlessly enhance and optimize legacy processes by as much as 50% with our low-code workflow engine, computer vision-based navigational aids and cross-platform mobile compatibility.
The future of our industry will be driven by AI and ML-based technologies and some of the potential benefit can be realized today through software-driven automation technologies like optimized warehouse tasking, control tower visibility, collaborative robotics, and vision picking.
Someday relatively soon, supply chain software will intelligently and holistically optimize supply chain planning and distribution. End-to-end system integration will enable the supply chain to be optimized backwards from financial and service level target metrics. Systems driving the warehouse floor will see every barcode and remember the context, virtually eliminating inventory loss. Collaborative robotics will work alongside humans to enable maximum efficiency and operational agility in an ever-changing business environment.
I was once a skeptic, but now I am a believer. The future of our industry will be driven by AI and ML-based technologies and some of the potential benefit can be realized today through software-driven automation technologies like optimized warehouse tasking, control tower visibility, collaborative robotics, and vision picking. Begin your own automation journey today to start transforming your operation and prepare for the tech-enabled future of supply chain.
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