The new artificial intelligence digital partner streamlining the supply chain
Imagine working with a colleague who can predict how long it will take to transport essential products from point A to point B. And then can repeat that forecasting across 500 global shipping routes.
Not only that, but the exact quantities of raw materials needed to make products that customers want will be on those pre-planned routes - because that smart colleague foresaw the amount of products needed.
This AI partner is collaborative, hungry for feedback, and can process data and information faster than anyone else in the office. Most importantly, it helps everyone else to do their jobs better.
That’s just one example of the innovative AI-powered tools being put to work in Syngenta’s Production and Supply (P&S) chain. These operations span manufacturing, packaging, and global distribution across the company’s geographical footprint (80+ countries).
As Antony Royal, Syngenta’s Head of P&S Productivity & Innovation, says: “AI has arrived at Syngenta and human-AI collaboration will be an increasing part of how we work. Every week I hear about a new AI experiment or an expansion of an existing AI capability across P&S."
Deliveries to growers become more efficient and timely through human-AI collaboration across complex supply chains.
Deliveries to growers become more efficient and timely through human-AI collaboration across complex supply chains.
Antony Royal, Head of P&S Productivity & Innovation at Syngenta.
Antony Royal, Head of P&S Productivity & Innovation at Syngenta.
Building capabilities
Every product you buy has lived an entire life before you’ve even picked it up: from design, to manufacturing, to packaging and transporting, before being sold.
The last three of these steps are part of a business’ production and supply chain. In a global company as large as Syngenta, it’s a complex process.
So, to work effectively in this supply chain is to calculate and balance an enormous amount of moving parts. Ever-changing data, stock levels, customer wants and needs, and the shifting tides of international transport timetables all need to be taken into account.
Syngenta is experimenting and innovating at all steps of the supply chain.
Syngenta is experimenting and innovating at all steps of the supply chain.
The problem is, the volume of this information can be vast. And it’s in flux. Raw materials used in the supply chain need to arrive at the right time. If they arrive too early, these materials take up valuable storage space. But if they arrive too late, this triggers a domino effect of delays on production lines – which could keep customers waiting.
So, Syngenta’s experts set to find out if, and how, machine learning could help employees solve these problems.
The Syngenta solution
When fed vast amounts of complex data, AI can recognize patterns and make predictions. That can help people make better, data-driven decisions.
Syngenta is experimenting and innovating at all steps of the supply chain.
Here are three examples of productivity improvements recently delivered:
Inventory and safety stock at manufacturing sites
The AI-powered safety stock solution recommends optimal inventory levels by analyzing service requirements, supplier reliability, and demand patterns. Through interactive dashboards and advanced analytics, users can evaluate trade-offs and adjust recommendations, helping Syngenta balance cost efficiency with supply security.
Transit lead time
Combining brain power and machine power, the team implemented a recommendation engine that uses historic actual lead times to predict lead time for certain materials and transit routes. A user interface allows the team to validate predictions and make changes directly to core systems. This allows colleagues to order raw materials at more precise times, improving inventory levels and holding costs, all while reducing the number of clicks in the system.
Invoice validation
Providing the team comprehensive visibility into any discrepancies in invoices from suppliers, a solution that digitalizes invoices using Optical Character Recognition (OCR) and Robotic Process Automation (RPA) technology was developed. Now, at a glance, operations specialists and procurement teams have the data necessary to engage with suppliers, stop overpayments, and track trends. Ultimately allowing the team to focus on more strategic work.
Today, staff can use AI capabilities to lighten the load of repetitive, data-heavy work: think processing invoices, forecasting stock inventories, and predicting logistics lead times. These predictions helped to reduce inventory across key materials, including active ingredients – the chemical compounds within a solution that are responsible for an intended biological or chemical effect. Inventory levels were optimized, too: teams shaved an average of two days off long transit lead times.
Importantly, these tools also save employees’ time – as much as a week’s worth every quarter.
That frees them up to focus on the work that matters. As ever, the changes will be people-led, with staff trained in how to work with AI.
Mike Hollands, Head of Production and Supply, Syngenta Crop Protection
Mike Hollands, Head of Production and Supply, Syngenta Crop Protection
“AI is a game-changer,” Mike Hollands, Head of Production and Supply, Syngenta Crop Protection, says. “In P&S, it has broad application in identifying patterns in manufacturing and supply chain data where AI-driven predictive simulations will allow for scenario planning and the optimization of operation processes, working hand in hand with our human experts. As AI transforms agriculture and supply chains, human-AI collaboration is critical to ensure that our people and farmers remain at the heart.”
