Artificial Intelligence Helps Supply Chains Minimize Waste In Food And Medicine
June 28, 2018
It’s estimated that Americans waste about 30% of their food and medicine and 91% of plastic doesn’t get recycled. In developing countries, about half of the food produced never even makes it to market.
The biggest problem, according to Dr. Mohamed Aly, CEO and founder of Seeloz, is massively inefficient supply chains that allow food, drugs, and other life-saving products to go to waste. It’s a problem that Seeloz is intent on fixing.
“If we could better predict how much we consume, and when and where, we’d all be better off,” Aly said. “It’s not even about monetary savings, but the effect it has on our resources. Exactly like using reusable stuff helps save the planet, we’re using technology to help save the planet.”
Seeloz categorizes four types of inefficiencies when it comes to the supply chains of healthcare, food, and other consumer products:
- Expired goods
- Excess inventory eventually resulting in overstock
- Poor demand forecasting leading to stock outs
- Storing product in the wrong location, typically triggering excessive cross-warehouse movements
Surprisingly, these forms of inefficiency are usually faced by the three main actors in the food and healthcare supply chains. Manufacturers are in constant battle to pace their production process to fit market needs. Distributors struggle to time and size their procurement and correctly stock warehouses to fulfill demand. Finally, providers are challenged to accurately determine demand from end consumers.
“Identifying the root cause of the problem – whether it’s a manufacturing decision or procurement decisions across the supply chain – is imperative to finding the solution,” Aly said. “To that end, we need to do a better job in letting all production, procurement, and warehousing decisions across the supply chain be fully driven by forecasted end-consumer needs.”
Bridging supply chain gaps
Exacerbating the problem is the fact that healthcare and food supply chains involve multiple ERP systems – including the manufacturer, distributors, and procurement side – along with other systems that maintain customer data that don’t communicate very well with each other, making it difficult to develop the intelligence necessary to better understand customer demand or needs.
“Seeloz has developed a layer of smartness incorporating artificial intelligence (AI) to bridge the gap between all aspects of the supply chain and injecting AI-driven automation into the different supply-chain workflows,” Aly said.
For example, a typical healthcare system may continuously procure and store around 100,000 to 250,000 surgery, pharmaceutical, and consumable goods. Today, these procurement decisions aren’t driven by understanding and forecasting patient needs. The problem becomes even more complex because a typical healthcare system would have to continuously determine actual supply to stock-up across a warehousing chain, typically involving central warehouse(s), a warehouse at each of the hospitals, and tens to hundreds of points-of-use within each hospital – clinics, departments, labs, ER, etc.
Seeloz developed a solution that leverages electronic medical records to accurately determine future patient needs at each facility and automates procurement and inventory management processes accordingly. This ensures any healthcare system has any given supply item at the right location at the right time, minimizing waste as a result.
Through a similar scenario, the solution caters to supermarket and pharmacy chains, food and healthcare supply distributors, consumer products manufacturers, and life science companies.
“Whether we talk to a pharmacy chain or a healthcare system, a food distributor or pharmaceutical manufacturer, we usually hear mind-blowing dollar figures for waste, typically tens to hundreds of millions annually per player and even reaching billions in some cases. However, when we examine how supply chain workflows are being run, the surprise quickly fades away. This is where automation will fill the gaps where humans would fall short,” Aly said. “These kinds of supply chain problems are beyond human capacity. There’s no way a human can grasp the correlation of different items across a supply chain of 100,000 items. It’s just impossible.”
Through its early implementations, Seeloz has proven it can reduce product expirations by more than 50% and reduce overall supply spend by five to 20% with more intelligent supply chain solutions.
“The more scale, the more we can improve these numbers. We’re just scratching the surface using AI,” Aly said. “These substantial reductions in annual supply spend will have a positive implication on the overall quality of service to the end consumer.”
Using the food industry as an example, less expired products mean consumers get better quality food at a lower cost, Aly said: “If we can help the whole supply chain, from manufacturers to distribution to better forecasts based on a demand-driven fashion, this would result in fresher, healthier food, prescriptions, and so much more.”