Comparing the supply chain ecosystem to an orchestra has a nice tune to it. We first wrote about it here.

Think of your supply chain ecosystem as an orchestra, your trading partners, as a large group of musicians, and yourself as its conductor. The conductor of the orchestra is responsible for delivering music to the audience by keeping the musicians on time and pace.

You are responsible for delivering products to the customers by keeping their flow through the different trading partners on time.

Let’s add automation and AI to the mix. There’s AI for load planning: load pickup forecast and vehicle ETA prediction. There’s AI for route optimization: route generation, backhaul planning, load assignment (matching the cargo with resources that will move it), and load efficiency optimization. Then there’s AI for predictive performance: analytics for exception handling. The self-driving vehicles and vessels, warehouse automation – robots working in warehouses to pack customer orders and storing them to maximize the storage capacity, etc. are all part of the AI revolution.

As the conductor of your orchestra, how can you make AI successfully work for you so that your products can reach your customers on time?

When digitization started changing how supply chains worked in the early 2000s, most companies invested heavily into it and still struggled to realize the full benefits of digitization.

That’s because digitization without digitalization won’t lead to digital transformation.

Two decades later, the same formula applies to realizing benefits from AI. Without data from a single source, any measurable success from AI deployments, in supply chain operations, won’t be possible.

Data from supply chain operations is scattered across various worksheets, paperwork of bills of lading and CMRs, in vendor-specific codes for events (e.g. for pickups), and across TMSes and systems.

Preprocessing this large amount of data (text, sensor, audio, image and video) — collecting, cleaning, and converting it into the same format in a time-sensitive manner— for your AI system is an unsolved challenge.

AI systems need this input of continuous reliable information and data from the entire supply chain to retain context (e.g. record of lead times, pickups and drop offs history of each trading partner), learn from feedback, and improve over time.

Blockchain lays the foundation down for AI by creating interoperability between your entire supply chain ecosystem.

All system applications, supply chain nodes, trading partners (carriers, forwarders, and warehouse managers, ports), and customers are connected and onboarded onto a single digital blockchain network. This makes data from the entire supply chain ecosystem available in the same standard format and from a single source.

All your AI systems, for all operations of the supply chain, are connected to this source for continuous real-time data processing, prediction, and analysis.

With blockchain, you, the conductor of this supply chain orchestra can synchronise individual systems and partners, to keep delivering products on time. As long as your supply chain functions as an ecosystem, new technologies can’t rock the boat of your business. They are here to give you more control over it.