The Autonomous Supply Chain

Can you picture a world in which the supply chain is seamless?

Where items arrive from the right sources, via the best route, at the required time, are stored correctly, and are issued according to an optimal production plan?

Where products are manufactured, packed, and loaded using industrial automation and are shipped by self-driving vehicles or drones to the client? Well, if you can, you essentially just imagined the autonomous supply chain.

Supply chain management has always been a challenging task in the electronics manufacturing sector.

Competition is fierce, margins are thin, products are complex, and volatility is the only constant.

In the age of mass-customization and short product lifecycle, electronics manufacturing service (EMS) providers are expected to be responsive, adapt to small batches, and offer short lead-times while continually cutting costs.

Adding shocks such as increasingly frequent natural disasters (linked to climate change) and trade wars that cut entire supply chains at once creates an equation that is very complicated to solve.

COVID-19 has forced companies to rethink their entire supply chains, raising fundamental questions about how modern businesses operate.

Is lean manufacturing still valid, or should we neglect the concept of just-in-time and readopt the just-in-case approach?

Should low-cost countries continue to function as the world's production floor, or is it time for reshoring to mitigate global risks?

Should supply chains manage a narrow, efficient supplier base, maximizing buying power and reducing complexity, or diversify to reduce the risk of a supply chain cut-down?

Most of the above dilemmas derive from the limitations of current IT systems and human capacity.

Artificial intelligence (AI) and machine learning (ML) provide the answer to managing this complexity, and for the past few years, have been widely used in multiple supply chain activities.

Implementing these technologies brings us closer to optimizing our results.

However, as long as we implement AI and ML to address specific challenges or links in the supply chain, we can expect to achieve a local optimum at best.

The next giant step would be to use the technology for creating a holistic, orchestrating solution, targeted to optimize our supply chain as a whole in real-time.

Today, this concept is mostly discussed in an academic context, referred to as the autonomous, or self-thinking, supply chain.

It incorporates autonomous vehicles, robotics, 3D printing, the Internet Of Things (IoT), AI, and ML.

In theory, the autonomous supply chain would not require any human intervention.

It would independently process all activities generated out of a customer sale order, including material planning and procurement, delivery of components to the warehouse, receiving, storing, and issuing the items to the production floor, manufacturing, packing, and shipping to the customer site.

It will even monitor the equipment in real-time, predict failures, and generate the production and shipping of replacement parts.

This entity will offer extensive predictive capabilities, increasing its capacity to forecast trends or significant discrete events that could potentially disrupt the supply chain.

That sounds a lot like science fiction; perhaps it is unrealistic to forecast that we will ever eliminate the need for human inputs. 

However, every one of these autonomous components already exists today, to some extent, and the technology keeps improving.

This autonomous supply chain is a significant element of the Fourth Industrial Revolution. It might be less mature than other technologies like IoT, but it has enormous potential to create a competitive advantage for companies and prepare them for the chaotic future.

The process for achieving a fully-autonomous supply chain is challenging and lengthy, but companies would be wise to start heading in that direction.

Whether they reach this ultimate goal or stop after making notable progress, the benefit in terms of their capacity to adjust to changes and offer a cost-effective, agile solution to their clients would be immense.