Supply chains are on the cusp of a data-fed revolution. Here’s how businesses can succeed.

This article is brought to you thanks to the collaboration of The European Sting with the World Economic Forum.

Author: Rob Handfield, Bank of America University Distinguished Professor of Supply Chain Management , North Carolina State University Poole College of Management & Tom Linton, Chief Procurement and Supply Chain Officer, Flextronics

• Supply chains are about to face great changes through automation.

• It will require managers to hand over the autonomy of decision making to machines.

• Business strategies will come to reply on predictions based on the flows of world events, global supply chains and smart technologies.

Images of the Ever Given containership blocking the Suez canal caused another bout of global handwringing over supply chain risks in March this year. It’s been a frequent occupation during COVID, in fact, and yet most people only have a vague notion of how supply chains operate.

Often the impression is that significant technology lies behind supply chain provision. However, if one looks behind the curtain at transportation providers, there really isn’t as much there as you think (somewhat like the Wizard of Oz!).

Most of the activity that occurs behind the scenes at all stages of the supply chain involves human activity, processing transactions on screens and Excel sheets. Today, there are few efficiencies to wring out of the four walls of manufacturing plants, but massive white space opportunities in the global supply chain.

The next era of change will make supply chains as efficient as manufacturing plants are today, through automation that relies on data streams from smart technologies.

This change depends on the notion of FLOW, which is at the heart of the supply chain revolution underway. It involves the cognitive integration of end-to-end supply chains drawing on AI and machine learning.

Supply chains in flow

The movement towards digital supply chains will require managers to be bold and willing to take risks by handing over the autonomy of decision making to machines. Removing humans of this responsibility represents a major leap in culture.

For example, suppose there is an increase in the lead time required to order and ship a part from a supplier. Normally, a human planner would increase the minimum order quantity in the planning system manually. But doing so requires that individual to first recognise that a change in lead-time has occurred and get approval for the decision, before entering it manually into the planning system.

A machine, by contrast, would perform all of these tasks instantly, based on sensing changes monitored in the supply chain. A machine would also be able to link increases in a finished goods inventory to planned reductions in incoming raw material inventory for a product line, in order to optimise working capital holdings.

The fundamental theme behind our upcoming book, titled the same – Flow – is that global trade can be viewed in the context of flows over time, building on the concepts of thermodynamics in the field of physics. If events and materials flow, it also means they can be predicted – and this is an essential point for managers.

The ability to predict: a major gain

Business strategies will rely more on predictions based on the flows of world events, global supply chains, and data exchanged smart technologies. Those companies that build algorithms to interpret these data flows will have the greatest potential to eliminate waste. The reduction in working capital through improved supply chain flows will be massive and will create a major leap in global productivity.

Leveraging advanced knowledge and smart technologies to filter data into a concise area of focus are a game changer.—Tom Linton

The massive business disruptions in healthcare and industrial supply chains brought about by COVID have accelerated the need to be more predictive in order to pre-emptively predict and influence supply chain performance. Machine-learning-powered algorithms now predict (1) which suppliers will deliver late; (2) when pricing will go up or down; and (3) when lead times for raw materials will change.

Welcome, predictive analytics

Companies will be able to exploit the tremendous amount of data from their transactional systems, and combine it with data from other supply chain intelligence systems and real-time news feeds to get directional indicators of which areas of their supply chain are most vulnerable to reduced performance.

A single large company’s supply chain can be incredibly complex, spanning thousands of suppliers and tens of thousands of parts moving across more than 100 countries worldwide. Leveraging advanced knowledge and smart technologies to filter data into a concise area of focus are a game changer.

We predict that, eventually, machines will automatically generate orders up and down the supply chain. They will do so based on an ongoing stream of new events, adjusting and accommodating to these shifts and notifying buyers and sellers on how to adjust production and shipment schedules accordingly.

The future is here

Estimates vary, but ballpark figures of how much pandemic-provoked disruptions have cost global economies are all in the trillions of dollars. Most enterprises found themselves behind the curve, reacting to border closures and at the mercy of supply disruptions due to stay-at-home orders. They have started looking at AI to automate their supply-chain planning in response.

Humans will still be very much “in the loop”, but a new set of analytical skills and decision-making based on incoming data will be required.—Rob Handfield

In fact, companies are adopting predictive analytics in a big way, based on the painful experience of having financial performance decimated by suppliers missing or delaying shipments, raw material prices increasing and lead times going up.

Convoy is a technology that works with truckers carrying freight. More than 80% of trucks on the road today are independent – and most of them are operating half full. This is because they travel on one leg of a route to deliver a shipment, and often return back the other way with an empty truck.

Technologies such as Convoy provide drivers with a menu of pick-up options to choose from, based on where they are located (much like Uber does with drivers). This automated feature will allow truck drivers to pick loads that are the most profitable and that suit their scheduling preferences, optimising the flow of materials in the supply chain based on updated price quotes, capacity and scheduling of vehicles.

The Forum’s recent TradeTech report explores in more depth how AI, IoT and other emerging technologies are helping increase supply-chain visibility and coordination.

As our planning systems collect more information about real-time events, updates to the system will become more frequent, allowing continuous adjustment in supply chain responses. Humans will still be very much “in the loop”, but a new set of analytical skills and decision-making based on incoming data will be required.

The new level of automation and smart sensing in supply chains will allow flows to become more predictable. Smoother flows will be the antidote to an increasingly bumpy, or uncertain, world.