What can we do to protect our supply chains from future crises? In the past, the majority of companies held a “cost-associated” perspective, rather than looking at the potential for using supply chain management to help build a sustainable company. Concentrating production in a few suppliers’ high-volume factories in low-cost countries is naturally attractive for global companies, but it comes at a risk: If a link in the chain breaks, the whole chain could break.
The faults in the fabric
Non-resilient supply chain systems rely on the hypothetical assumption of an equilibrium state, where global production and delivery runs more or less in a stable manner. Under this premise, optimisation leads to a business setup where your supply chain is specialised — focused on a small number of highly optimised suppliers. This would run fine, as long as there is no severe disruption.
But history tells us that crises and states of flux are much more natural — and thus more common — than a state of perfect equilibrium. Therefore, relying on an assumed steady state is a risky bet. Odds are, your production will end up breaking down.
A stress-resistant system
So, what’s the alternative? The extreme opposite would be a supply network that is maximally distributed and diversified in a way that whenever a single link breaks, there is always another to keep supply stable. In its full form, this will guarantee resilience — but at the same time explode costs. How do you balance resilience with cost optimisation?
There’s an easy answer: artificial intelligence (AI). If you want to make responsible business decisions about the daily operations within your supply chain, real-time information and transparency are key.
Just imagine how much a production site’s map could help — showing shipping routes, shipment durations and the exact location of your supplies at any given minute. You could then link this information to other data and cross-examine it, or even enrich it with closed-borders policies and determine how that affects your transportation time or other parameters.
With AI, you can process all the information you need — not only historical information, but also information gained from advanced simulated scenarios. You can evaluate crisis scenarios in stress tests to design a supply chain management network that balances optimisation in terms of costs with optimisation in terms of resilience.
A lasting solution
There’s a lesson to be learned from companies that have prepared themselves to be more resilient. The key in a scenario like this is to have reliable information quickly in order to make good decisions and react to the situation in real time. If you don’t have clear transparency into what is going on in your current system, or if you don’t know any alternatives and what they might mean for your supply chain, then you can only guess.
Companies that take full advantage of AI are much less affected by crises today. They can easily assess alternatives (or the lack thereof) and ultimately get information faster and more consistently in order to make better decisions with a global impact. In a system where each component affects everything else, this is proving to be the best solution.