Is an AI-powered supply chain the answer to challenges like Brexit?

Recent chaos caused by Brexit legislation has been well-reported. Due to a stringent government immigration policy concerning low-skilled workers, a truck driver shortage left thousands of petrol stations without fuel. Food deliveries and goods destined for high street stores have also been affected.

The Head of The British Retail Consortium, Helen Dickinson, has warned of an inevitable fallout, with three in five CEOs advising of price hikes before the end of 2021, due to Brexit’s impact on the supply chain. And one in ten CEOs have raised their prices already. Business leaders everywhere are feeling the consequences.

With disruptions to the supply chain part of the ‘new normal’ for businesses due to the Covid-19 pandemic, the effects of Brexit may be judged by some to be unavoidable. But both Covid-19 and Brexit are merely extreme examples of everyday occurrences. Supply chain challenges occur regardless of pandemics and government policies.

The question for business leaders remains: how to stay competitive, regardless of the climate? As we’ll see below, using artificial intelligence (AI) and machine learning (ML) in supply chains can enable a company to make the best of any situation.

 

A new approach to supply chain problems

The answer can be found by looking at supply chain problems from a different angle. Instead of seeing specifics – such as the Covid-19 pandemic and Brexit – as the problem, the supply chain itself is the culprit. Too many companies are relying on systems that are out-dated and hard to adapt (making it impossible to react to events as they occur).

The key response to any supply chain crisis is to be prepared for it before it happens, and to be able to react with the best possible outcome. Businesses must become more agile in order to do so, and adopting artificial intelligence (AI) in supply chain management is central to this.

As Sam Herbert, Chief Operating Officer at Clinigen Group, a pharmaceutical business says, "Having spent a large part of my career in supply chain, the pandemic and Brexit were not the first large disruptions I have seen, just the most sustained... The logical step for businesses is to integrate more real-time tools to optimise their logistics networks for constantly changing situations." at Clinigen, he says they have changed their mindset around shock events; "shifting from thinking about one-off projects related to this type of 'event' (and others, like procurement)" and instead, "investing in a continuous resilience capability".

 

Distributed stock

One part of an agile approach lies in embracing a distributed stock model. Instead of holding stock in a central warehouse, a business can distribute its products across multiple sites.

If a supply chain crisis puts one location out of action, orders can be fulfilled by using the best positioned and thus most cost-effective site. Any business leader scratching their head at the logistics of this isn’t alone. There’s the initial cost of purchasing new warehouses, and the organisational nightmare of managing a multi-site distribution model.

But such headaches only come with a conventional approach. Automating the system removes all hurdles, as AI and supply chain management have a harmonious relationship.

 

Drop-shipping

Further agility can be found with a back-up drop-shipping policy. If a normal channel is affected, businesses can ship direct from manufacturer to customer, bypassing their own order fulfilment sites. As with distributing stock, adding this option to your business strategy may be a lengthy process when using traditional methods.

However, following an initial set-up, automating the method with an end-to-end integrated logistics system simply brings the manufacturing site in line with regular procedures.

Going agile with the likes of distributed stock and drop-shipping options enables you to fulfil orders regardless of external events. Even if your business is affected, an artificial intelligence supply chain has multiple options at its disposal to deliver the best possible solution.

 

Artificial intelligence in supply chain management

Adopting artificial intelligence in supply chain management is merely a step towards process improvement, bringing traditional methods in line with the digital age.

Leading management consulting firm McKinsey estimates that “firms will derive between $1.3trn and $2trn a year in economic value from using AI in supply chains”. The Economist predicts AI’s role in the supply chain to have “a bigger economic impact than any other application of the technology and affect a larger number of businesses.”

In the modern era, an AI and supply chain approach will no longer be an option for businesses wanting to survive – it’ll become a necessity.

The 7bridges AI-powered logistics platform was created to enable supply chains to enter the digital age. Far from adding expense and complexities to an already multifaceted process, the software saves money and simplifies the entire system.

Orchestrating and executing a distributed stock model, or enabling dynamic carrier switching are no longer a complex hurdle when automated in our platform. 

The AI at the heart of our technology can also analyse and make data-led predictions regarding the efficiency of your strategies, finding better routes to faster fulfilment. Using machine learning, it’ll also get cleverer with each order; knowing your systems and routes even better than you do. And through stress-testing, it can check for weak-links along all points off the chain itself, identifying potential problems before they grow into something unmanageable.

 

Bringing supply chains up to date

7bridges transforms your business’s approach to order fulfilment. By adopting machine learning in supply chain management, you benefit from incredible agility during times of disruptions. The truth is, humans simply can’t analyse the vast amounts of information required to run such complex supply chains effectively, but our AI-powered logistics platform can do so.

We'll make it simply to deploy distributed stock models such as ship-from-store and drop-shipping. No need to employ expensive consultancies or hire new staff. It can all be handled within our platform.

Businesses can also expect savings on their logistics costs by 30% in normal conditions, with the best possible deal found whenever the supply chain experiences upheaval. A return on investment can be expected in as little as four weeks.

Adopting artificial intelligence and machine learning in your supply chain:

 

tick icon (2)Reduces the risk of unfilled orders, reduced profit margins or the need to raise prices.

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Helps you rapidly adapt and switch providers in the face of rising freight costs and carrier surcharges

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Offers you unparalleled visibility and control over your logistics data and processes 

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Gives you back time to spend on improving other aspects of your business

 

Future chaos caused by Brexit, the Covid-19 pandemic, or any other disturbance to the supply chain is managed by our software in the most efficient way possible. In today’s climate, embracing AI is a simple solution to staying competitive and building a pathway to future success.


 

7bridges’ whole ethos is to enable your business to keep running in any eventuality. To learn more about how we help businesses like yours gain clarity, control and create greater supply chain resilience - get our free guide to Supply Chain Resilience.

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