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How AI can power post-coronavirus supply chains

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According to 2020 report from MHI and Deloitte, 12%of supply chain professionals said that their businesses are currently using artificial intelligence (AI) in their operations, with 60% expecting to be doing so in the next five years. These figures are likely to inflate following coronavirus, as supply chains come to rely more heavily on AI for damage control and digital transformation.

So, what does this mean for AI in the supply chain? When it comes to the supply chain, digital transformation brings value by creating a more dynamic response between the procurement departments of suppliers and manufacturers.

In this pandemic age, it is certainly time to look at digital transformation and Industry 4.0 to ensure you remain a competitive, efficient, and productive business. Ultimately, the dream scenario would be a real-time connected supply chain that can aid you in understanding your production status.

The report said that 28% of the supply chain respondents were using predictive analytics, which uses some of the same techniques as AI. As a business, you may already be on the digital transformation path. And with coronavirus forcing you to step away and take a good look at your processes, it may be time to examine what AI can do for you.

What is AI to your business?

One of the first steps you will have to make on your AI journey is to examine what AI means to you. For some, AI about giving people time through machine automation. Freeing up people to do what they are good at – using conscience and cognitive capabilities to think, consider, analyze, make informed decisions and provide wisdom.

For others, it is about taking humans entirely out of the equation. For them, AI is about creating systems that emulate human performance, typically by learning, coming to its conclusions, seeming to understand complex content, engaging in natural dialogue, enhancing human cognitive performance, or replacing people in the execution of non-routine tasks.

AI and the supply chain

More specifically, with the supply chain, you could look at AI and machine learning’s ability to carry out smart contracts and payments which can optimally match data between manufacturers and suppliers.

Another type of AI that could work for supply chain management is ‘cognitive automation‘, which uses massive processing power and machine learning algorithms to improve supply chain speed and cost-efficiency. In effect, this automates the data collection and analytical work done by people in the supply chain, often using Excel spreadsheets. With supply chains becoming more complex, this is increasingly difficult to do.

In process or discrete manufacturing, you could use AI to provide a more accurate delivery date to a customer. The technology could also offer you end-to-end visibility of global demand and supply through the real-time processing of data through multiple systems in real-time.

There’s a lot of data in the supply chain, but having AI can help you discover and draw out the insights and patterns that allow you to make decisions in a timely matter, that can help you meet expectations at the speed customers might now expect.

What you should do now

You need to look at the ERP systems your IT department is maintaining, checking whether they are fit for purpose and within budget parameters with procurement departments who have tight production schedules and deadlines, as well as quality requirements.

Perhaps the more important question you should ask is if you have the right supply chain talent onboard that can make the best use of AI. According to the research, 56% of respondents said that hiring top talent was a top challenge, and 78% said there was high competition for the talent available. Of course, since coronavirus hit, this situation may have changed.

Of course, you also need to ensure you have access to data, as you can only get AI applications to work by training them on historical data. However, the MHI/Deloitte report found that only 16% of respondents consider the data stream management of their organization to be either “good” or “excellent.”

Thanks to Industry 4.0 and the Internet of Things, data is more available thanks to the widespread use of sensors. However, you still need the right systems that can allow you to understand what information is necessary to drive the insights you require.

It is here that putting data in the cloud could be crucial, as it will allow you to share data with vendors and other business partners when looking at integrating AI applications into your systems.

To wrap up:

• Identify the problems you want to solve and the opportunities you should embrace with AI.

• Research and learn what benefits AI capabilities provide to other companies.

• Empower your team to start now with AI solutions. Measure results to build the business case for more AI-powered solutions. Encourage your teams to explore your current solutions for AI capabilities or add-ons.

• Train and help your talent gain experience. Let them pursue areas where AI can add value.