This article was originally published on Sage.
Are you using artificial intelligence (AI) as part of your business processes, or have you got plans to do so in the future?
According to a 2020 report from MHI and Deloitte, 12% of supply chain professionals said their businesses are currently using (AI) in their operations, with 60% expecting to be doing so in the next five years.
These figures are likely to inflate following coronavirus (COVID-19), as supply chains come to rely more heavily on AI for damage control and digital transformation.
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’s certainly time to look at digital transformation and Industry 4.0 to ensure your business remains competitive, efficient and productive.
Ultimately, the dream scenario would be a real-time connected supply chain that can aid you in understanding your production status.
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 and your business.
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, analyse, make informed decisions and provide wisdom.
For others, it’s 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 that 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 spreadsheets. With supply chains becoming more complex, this is increasingly difficult to do.
In process manufacturing 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.
Ultimately, that means you can meet expectations at the speed that customers might now expect.
What you should do now
You need to look at the enterprise resource planning (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 MHI and Deloitte research, 56% of respondents said hiring top talent was a big challenge, and 78% said there was high competition for the talent available.
Of course, since coronavirus hit, this situation may have changed.
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 and Deloitte report found that only 16% of respondents consider the data stream management of their organisation 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’s 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, here are a few pointers from this article you for you to take away and action:
- 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.
Image via Sage