Artificial Intelligence and its Role in the Supply Chain

Artificial Intelligence and its Role in the Supply Chain


Last week, Moore Global presented another edition of the Moore Manufacturing and Distribution Summit Series, “Has the 5th Industrial Revolution Started?”.

Peter Morley and Brian Mahon from Moore Insight were pleased to participate in an interesting session, along with Mark Fagan, Partner at Citrin Cooperman and M&D Global Leader and Kai Reuning, Director at Moore Johannesburg.

In this “Artificial Intelligence and its Role in the Supply Chain” session, the Moore Insight Directors had the opportunity to discuss how artificial intelligence can help manufacturing and distribution companies increase efficiencies and minimise disruptions in their supply chain.

The panel focused on how technology can minimise supply chain and labour disruptions, and how AI is impacting the M&D industry. They also explained some facts and fiction about artificial intelligence.
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The Key Components of Artificial Intelligence
More specifically, Brian shared with the audience his thoughts on the components of AI and their use cases. Language and Speech, including chat bots, virtual agents, speech recognition and natural language processing is one of the AI technologies that are becoming more commonly encountered in both consumer and business to business contexts. Data collection is the purpose of the use of this technology, that ERP providers are starting to adopt.

Moving on, Brian Mahon explained how intelligent operations are massively enabled by the internet of things (IoT) technology. IoT unlocks a huge amount of possibilities to capture data; a great opportunity for the manufacturing and distribution industry to not only have post-event information processing, but to be able to do predictive processing of information.

The ability of Machine Learning (ML) and Deep Learning to process vast amounts of data, collected from various touchpoints within an M&D company, allows us to bring this information together. They key here is to use this data intelligently and ensure high quality of the data that a company relies upon. Data Cloud Engineering is about understanding what the data is and where it should live, and platforms such as ERP Systems can help bring all the disparate information sources together.
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Key Considerations before Implementing AI
The panel of digital transformation experts discussed the key areas that middle-market M&D companies need to pay attention to, when it comes to their technology. They also provided key insights on how a company can determine where to start, when it looks to make incremental improvements in its supply chain.

Kai Reuning from Moore Johannesburg shared his thoughts on how M&D companies should always be pragmatic and to work through a number of key considerations, when it comes to technology:
  • As an M&D company, consider linking an AI project to top-line and bottom-line growth, to avoid just a fancy AI addition to the company.
  • Keep in mind the overall business strategy and how AI fits in it.
  • Be clear about what problem you are trying to solve and how artificial intelligence can help you solve it.
  • Focus on AI that has already been mastered, such as prediction, automation and classification.
  • Ensure integrity and high quality of data.
  • Get sufficient buy-in from management and staff, before implementing an AI solution.
  • Start small!
The People Element in AI Implementation
People and their buy-in are a crucial factor in every implementation project. Resistance to change coming from the workforce is a common challenge and often results in underutilised ERP systems or new over-customised systems that fail to demonstrate the optimised features of the new technology.

Having come across multiple situations like the above in his 30 years of experience, Peter Morley shared his views on how to combat this wide problem of disparity between people and systems.

According to Peter Morley, the key message for management teams across M&D companies is to understand their organisation and their processes, in order to get the best out of their systems. To achieve that, a holistic approach that covers the whole scope of the business is required.

In his own experience from working on multiple systems implementation projects throughout the years, MOORE Insight have developed proven methodologies to support their clients map their internal and external processes and develop a view of their total business landscape.
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Key Takeaways
Brian Mahon and Peter Morley highlighted the key messages to take away from this discussion, that could really make a difference to manufacturing and distribution companies that are looking to implement artificial intelligence, in order to increase efficiencies in their supply chains.
  • Data Quality is a need to have, when adopting AI technologies.
  • Focus on the value that AI would drive for your business.
  • Understand what the touchpoints to integrate the data are.
  • View your systems as a creator of data, rather than a store of data.
  • Integration of systems is key.
  • Use the integrated systems to understand your business sociology.
Watch the full session here: