Businesses have always faced challenges managing their supply chains, but the recent pandemic has brought with it a new sense of urgency as companies attempt to keep their supply chains resilient in the face of adversity. More than a decade ago, businesses began to incorporate data-driven technologies and instruments to make their supply chains smarter. Now, they are looking to artificial intelligence (AI) and data science experts to expand their ability to improve connections between customers and suppliers, from parts to production to global delivery. 

Artificial Intelligence and the Supply Chain

Many changes are driving the improvements to modern supply chain management. A recent study by IBM reported that 95 percent of the highest performing companies see AI as the key to innovation. Businesses now have access to products and processes that will learn and adapt to changing conditions. Machine learning has moved beyond algorithms for analyzing data feeds to providing recommendations and alternatives in sales and operations. Natural language processing, furthermore, enables tools and programs to understand speech and text much like actual human beings can. 

The ROI of AI in Supply Chain Management

Businesses of all sizes are considering the value of investing in data science experts and AI for their supply chains. In one McKinsey survey, 61 percent of supply chain management executives reported a decrease in costs from the incorporation of AI technologies across their supply chains, and 63 percent saw an increase in revenue. 

Proctor and Gamble, for example, implemented an AI-driven platform for supply chain planning to enhance process efficiencies. Typically, a large staff was needed to manage supply and demand across product lines, but when the data science experts at P&G began utilizing machine learning algorithms, the needed time was greatly reduced by using a system that automatically adjusted staffing plans and stocking strategies. These changes freed up planning teams for other projects and reduced their inventory and the associated carryover costs.

The AI-Driven Transformation of Supply Chain Management

With advances in AI such as machine learning and natural language processing, as well as related technologies like the Internet of Things (IoT), companies are seeing a dramatic transformation in their supply chains. Data science experts and executives are implementing AI alternatives that can drive transformational change in five primary areas:

  • Planning - Creating increased transparency across the supply chain from end to end, allowing for faster decision making. AI also enables real-time margin optimization.
  • Logistics and Distribution - Significant cost reductions and lower environmental impact can be achieved through the optimization of cargo routing and vessel sharing.
  • Procurement - While cloud-based computing has increased supplier transparency, AI will allow for full data integration and optimization of purchasing raw materials.
  • Production - Agile manufacturing is focused on rapid customer service. With the introduction of AI, planning and scheduling can be further optimized.
  • Sales and Marketing - AI will provide increased accuracy in demand forecasting and pricing. Additionally, sales analytics will see improved detail and transparency.

Supply Chains of the Future 

The pandemic has had a dramatic impact on supply chains around the world, resulting in historic product shortages, affecting consumers and businesses alike. Manufacturing has been delayed while existing products are stuck in limbo aboard cargo ships languishing in ports around the world. At the same time, only four percent of supply chain leaders believe their organizations are future-ready. Companies must completely rethink how they build and manage their supply chains and look for advances in the following areas:

Cognitive Automation

Machine learning and AI will allow for real-time supply chain decisions to be made autonomously based on business rules and current conditions. Cognitive automation can reduce human error while accelerating complex processes. 

Forecasting for Process Optimization

Recent history has demonstrated the massive disruptions that can occur when any part of the supply chain breaks down. AI can supercharge advanced forecasting and advanced planning solutions across all parts of the supply chain. Communication and delivery can then continue in the midst of global crises.

Supply Chain Resilience

Organizations can handle massive shocks to the supply chain as AI corrects and responds to data issues in real-time. This improved flexibility and agility will allow leadership to make better and faster decisions. 

Skills Shortage

Staffing can be a challenge to any organization even in the best of times. AI can aid in recruitment and hiring of data science experts across the supply chain organization, reducing the time and costs associated with hiring and developing staff.

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Preparing for a Future in AI

With supply chain challenges expected to continue worldwide for some time, organizations will be looking for individuals with the education and skills required to thrive in such an environment. AI engineers and data science experts will be in high demand for the foreseeable future as 2.3 million jobs are created. Those seeking to improve their skill sets and credibility should look to degrees and certificates in data science and artificial intelligence. The dual master’s program at Simplilearn will develop skills in areas such as data analytics, machine learning, and artificial intelligence — making learners future-ready to build the supply chains of tomorrow. 

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