Artificial Intelligence (AI) in supply chains is not a novel concept. Infect. AI is making today’s supply chains more resilient and even better equipped for uncertainties, which were simply unthinkable just a few years back. Using AI in supply chain professionals across industries are gearing up for catastrophes that could shift the tide of industry operations in a jiffy. They are prepared with the right kind of intelligence and resources to take swift action when needed. They are not going to be caught by surprises.
COVID-19 has taught us a few lessons
- Never take existing supply chain capabilities for granted- these could be swept away with a global crisis within the blink of an eye.
- Always have a backup plan to revive lost sales as global demand could see dips and peaks without any forewarning.
- Watch out for early signals to ensure you are prepared to tackle supply-demand imbalances without shaking the apple cart.
AI is not just helping supply and demand planners resolve pressing operations issues, it is the most important tool to guarantee process efficiencies, cut down costs and enable sustainable improvements across the value chain. Right from the shop floor to top floor, AI-driven applications are proving their mettle in analyzing data and providing these numbers in real-time to take critical supply chain planning and operational decisions in the most accurate manner possible.
With global competition gaining momentum, there is now an urgent need to also streamline and optimize business operations, end to end across the supply chain. Holistic AI-driven supply chain intelligence is what is the need of the hour.
Here are 4 tips on how AI in Supply Chain is changing the business
- Holistic value with deep analytics – This is where artificial intelligence (AI) is proving to be such a game changer. Unlike standard software, which primarily aims to automate tasks, AI has the ability to rise above ground level and provide a much-needed larger-picture perspective on supply chain business operations, without losing sight of the little details – such as inventory management – that can often lead to cumulative losses. Coupled with Machine Learning (ML), AI has the potential to turn the tide back in favor of businesses by imbibing a level of transparency, discipline, efficiency, and effectiveness – agnostic of scale or industry – that has simply not been possible so far.
- Complete demand fulfillment at all times- With AI-powered demand sensing and forecasting capabilities, there is no possibility of under or overproducing again. The ability of AI systems to analyze and decipher massive datasets rapidly and at scale ensures highly accurate demand forecasts. This enables highly precise capacity planning, tailored to meet demand every time. With intelligent algorithms that identify and predict new demand patterns by way of shifting consumer habits, changing seasons, etc., adapting to changing demand becomes easy, and as a result, businesses become more resilient in the face of changing market conditions.
- Maximum capacity and resource utilization – AI in supply chains can not only provide the much needed visibility into and accuracy of demand forecasting and inventory management, it also helps providing critical analysis and insights into the desired operational efficiency by evaluating the performance of suppliers, output, and processes – thus helping identify and leverage potential cost savings. This ensures business plan capacity requirements, provide a resource buffer when needed and proactively identify underperforming sections within the supply chain, such as delayed supplies, unsold inventory, and inefficient distribution.
- Enhanced sustainability- Supply chain managers today, need to keep the focus on sustainable operations as most of an organization’s emissions are produced through its supply chain. AI plays a significant role here in reducing the carbon footprint and fine tuning supply chain planning operations towards a greener and eco-friendly approach. Using AI and Machine Learning models, supply planners can cut down gas consumption where needed, thus resulting in lesser inventory levels, reduced waste and carbon emissions. AI-driven sustainability efforts see immense benefits in the long term and help balance revenue generation along with environment-friendly processes.
Making a Case for AI in Supply Chains A Reality with Throughput
AI in supply chain management not only speeds up accuracy, efficiency, and reliability across your supply chain, it also prepares it for future events. Using AI and Machine Learning for demand forecasting in the supply chain is one of the most promising areas of Artificial Intelligence (AI). These solutions work together to improve forecasting accuracy by combining AI learning algorithms with Big Data to analyze an infinite number of contributing factors simultaneously. By learning from the data on past and current performances, AI-enabled approaches continuously refine and enhance the process of demand forecasting in the supply chain.