Kate BrownThe Impact of AI and Advanced Analytics in Manufacturing
July 2, 2024Comments
The manufacturing realm is growing increasingly dynamic, and with those changes comes a need to apply innovation not just in isolated applications but holistically.
Advanced analytics and AI should now touch every facet of your value chain, from inventory forecasting and procurement to quality control and production. Embracing these technologies holistically allows you to better position your company for success, increasing efficiency and agility across your operations.
When implementing AI and advanced analytics in manufacturing, consider their synergistic relationship across key aspects of your operations, including:
Inventory
Advanced analytics and AI allow you to take a proactive approach to inventory, helping you increase customer satisfaction, reduce carrying costs and free up your working capital for more strategic investments.
These tools leverage historical sales data, external factors and market trends to provide you with highly accurate demand forecasts. They can also continually refine predictions and identify patterns so that you can anticipate demand fluctuations and adjust production accordingly.
Procurement
Optimizing procurement is critical to helping you improve cost management and efficiency.
AI-driven procurement solutions can help you streamline operations by automating routine tasks, including order processing, supplier selection and negotiation. And they help you make procurement decisions faster with a real-time analysis of risk factors, market dynamics and supplier performance.
Predictive analytics can also help manufacturers anticipate supply chain disruptions, enabling you to take proactive steps in minimizing operational risks and helping to ensure business continuity.
