Boost customer relationships, end-to-end visibility, and operating margins
Supply chain disruptions are here to stay. But advanced technologies can be strong allies that help you navigate these challenges, from tariff changes and spikes in raw material pricing and logistics costs to evolving consumer buying behaviors.
But for that to happen, you'll need to break out of the traditional forecasting methods and integrate AI and machine learning (ML) into your forecasting processes. So, how can you do this?
Our global delivery leader in high tech and manufacturing, Tarun Srinivasan, outlines seven practical steps that guide you through transforming your demand forecasting strategies using AI/ML.
Read our whitepaper produced in collaboration with Industry Week
By adopting the seven strategic steps, you'll be equipped to:
Identify potential disruptions and impacts
Make smarter, faster decisions with AI-driven analytics
Enable frictionless operations through streamlined exchange of insights across departments
In our recent study with HFS, 53% of supply chain and procurement executives stated that they are shifting funds from other resources to fund gen AI initiatives. The number indicates that companies are willing to cautiously experiment with new technologies to enhance the capabilities of traditional AI systems, aiming for more predictive and autonomous supply chain operations.
Are you ready to raise your AI game, too?