With the recent global and regional socio-economic disruptions caused by the pandemic, industries such as retail, consumer products, manufacturing, pharmaceutical, and life sciences all struggle to align production and stocking with rapidly shifting purchasing demands. At the same time, some channels have surged ahead: online retailers, delivery services, and pharmacies are thriving. In this new reality, organizations without a robust and agile predictive capability face supply chain management challenges.
In this latest Data Science Central podcast, we discuss how injecting AI into existing business intelligence solutions can greatly enhance the ability of organizations to predict future demand for goods, even in uncertain and dynamic times.
You’ll learn about:
· Consumer and industry trends affecting supply chains
· The impact of AI on supply chains within organizations implementing it
· Real-life supply chain use cases for AI around demand, logistics, warehousing, price optimization, and more
· The five fundamental steps organizations need to take to achieve AI-driven forecasting
Ari Kaplan, Director of AI Evangelism and Strategy - DataRobot
Sean Welch, Host and Producer - Data Science Central