AI/ML in Supply Chain Decision Making

#artificial #intelligence #machine #learning #supply #chain #management #decision #making
Share

Machine learning is transforming supply chain management by  enabling businesses to make faster, data-driven decisions in an
increasingly complex and volatile market. By analyzing vast amounts of historical and real-time data, ML helps companies improve demand
forecasting, ensuring better alignment between supply and customer needs while reducing stockouts and overstocking. It also plays a
critical role in optimizing inventory by balancing stock levels, cutting down holding costs, and enhancing overall efficiency. Supplier
evaluation is another area where ML proves invaluable, as it helps assess pricing trends, delivery performance, and quality metrics to
identify the most reliable partners. Additionally, logistics and transportation benefit significantly from ML-driven route and schedule
optimization, reducing fuel costs and improving delivery times. By integrating machine learning into supply chain operations, businesses
can enhance agility, reduce inefficiencies, and gain a competitive edge in an increasingly dynamic market.


  Date and Time

  Location

  Hosts

  Registration


  • Date: 07 Apr 2025
  • Time: 11:30 PM UTC to 01:00 AM UTC
  • Add_To_Calendar_icon Add Event to Calendar
If you are not a robot, please complete the ReCAPTCHA to display virtual attendance info.
  • Contact Event Hosts
  • Starts 15 March 2025 04:58 PM UTC
  • Ends 06 April 2025 04:58 PM UTC
  • No Admission Charge

  Speakers

Topic:

AI/ML in Supply Chain Decision Making

Machine learning is transforming supply chain management byenabling businesses to make faster, data-driven decisions in an
increasingly complex and volatile market. By analyzing vast amounts ofhistorical and real-time data, ML helps companies improve demand
forecasting, ensuring better alignment between supply and customerneeds while reducing stockouts and overstocking. It also plays a
critical role in optimizing inventory by balancing stock levels,cutting down holding costs, and enhancing overall efficiency. Supplier
evaluation is another area where ML proves invaluable, as it helpsassess pricing trends, delivery performance, and quality metrics to
identify the most reliable partners. Additionally, logistics andtransportation benefit significantly from ML-driven route and schedule
optimization, reducing fuel costs and improving delivery times. Byintegrating machine learning into supply chain operations, businesses
can enhance agility, reduce inefficiencies, and gain a competitive edge in an increasingly dynamic market.

 

Biography:

 

With 20+ years of expertise in supply chain planning, ERP, and advanced analytics, I specialize in Supply Chain Analytics & Optimization, leveraging AI and ML-driven solutions to enhance operational efficiency and decision-making. Throughout my career, I have worked with leading global organizations such as Oracle, GE, and PwC, where I played a critical role in driving supply chain transformation and technology adoption. My experience spans diverse industries, including consumer goods, high-tech manufacturing, retail, distribution, and software development, where I have worked across Production Planning & Control, product development, and consulting. This cross-functional background enables me to bridge the gap between technology, analytics, and business strategy, helping organizations implement AI-driven supply chain solutions and optimize operational performance. I hold a Master’s degree in Computer Science with a specialization in Big Data Technologies and a Postgraduate Diploma in Supply Chain Management, equipping me with a strong foundation in both data-driven decision-making and supply chain strategy. Additionally, I am currently pursuing an MS in Analytics, further deepening my expertise in advanced data science, machine learning, and predictive modeling for supply chain applications. I have earned multiple certifications from the Confederation of Indian Industry (CII), Association for Supply Chain Management (ASCM/APICS), American Society for Quality (ASQ), and Oracle in supply chain analytics and advanced AI-driven concepts, including generative AI, reinforcing my ability to integrate cutting-edge technologies into real-world supply chain solutions. As a committed member of APICS, INFORMS, IBF, IIBA, and ASQ, I actively contribute to the industry through peer reviews, judging engagements, and thought leadership initiatives.

Areas of Expertise:

  • Supply Chain Analytics & Optimization
  • AI/ML in Supply Chain Decision-Making
  • ERP & Analytics Integration
  • Digital Transformation in Supply Chains
  • Industry 4.0 & Generative AI in Supply Chain

Email: