Webinar Details
St. Louis Fundamentals of Risk Management
As global supply chains become more complex - join subject matter expert, Michelle Rohlwing, and ISM St Louis on a 2-hour event to learn to identify, analyze, and assess risk systematically throughout the global supply chain; and how to prioritize solutions.
The webinar link will be sent to attendees once registration closes.
Member Price: $0.00
Date
Jan 23, 2025
Time
11 AM - 1 PM CT
Location
Additional Information
Presenters
Michelle Rohlwing serves as the Innovation Product Development and Learning Manager at the Institute for Supply Management.
Previously, at Schneider Electric, she held a variety of Supply Chain leadership positions over her 20-year career there. Roles included addressing the development needs of Global Supply Chain leaders, leading the Sales Inventory and Operation Planning process, managing global inventory, and lastly implementing major transformations in forecasting, planning, and purchasing processes.
Her early career at Schneider Electric included roles as a Logistics Engineer, Project Engineer, and Manufacturing Engineer. In these positions, she contributed to the integration of standardized planning processes, managed equipment transfer projects, ensured compliance with RoHS regulations, and led multiple Kaizen events and Six Sigma projects.
Michelle holds an MBA from Cardinal Stritch University and a Bachelor of Science in Industrial Engineering from Northern Illinois University.
Description
As global supply chains become more complex and interdependent, multiple risk factors increase. Organizations can no longer depend on a single risk organization to comprehend the magnitude of such variables. Supply management professionals are now tasked with comprehension of all facets of risk management. In this session, subject matter expert Michelle Rohlwing will share the tools to help identify, analyze, and assess risk systematically throughout the global supply chain. In addition, how to prioritize solutions based on impact to the business and probability of occurrence.