Business Operations and Analytics
All sectors of the modern economy rely on fundamental quantitative tools for analysis, prediction, and optimization, to leverage data for the purposes of improving decision making. These tools allow companies and not-for-profit organizations to do more with limited resources. This gives businesses competitive advantages in the marketplace by lowering cost, increasing profits margins, and improving customer satisfaction.
This area includes:
Manufacturing and Service Systems: Designing better manufacturing systems and service operations by creating more efficient and effective facilities and processes that increase customer satisfaction and improve profit margins for businesses and not-for-profit organizations.
Supply Chain Management: Optimizing the efficiency of global supply chains to reduce overall cost and make them more robust to disruptions by managing production, distribution logistics, and inventory control to guarantee a reliable supply of goods at affordable prices to customers.
Scheduling: Developing resource allocation plans to improve the flow of materials and people in manufacturing and service systems to increase efficiencies and improve the quality of the customer experience.
RELATED NEWS
-
Saif Benjaafar Named Distinguished Fellow of MSOM Society
The University of Michigan Industrial and Operations Engineering Professor has been named a Distinguished Fellow by the Manufacturing and Service Operations Management (MSOM) Society of the Institute for Operations Research and the Management Sciences (INFORMS).
-
Standardizing bilevel optimization for future researchers and practitioners
Bilevel optimization is used not only in research, but also in business to identify the best solutions for a variety of hierarchical problems. A U-M researcher aims to develop a comprehensive software package that will enable many industries to use this in everyday decision-making.
-
U-M IOE takes home awards from the INFORMS Annual Meeting
IOE faculty and students bring in awards from the 2023 Institute for Operations Research and the Management Sciences Annual Meeting.
-
Helping people get back to work using deep learning in the occupational health system
University of Michigan researchers have produced a new prediction model using longitudinal information and deep learning to better predict the return to work time for people with occupational injuries.
-
Xiuli Chao receives funding from J&J to develop algorithms for continuous production process
U-M IOE’s Xiuli Chao receives funding from Johnson & Johnson for a project centered on developing optimization algorithms to improve continuous production process.
-
Xiuli Chao receives funding to improve the efficiencies of sharing economy
U-M IOE professor, Xiuli Chao, receives funding from Didi for a project focused on improving the efficiencies of sharing economy through enhanced matching and contract design.
-
Mitigating uncertainties in remote computer numerical control using data-driven transfer learning
U-M IOE’s Raed Al Kontar receives research funding from Cyber-physical Systems, a National Science Foundation program, for a project centered on the refinement of computer numerical control as a cloud service.
-
Jessie Yang receives funding from Dell for analysis of online user-generated data
U-M IOE assistant professor, Jessie Yang, has received research funding from Dell Inc. for sentiment analysis of online user-generated data for business intelligence enrichment.
-
Xiuli Chao and Ruiwei Jiang receive MCubed funding for data-driven optimization of online retailing
Two U-M Industrial and Operations Engineering (IOE) researchers have received MCubed funding from the University of Michigan for work on data-driven optimization for online retailing.