ODT offers integrated programs in the broad areas of supply chain and operations, business analytics, and information systems, all within an atmosphere that blends academic rigor with camaraderie and support. Together, the three areas of study in ODT combine and complement one another to increase efficiencies, improve processes, and deliver goods and services that affect everyone’s daily lives. The areas of study include:
Faculty
Name & contact
Professional interests

Frank E. Akaiwa
Senior Lecturer
fakaiwa@iu.edu
HH 4100
Bloomington
Business Process Management, Enterprise Resource Planning (ERP), Enterprise Applications, XML Tools and Techniques, Database Management and Spreadsheet Analysis Tools and Techniques, Emerging Technologies

S. Chris Albright
Professor Emeritus
HH 4100
Spreadsheet Modeling for Optimization, Statistical Analysis and Simulation, Developing Excel Add-ins for Statistics, Statistics for Research, Stochastic Models in Management Science, Quantitative Methods for MBA Core, Web Page Development and Database Access with .NET, Data Mining, VBA for Excel

Hillol Bala
Professor
hbala@iu.edu
HH 4100
Bloomington
Digitalization in organizations and society, including healthcare contexts; IT-enabled organizational change; IT use, adaptation, and impacts; enterprise systems implementation

George Ball
Associate Professor
gpball@iu.edu
HH 4100
Bloomington
Product recall causes, effects and the recall decision-making process. Food and Drug Administration (FDA) regulatory policy, pharmaceutical, medical device, and automotive supply chain quality

Doug Blocher
Professor
dblocher@iu.edu
HH 4100
Bloomington
Customer Order Scheduling, Changeover Scheduling, Supply Chain Management, Lead Time/Cycle Time Reduction

Kurt M. Bretthauer
Professor
kbrettha@iu.edu
HH 4100
Bloomington
Service Operations Management, Healthcare Services, Supply Chain Management

Carl M Briggs
Clinical Professor
briggsc@iu.edu
HH 4100
Bloomington
Enterprise Project Management, Analytical Techniques for Supply Chain Procurement, Simulation Modeling Tools and Techniques, Scholarship of Teaching and Learning, including distance/online learning

By visualizing and analyzing large data sets, the S326 course I developed introduces useful tools to leverage network resources and social features and offers hands-on practices to explore economic relationships embedded in social media data.
Lucy Yan, Professor