Jamison M. Day, Ph.D.
Assistant Professor of Supply Chain Management
Department of Decision and Information Sciences
Bauer College of Business at the University of Houston
Jamison M. Day is an Assistant Professor of Supply Chain Management in the Bauer College of Business at the University of Houston. Prior to obtaining his Ph.D. in Operations Management and Decision Science at the Indiana University Kelley School of Business, he served as the Chief Technology Officer of Advanteq, LLC, a technology and business development firm. He has over 12 years of experience in information system and decision support technology and his clients include Microsoft, American Red Cross, Pain Enterprises, and the Journal of American History.
Currently, Jamison’s primary focus centers on integrating theory from complexity science and supply chain management to improve inter-organizational coordination in disaster relief efforts. His other research interests include supply chain bullwhip effect (order variance magnification) mitigation strategies, coordination of distributed solution methodologies, and intuition refinement. He has published articles appearing in publications including Decision Sciences, European Journal of Operational Research, OMEGA, International Journal of Logistics Systems and Management, and World Energy Monthly Review. His findings have been presented at several regional and national conferences. He is a research associate for the Center for Public Policy and a member of the Decision Sciences journal editorial review board.
Jamison is an accomplished educator and has won the Panschar Award for the “Outstanding Associate Instructor of the Year” at Indiana University. He has also been awarded several academic honors including a Doctoral Fellowship Award, the Richard & Virginia Stoner Scholarship, and the Indiana University Distinguished Alumni Scholarship Association Award.
Jamison is currently a member of Decision Sciences Institute (DSI), INFORMS, the Production and Operations Management Society (POMS), and the Academy of Management (AoM). He serves on the board of directors for Shanmar, Inc. and the Houston chapter of APICS (the Society for Operations Management).
Jamison thoroughly enjoys applying his knowledge of quantitative decision modeling (numerical-based problem solving) to problems driven by real-world applications as evidenced by his engagement in several consulting projects. His recent consulting projects include:
- Creating a pricing and bundling decision support tool for Microsoft that helped increase profitability of their corporate pricing and bundling strategies.
- Developing a round-table scheduling application for the Indiana University Kelley School of Business MBA Career Service to match recruiters and students throughout multiple interview stages based on various preferences.
- Generating a cyclical distribution heuristic for a gas products manufacturer that routes and schedules CO2 distribution to over 900 heterogeneous customers across a tri-state area for a recurring time horizon.
The pricing and bundling decision support tool created for Microsoft required integrating several conceptual innovations into a new technological application to construct a tractable problem. Breakthrough ideas in research of a classic pricing problem led to new understanding that opened up opportunities for solving a new bulk-purchase pricing and bundling problem. The tool itself was created in C# on the Microsoft .NET platform and employed ILOG’s CPLEX, a linear and quadratic program (LP & QP) optimization tool. Output from the tool suggested improvements for several executive management decisions and impacted the development of the 2003 line of Microsoft Office bundle offerings. The tool accepts multiple-unit purchase intentions for several corporate customer segments along with segment density information before using a genetic algorithm that attempts to optimize profit by creating and fine-tuning a complete bundling and pricing strategy across several individual products.
The round-table scheduling application created for the IU Kelley School of Business replaced a manual system that required over 3 man-months of time and yielded less than 50% satisfaction from students and recruiters. The new automated system required less than 2 man-weeks of simple data entry and yielded over 95% satisfaction. The Graduate Career Services office runs a round-table event each semester in which many recruiting companies come to campus to interview MBA students in an informal setting. In eight periods throughout the day, groups of five to seven students are assigned to meet with a recruiter representing a company that will hire several students later in the year. Students are allowed to specify a list of companies they would prefer to speak with, as well as the type of job they are interested in interviewing for (Marketing, Finance, IT, Consulting, etc). Although there are many models in existing research that handle this problem, the method used was created specifically for this application. The Excel spreadsheet application created requires less than one minute to schedule 8 rounds of interviews with 100 recruiters and over 600 students.
The cyclical distribution heuristic created for a gas products manufacturer required innovations in data-collection and a creative formulation that maintained near-optimality while also yielding a solution of a classic intractable optimization problem in a reasonable amount of time. A method was developed to route multiple CO2 distribution vehicles to over 900 customers (each with a different storage capacity and utilization rate) in over 100 cities over a recurring monthly time horizon. A time-horizon aggregation technique was used along with a standard multiple traveling salesman problem (MTSP) to create a manageable set of familiar (repeating) routes that ensures no customer will run out of CO2 under normal operation. When applied to the company in question, the heuristic solution created a solution that reduced driving time by 28% and reduced driver labor cost by over 30%.