Operations Research Training for Regional Business Analysts
The advent of the new TxDOT regions creates a myriad of business optimization
opportunities. In-house operations research/management science (OR/MS) training for
lead business analysts in the new regions will enhance their ability to deal with the wide
variety of operational problems they will encounter. The ultimate result will be a cadre
of trained lead analysts who can work synergistically, effectively direct the work of their
staff analysts, and call upon external expertise as appropriate.
Regional business analysts will be expected to assist managers with forecasting, resource
allocation, cost minimization, efficiency analysis, and optimization of operations in
general.
A variety of tools are available to solve these classic business problems within the field
of operations research/management science (OR/MS). The Institute for Operations
Research and Management Science (INFORMS) defines their field as “the science of
better.” For this reason, the department needs analysts with some degree of formal
training in management science methods. While the universities (usually departments of
Business, Industrial Engineering, or Mechanical Engineering) offer strong expertise in
OR/MS, the department needs internal analysts with sufficient knowledge to select
suitable researchers, provide guidance, and assess their work.
The purpose of this training is to provide analysts with an enhanced capacity to recognize
business problems that are amenable to established OR/MS methods. This is how the
subject is typically presented in college management science courses. Once a situation is
identified as a possible candidate for optimization methods (for example), a lead analyst
can discuss the problem with other analysts and possibly consult with an established pool
of university operations research experts.
The training will be provided through a series of short courses held in Austin by selected
university professors who are part of the OR/MS “brain trust” that has historically
consulted to the department.
Coursework will consist of a series of business decision case studies analyzed on a
common Excel framework using standard features and some add-ons. Guided by
instructors, each case will be worked through a “hands-on” approach by attendees in a
TxDOT computer classroom. As a course reference, a textbook will be provided, The
Art of Modeling with Spreadsheets: Management Science, Spreadsheet Engineering, and
Modeling Craft.
Upon the completion of the course, the participants will:
1. Recognize business problems that are amenable to established OR/MS
methods rather than having to approach every problem ad-hoc.
2. Become better able to direct the work of their staff analysts.
3. Be knowledgeable of the toolbox of analytical software for
a. Forecasting
b. Decisions with multiple criteria
c. Optimization
d. Estimations with parameter uncertainties
e. Deciding the best course of action given unpredictable future
events
4. Be aware of the consulting resources available for advanced analysis.
5. Be better able to prescribe training for their analytical staff.
Instructors: Dr. James Dyer, Fondren Centennial Chair in Business and Dr. Leon
Lasdon, David Bruton Jr. Chair in Business Decision Support – both in the McCombs
School of Business, The University of Texas at Austin.
Course Topic Overview
The course will begin with forecasting, which is accomplished with various statistical
tools. For example, analysts commonly use the simple regression capability in Excel, but
often have no formal training in its use and pitfalls; likewise for the more difficult tool of
multiple regression. Also covered will be the other fundamental forecasting approach,
time series analysis, the state of the art and science of projecting trends into the future.
The second topic, closely related to the first, addresses estimates and forecasts when
many underlying variables are uncertain. The “Monte Carlo simulation” method was
designed to deal with this situation. It produces not only the needed estimate, but also
information about how “solid” that estimate is, which can be very useful for decision
makers.
The third topic concerns the most common form of decision problem: choosing,
prioritizing or allocating among alternatives given multiple criteria for evaluation. While
this is frequently done ad-hoc on a spreadsheet, a process has been developed to formally
structure the decision in a way that allows more precise capture of values and
preferences, thus providing insight into the decision as well as a solution. The
formalization is called multi-attribute utility theory, upon which numerous software
applications are based.
The fourth topic addresses optimization, defined as either 1) making decisions which
result in the maximum benefit within a budget or 2) meeting a desired level of service at
minimum cost. This session will employ the optimization technique of linear
programming, which can quickly provide the best answer as opposed to trial-and-error,
which could continue indefinitely and inconclusively.
Improving Operational Decision Making
With Spreadsheet-Based Modeling
- Syllabus -
Topic 1: Forecasting (Wednesday)
Determining interrelationships and regression analysis; time-series forecasting methods;
sensitivity analysis.
Case study – forecasting TxDOT fuel-tax revenue
 Short-term [time series]
 Intermediate-term [simple regression]
 Long-term [multiple regression, lagged variables]
Topic 2: Risk Analysis in Excel (Thursday morning)
When risk-analysis simulation is needed; widely used Excel simulation add-ons; model
formulation and interpretation of results
Case study – applying @RISK software to TRENDS revenue forecasting model
Topic 3: Multiple-criteria decision making (Thursday afternoon)
Formulating a decision hierarchy; transforming criterion values to utility values; criterion
importance weighting; scoring the alternatives; sensitivity analysis.
Case study – selecting transportation research projects
Case study – identifying dangerous intersections
Topic 4: Optimization using the Microsoft Excel Solver (Friday)
Spreadsheet engineering principles. Common types of optimization problems (capital
budgeting, cash management, transportation, production and inventory management, goal
programming); Excel Solver capabilities and limits; a framework for formulating
optimization models, understanding their solutions, and communicating results.
Case study – maintenance office location
Case study – target setting and funds allocation to road tiers
JAMES S. DYER
The Fondren Centennial Chair in Business
McCombs School of Business
The University of Texas at Austin
Professor Dyer received his B.A. with honors, Phi Beta Kappa, in physics in 1965 with minors
in mathematics and philosophy from The University of Texas at Austin. He received his
Ph.D. in business administration in 1969 with major field in statistics and minor fields in
quantitative methods and management from The University of Texas at Austin.
Dyer has been a professor at a major university since receiving his degree from graduate school
in 1969. His academic experiences include the following:
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A member of the faculty of the McCombs School of Business since 1978, he served
on the faculty of the University of California, Los Angeles for nine years, before
returning to The University of Texas. In spring 1999 he was the Philip J. Rust
Professor of Business at the Darden School of Business at the University of Virginia.
He served as chair of the Department of Information, Risk, and Operations
Management at The University of Texas for nine years (1988-97). This department
offers courses in decision and risk analysis. He also served as chair of the
Department of Management from 1982-1986.
He teaches courses on risk analysis and investment science in the MBA and Ph.D.
programs at The University of Texas. He also teaches in The University of Texas
Executive MBA programs offered in Dallas and Mexico City.
He has offered executive education programs in a number of cities in the United
States, as well as in Australia, China, New Zealand, Singapore, Indonesia, Columbia,
Ivory Coast, Mexico, Austria, England, Italy, Kuwait, Kazakhstan, and Angola.
He served as chair of the Decision Analysis Special Interest Group of the Operations
Research Society of America (now known as INFORMS). This group has a
membership of over 1000 academics and practitioners in the fields of risk analysis
and investment science.
He has published three books and more than sixty articles on risk analysis and
investment science. He received the College of Business Administration Foundation
Advisory Council Award for Outstanding Research Contributions in 1999.
LEON LASDON
The David Bruton Jr. Chair in Business Decision Support
McCombs School of Business
The University of Texas at Austin
Leon Lasdon received his Ph.D. in Systems Engineering from Case Institute of
Technology in 1964. He taught in the Operations Research Department at Case Western
Reserve University from 1964 to 1977, when he joined the Management Science and
Information Systems Dept., McCombs School of Business, The University of Texas at
Austin. He holds the David Bruton Jr. Chair in Business Decision support.
Professor Lasdon currently teaches two MBA level courses: Decision Support
Modeling and Financial Modeling and Optimization. He also teaches Ph.D. level courses
in nonlinear optimization and large-scale systems optimization. He was one of three
faculty named “outstanding graduate teacher” in 1984. In recent years he has
incorporated an active learning approach into his classes, emphasizing student discussion
and problem solving in small groups.
Prof. Lasdon is co-author of the Microsoft Excel Solver. His GRG2 nonlinear
optimizer is used in that solver. For more information see an article titled “Design and
Use of the Microsoft Excel Solver,” which appeared in the INFORMS journal
INTERFACES, Sept.-Oct., 1998. His research and consulting activities include
optimization software, supply chain modeling and optimization, customer relationship
management and other marketing issues, process control, and engineering design
optimization. His nonlinear optimization software is widely used in financial asset
allocation, option pricing, process control, and engineering design. He is the author or
co-author of over 100 refereed journal articles and three books. Recent papers are
available at www.utexas.edu/courses/lasdon (link to “papers”).