MSBA-BA students solve real-world problems for real-world companies
July 19, 2019
Projecting need and labor demand for a local construction equipment dealer. Creating and measuring the success of an opioid awareness campaign. Researching and implementing autonomous meeting management tools for NASA. Identifying intellectual properties with the potential for success for the Virginia Tech Applied Research Corporation. Determining optimal locations for wayside detection systems for Norfolk Southern. Developing a system to monitor purchase card compliance for the Virginia Tech Office of Audit, Risk, and Compliance. All real-world problems for real-world companies, and all with real-world consequences.
For those participating in the Masters of Science in Business Administration with a concentration in Business Analytics (MSBA-BA) program, the final hurdle to overcome prior to graduation is the capstone project. A distinctive feature of the MSBA-BA program, the capstone project requires “teams of interdisciplinary students to solve a real-world problem provided by various corporate sponsors,” according to Mike Flint, director of the Center for Business Intelligence and Analytics (CBIA), home to the MSBA-BA program.
Spread out over 10 months, the capstone project experience begins in September as sponsor companies pitch their problems to the program’s students during a live event. After the pitch event, students rank their top three choices. Given the diversity of the possible projects, most students gravitate toward projects based upon their background. “Several of our engineering students chose the Norfolk Southern project because it was engineering in nature,” said Flint. “It really just depends on what project ‘speaks’ to them.”
Using the students’ project rankings, four-to-five member teams are formed utilizing a prescriptive data analytics model – naturally – designed specifically for the task by Cliff Ragsdale, Bank of America Professor of Business Information Technology and academic director for CBIA. “The model considers the students choices, the skills the customer believes they need, as well as the backgrounds of the students to make team recommendations,” explained Flint. “Once we review the model output, and make any ‘soft’ adjustments, we assign students to teams.”
After project teams are formed, the students attend several workshops where they learn different project management techniques. The teams then have numerous interactions with their “customers,” including at least two on-site visits, during the life of the project. At the completion of the capstone project, the teams “will prepare a professional consulting report which summarizes and supports their findings and builds a case for their recommendations,” said Flint. The project concludes with a formal business presentation attended by the corporate sponsors as well as CBIA program personnel.
Along the way, each team will need to complete real-world deliverables, dependent upon their corporate sponsor. “Each customer has different success targets and they communicate those to the students in the September project pitches,” said Flint. From issue trees and project plans to draft reports and slide deck drafts, every team needs to complete a different set of benchmarks to show how their project is progressing. “These techniques are patterned after what industry does in their own delivery of consulting projects,” Flint continued.
So how did the 2019 class (also known as Cohort 3) do in delivering solutions to the aforementioned problems?
For the team working with Foundry26, a marketing and analytics subsidiary of Carter Machinery, the objective was to enhance the company’s labor hour prediction capabilities to improve the optimization and allocation of technicians. The predictive model the group ultimately developed was determined to be so accurate that Foundry26 is now looking to integrate the model into their preexisting software.
The team working with Leidos – a global leader in the integration and application of information technology, engineering, and science – to explore effective routes for opioid awareness campaigns were forced to reevaluate their initial strategy when they received a miniscule response rate to a survey of Virginia Tech students. This compelled the team to research how 18-34 year olds were receiving their information on opioids, soon discovering that people within this age range were not seeking out information on their own, nor was the information available on social networking sites resonating. The team recommended that a compulsory education program be used with those in their early teens, as similar programs focusing on alcohol abuse have shown success.
The NASA Langley Research Center needed a recommendation on a universal autonomous meeting management software, one that could relieve their current administrative burden. The team researched numerous platforms, ultimately developing a weighted matrix that would score each program in a variety of categories. They were then able to make two different recommendations to NASA, a short-term and a long-term solution based upon the matrix scores as well as a cost-benefit analysis.
The Virginia Tech Applied Research Corporation tapped their team to develop a model that will be able to identify intellectual properties with the potential for successful commercialization. As the team began their research into the problem, they realized that the project was bigger than the data; that is, the necessary data needed for a predictive model was non-existent. The team developed a “roadmap” to a predictive model, outlining the necessary information needed to develop a successful analytics platform.
Norfolk Southern asked their team to develop a system to determine the optimal locations for wayside detection systems – devices used on railroads to detect problems in passing trains. The team developed a mathematical model comparing three different scenarios and their cost. They then transferred the information into a Tableau data model, allowing Norfolk Southern to visualize the recommended solution.
A multi-national team took on the problem faced by Virginia Tech’s Office of Audit, Risk, and Compliance, reviewing over 6,000 transactions on purchase cards, or P-Cards, to ensure accuracy. The team developed predictive analysis software that is 75 percent accurate at identifying problematic transactions. The software has been so useful, in fact, that the Office of Audit, Risk, and Compliance is now the first higher education agency that has put a predictive analysis system into use.
The success of the MSBA-BA teams speaks to the quality of both the program and as well as its students, which is why companies are excited to partner with the capstone project.
“We’re finding our program speaks loudly to large, established companies, medium-size companies, as well as small companies and start-ups since they all see a need for high-impact business analytics leaders (or HIBALS) who can engage a customer, understand their problem, solve it, and present it in a clear, concise manner,” said Flint.
“I believe we saw that in the project presentations and our sponsors agree.”
Written by Jeremy Norman