The consensus among researchers and educators strongly supports the use of real-world data in teaching data science and statistical concepts; however, two main obstacles often limit educators: time and concept alignment. Educators often struggle to find sufficient time to identify and curate real-world datasets that align with lesson objectives or reinforce key statistical or data science concepts. Consequently, educators often resort to prepackaged datasets. Even when educators do find a dataset that has a clear use case, they often don’t fully develop the lesson for a broad curriculum or provide their content online for others to use. To address these issues, and to motivate student interest in statistics, data science and sports analytics, we created the SCORE Network.

For operations research and management science (OR/MS) professionals, the ability to effectively communicate complex analytical work is not just a skill but a necessity. Although most presentations of analytical work at OR/MS conferences are for technical audiences and focus on the details and process of building mathematical models and analyzing data, the real impact of analytical work is observed through implementation. Therefore, it is crucial for OR/MS professionals to receive training in managerial presentations – especially in delivering concise and compelling demonstrations of credible results to guide nontechnical managers, executives and other decision-makers.

As operations researchers and decision scientists, we are efficiency experts. We create algorithms that make routes for food delivery, design schedules for healthcare workers, and set prices for goods and services. But how often do we find inefficiencies in the paths those algorithms take to production? So, what can we as decision science/operations research practitioners do to efficiently deliver more model code and model value? A first step: Adopt modern Git practices.

As artificial intelligence (AI) continues to transform industries, business schools and higher education more broadly must adapt to the rapid pace of innovation to ensure that today’s students and tomorrow’s leaders are prepared to thrive in an increasingly technology-driven world. This requires a broad-based approach to education, ensuring that AI is accessible not just to those with technical aptitude but to students approaching business from all backgrounds.

The contributions of Harry Markowitz to optimization are vast, so as a Ph.D. student building on portfolio theory, it was inevitable I would come across his work. The more I read, the more I was awed by the life of a man who sowed the seeds for two entirely distinct fields of research. His is an incredible story, with coincidences, connections and copious name drops weaved throughout, and one that emphasizes the importance of interdisciplinary thinking.