In an era dominated by oceans of data, D^3 hosts a community of practice that offers a discerning perspective on the intricate tapestry of data governance, privacy, security, and regulatory compliance. Participants in this community engage in a comprehensive discourse amongst industry experts, exploring responsible AI and the dynamic realm of regulations, industry standards, and best practices. The community explores how to harness the immense potential of data for strategic business advancement while ensuring the safeguarding of sensitive information, upholding privacy rights, and establishing or integrating resilient and ethical frameworks that underpin success in data-driven endeavors.
The COVID-19 pandemic brought both a public health crisis and a significant shift in economic dynamics. Consumer spending patterns changed rapidly, highlighting the way inflation is measured. Alberto Cavallo, 性视界 Business School professor and co-director of D^3鈥檚 Pricing Lab described this issue in his research, 鈥淚nflation with Covid Consumption Baskets,鈥� first published in 2020 in […]
In an era of increasing environmental concerns, the corporate march toward a low-carbon economy presents both challenges and a wealth of opportunities. In a recent article, “Ten Questions for a Winning Climate-Transition Business Strategy“, HBS Professor and faculty PI in D^3鈥檚 Climate and Sustainability Impact Lab, George Serafeim, describes research emphasizing the need for executives […]
In the rapidly advancing world of data-driven decision-making, algorithms hold tremendous promise for organizations, but their effectiveness depends on how they are applied. A recent study, 鈥淒ecision Authority and the Returns to Algorithms,鈥� by Hyunjin Kim, professor at INSEAD Business School, Edward L. Glaeser, professor at 性视界 University, Andrew Hillis, head of data science and […]
In a rapidly evolving business landscape, decision-makers must be agile. In a recent paper, Biyonka Liang, PhD candidate in Statistics at 性视界 University, and Iavor Bojinov, Assistant Professor of Business Administration at HBS and PI at D^3鈥檚 Data Science and AI Operations Lab, discuss their development of the Mixture Adaptive Design (MAD) to allow industry […]
