The Digital Data Design Institute at Harvard invites individuals to embark on a journey into the future of business across industries and sectors. This collaborative effort bridges the intellectual chasm between academic research and industry practitioners to scrutinize innovative operating models and business models that are redefining traditional business paradigms that succeed in the age of AI and beyond. We delve into the intricate dynamics of digitalization, ecosystem-driven strategies, and platform-centric approaches that are shaping the contemporary business landscape. Together, we explore strategies and insights poised to empower organizations to excel in the ever-evolving world of commerce.
Since the COVID-19 pandemic, the rise in remote work practices has inarguably created new business opportunities, such as the ability to hire the most qualified candidate for a position regardless of geographical location. However, research from Eamon Duede, Assistant Professor at Purdue University, Misha Teplitskiy, Assistant Professor at the University of Michigan School of Information, […]
In today’s complex global economy, some businesses grapple with fundamental decisions regarding their structure and operations. A core challenge lies in determining when to vertically integrate suppliers and when to maintain external contracts. Recent research by Harvard Business School Professor, Laura Alfaro, and a research team (see the bottom of the page for author details) […]
In today’s fast-evolving business landscape, the ability to innovate rapidly has become a defining factor for success. Companies like Netflix, Amazon, and Microsoft have leveraged robust experimentation frameworks to enhance decision-making, optimize products, and continue innovating. Iavor Bojinov, Assistant Professor at Harvard Business School and Principal Investigator at the Digital Data Design Institute (D^3) Data […]
In an era of data-driven business decision-making, the ability to design experiments that produce reliable, actionable results is essential. In their research, “Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference”, first published in 2022 and updated in 2024, Michael Lindon, research scientist at Netflix; Dae Woong Ham, Assistant Professor at University of Michigan’s Ross […]
