In my graduate and post-graduate education, I was trained in both theoretical and applied statistics as well as production and organization economics. I have applied these approaches throughout my career.

As someone interested in how organizations function, I use various economic approaches to understand competitive strategies, governance, value chain structures, value creation, and profitability. As the chairman of an industrial start-up, I apply many of these same approaches to decision-making in authentic decision settings. To me, the gap between theory and practice isn't nearly as wide as one might think -- many of the prominent theories of management are indeed about the practice of management.

As a research scientist, I work with a broad range of primarily non-experimental (i.e., observational and naturally occurring) data in multiple contexts of inquiry, ranging from organizational structures, innovation, and business strategy to psychiatric disorders, nuclear safety, and immigration. I use a variety of different research methods, but specialize in multivariate statistical methods in particular, and more generally, statistical reasoning. As for the latter, I find it extremely important to understand the general reasoning practices underlying the use of all research methods (here, I refer specifically to the use of deductive, inductive, and abductive reasoning). My focus is always squarely on the application of the method in research practice: to understand science, one must understand the practice of science. If you think scientific practice coincides with scientific ideals, well, you need to think again.