An important contributor to my applied work is theoretical research, which is focused on developing a sound conceptual foundation for the largely practice-shaped domain of organizational threat assessment. With that goal in mind, my first book, Risk Profiling of Organizations, originally published in 2009, outlines an approach for amalgamating of multi-source and multi-type data into an organization-specific risk profile, while my more recent (2017) work, Threat Exposure Management, details a comprehensive planning and management framework meant to unify the now-distinct disciplines of enterprise risk management, business continuity planning, organizational resilience, and change management under a common planning and management umbrella.

My more recently (2019) published research, Evidence-Based Decision-Making, addresses the more general domain of organizational decision-making and organizational learning. Here, I put forth a conceptual framework, supported by the enabling 'how-to' calculus, for amalgamating the totality of empirical and experiential choice related evidence. I was delighted to learn that my work captured the attention of book critics at Book Authority, who picked it as their #1 Best New Decision Making Book to Read in 2019.

My still more recent research, Organizational Learning in the Age of Data, published in July of 2021, extends the key ideas laid out in Evidence-Based Decision-Making onto broader organizational learning contexts, by tackling notions of human-machine interactions, digital, analytic, and informational literacy, and data-enabled creativity. One of that book's central themes is the interplay between human reasoning and machine logic in the context of organizational functioning, specifically, the fairly common situations in which subjective beliefs are pitted against objective evidence, giving rise to conflict rather than enhancing the quality of organizational sensemaking. Continuing that theme, my current work, tentatively titled Data Analytic Literacy, scheduled to be published in the latter part of 2023, takes a much closer look at what is required - knowledge- and skills-wise - to be deemed a competent user of today's rich and varied data resources. And lastly, concurrently I am also working on an in-depth overview of how readily available and informative data can be used to develop more analytically robust benchmarks - I expect that work, tentatively titled Probabilistic Benchmarking: Norm-Setting in the Age of Big Data, to be published in the latter part of 2024.