Meet the Founder

Andrew Banasiewicz, PhD

Hello and thank you for visiting. I am Dr. Andrew Banasiewicz and I am the founder of Erudite Analytics; the following is a brief summary of my professional background and personal hobbies; my full professional bio can be found here. You may also enjoy listening to my recent big data / business analytics discussion on New Hampshire's WBNH 105.1 or take a look at a short write-up in a local newspaper.

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My Story

Let me begin with a broad self-characterization: I have an undying passion for cerebral and physical fitness - the former manifests itself in my commitment to research, and the latter in my athletic hobbies, captured in a few pics shown here.

I founded Erudite Analytics in 2013 with the goal of offering independent research & analysis services, focused primarily on statistical estimation of organization-specific exposure to executive, casualty, and other risks. Prior to founding Erudite Analytics I spent nearly two decades with risk management and marketing organizations as a senior-level quantitative analyst specializing in predictive analytics, text mining, and impact measurement as means of data-substantiated decision-making.


During that time I have had the opportunity to work with numerous Fortune 500 organizations spanning a wide range of industries including energy, automotive, financial services, pharmaceuticals, consumer packaged goods, gaming & hospitality, to name just a few. That broad, cross-industry experience not only provided me with numerous opportunities to immerse myself in many different types and sources of data, but has also contributed to shaping of my current decision-making research and risk estimation work.


For instance, the Erudite Analytics' multi-attribute methodologies for estimating  the likelihood and severity of company-specific exposure to securities class action litigation can be seen as products of more than a decade of evolutionary data-method-outcome thinking and approach re-engineering; similarly, our current methodology for estimating the likelihood of adverse development of casualty claims can also be seen as a product of a multi-year, cross-industry, improvement-minded analytical re-engineering process.


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 still more recent (2019) research addresses the more general domain of organizational decision-making and organizational learning - here, in Evidence-Based Decision-Making, 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 most recent research, Organizational Learning in the Age of Data, published July 9, 2021 by Springer, 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. More specifically, in my newest book I discuss the impact of advanced information technologies, such as machine learning and broader artificial intelligence, on organizational decision-making processes and practices. One of the 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.

In addition to my hands-on risk estimation work I am also an active educator, serving as the Professor of Practice and Director of online Data Science & Business Analytics programs at Merrimack College, and a Professor of Business Analytics at Cambridge College. I formerly held a full-time faculty appointment at Boston University, and part-time appointments at Providence College and Harvard University; I also delivered numerous invited guest lecturers, including ones at Tribhuvan University in Nepal, Audencia Business School in France, and Bandung Institute of Technology in Indonesia. Professional affiliation-wise, I am a Fellow of several professional practice organizations including the Center for Evidence-Based Management, and the Australian Academy of Business Leadership; I also serve as a Director and the Chair of Professional Practice for the Society of Risk Management Consultants.

My self-introduction would be incomplete without mentioning my less cerebral interests, which include scuba diving and endurance sports. I feel fortunate to have had the opportunity to experience some truly amazing underwater wonders, including diving in Australia's Great Barrier Reef and Hawaii's Lanai 'cathedrals', and cage diving with great white sharks off the coast of South Africa; I feel just as fortunate to be able to continue to compete in endurance races, including New York, San Francisco, Hawaii and other marathons, in addition to numerous Ironman 70.3 mile triathlons, and three - and counting - 140.6 mile full Ironman triathlons.