Operations Research Analyst at the Office of the Chief of Naval Operations (OPNAV)
Matt Powers received his MS in OR from the Naval Postgraduate School’s Operations Research program in September 2012, where he received the Chief of Naval Operations Award for Excellence in OR. He began his OR career in October 2012 at the Joint Center for International Security Force Assistance, known as JCISFA, at Ft. Leavenworth, KS, where authored the JCISFA Assessments Handbook. In October 2015, Matt reported to the Joint Staff, Joint Lessons Learned Division in Suffolk, VA where he was named Lead Military Analyst of the Research and Analysis section. Matt’s most recognized Joint Staff contribution was his development of an Excel-based text analysis tool, combining advanced Excel formulas and VBA code, that rapidly transforms large collections of text data into relevant information for near real-time identification of lessons applicable to multiple functional and organizational lessons learned communities. For his work, Matt was personally recognized by the Chairman of the Joint Chiefs of Staff, General Joseph Dunford, USMC. In September 2018, Matt reported to the Pentagon as an Operations Research Analyst in the Navy Assessments Division, and is currently a PhD student in George Mason University’s Systems Engineering and Operations Research Program. Matt’s published analyses have appeared in the Proceedings of the Spring and Winter Simulation Conferences, International Association of Peacekeeping Training and Education Centers, the Proceedings of the NATO Operations Research and Analysis Symposium, Analytics Magazine, and a textbook on Cross Cultural Decision Making. Matt is a MORS Board Member, and was the Chair for the 2018 Emerging Techniques Forum. Matt is married to the former Ms. Shyla Winter, and they have two sons, Aidan and Benjamin, and one daughter, Lucy. When he is not on duty, he likes to exercise, read, and coach his children in basketball.
Tuesday, April 16, 9:10–10:00am
CHUPPET: Learn Simply with Simple Data Science
Data overload occurs when organizations are drowning in the amount of available information such that they gain little insight under current business practices. Commercial machine learning software offer solutions to this overload, but bureaucratic, budgetary, and/or technical limitations may prevent the ability to leverage such software. A solution to these limitations is the Excel-based Content Heuristic Unstructured Parsing and Predictive Electronic Tool (CHUPPET), and the follow-on tool CHUPPET Next. CHUPPET and CHUPPET Next identify relevant themes within relatively large sets of text collections while mitigating the effect of analyst bias or lack of subject matter experience. Widely accepted machine learning, data mining, and classification techniques discriminate between relevant terms, while quantifying the relevance and document sentiment so that objective trends are identifiable. The CHUPPET tools enable analysts with varying levels of technological experience to employ rigorous computational methods to unstructured, textual data. Excel is commonly available, familiar to many, CHUPPET and CHUPPET Next require no special installation, require minimal training, and can be tailored by programmers familiar with Visual Basic for Applications. The CHUPPET tools are available for use on request at no cost. As of this writing, the CHUPPET tools are regularly used in the Joint Lessons Learned Division and the Center for Army Lessons Learned to generate periodic reports and to rapidly respond to leadership questions. CHUPPET earned its developer personal recognition from the Chairman of the Joint Chiefs of Staff, General Joseph Dunford, USMC.