Seventy-five years ago, near the beginning of World War II, the field of operations research was born in Britain. Today, as the U.S. emerges from the longest sustained war in its history, the military faces a post-war drawdown. During the mid-1990s, much of the conventional wisdom was that the U.S. was in the midst of a so-called “Revolution in Military Affairs.” Technology would provide a global precision strike capability that would give us “an ability to bomb any target on the planet with impunity, dominate any ocean, and move forces anywhere to defeat just about any army.”
In an excellent article just published in OR/MS Today (Feb., 2014), we read of a “vigorous military science” in the 1990’s, resulting in an excessive focus on modeling and simulation technology. For example, medical “planning factors” were derived from attrition-based, theater-level campaign model casualty projections, vastly over predicting casualties, thereby creating unnecessary and unaffordable requirements for medical force and supply support. More recent analyses of casualties have yielded major improvements in forecast accuracy and an ability to better design more responsive, lower cost medical support requirements. Research efforts have expanded to other areas, identifying spare part consumption patterns and readiness “drivers.” Using empirically derived usage patterns, profiles, and trends, the operational planning, demand forecasting and budget requirements have been significantly improved.
Persisting supply chain problems that existed 10 years ago are now also becoming increasingly more apparent. With mounting pressures to generate savings and find efficiencies, these issues include the inability to relate resources to readiness due to poor inventory management and fragmented supply chain operations across the materiel enterprise. The promise for improved performance attributed to large investments in enterprise resource planning (ERP) systems has not been realized, continuing to plague the services. But a recent study suggests major OM improvements can be achieved using decision-support systems empowered with advanced analytics, including dramatically improved demand forecast methods, sensor-based technologies for part replacement, and integrated supply chain optimization methods. These effects are likely to be in the range of many billions of dollars, resulting in a ROI of several orders of magnitude.