Managing Uncertainty and Risk in Public-sector Investments

摘要

The Department of Defense (DoD) has an annual budget approaching a half-trillion dollars. A significant portion of that budget is either directly or indirectly affected by Information Technology (IT) Infrastructure modernization initiatives. Nationally, investment in IT infrastructure modernization is about $250 Billion a year, spanning approximately 175,000 projects. Unfortunately, various studies indicate that only 28% are completed on time and on budget-with the number dropping to around 9% for larger companies in 1994, including government programs. By 1998, these numbers had improved, with success rates for larger companies, for example, up to 24%. But, only small organizations have managed to implement more than half of their applications into one integrated system (Smith, 2000; Johnson, 1999, December; Keller, 2006, May 29). The factors driving these numbers are myriad-and include the sheer scope and complexity of infrastructure modernization programs, unstable/undefined requirements, unstable funding, moving target objectives, and evolving threats. As a result, the costs of integration complexity increase exponentially, but yet are almost invariably under estimated. These challenges notwithstanding, one Gartner study asserts that IT asset productivity will drive market capitalization (Gartner, 2002, July). Given the scope, importance and complexity of these projects, reliable, cost- effective, early warning indicators of problems are essential. Yet, classical investment theory provides little guidance for dealing with public-sector investment. The result is a general absence of computationally efficient, predictive models applicable to the analysis of those investments.