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Sharper analysis essential to predict cost of major systems

Feb. 19, 2012 - 06:00AM   |  
By SEAN CONNORS   |   Comments

Overspending on technology programs has long been a problem, and the government is being forced by the budget environment to address it. This is especially true for major weapons systems.

The Pentagon's challenge is to be smarter about how it maintains readiness even as budgets stagnate.

One way to do this is through the use of advanced predictive analysis technologies. For too long, program managers, Defense Department executives and the defense contracting community as well as Congress have relied on misinformed assumptions about the life-cycle demands on weapons systems and the need for investments in spare parts, resets and replacements. The result has been numerous instances of over-cost and over-schedule programs.

We have to be more accurate in our predictions about asset life-cycle demands, more honest about our assumptions regarding those demands and more aggressive in driving out unnecessary costs all without sacrificing battlefield readiness.

In the private sector, profits depend on the ability to be ruthlessly accurate and honest in the management of complex assets. To do this, companies rely on advanced predictive modeling technology to accurately forecast demand for repair and parts. More cost-efficient maintenance investments are the result.

Unfortunately, government's adoption of these techniques is limited. DoD's annual investment in maintenance is more than $80 billion, according to DoD budget documents. The overinvestment in maintenance and replacement systems is measured in billions of dollars annually, according to several Government Accountability Office reports on excess spare parts inventory across the services.

But there are exceptions.

The MRAP Joint Program Office recently used an advanced predictive analytics approach to get a clearer picture of future maintenance and investment needs for mine-resistant ambush-protected vehicles, and of how to maintain combat capacity into the future. The office simulated thousands of armored vehicles operating and being maintained into the future in a variety of deployment and operations scenarios. Given the complexity, uncertainty and sheer number of variables affecting vehicle readiness, only the most advanced predictive tools were appropriate.

In the end, the office identified $2 billion in cost-avoidance opportunities, including significant changes in spare parts acquisition plans, effective reset alternatives and replacing certain vehicles instead of repairing them. Readiness will remain constant even as maintenance manpower and replacement part costs will decline.

Imagine if every Defense program undertook the same type of effort each year.

Fortunately, this can be replicated almost immediately. The underlying modeling principles allow for rapid adaptation on a variety of heavy industrial equipment fleets. In fact, similar methods are regularly used for power generation facilities, processing plants, high speed rail and shipping ports.

Wider deployment across the government is easy if the will exists and policies encourage it. The likely result will be billions of dollars in savings that can be reinvested as force structure decisions evolve.

Advanced predictive analysis improves forecasting. It takes a systems integration and simulation approach, versus an emphasis on assumptions based on historical data only. It is based on the unique attributes and utilization of individual parts, rather than simplified assumptions superimposed on a fleet as a whole.

Doctors do not treat 40-year-old males based on the average health condition of all 40-year-old males; they create a customized care plan. DoD should not plan for asset maintenance based on average historical performance. Life-cycle maintenance plans should account for changing, complex variables.

Technology is available that can integrate those data sets into a living decision support platform. It allows managers to continuously identify risks associated with equipment, and reduce life-cycle spending.

In the end, the guaranteed return on investment is enormous because the cost to implement these improvements is low.

For programs that have implemented this technology, return on investment has exceeded 100 times.

The Defense Department, and government overall, has an unprecedented opportunity to dramatically improve management of complex systems. It is time for the Pentagon to deploy advanced predictive analytics and decision support platforms for life-cycle management across all programs to find billions in savings without sacrificing readiness.

Sean Connors, a 20-year veteran in advanced logistics software development for heavy industry and defense, is president and CEO of Clockwork Solutions, based in Austin, Texas.

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