Cost As An Independent Variable: Principles And Implementation - defense systems

Acquisition Review Quarterly, Fall, 2000 by Michael A. Kaye, Mark S. Sobota, David R. Graham, Allen L. Gotwald

Cost as an independent variable is a key tool in the thrust to reduce total ownership cost for defense systems. While the need for CAIV is driven by cost constraints, success relies upon identification and use of viable performance, cost, schedule, and risk "trade space." The Air Force has integrated CAIV concepts with those in the Reduction in Total Ownership Program (R-TOC), and has published a comprehensive guidebook for better understanding.

The Defense System Affordability Council (DSAC) Strategic Plan established Goal 2 to Lower the total ownership cost (TOC) of defense products. The plan further established separate, aggressive objectives under that goal for systems in acquisition and fielded systems. These goals are further emphasized in the draft new DoD 5000.1 and 2.

To provide a focal point on all reduction in TOC (R-TOC) efforts, encompassing weapon system, infrastructure, and indirect dimensions, the Air Force established an R-TOC program office (SAF/AQXT). SAF/AQXT and the authors collaborated to publish the R-TOC Guidebook, which integrated Cost as an Independent Variable (CAIV) and a comprehensive RTOC process for fielded systems (1999). The R-TOC process relies on baselining operating and support costs, identifying TOG drivers, and identifying R-TOC opportunities. CAIV drives system design decisions by providing comprehensive information on alternatives and impacts.

Whereas CAIV and the R-TOC process have many principles in common, CAIV exerts the most leverage when it influences system design and the R-TOC process is most effective on fielded systems. The relationship is shown in Figure 1.

CAIV CONSTRUCT

CAIV is a key strategy for implementing R-TOC in the acquisition process, and is particularly effective during system development. Air Force Instruction (AFI) 10-601 (1998) defines CAIV as "the process of using better business practices, allowing trade space for industry to meet user requirements, and considering operations and maintenance costs early in requirements definition in order to procure systems smarter and more efficiently."

CAIV is founded upon two primary principles: First, system costs are constrained. Whereas some programs do obtain additional funding when needed, such funding is often at the expense of other programs or future modernization. Second, "trade space" is the foundation for smart decisions. Trade space is the range of alternatives available to decision makers. It is four-dimensional, comprising performance, cost (TOC), schedule, and risk impacts.

The Air Force established a set of tenets that are core to CAIV implementation. The concept of well-understood trade space is the capstone tenet that enables decisions critical to meeting user needs while reducing TOC. The remaining five tenets are the pillars that enable trade space to be defined and exploited. Figure 2, the CAIV model, depicts the relationship of the CAIV tenets.

TRADE SPACE

CAIV provides better support for critical decisions by identifying viable performance, schedule, cost (TOC), and risk trade space. Identification and use of viable trade space, or the range of alternatives, with full knowledge of real and potential impacts, is essential for making the right decisions to meet user needs while reducing TOG. CAIV employs a hierarchy of cost reduction opportunities and tradeoffs to meet aggressive cost targets, first looking to improve acquisition and sustainment efficiencies, then scrutinizing noncritical requirements. Tradeoffs of critical performance requirements are only to be addressed as a last resort, with the agreement of the Milestone Decision Authority and user.

Trade space is commonly defined by alternatives in terms of the performance, cost, and schedule impacts that each alternative presents. Risk must also be included in two ways. First, risk is a fourth dimension in the trade space, recognizing that critical decisions may be driven by the risks of certain alternatives. Second, risk actually "discounts" the anticipated performance, cost, and schedule options; in other words, it lessens the trade space to ensure a decision maker does not trade away something that may not be attainable. For example, assume you have a system with anticipated range of 2000 miles versus a requirements threshold of 1500 miles. You could trade away up to 500 miles of range for a fully tested, validated system and still meet threshold. However, you definitely would not trade away 500 miles of range at the beginning of program definition and risk reduction (PDRR), when there are potential weight growths, fuel consumption increases, etc.

Figure 3 portrays the cost-performance trade space for a key performance parameter (KPP), characterized by threshold and objective values. Note that Figure 3 shows a "risk reserve" line to depict the amount that the trade space is restricted, to prevent trading away what is not yet realized. The "solution set" line represents the optimum cost-performance combinations: Points in the shaded region are solutions, but for any given point, either more performance for the same cost or the same performance for less cost is possible.