Total Ownership Cost Models for Valuing System Flexibility

A significant challenge in systems engineering and acquisition is to justify investments in system flexibility as opposed to buying more features or copies of a less-flexible systems. The Total Ownership Cost (TOC) has the advantages of having clear cause-effect relationships that are easy to understand and reason about. We present two TOC models for valuing flexibility that have been calibrated to project data. One is for a single system; the other is for a family of systems. We also illustrate the use of TOC in acquisition decision situations, and discuss areas for further research in extending the models. Overview of the Total Ownership Cost (TOC) Approach Many organizations use separate budgets for system development and system life-cycle support. This usage frequently leads to suboptimizing system architectures and designs to minimize development costs, which in turn results in inflexible, hard-to-modify systems and higher overall costs for the system’s owners. The concept of Total Ownership Cost (TOC), including the costs to research, develop, acquire, own, operate, maintain, and dispose of a system, has been in use since at least 1929 as a basis for making ownership decisions involving investments in flexibility and maintainability (AREA, 1929). This can be done by determining the relative costs of system development, operations, and support with and without the flexibility investments over a given system life span. The major sources of added ownership cost due to shortfalls in flexibility are rework during development, adaptation to change during operations and support, and duplication of effort in developing and supporting similar systems. TOC Advantages for Valuing Flexibility The TOC approach has several advantages with respect to alternative methods such as real options analysis, insurance analysis, portfolio analysis, entropy measures, and cost-of-delay analysis. It is easy to understand, has clear cause-and-effect relationships, can be used to complement and contextualize alternative methods, and can be tailored to particular domains. It is easy to understand across various acquisition stakeholders (program managers, oversight managers, systems engineers, cost analysts, contract managers, warfighters) because its costs (investments in reducing downstream rework, change processing, and duplication of effort) and benefits (the effects of the investments on TOC) are expressed in simple arithmetic formulas as compared to complex mathematical formulas and probabilistic assumptions. Its cause-effect relationships (the investments and their effects on reducing downstream rework, change processing, and duplication of effort) are straightforward and can be calibrated to project data. It can be used either in standalone mode or to complement and contextualize alternative methods such as those listed above. And once experience and data are available in particular domains, their relative investment costs and ownership costs can be more accurately calibrated and related to domain-specific cost drivers and decision alternatives.