Advancing the Use of an Analytical Hierarchy Process and Improved Random Indexes for Making Prioritized Decisions in Systems

In the early stages of the systems engineering process, an important focus is to create an understanding of the stakeholder needs. This is primarily done to prepare the system specification that forms the basis for the system’s design. By extension, example steps in this process include surveying stakeholders to better capture their intent, deriving and documenting requirements, and then using those requirements for subsequent activities, such as developing a functional baseline and candidate design alternatives. During this process, it is important to consider the full system lifecycle. As such, one major objective of a systems engineer is to translate the stakeholder’s needs into functional and nonfunctional requirements (NFRs). Despite this important role, early system designs are often faulty because important NFRs are poorly prioritized or not prioritized at all. While the prioritization of all requirements can be useful, this work focuses specifically on NFRs. It has been identified that the inability to identify the most useful NFRs can lead to system failure. Furthermore, the lack of NFR prioritization is considered one of the most expensive and difficult errors to correct, as well as one of the ten most significant risks in engineering. Systems need more emphasis on the relationships between the system’s elements, rather than on the individual elements or the whole system. Relationships among elements in a system can illustrate more than just the behavior of each element. The illustration can include the purpose for the system and the implications of changing how the NFRs associated with those elements are prioritized. This emphasis requires quantifiable tools and rigor to inform the decision makers. This research’s objective is to contribute to quantifiable decision-making methods and prioritization of NFRs in three ways: the development of a process to determine unique random index; the use of a continuous ranking scale; and the development of a universal decision-making heuristic to accompany prioritization of NFRs.

I. Introduction

The management of technical functions, such as research, development, and engineering in industry, government, university, and other settings, according to this journal [1], is used to emphasize the studies carried on within an organization to help in decision-making. The impact of the study presented here is through the interpretation of subject matter experts (SMEs) relative to each other and those needs of the customer. These interpretations are derived from desired behavior understanding of the system.