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Stakeholder analysis was first explored as a methodology to assist business leaders with their strategic management functions. Stakeholder analysis has since expanded beyond the corporate arena. Stakeholders are a vital element in all complex systems problems; they are the customers, users, clients, suppliers, employees, regulators, and team members of a system. They fund a system, design it, build it, operate it, maintain it, and dispose of it. Each stakeholder contributes their own value-added perspective, as described by the systems principle known as complementarity. While many approaches exist for classifying and determining their attitudes, these approaches stop short of evaluating stakeholders in a holistic and dynamic manner. This paper closes this research gap by discussing an approach to managing stakeholders using fuzzy cognitive mapping, an approach which allows for qualitative and quantitative evaluation of stakeholders on a given problem. The developed approach extends previous work by the author to showcase how stakeholders may be mapped holistically and dynamically.

Stakeholders are a vital element in all complex systems problems. They are customers, users, clients, suppliers, employees, and team members. They fund the system, design it, build it, operate it, use it, maintain it, and dispose of it. While many approaches exist for classifying and determining their attitudes, these approaches stop short of evaluating stakeholders in a holistic manner. This paper closes this research gap by developing the metric of stakeholder situation influence, a measure which allows for quantitative evaluation of stakeholder influence on a given problem. This measure is derived from Leontief Input-Output analysis. The developed approach extends previous work by the authors to showcase how stakeholders may be mapped holistically in a manner that serves to improve scenario situational awareness and support resource allocation decisions.

As machine age problems have given way to systems age messes, the underlying complexity associated with understanding these situations has increased exponentially. Accordingly, the methods we use to address these situations must evolve as well. Unfortunately, many antiquated methods for dealing with situations remain prominent. Systems engineering, traditionally, is the practical application of procedural problem solving, typically geared toward the acquisition of large-scale systems. The underlying paradigm for solving these problems can be characterized as systematic thinking. While quite appropriate for machine age problems, this approach lacks the theoretical rigor to deal with systems age messes. Thus, a new paradigm of systemic thinking, conceptually founded in systems theory, is necessary. This paper briefly discusses systems engineering, contrasts it with systemic thinking, and introduces practical guidelines for the deployment of a systemic thinking paradigm.

The Enterprise AID − for assessment, improvement, and design − methodology is a systems science-, operational test and evaluation-, and multicriteria decision analysis-based approach to design and deployment of performance measurement systems (PMSs) tailored to specific enterprises pursuing any or all of enterprise assessment, improvement, or design. Its two phases of design and deployment sprang from designers’ inductively generated and now prototyped response to a gap they recognized between performance measurement capabilities required by contemporary enterprises and those offered by contemporary PMSs. This paper illustrates key concepts underlying AID , while a companion document, The Enterprise AID methodology: Application , draws from a prototyping effort to identify value to be gained by stakeholders from PMSs designed and deployed with methodology application.

Complex systems problems require the use of a formal philosophical construct and dictate the use of a rigorous systems approach. A systems approach may utilize one of a variety of proven methods, but in each case it involves the imposition of order that ranges from the philosophical to the procedural. Independent of the construct or rigor used to address the complex systems problem is the opportunity to commit a number of errors as part of a systems approach. This paper will discuss six classifications for problem solving errors that may be experienced during the application of a systems approach as part of understanding and treating complex systems problems.

Enterprise AID - assessment, improvement, and design - is a methodology for the design and deployment of performance measurement systems (PMSs) able to address specific problems of specific enterprises pursuing any or all of enterprise assessment, improvement, or design. It features two successive phases respectively invoking its design and deployment capabilities, and it represents designers’ inductively generated response to what they perceive as a gap between capabilities needed to support contemporary enterprises and those offered by contemporary PMSs. This paper describes a prototype application of the methodology centered on a university research center and presents generalized lessons learned from that effort, including the importance of consensus on problem statement definition, recognition of the need to realistically limit the number of measures within a PMS, and others.