Hierarchical Goal Analysis – structure for an operational and capability framework.
Different approaches have emerged for the analysis of complex cognitive systems to identify requirements for the design of workspaces, displays and controls, decision support systems, and/or computer supported cooperative work. These socio-technical systems demand a comprehensive systems approach to analyse technical issues, and policy issues, and behaviour of the users. Hierarchical Goal Analysis (HGA) offers a relevant structural basis for building an operational framework which can serve several purposes.
HGA is based on the theory which posits that humans operate as perceptually driven, goal referenced, feedback systems. All human behaviours are responses to errors or differences that are perceived between current states of the world and goal states.
Rather than tasks and functions, HGA uses goals, defined as desired states for variables that are monitored and controlled by operators in a system, as the primary units of analysis. HGA tends to view the system from the operators’ perspective. HGA asks what operators need to monitor, control, and achieve. For HGA, operators can be human or automated systems.
HGA is not the only approach to analyse goals, however other, more well-known goal-based approaches are, in general, performed for a specific operator, class of operators, or team of operators, so the identification and decomposition of goals are based on the roles and responsibilities that have been pre-assigned to the operator(s). If an operator’s role is modified, goals may need to be added and/or removed from the hierarchy.
In contrast, an HGA is performed for a system with an unspecified number of operators belonging to different classes and/or teams. It identifies and decomposes all goals before any goal is assigned to any operator. Even if there are changes to the role(s) assigned to the operator(s), the goal hierarchy itself does not need to be revised.
The process followed in an HGA seems to offer the flexibility required to support the design of envisioned worlds, where the number, types, and roles of operators may be undecided or subject to change. In terms of accommodating changes, new operator positions can be created and new automated processes can be introduced to support future operations. The flexibility to consider re-allocation of roles between human operators and/or automation by re-using and adapting significant portions of the original analysis is a powerful facet of HGA.