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Human-Centered Engineering

Human-centered engineering is a specialized field within systems engineering that seeks to integrate human and technological capabilities into an effective sociotechnical system.

The goal of human-centered engineering is to increase the fit, alignment, or congruence between four elements: the capabilities of human beings; the technology they use; the social and organizational structures within which they work; and the mission and tasks they seek to accomplish.

All four of these elements can be “engineered” to increase their fit and therefore increase the performance of the sociotechnical system:

1. Improving Human Capabilities

Human knowledge and skills may be improved through training. Training requirements should be based on the nature of the work to be done and the technology that will be used to perform this work.

2. Improving Technology Design

Technology that has been designed to be aligned to human capabilities is often described as “usable” or “user friendly.” A variety of techniques and guidelines exist for designing more useful and usable interfaces for software applications and for testing the usability of these interfaces (see entry on human-computer interaction for guidelines and references).

3. Improving Organizational Structures

Most human work is performed in organizations. Organizational structures typically specify how work is to be allocated and performed, how resources are to be distributed and controlled, and how power and authority are to be assigned. These organizational structures may be designed to improve performance by increasing their alignment with the nature of the tasks to be performed, the capabilities of the technology to be used, and the capabilities of the human beings who belong to the organization.

4. Improving Mission Tasks and Processes

The tasks to be performed by an organization typically have their own structure, including dependencies among tasks, requirements for resources and expertise, and processes for carrying out and coordinating tasks. These workflow processes may be improved by increasing their alignment with human and technology capabilities and organizational structure.

Aligning the Four Elements to Improve Sociotechnical System Performance
Independent improvements in any of these four elements can improve the overall performance of a sociotechnical system, but human-centered engineering strives to maximize performance by improving all four elements simultaneously, making them better aligned or more congruent. This is done through the use of theories from many different disciplines (e.g., industrial/organizational psychology, computer science, cognitive science, sociology, and human factors) to identify the key variables for each element and the relationships these variables, the development of computational models that capture and represent complex interactions among variables, and the identification of quantitative performance measures that can be used to capture data on actual performance to evaluate the effectiveness of designs, test theories, and improve models.

See also:

Systems engineering Human factors Sociotechnical systems Human-computer interaction Training Organizations Cognitive ergonomics

Additional Reading
Cohen, M. S., Freeman, J. T., & Thompson, B.T. (1998). Critical thinking skills in tactical decision making: A model and a training method. In J. Canon-Bowers &: E. Salas (Eds.), Decision-making under stress: Implications for training & simulation. Washington, DC: American Psychological Association Publications.

Entin, E. E., & Serfaty, D. (1999). Adaptive team coordination. Human Factors, 41, 312-325.

Klein, G. (1999). Sources of power: how people make decisions. Cambridge, MA: MIT Press.

Levchuk, G. M., Yu, F., Levchuk, Y., & Pattipati, K. R. (2004). Networks of decision-making and communicating agents: A new methodology for design and evaluation of organizational strategies and heterarchical structures. Proceedings of the 9th International Command and Control Research and Technology Symposium, San Diego, CA.

MacMillan, J., Entin, E. B., Morley, R., & Bennett, W. (in press). Measuring team performance in complex dynamic environments: The SPOTLITE method. Military Psychology.

Norman, D. (2002). The design of everyday things. 2002, New York: Basic Books (Perseus).

Orvis, K. L. & Lassiter, A. R. L. (2007). Computer-supported collaborative learning: best practices and principles for instructors. Hershey, PA: The Idea Group.

Pew, R. W., & Mavor, A. S. (1998). Modeling human and organizational behavior. Washington, DC: The National Academies Press.

Pew, R. W., & Mavor, A. S. (2007). Human-system integration in the system development process. Washington, DC: The National Academies Press.

Serfaty D., MacMillan J., Entin, E. E., & Entin E. B. (1997). The decision-making expertise of battle commanders. In C. E. Zsambok and G. Klein (Eds.), Naturalistic decision-making. New York: Lawrence Erlbaum.

Stacy, W., Ayers, J., Freeman, J., & Haimson, C. (2006). Representing human performance with Human Performance Measurement Language (HPML). Proceedings of the Interservice/Industry Training, Simulation and Education Conference. Arlington, VA: NDIA.

Stacy, W., Merket, D., Puglisi, M., & Haimson, C. (2006). Representing context in simulator-based human performance measurement. Proceedings of the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC). Arlington, VA: NDIA.

Stacy, W., Merket, D., Freeman, J., Wiese, E., & Jackson, C. (2005). A language for rapidly creating performance measures in simulators. Proceedings of the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC). Arlington, VA: NDIA.

Stacy, W., Freeman, J., Lackey, S., & Merket, D. (2004). Enhancing simulation-based training with Performance Measurement Objects. Proceedings of the Interservice/Industry Training, Simulation and Education Conference (I/ITSEC). Arlington, VA: NDIA.