How do you analyze workplace systems for human factors?

1 Define the system

The first step in analyzing a system is to define it. A system is a set of interrelated elements that work together to achieve a common goal, and in a workplace setting, it could include people, tasks, tools, equipment, environment, and organization. To define the system thoroughly, you should consider questions such as the purpose and function of the system, who its users and stakeholders are, what tasks and activities are performed by the system, what tools and equipment are used by the system, and what environmental and organizational factors influence it. Answering these questions will help you scope the boundaries and components of your analysis as well as identify any key human factors issues.

2 Collect data

The second step is to collect data on the system and its human factors. This can be done through observation, interviews, surveys, questionnaires, document reviews, incident analysis, and performance measurement. Depending on the purpose and scope of your analysis, you may want to consider collecting data on how people interact with the system and its elements, their skills, knowledge, abilities, and attitudes; the physical, mental, and emotional demands and outcomes of the system; sources and effects of human error, fatigue, stress, injury, and illness; and how people cope with and adapt to the system and its challenges. By collecting data in this way, you can gain a comprehensive and objective understanding of the system and its human factors.

3 Analyze data

The third step in the process is to analyze the data you collected and identify the strengths and weaknesses of the system and its human factors. Different data analysis methods can be used, such as qualitative, quantitative, or mixed approaches, depending on the type and quality of your data. Descriptive statistics, inferential statistics, thematic analysis, and human factors models and frameworks are some of the techniques you may use. For example, descriptive statistics include frequency, mean, median, mode, standard deviation, and range; inferential statistics include correlation, regression, t-test, ANOVA, and chi-square; thematic analysis involves coding, categorizing, and interpreting themes and patterns; and human factors models and frameworks include human error classification, workload assessment, stress management, ergonomic design, and human-system integration. Through data analysis you can gain valuable insights about the system and its human factors.

4 Recommend improvements

The fourth step is to recommend improvements to the system and its human factors based on your data analysis. Suggestions may include providing training, feedback, and support to the people involved in the system; simplifying, standardizing, or automating the tasks and activities; enhancing, modifying, or replacing the tools and equipment; and optimizing, controlling, or adapting the environmental and organizational factors that influence the system. By recommending these changes, you can propose solutions to any human factors problems or opportunities in the system.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?