Observations
Observation is another way to collect data required to conduct a job analysis. To simply put, observation is a process in which an analyst observes and records what a worker does (Brannick et al., 2019). Observations can be an effective methodology in collecting data about a job especially when the analyst spends a long period of time (e.g., a day or week) to fully capture what’s being done and carried out by the worker at the workplace. Unlike interviews that are heavily dependent on the questions being asked, the observations enable the analyst to capture the true current state of the job along with the things that would have otherwise been difficult to capture (e.g., interaction with other co-workers). As a healthcare consultant, I’ve conducted observations to fully understand the tasks of operations managers over a week. The objective was to identify whether any tasks can be delegated to other employees in order to reduce the person’s workload which could, in turn, prevent the person from burning herself out. The challenges associated with observations can be summarized as follows. First, it requires an organized effort in that all the stakeholders who are involved (e.g., job incumbents, their co-workers, and supervisors) must fully understand and agree with the objective of the observations. In my experience, I’ve conducted observations in which there were not enough buy-ins and as a result, there was some resistance from the job incumbent which impacted the information I collected. Another challenge is that, though in an ideal world the analyst’s present has little or no effect on the worker’s behavior, I find that their behavior inevitably changes when they are aware that they are being observed. Also, there are inevitably variabilities in the tasks that are carried out depending on when the job holder is being observed. For instance, after observing a nurse at an emergency department for a week, I was informed that that particular week was not as busy as the average, and as a result, I failed to capture some of the key tasks that she would have otherwise carried out.
Choosing the Right Methodology for Data Collection
The outcome of choosing an inappropriate method can in fact be costly or unethical. In order to avoid any issues associated with choosing a wrong data collection methodology, as with any analysis, it is crucial for the organizations to determine the objective of the analysis and generate different ways to achieve the objective. These crucial steps, however, are often overlooked, and instead, organizations tend to prematurely select a data collection methodology that is most effective in achieving the objective. Prior to selecting a methodology, organizations should clearly understand what resources are available within and outside the organization as well as the data that have been collected previously that they could utilize (e.g., internal database and external database such as O*Net). From my experience, another thing that is often overlooked is the involvement of SMEs, especially the job incumbents. When developing a job description, for instance, it is absolutely crucial to get inputs from those who are currently doing the job. Only after having completed these steps, organizations should proceed in generating ideas based on design thinking (Norman, D., 2013) and selecting the appropriate data collection methodologies.
References
Brannick, M. T., Levine, E. L., & Morgeson, F. P. (2019). Job and Work Analysis: Methods, research, and applications for human resources management (3rd ed.). Sage.
Norman, D. (2013). The Design of Everyday Things. MIT Press.
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