The unit of analysis refers to the level of aggregation at which information is analyzed and conclusions are drawn. It is the major entity that you are analyzing in your study. 

It should be given serious consideration even as the research question is being formulated and the research design is planned. 

If, for instance, the problem statement focuses on how to raise the motivational levels of employees in general, then we are interested in individual employees in the organization and have to find out what we can do to raise their motivation. Here the unit of analysis is the individual. We will be looking at the data gathered from each individual and treating each employee’s response as an individual data source. 

If the researcher is interested in studying two-person interactions, then several two-person groups, also known as dyads, will become the unit of analysis. Analysis of husband–wife interactions in families and supervisor–subordinate relationships in the workplace are good examples of dyads as the unit of analysis. 

However, if the problem statement is related to group effectiveness or if we want to compare two groups (e.g., departments), then the unit of analysis will be at the group level. In other words, even though we may gather relevant data from all individuals comprising, say, six groups, we aggregate the individual data into group data so as to see the differences among the six groups. 

If we are comparing different departments in the organization, then the data analysis will be done at the departmental level – that is, the individuals in the department will be treated as one unit – and comparisons made by treating the department as the unit of analysis.

The Chief Financial Officer of a manufacturing company wants to know how many of the staff would be interested in attending a three-day seminar on making appropriate investment decisions. For this purpose, data will have to be collected from each individual staff member and the unit of analysis is the individual 

Having read about the benefits of mentoring, a human resources manager wants to first identify the number of employees in three departments of the organization who are in mentoring relationships, and then find out what the jointly perceived benefits (i.e., by both the mentor and the one mentored) of such a relationship are. Here, once the mentor and the mentored pairs are identified, their joint perceptions can be obtained by treating each pair as one unit. Hence, if the manager wants data from a sample of 10 pairs, he will have to deal with 20 individuals, a pair at a time. The information obtained from each pair will be a data point for subsequent analysis. Thus, the unit of analysis here is the dyad. 

A manager wants to see the patterns of usage of the newly installed information system (IS) by the production, sales and operations personnel. Here, three groups of personnel are involved and information on the number of times the IS is used by each member in each of the three groups, as well as other relevant issues, will be collected and analyzed. The final results will indicate the mean usage of the system per day or month for each group. Here, the unit of analysis is the group. 

Procter & Gamble wants to see which of its various divisions (soap, paper, oil, etc.) have made profits of over 12% during the current year. Here, the profits of each of the divisions will be examined and the information aggregated across the various geographical units of the division. Hence, the unit of analysis will be the division, at which level the data will be aggregated. 

An employment survey specialist wants to see the proportion of the workforce employed by the health care, utilities, transportation and manufacturing industries. In this case, the researcher has to aggregate the data relating to each of the subunits comprised in each of the industries and report the proportions of the workforce employed at the industry level. The health care industry, for instance, includes hospitals, nursing homes, mobile units, small and large clinics and other health care providing facilities. The data from these subunits will have to be aggregated to see how many employees are employed by the health care industry. This will need to be done for each of the other industries. 

The Chief Financial Officer (CFO) of a multinational corporation wants to know the profits made during the past five years by each of the subsidiaries in England, Germany, France and Spain. It is possible that there are many regional offices of these subsidiaries in each of these countries. The profits of the various regional centres for each country have to be aggregated and the profits for each country for the past five years provided to the CFO. In other words, the data will now have to be aggregated at the country level. As can be easily seen, the data collection and sampling processes become more cumbersome at higher levels of units of analysis (industry, country) than at the lower levels (individuals and dyads). It is obvious that the unit of analysis has to be clearly identified as dictated by the research question. Sampling plan decisions will also be governed by the unit of analysis. For example, if I compare two cultures, for instance those of India and the United States – where my unit of analysis is the country – my sample size will be only two, despite the fact that I shall have to gather data from several hundred individuals from a variety of organizations in the different regions of each country, incurring huge costs. However, if my unit of analysis is individuals (as when studying the buying patterns of customers in the southern part of the United States), I may perhaps limit the collection of data to a representative sample of a hundred individuals in that region and conduct my study at a low cost! 

A researcher wants to know what is the impact of top management support on firm performance. To test this, he takes 200 employees from an MNC in Bayan Lepas as his respondents. What problem will he encounter?