Let's take the example of a hypothetical organization consisting of a CEO, directors, and managers. The CEO wants to know how many new hires have joined the company. The CEO sends a request to his or her directors to report back the number of hires in their departments. The directors in turn send a request to managers in their individual departments to provide the number of new hires. The managers provide the number to the directors, who in turn send the final value back to the CEO.

This can be considered to be a real-world example of MapReduce. In this analogy, the task was finding the number of new hires. Instead of collecting all the data on his or her own, the CEO delegated it to the directors and managers who provided their own individual departmental numbers as illustrated in the following image:

In this rather simplistic scenario, the process of splitting a large task (find new hires in the entire company), into smaller tasks (new hires in each team), and then a final re-aggregation of the individual numbers, is analogous to how MapReduce works.