How Do We Measure Work?

Until now, we have been discussing work on a conceptual level (using conceptual criteria). But, at some point, we need to translate those concepts into actual measures (actual criteria). For example, a restaurant server's performance may be described according to a conceptual criterion like customer service. Customer service can be measured in a number of ways. The measure (such as customer ratings) is the actual criterion.

As you learned in the PSYCH 281 lesson on performance management, there are a number of ways to measure performance. These methods range from objective to subjective. An objective (actual) criterion is one that is unaffected by subjective human biases. Examples include number of sales, number of products produced, and number of days absent from work. Objective criteria work best when the employees' performance levels are within their control. For example, it is inappropriate to compare metrics like parts per hour between two employees when one is using outdated machinery and the other is not. In addition, some complex processes cannot be thoroughly reflected in a single score. Depending on the complexity of one's research methods and topics, publishing research articles could take months or years. Comparing researchers solely on the total number of articles published quarterly would not adequately assess their impact on the field.

Subjective criteria are those that are based on human judgement. Supervisory ratings are a common example. Subjective criteria are necessary because some jobs cannot be easily reflected or measured objectively. Imagine trying to measure the performance of a therapist in objective terms. We could try to design indices of mental health and assess improvements in patients' mental health post therapy. But, because the mental health of a therapist's patients depends on a large number of factors, including the patient's diagnosis and environment, it would not be fair to measure and rank therapists based solely on indices like this. Subjective actual criteria give us an opportunity to reflect performance using complex dimensions. Unfortunately, they are affected by human biases and can be difficult to interpret.

In summary, measuring performance adds yet another layer of difficulty onto the already difficult criterion problem we described earlier.