SBP 3d: Difficulty in Measuring Output

This principle occurs because output is variable and nonstandard, as discussed in SBP: Heterogeneous Production.

Most companies want to be productive. In general terms, productivity is what we get out of a process given the resources we put in. Thus, if we desire to measure changes in productivity over time, or compare the productivity of various service providers, we need to have some way of measuring output. Manufacturers of standard items can simply count the number of items produced. For a service company, counting items produced is a rough measure of output. The service business may handle fewer customers over time, but the processing requirements may be much more complex. For example, a consulting firm may originally handle simple jobs with a lot of clients, but as the firm's specialized expertise develops, they may handle more time-consuming projects involving fewer customers. Measuring time expended is to measure an input, not output. The primary output of most consulting firms is advice. How does one quantify the magnitude of advice? How do we tell if one consulting office is capable of producing “more” advice than another?

Be careful in selecting productivity measures, since these measures tend to define what employees focus on in the production process. (This will be discussed later in the A Measure of Motivation Service Business Principle.)

In education, how do we measure productivity? One way is to count the number of graduates. The problem with counting graduates is that it fails to capture the knowledge they have gained–it would be easy to “crank out” graduates with little competency (as is done in many highschool programs in the U.S.). Another way to measure education productivity is to count the number of courses taken or grade point averages. Yet, those are only vague surrogate measures of knowledge. Another means of measuring productivity is to tabulate job placement statistics or starting salary statistics. Yet, how many of those graduates could have gotten just equally good jobs by skipping class and “cramming” for exams–knowing little but being able to give a great job interview. Another way of measuring education productivity is to ask graduates who have been out a few years how much useful knowledge they thought they received from various courses. That is, unfortunately, a very delayed measure of education productivity. The bottom line is that measuring the output of education is no trivial matter.

A common way to measure productivity of airlines is to calculate the “passenger load factor,” which is the percent of available flight seats which are occupied. The problem is that such a measure almost discourages increasing capacity even when it might be warranted. (Over-booked flights show high passenger load factor, but may reflect many passengers lost to other airlines.) Another measure of productivity that is used is “passenger seat miles,” which captures the idea that a passenger who flies 1000 miles represents twice as much production as a passenger who flies 500 miles. Yet this measure does not really capture a concept of cost of production nor value to the passenger. (Is a 1000 mile flight twice as costly or twice as valuable as a 500 mile flight? Probably not.) Another measure of airline output is to count the raw number of passengers, which measurement is no panacea. We wind up having to measure output in a number of different ways.

With manufacturing, output is often relatively uniform, allowing clearly numerical output measurement (i.e. counting units of output).

1. How do we measure output? In terms of number of customers served? In terms of value provided to each customer? In terms of revenue generated?
2. In what way might the way we measure output vary customer to customer? Do some customers use one measure and other customers use another?

Describe three different ways “output” could be measured for your business process. Are the three exactly correlated with one another? In other words, is one measure of output simply a constant times another measure of output? Describe what each of the measures of output might be interpreted, and how each might be used to monitor productivity over time. Comment on which of the three you think is the most appropriate measure of output, and why.