- Defining Operations Management
- Organizational Decision Levels
- Key Terminology
- Critical Processes
- Measuring Productivity Levels
- Inventory Determination
- Inventory Policy Choices
- Inventory Policy in a Fixed-Order Quantity System
- Independent Versus Dependent Demand
- ABC Inventory Classification
- Vendor Managed Inventory (VMI)
- Challenges Facing the Modern Operations Manager
- Discussion Questions
Measuring Productivity Levels
Recall that operations management is responsible for managing the transformation of numerous inputs into a range of outputs, such as goods or services. But how do we know whether this transformation process is efficient? A measure of how efficiently inputs are converted into outputs is called productivity. Productivity measures how well resources are used. It is computed as a ratio of outputs (goods and services) to inputs (labor and materials). The more productive a company is, the better it uses its resources. The equation is as follows:
- Productivity = output/input
This measure of productivity can be used to measure the productivity of one worker or many, as well as the productivity of a machine, a department, the whole firm, or even a nation. Total productivity is used when measuring productivity for all inputs combined, such as labor, machines, and capital. For example, let’s say a company produces weekly the equivalent of $10,000 in output in the form of finished goods. Let’s also say that the weekly value of all the inputs combined—including labor, materials, and other costs—is $5,000. Total productivity for the week for the company is
- Total Productivity = output/input = $10,000/$5,000 = 2.0
Although total productivity is valuable to give a company a sense of how it is doing on the whole, it is often much more useful to measure the productivity of one variable at a time. This allows us to evaluate how efficiently various resources are being used. Partial productivity or single-factor productivity is when we compute productivity as the ratio of output relative to a single input. For example, we can compute machine productivity or labor productivity. For machine productivity we can see how many units a machine is processing over a certain period of time; similarly for labor productivity we can compute how many units a worker can process over a certain period of time, such as a day, hour, or month.
The interpretation of productivity is not as easy as you might think. Productivity is a relative measure that should be tracked over time. This allows us to benchmark against ourselves, our competitors, and our industry. Just looking at the number, such as the 2.0 in the previous computation of total productivity, does not reveal much. Consider, for example, if one worker at a sub shop produced 20 subs in 2 hours, the productivity of that worker is 10 subs per hour. This number by itself does not tell us much. However, if we compare it to the productivity of two other workers, one who produces 8 per hour and another 5 per hour, it is much more meaningful. Although this is a simplistic example, it illustrates the point that performance expectations are relative, and they need to be benchmarked and compared over time. By comparing our productivity over time and against similar operations, we have a much better sense of how high our productivity really is.
Another criterion for evaluating productivity and setting standards for performance is considering the company’s strategy for competing in the marketplace. This is called a competitive priority, and it defines how a company competes. A company that competes based on speed would probably measure productivity in units produced over time. However, a company that competes based on cost might measure productivity in terms of costs of inputs such as labor, materials, and overhead. On the other hand, a company that competes on quality may measure productivity based on the number of errors made. The important thing is that the productivity measure selected provides information on how the company is doing relative to the competitive priority it defines as most important.