Quantity and complexity
It is not surprising that quantity is an often used measure of productivity. Lean Enterprise describes how the productivity of software engineers are measured:
Individual productivity is most commonly measured by throughput—the time it takes to complete a standardized task under controlled conditions. This approach is premised upon a Taylorist view of work where managers define the tasks to be done and workers try to complete these tasks as rapidly as possible. Thus, old-school metrics such as lines of code per day and number of hours worked are used to measure individual productivity of software engineers.
But the problem with quantity in an information, or knowledge context, is that it adds complexity. In a lean generative culture the quantity metric gets flipped around. The focus shifts to quality, but quality is hard to measure.
The flaws in these measures are obvious if we consider the ideal outcomes: the fewest lines of code possible in order to solve a problem, and the creation of simplified, common processes and customer interactions that reduce complexity in IT systems. Our most productive people are those that find ingenious ways to avoid writing any code at all.