Programming productivity

Programming productivity (also called software productivity or development productivity) describes the degree of the ability of individual programmers or development teams to build and evolve software systems. Productivity traditionally refers to the ratio between the quantity of software produced and the cost spent for it. Here the delicacy lies in finding a reasonable way to define software quantity.

Productivity is an important topic investigated in disciplines as various as manufacturing, organizational psychology, industrial engineering, strategic management, finance, accounting, marketing and economics. Levels of analysis include the individual, the group, divisional, organizational and national levels [5]. Due to this diversity, there is no clear-cut definition of productivity and its influencing factors, although research has been conducted for more than a century. Like in software engineering, this lack of common agreement on what actually constitutes productivity, is perceived as a major obstacle for a substantiated discussion of productivity. The following definitions describe the best consensus on the terminology.

While there is no commonly agreed on definition of productivity, there appears to be an agreement that productivity describes the ratio between output and input:

Productivity = Output / Input

However, across the various disciplines different notions and, particularly, different measurement units for input and output can be found. The manufacturing industry typically uses a straight-forward relation between the number of units produced and the number of units consumed. Non-manufacturing industries usually use man-hours or similar units to enable comparison between outputs and inputs.

One basic agreement is that the meaning of productivity and the means for measuring it vary depending of what context is under evaluation. In a manufacturing company the possible contexts are:

As long classical production processes are considered a straightforward metric of productivity is simple: how many units of a product of specified quality is produced by which costs. For intellectual work, productivity is much trickier. How do we measure the productivity of authors, scientists, or engineers? Due to the rising importance of knowledge work (as opposed to manual work), many researchers tried to develop productivity measurement means that can be applied in a non-manufacturing context. It is commonly agreed that the nature of knowledge work fundamentally differs from manual work and, hence, factors besides the simple output/input ratio need to be taken into account, e.g. quality, timeliness, autonomy, project success, customer satisfaction and innovation. However, the research communities in neither discipline have been able to establish broadly applicable and accepted means for productivity measurement yet. The same holds for more specific area of programming productivity.

...
Wikipedia