Programming productivity - Wikiwand
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.[1] 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.[2] The following definitions describe the best consensus on the terminology.[3]
Productivity
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 straightforward relation between the number of units produced and the number of units consumed.[4] 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 on what context is under evaluation. In a manufacturing company the possible contexts are:[3]
- the individual machine or manufacturing system;
- the manufacturing function, for example assembly;
- the manufacturing process for a single product or group of related products;
- the factory; and
- the company's entire factory system
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),[5] 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.[1] The same holds for more specific area of programming productivity.
Profitability
Profitability and performance are closely linked and are, in fact, often confused. However, as profitability is usually defined as the ratio between revenue and cost
Profitability = Revenue / Cost
It has a wider scope than performance, i.e. the number of factors that influence profitability is greater than the number of factors than influence productivity. Particularly, profitability can change without any change to the productivity, e.g. due to external conditions like cost or price inflation. Besides that, the interdependency between productivity and profitability is usually delayed, i.e. gains in productivity are rarely reflected in immediate profitability gains are more likely realized on the long-term.
Performance
The term performance is even broader than productivity and profitability and covers a plethora of factors that influence a company's success. Hence, well-known performance controlling instruments like the Balanced Scorecard do include productivity as a factor that is central but not unique. Other relevant factors are e.g. the customers’ or stakeholders’ perception of the company.
Efficiency and effectiveness
Efficiency and effectiveness are terms that provide further confusion as they themselves are often mixed up and, additionally, efficiency is often confused with productivity. The difference between efficiency and effectiveness is usually explained informally as efficiency is doing things right and effectiveness is doing the right things. While there are numerous other definitions,[3] there is a certain agreement that efficiency refers to the utilisation of resources and mainly influences the required input of the productivity ratio. Effectiveness on the other hand mainly influences the output of the productivity ratio as it usually has direct consequences for the customer. Effectiveness can be defined as "the ability to reach a desired output".
Generally, it is assumed, that efficiency can be quantified, e.g. by utilization rates, considerably more easily than effectiveness.
Quality
Tangen states: "Improvements in quality, other than the fact that no-fault products add to output levels, ought not to be included in the concept of productivity."[3] However, most of the classic literature in non-software disciplines, especially in the manufacturing area, does not explicitly discuss the role of quality of the output in the productivity ratio.[6] More recent works from non-manufacturing disciplines have a stronger focus on knowledge, office or white-collar work and hence increasingly discuss the role of quality with respect to quality.[5][1][7][8][9]
Drucker stresses the importance of quality for the evaluation of knowledge worker productivity: "Productivity of knowledge work therefore has to aim first at obtaining quality—and not minimum quality but optimum if not maximum quality. Only then can one ask: "What is the volume, the quantity of work?""[5]
Saari captures the importance of quality with his extended formula for productivity:[8]
Total productivity = (Output quality and quantity)/(Input quality and quantity)
However, it appears that these efforts to include the quality in the determination of productivity did not lead to an operationalizable concept yet. It currently remains unclear how to quantify the vague terms “Output quality and quantity” as well as “Input quality and quantity”, let alone to calculate the ratio.