At present, there had been numerous productivity measurement techniques used by different groups of people for different purposes and reasons. These techniques had been developed for different applications, too.
There is a need, therefore, to combine and unify these differing views and techniques. Basically, this is simply to be able to come up with a better and more comprehensive understanding of the concept of productivity.
However, in discussing productivity, different authors had allocated the use in different ways such terms as “measurement”, “evaluation”, “performance”, “improvement”, and “productivity”.
Let us introduce them.
Performance
Strictly speaking, productivity is interpreted as the output divided by input (O/I).
This is because it is easily defined, calculated and implemented.
Performance, however, is a broader term than productivity because it includes such factors as quality, customer satisfaction, and worker morale. These are not easily quantified.
Their inclusion into the calculations makes them more difficult to make them fuzzy and dilutes the clarity of the measurements.
Productivity
Again, strictly speaking, measurements are numerical indexes. Productivity measurement is one. It is expected that the same inputs should produce the same outputs – a number factor.
One advantage of this is the fact that the index does not depend on who collected the data or when it was collected.
Evaluation and measurement
Productivity improvement
Measurement is the methodology of establishing the amount of work involved in a work function. Evaluation is using measurements that are not strictly quantitative. It makes use of such measures as good, bad, poor, superior, fast, and others.
The use of qualitative measures makes the manipulation of the data difficult, although it allows the inclusion of previously unmeasured work aspects. It is hoped that the application of fuzzy mathematics to such terms may make them useful someday.
Measurement is the methodology of establishing the amount of work involved in a work function. Evaluation is using measurements that are not strictly quantitative. It makes use of such measures as good, bad, poor, superior, fast, and others.
The use of qualitative measures makes the manipulation of the data difficult, although it allows the inclusion of previously unmeasured work aspects. It is hoped that the application of fuzzy mathematics to such terms may make them useful someday.