For an economic component so vital, productivity needs to be measured. The data gathered shall in turn be used in calculating the other economic components for an accurate reading.

The famous Peter Drucker is more to the point: “Without productivity objectives, a business does not have direction. Without productivity measurement, it does not have control.”



Collecting data is an essential requirement in measurement. The three basic ways of collecting data on a phenomenon or system are inquiry, observation, and documentation.

Afterward, the basics are done – the outputs are evaluated against the inputs. Some writers put in some qualitative indicators which create problems, although the rest confine the discussion of productivity to simple O/I (output and input) factors.

Some of the productivity measurement techniques are the following.


Mundel (1989)

Mundel created a computer software package that evaluates productivity. In it, direct adjustments for quality are excluded as well as raw materials. This is because the result is knowledge.

Here, productivity is calculated using simple O/I algorithms. It presents eight levels of work units, from the lowest-motion up to highest-results-achieved because of outputs.



Sassone (1991)

The technique used by Sassone is simple to implement. Work is classified by the lowest level of employee. Work is then recorded by the type. Finally, data is compiled in a matrix format and analyzed.

The matrix shows the amount of effort expended by each employee type, and whether they are working above or below their level, indicating a mix of workers in a workgroup.

It also shows the consequences of common assumptions like cutting support staff can actually reduce costs.


Sink (1985)

Sink has several techniques in evaluating productivity using mainly his three main methodologies. One is a computerized model of measurement based strictly on O/I (output/input).

The second one uses structured group processes in measuring white-collar or knowledge workers.

It uses the group technique to establish consensus about what and how productivity should be measured.

The third system is designed to evaluate various productivity measures and decide which are the most important. It also allows the combining of dissimilar productivity measures.


Other techniques

There were other researchers who use the group technique. Bernard (1986) used project teams and stressed maximizing diversity with the premise that managers cannot be assumed to know what really is going on.

Thor (1990) also dealt with group techniques. These include a participatory style, with each group having a facilitator who should be familiar with the technique but at the same time relatively unknown to the group.

A methodology that depended on estimation was used by Kristakis (1984).

The manager lists down the types of work in the group and breaks them down into detailed operations. The manager will then estimate how long each work process takes.

Time diaries, estimates, work samplings, and direct observations are some of the tools employed by Anthony (1984).

The gathered data are analyzed by a computer and reviewed to eliminate insignificant items.

All in all, each of these other techniques of productivity measurements has its good points worth taking a look at. Most are saddled, however, with inaccuracies and some were outdated.

Nevertheless, all are in one opinion that there is a need to measure

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