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Productivity indexes (or more correctly indices) can be calculated for an individual worker, groups of workers, whole companies or sectors of industry and commerce nationally. Productivity or performance is dealt with elsewhere (see References below).
The British Standards Institute's BS 3138 defined productivity ratio as "The standard hours equivalent to the production achieved whether completed or not, divided by (or expressed as a percentage of) the actual number of direct working hours". There is no 'global' version in this BS Glossary to measure inter-company or sector levels of productivity comparisons.
The generic definition often used is output divided by input of resources. Input is not just manhours, nor is it just capital investment nor any one factor, but a whole range of factors. Similarly output. In some cases it may be simplified to whatever the organization is in business to produce, such as number of cars over a specified period. example: productivity = (number of cars produced) ÷ (manhours to produce these).
However, banks and supermarkets, for example offer services in many forms so have a more complex 'output'.
Fundamentally it is this difficulty with defining both output and input in terms of factors common to all sectors that has caused the main problem. This has forced providers of productivity indexes and benchmarking to stick mainly to single-factor measures with which they can compare like with like, albeit in a very simplistic way.
To get a better idea of the issues involved it may be useful, first of all, to analyze the problem into its constituent parts. There are several questions of concern and the three which spring to mind immediately are level, range and complexity of the index.
Relative indexes such as the IMS Index derived by NTC Publications, trace the movements of specified parameters of companies in terms of 'rising', 'falling' or 'no significant change' over each specified period. At first sight this might appear rather imprecise because organizations are asked for a subjective judgement as to whether this month their particular output/productivity/other measure rose, fell or remained the same when compared with last month. In fact such indexes provide extremely useful guides to the way the sectors are moving and can act as lead-lag indicators for future predictions. Movements showing improvements or degradations in productivity may be as useful as absolute indexes and often more reliable.
Absolute indexes are based on a scale, usually showing productivity as a percentage or sometimes in numerical units. An example of this is the Economist Intelligence Unit's Car Manufacturers' Index which is a simple, single-factor ratio of 'cars per man'.
