Labour Productivity

Labour productivity

Labour Productivity is a key performance indicator which shows how well each unit of labour is used to make a unit of output. It is commonly used in operations management and strategic analysis to compare the productivity of workers in different ways such as in the same or different industries and between manufacturing plants or work sites within an industry or a company.

This measure is also used in the service industry such as fast food restaurant chains, retail banking services and insurance companies just to name a few. Operations managers are regularly concerned with productivity measures as they are usually aiming to maximize the amount of outputs per unit of input, in this case labour hours or labour costs.

Formula for Labour productivity

Labour Productivity = Units of Output/ Units of Labour

The units of Labour refer to the units of labour used in creating the Units of output in the above formula. In some cases the Units of labour are substituted by total labour costs to compare labour production costs between different manufacturing facilities or regions.

Examples of Labour productivity comparisons

Comparing labour productivity between concrete plants:

Concrete plant A
Daily output: 120 cubic meters
Daily labour hours : 40 hrs
Labour Productivity = 120m3/40hrs = 3cubic meters per labour hour

Concrete plant B
Daily output: 160 cubic meters
Daily labour hours : 68 hrs
Labour Productivity = 160m3/68hrs = 2.35 cubic meters per labour hour

As you can see the Labour productivity rates for these two concrete plants are different and usually many factors must be analysed first to determine the difference and derive a strategy to increase the underperforming plant. Some of the possible factors which may be examined by operation managers and production engineeers which may lead to lower labour productivity rates are listed below.

Analysis of Labour Productivity

When analysing the difference in labour productivity rates between the concrete plants there may be different factors which cause the variance in results. Operations managers and supervisors should consider the following possibilities:

– Different skill levels of operators
– Different Plant configurations such as layout and plant
– Age and condition of plant and equipment affecting plant downtime
– Distance from supply sources of raw materials
– Reliability and quality of raw material supply
– Quantity and quality of supporting resources such as maintenance teams etc
– Weather

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