• For most of the 20th century, when labour-intensive manufacturing industry dominated developed economies and direct labour was the main input resource, measuring ‘how much you got out’ of ‘how much you put in’ was usually not a problem:

    • Output volumes were easy to count – output specifications varied little

    • Input resources were covered (mostly) by simply counting the number of direct labour employees used or the hours they worked – skill and experience levels were ignored, deemed to be much the same

  • Productivity was defined as: Output volumes/ Labour inputs

  • This partial ratio was taken to be a good measure of the productivity of any manufacturing company

  • It was also used at process or task level, when most work was either ‘blue-collar’ or highly repetitive clerical ‘white-collar’ – workers were wanted for their hands, not heads – their brawn, not brains

  • The issue facing most companies at the time was how to maximise output volumes from the costly input resources available in order to maximise profits – they assumed all output could be sold, no matter how shoddy or late it was

  • Then, in the second half of the 20’th century, service industries came to dominate western economies, and quality and service levels became the big business issues  – together, they pushed the ‘old’ productivity ratio to the sidelines

  • It took many years to realise that productivity was still the most important issue facing any organisation, but the ‘old’ productivity ratio missed much of the new picture

  • The ratio of outputs to inputs still mattered but:

    • ‘Outputs’ somehow had to include quality and service level outcomes – effectiveness in other words

    • ‘Inputs’ had to include other increasingly important inputs such as indirect labour, materials, energy and capital (e.g. costs of factories, production lines, machines, equipment, systems, ICT) – plus corporate knowledge and employee motivation levels

  • Better measurement of productivity has thus been needed ever since

  • A single measure will no longer suffice covering a whole business unit will no longer suffice – a set of cardinal measures is needed to provide the big picture of any organisation’s performance level

  • This set should be made up of at most 10 measures per manager, whatever his or her level – it covers the most important outcomes, outputs and inputs employed by any manager and his team viz:

    • Financial outcomes 

    • Customer outcomes 

    • Physical inputs and outputs 

    • Mental inputs

  • And when the same set of measures is used by all managers at all levels, this provides them with a common language for understandable communications both up and down levels of the organisation – and from side to side

Cardinal measures

If you want to manage productivity well, you first need to measure it well and ensure your team understand the few cardinal measures you use   Every organisation, whatever its size, has plenty happening by the hour, week or year – customers seen, calls taken, transactions made, incidents attended, press releases written, widgets produced – …

Cardinal model

The cardinal model below covers the set of cardinal measures needed by managers at all levels It links all cardinal measures at all levels and thus shows the inter-relationships between each one Managers cannot just focus on one or two of the above cardinals and ignore the rest – they must always consider all those …


There are several target options available: RPs – Reference Periods = What you once did – a performance benchmark achieved in the past, equivalent to an athlete’s PB – average performance over a 4 week historical period, say – it lets you assess if you’ve made any progress since Budgets = What you are expected …

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