The literature review introduces some key questions:
- What is the objective of a task?
- What are the outputs that need to be produced to accomplish the task?
- How can the outputs be counted?
- How much and what kind of resources are needed to produce the outputs?
- What is a feasible and desirable operating plan for the next time period?
- Can the measures be replicated and standardized?
There are a variety of different measurement methodologies: function point analysis; operations-based productivity measurement; data envelope analysis; efficiency, standard times, and operating efficiency; operation functional analysis; engineering operations analysis; administrative productivity indicator and multiple output productivity indicator; multi-minute measurement; achievement method -- completion of goals; normative productivity measurement methodology; percentage of time spent in value-added activities; professional time utilization; outcome as a measure; outcome input ratio; quality and activity; economic value added; cross functional analysis; generator activity measurement technique; interviews and surveys; peer evaluations; macro, micro, and mid-KW productivity models (quality, schedule, cost, absenteeism, overtime, lost time, cost reduction).
Wow. That's quite a list. Unfortunately it reminds me of the fanciful machines of the Theatra machinara or the explosion of life represented in the Burgess Shale. Each of these approaches represents a lot of work but is likely some sort of evolutionary dead-end. Fortunately, Ramirez provides a summary of the dimensions we see represented in the models (by frequency):
- Quantity. Outputs (quantities) and outcomes (satisfaction, etc.)
- Costs and/or profitability.
- Timeliness.
- Autonomy.
- Efficiency (or "doing things right")
- Quality
- Effectiveness (or "doing the right things")
- Customer satisfaction
- Innovation/creativity
- Project success
- Responsibility/importance of work
- Perception of productivity
- Absenteeism
Quantity is the most referenced metric. Unfortunately, it's also the hardest to determine since so many organizations struggle with the issue of "what do we do?".

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