Evaluation metrics is a subject that has evolved as a result of our involvement in economic policy design, project evaluations and audits as well as needs analysis in decision analysis and systems engineering. In order to evaluate the performance of a policy or investment project it is necessary to be able to specify an unambiguous quantitative and measurable objective.
By way of example, most economic policies have an underlying objective of securing what is referred to as growth. This term is often associated with such words as innovation, productivity and value for money. If growth is an objective it is important to identify how this is measured as well as identify the mechanism whereby that objective is to be achieved. In this context the interpretation of the world productivity is important. Productivity has two interpretations:
- A higher volume of output
- More output for less input
The higher volume of output simply means more overall output or a "larger pie" however, this does not necesssarily means higher levels of production efficiency.
More output for less input is a common result of the learning curve which is associated with less waste and lower unit costs of production. This higher level of production efficiency opens up the possibilities of profitable but lower unit priced comptetitive output and which the income-price elasticity of demand propels such lower priced goods and services into markets, enhancing the purchasing power of disposable incomes.
Needs analysis is an essential first step in identifying the actual issue to be addressed or solved by identifying a solution as a policy or system. Needs are deficiencies in provisions such as insufficient availability of goods or even of income levels and purchasing power. Needs are not verbs or processes because this would assume that the "solution" is already defined as an existing process which in reality could be the cause of the provision deficiency. In this work the guidelines developed by
Roger Kaufman provide the basis for our approach, including his
Organizational Elemmental Analysis in designing the necessary organizational procedures to deliver the required outputs.
Data specification requires data names, units and locations of objects that the data relates to and in the context of statistics, formulae that combine data in useful relationships. In our development work we developed a specific procedure to aid this type of data specification in the form of
Data Reference Models 1 which is an Open Quality Standards Initiative (OSQI) procedure.
1 McNeill, H. W.,
"Improving communications within systems groups", Decision Analysis Initiative 2010-2015, Portsmouth, August, 2014.
