Metrics are men made artificial products to describe properties of tangible and intangible objects.
A metric is a standard for comparing a property of a tangible or intangible object. There are subjective and objective metrics. And there are qualitative and quantitative metrics.
Objective metrics are based on a standard that has been agreed. There's a unit attached to each objective metric.
Subjective metric are based on subjective standards.
Four types of metrics are useful. The normative, the qualitative, the quantitative (linear) and the quantitative (multidimensional) metric.
An economic value is a subjective property that is given from a human to an object. No men no value, only price [\$] or cost [\$]. Real (implicit) value [iV] is a combination of subjective and objective properties, threatened and visualized as a vector.

• Metrics are artificial men made objects.
• Metrics had and have to be invented (were not thrown from heaven).
• Metrics have a unit.
• Objective metrics are standardized.
• Measuring = comparing relative to standard.

"Count what is countable, measure what is measurable and what is not measurable, make measurable!"

Galileo Galilei, 15.02.1564 - 08.01.1642

### Goto moreAbout Objects, Indicators and Weight ### Goto moreVector applications and Excel Templates DIY ## Metrics... development of....

### 1. Normative Metrics

Normative metrics must be interpreted.
Standard rules for behavior in a family, group, enterprise, religions, nations.....

### 2. Linear Metrics

Most metrics are one-dimensional (linear) measures. In most cases this is sufficient to describe a specific property of an object. It's easy to make arithmetic calculations with linear metric and visualize it.

### 3. Multidimensional

If different properties of an object have to be threatened as a compound, then multi-D vectors (matrices) are used. Needs strong imagination to understand numerical calculations. It's more understandable if visualized as vectors.

### 4. Graphical arithmetic

Graphical arithmetic with vectors makes it easier to show and communicate the interdependence of several indicators and clusters. It not only shows the performance of each cluster but also in relation to the performance of a whole unit.