Normalization Chart (TW patent obtained)
Normalization chart is commonly used to “remove” the original unit of the datasets so datasets in different units can be comparable in one chart. Normalization is also frequently used when presenting the relations among datasets in the same unit but in different scale, for example, “revenue” and “net profit”. The most frequently used normalization method is the “base value” method, which uses the 1st value of each dataset as the denominator to normalize the respective entire dataset.
However, such base value method may present misleading comparisons or relations among the different datasets if scales of the base values of the compared datasets are significantly different. For example, the base value of one dataset is 100 and the other is 20. Not to mention base value method requires additional conversion when the 1st value of the dataset is a negative value and cannot even perform when the 1st value of the dataset is zero.
Therefore, Graphician normalization method was invented to provide a solution for all these issues.
Examples of Graphician Normalization Chart
Misled by “Base Value” method：Which dataset increased/decreased more?
| Period | A | B |
|---|---|---|
| Q1 | 100 | 20 |
| Q2 | 20 | 100 |
| Change | -80 | +80 |
- Line A’s decrease should be equal to Line B’s increase
| Period | A | B |
|---|---|---|
| Q1 | 100 | -20 |
| Q2 | -80 | -100 |
| Change | -180 | -80 |
- Line A’s decrease should be more than Line B’s decrease
- Graphician algorithm provides a normalization method which can correctly present the relations among multiple datasets.
Application of normalization chart
- Graphician normalization can clearly and correctly present the relations among datasets. And lead the reader to the correct conclusion or help to identify the issue.