After we examined the use of scales, it became clear that there is no 100% correct or 100% neutral way to present data. Appearance and purpose are completely intertwined.
This also applies for using percentages. Let’s assume that we are comparing the companies BIG and SMALL. While SMALL increased annual revenues from €10 to €20 million, BIG’s growth jumped from €40 to €70 million.
Both of the following statements are correct:
SMALL had a €10 million increase in revenues. BIG’s €30 million revenue growth was 3 times as strong.
SMALL expanded revenues by 100%. BIG experienced a 75% revenue increase, which is only ¾ of the growth that SMALL generated.
Both statements make causal assumptions. In the case of statement 2, most people would say that it is not fair to compare companies of different sizes in absolute numbers. One assumes that size has an influence on the absolute revenue growth. This influence levels the relative observation.
In the case of statement 1, most people would assume that the customers focus on the implied quality of the services and not the size of the company. This assumption could apply for architects, for example, because their fees are primarily based on the total cost of construction.
Even Galileo examined these types of questions. A horse, whose objective value was 100, was taxed by one expert at 10 and by another at 1000. Galileo felt that these variances were equidistant: 1000_100=100:10. Others involved in this scientific dispute felt that the variance between 100 and 1000 was 900, and thus, much larger than the variance of 90 between 100 and 10.
As we see again and again, it all just depends…
