Unlike some assets, data’s value does not necessarily increase with age. In today’s fast paced world, organisations need current data to base decisions on. If I want to understand today’s air passenger, I would not look to data from the 1960s or even the 2000s because the flying experience has changed so much in that time. However, if I wish to consider how flying has changed over a period of time, then there is a value to the older data, as it would allow me to look at trends and patterns and learn from them.
The format of the data also causes problems. Currently there is no international standard for the way data must be labelled, which means it is hard for organisations to use other people’s data. You could have the most insightful data in the world, but if no one else can use it, its value is greatly diminished. Artificial Intelligence (AI), which learns from data patterns and trends, also finds it much harder to deal with data in multiple formats. An issue that Matt Bencke, CEO of Mighty AI, believes needs to be addressed, before data can “become the catalyst that differentiates and accelerates your AI" 2
. Moreover, as AI’s use continues to grow, it is not hard to imagine how the value of data could become defined in part by its ability to be assimilated by AI, regardless of what it could tell us.