If we buy to this idea that Data is an asset, just like materials or Buildings.
Then we have to apply all the same measurements to it.

• Keep track of its location.
• Track its “shelf-life”.
• Trade it: buy if needed and sell if you don't know what to do with it.
• Insure it.
• Collect your Dividends.

The last point I want to stress for now.

There is a great publication from Harvard makes a great point, also this Kerney
Paper is a good summary about how to assess if your Company is a Leader or laggard.

If there is one Book that changed my thoughts about data as no other, it is the Book called "Factfulness" by Hans Rosling

He points out some fundamental soft skills for Data

Think like been aware of the fact that there is rarely a gap between two entities rather than there is a normal distribution.
Do not compare averages, do not compare extreme values and so on.

Be aware of your biases and perspectives!

If you are on the rooftop of a skyscraper,
anybody on the ground looks equally small.
You could think that size differences for them would be irrelevant.
Because the variation from your point of view is so small.
But for the people on the ground, it makes a big difference if someone is 1.5 m or 1.8 m tall.

Coupling is a device that joins two things together:

Source

If you join together Technical Data sources, you increase the coupling of these two systems.
This concept is widely agreed upon in Coders, but not so common in Business functions.
Basically it means:

If you have a System A connected to System B and System B itself is connected to System C. You will notice side effects changing data on system A. These side effects happen in B and C and may not be obvious.

Also, if system A goes away and System C depends on it, that could end up bad.

Sometimes it is enough to just cache the Data from system A to system B periodically.
So a short downtime of A will not affect System B.
But this could have side effects too, out of date data for example.

Do not underestimate the time and effort needed to have a clear understanding where your data is used.