Garbage in, garbage out

Since last year, I have mainly worked with information governance for several clients.

It's very obvious that top management in many organizations now see information & data quality as something really important. The more we implement and use AI, the more important it gets.

Today, lack of ownership and lack of structure, i.e. Information Architecture, is the common theme for them, and both issues need to be resolved to improve information & data quality.

This is a coin with two sides. You can't be accountable or responsible for something not well defined, and without structure. Neither structure is enough if nobody or somebody is responsible for parts of the structure.

Most organizations need to improve their maturity in this area, to succeed with AI intiatives and traditional transformation projects.

This work is cross departments and cross release trains, thus very hard to solve in classic agile sprints. However, implementation must be done stepwise, as the effort often is huge.

What happens if you don't improve?

Garbage in, garbage out is still the result regardless if you use AI or traditional software.