# Meaningful Data Programs By:: [[Brian Heath]] 2022-10-14 There is no such thing as a single source of truth. Truth is subjective to the observer. What you see as truth isn't what I see as truth. Using the same words to describe our truth does not mean we are aligned. Words are artificial representations of infinitely complex ideas and experiences. We can't even agree on truth as trivial as the best style of pizza. You make think this is a preference, but it is a truth to that person. If there is a single source of truth, we would all agree after further [[examination]] that Detroit Style Pizza is the best. It may sound silly in this context, but the same truth gap exists even within more rigorously defined fields such as mathematics and science. Gödel's Incompleteness Theorem posits that in any reasonable mathematical system there will always be true statements that cannot be proved. Truth can't be proven. Even if the truth is true; even in mathematics. Truth is truly elusive. Many organizations and people either categorically reject such ideas or are unaware of them. It is not uncommon for business leaders to mandate a single source of truth as the prime directive of data and analytics. This is mathematically and practically impossible. It represents a gap in understanding the nature of data and [[knowledge]]. There are two paths forward from here. You can fake it and claim you've achieved a single source of truth. If you go down this path, make sure you exit the organization within a year or two of declaring victory. The other path is to educate leaders on this gap and find [[Pragmatic]] solutions. This path is equivalently dangerous. It rejects the directive, highlights cognitive dissonance that the leader may not be prepared to accept, and challenges cultural norms. You'll likely be an outcast. Navigating these waters requires the right combination of politics, creativity, expert power, and status. Data programs based on truth are doomed to endless suffering and strife. Data programs based on finding meaning might find a purpose. Meaning propels understanding, understanding propels work, and work propels meaning. It is a virtuous cycle of continuous improvement that evolves with the organization. This is the future of data programs. #### Related Items [[Data]] [[Analytics]] [[Truth]] [[Business]] [[Management]]