Add one, remove one
In the world of home-organizing, there's the "one in, one out" rule. Simply put, for every new item that enters your home, one similar item must leave, helping to maintain a constant level of possessions and prevent clutter accumulation.
This would be a great rule for database managers when considering adding new fields of data to collect!
If staff wants to add a new field to collect a new data point, the first question is "Which data point/field are we going to remove?"
I'm only half-joking. Too often I see my clients adding new fields of data to collect while simultaneously not keeping up with the other data points they are supposed to be already collecting.
So when you think about adding a new field, ask yourself: "Are there other data fields we could remove while we're adding this new one?"
![]()
Wes's Wednesday Wisdom Archives
When “overcommunicating” becomes overwhelming
When “overcommunicating” becomes overwhelming There is a common belief in project management and general business management that overcommunicating […]
Communicating when there is a major technology change
Communicating when there is a major technology change For those of you who are ASAE […]
Everything works, until it doesn’t.
Everything works, until it doesn’t. “If something cannot go on forever, it will stop.” – […]
Some things are unknowable
Some things are unknowable One of the most challenging aspects of moving to a new […]
Do we have access to that data?
Do we have access to that data? When I work with my clients on a […]
The three “buckets” of contact data
The three “buckets” of contact data Broadly speaking, when collecting data on contacts (individuals or organizations), […]
Balancing what is possible with what is realistic
Balancing what is possible with what is realistic When I work with clients on technology […]
“Humans want to be surrounded by beauty.”
“Humans want to be surrounded by beauty.” “Humans want to be surrounded by beauty.” – […]
Data managers vs data consumers
Data managers vs data consumers When I work with clients on any data management project, […]
Another universal truth
Another universal truth There are many universal truths in data management. Some examples: You will […]
