New Year's Resolutions
Why do New Year's Resolutions fail? Research suggests that part of the challenge is that the actual resolutions are too large/complex/difficult to achieve (e.g., I will lose 30 pounds by June 1st). And when we inevitably fail to reach the goal, we give up, telling ourselves "Well, I guess I just can't do that."
I see the same thing happening with data management. An unrealistic goal is set (e.g. "We'll have 99.5% accuracy with our email delivery by the end of the month!") and when the goal is (invariably) not reached, everyone declares "Welp, this is hopeless, no point in trying!"
A better approach is to set less specific and more achievable goals and to measure your progress frequently.
Suppose you have 80% email deliverability now. A more achievable goal would be to say "We're going to increase deliverability over the next three months," and then measure your progress every couple of weeks for the next three months. Some weeks you'll improve, some you may not. But you'll be working in the right direction and you'll likely develop a habit of continuing to work in that direction.
The idea isn't perfection (which can't be achieved) but progress, improvement, and success.
So what kind of New Year's Resolutions have you set for your data management? And are they realistic?
![]()
Wes's Wednesday Wisdom Archives
Negativity bias is why we need database PR
Negativity bias is why we need database PR I’ve written before how cognitive biases can affect […]
A system change requires a culture change
A system change requires a culture change By its very nature, when you introduce a […]
Where is that data?
Where is that data? This is what data management nirvana looks like: When the question starts with […]
Be deliberate, but act quickly
Be deliberate, but act quickly Be deliberate, but act quickly. These are my words of […]
Why associations don’t like the “S” word
Why associations don’t like the “S” word A couple of weeks ago I asked my […]
The “S” stands for “Standard”
The “S” stands for “Standard” In a conversation with a past client, we were discussing […]
Is that meaningless data?
Is that meaningless data? I’m not a big quotes guy, but one of the few […]
Be aware of unintended consequences
Be aware of unintended consequences I’ve written before that every decision involves a trade-off. When […]
Positive change is harder to see
Positive change is harder to see Humans are wired to see negative change because we […]
MVP: Minimum Viable Product
MVP: Minimum Viable Product In product development there is a concept known as MVP, or […]
