There is one thing you can (and should) prioritize today that your future self will thank you for. Do you know what it is?
Hint: It’s much simpler and far less sexy than you think.
The answer: Prioritize data integrity.
(I told you it wasn’t sexy.)
I know. I know. I can hear your groans and eye rolls.
But don’t act all surprised. You see the GIGO sign every time you walk past Data Dan’s cubicle. Garbage in equals garbage out.
“What does this have to do with my future?”, you say. I’m glad you asked.
If AI is a hot topic now, in five years, it will be as integrated into our lives as smartphones are today.
We are all being asked to do more with less, and AI is the ticket to making that happen—your data is its fuel. Its strength lies in its ability to quickly, efficiently, and cheaply scale operations. The flip side is that if bad data is present, AI will rapidly intensify those problems.
To avoid putting yourself in such a situation, pay attention to this friendly public service announcement from the year 2029:
The extent to which you can successfully leverage AI depends on the extent to which your data is clean.
The Implications
At first glance, data integrity sounds like it’s not THAT big of a deal—right?
Well, think again. Consider data integrity the metaphorical stone cast into the water, and these are the ripples:
Good data better positions your shop for AI adoption.*
AI adoption better positions your shop for optimized operations.
Optimizing operations positions your shop to connect with donors more meaningfully.
More meaningful connections with donors positions your organization for increased donor retention.
Increased donor retention positions your organization to increase donations.
Increased donations positions your organization to fulfill its mission.
By reversing this logic, we could infer that NOT prioritizing data integrity has a significant opportunity cost. Suddenly, this feels more urgent than ever.
* Regardless of whether or not your organization ever adopts AI, good data still positions your shop for optimized operations and therefore the remaining sequence of events.
The Tactics
The act of ensuring data integrity is a two-step process:
1. Repair
Clean up your data. This is a reaction to what has already been entered into your database. When you look at a spreadsheet or your CRM and think, “That’s not right,” flag it and fix it.
2. Prevent
My unique perspective comes from a life steeped in the ethos of preventive care. As both the daughter and daughter-in-law of dentists, the adage "prevention is key" was a familiar refrain. The best way to avoid a root canal is to take care of the teeth you have.
In our industry, that means noticing where there are recurring errors. Is it because two departments are operating independently? Is it because two tech solutions are not syncing correctly? Do you have a data dictionary that specifies each field or formula?
Repair and maintenance go hand-in-hand. Cleaning up bad data but doing nothing to prevent it from reoccurring is like brushing your teeth while eating Oreos.
The Next Step
It’s not lost on us that many of you don’t technically ‘own’ the data that you could potentially leverage. That responsibility often falls within data services.
But you can still have an impact.
Consider meeting with the budget manager for data services. Here’s a script to consider:
“I want you to know how much I value what you and your team do. I see how critical data integrity is to what we do. I am being tasked to do more with less, and your team’s work directly impacts that. It wouldn’t be fair of me to ask you to increase your work without offering you the resources to make that happen. So how can I assist you in this effort?”
What are some ways that your team has started to prioritize data integrity?
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