What To Do When Your Data Automation Fails (And Why You Need a Manual Backup)
Just recently, we hit a snag that many data-driven businesses will find all too familiar: a critical third-party integration went down without warning.
It was an external API, not one of our internal systems. And just like that, our end-to-end process, which usually runs seamlessly in the background, hit a wall.
The result? Our automation failed. And our team had to scramble.
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Step-by-Step: Our Manual Data Recovery Process
We fell back on our manual processes—the one we rarely touch, but keep in place “just in case.” That meant:
- Extracting the data from SQL
- Converting it into a .CSV
- Uploading it to a legacy tool for batch processing
- Waiting for the process to complete
- Downloading the output
- Importing it back into SQL and updating our data store
A job that usually takes seconds through automation took about eight minutes and a healthy dose of human focus. And yes, while eight minutes isn’t catastrophic, the process now relied entirely on humans following every step correctly.
And let’s face it: eight minutes is a lot of time to make mistakes…
Why You Still Need Manual Processes in 2025
What if we didn’t have a back-up plan? That’s where things could’ve gone sideways.
And we’ve seen that happen before…to spectacular effect [link McDonald’s outage here].
If we hadn’t maintained that manual fallback, we’d have been stuck—unable to deliver to clients, making rushed decisions under pressure, and increasing the risk of errors that affect data quality and compliance.
And that brings us to an important point:
What Does This Have to Do With Data Management?
We talk a lot about automation—and for good reason. It’s faster, reduces errors, and lets our systems run 24/7 without human intervention. But there’s something we often overlook:
Manual processes age differently.
Your automation evolves—new tools, new efficiencies, tighter integrations. But your manual backups? They tend to sit untouched, untested, and gradually fall out of sync with your live systems.
And when you finally need them… they might not work the way they used to.
Here’s the Real Takeaway: Don’t Let Your Manual Processes Gather Dust
If you rely on automation (and you should!), you also need to:
- Review your manual fallback processes regularly
Are they still valid? Still compatible with your current systems?
- Keep them aligned with how your automation has evolved
If you’ve upgraded your workflows, your manual processes should evolve too.
- Test them periodically
Don’t wait for a crisis to find out something no longer works.
Automation Is Essential. But Resilience Is Everything.
This isn’t a warning against automation or AI. It’s a reminder that true operational resilience includes redundancy, and redundancy only works when it’s up to date.
So next time you automate a process, ask yourself:
If this failed tomorrow, do we have a fallback that still works?
If not—it’s time to dust it off and give it some attention.
If you’re relying on third-party APIs to validate addresses, consider using DataTools Kleber for real-time and batch validation in a single platform—hosted securely on AWS, with zero downtime, and ISO 27001 certification.
Don’t wait for automation to fail. Let’s discuss how you can keep your data pipelines clean and resilient.
