Bad data isn’t loud. It doesn’t announce itself. It’s a quiet pain that shows up as second-guessing, workarounds, and decisions that take longer than they should. I’ve seen this pattern play out across teams and companies for years.
In my work with Salmon, this issue keeps resurfacing in one form or another. Different companies, same underlying problem.
The story below is fictional, but it reflects a real scenario we’ve encountered.
A Familiar Story Inside Growing Companies
Meet Sarah Chen, Director of Revenue Operations at a major software company with global presence, 10,000+ employees. She is what you’d expect from a seasoned pro; calm under pressure and trusted across the org. Sarah seems to always have the answers. Lately, there’s an area of the business that is keeping her up … causing the most amount of stress.
The Current State
- Marketing initiatives are pushing into new regions and product lines faster than her revenue operations can adjust.
- Sales is convinced their pipeline is full of bad data and it seems to be getting worse every month.
- Her CRM is technically “up-to-date,” but everyone knows that’s not true in practice.
Sarah isn’t dealing with one big problem. She’s dealing with fifty small ones that compound every week. And these issues are NOT uncommon.
Where the frustration actually sits
It’s not that the team can’t find data. It’s that the data constantly contradicts itself. It’s not that the team can’t find data. It’s that the data rarely aligns once they start using it.
- Records conflict across systems.
- Enrichment looks complete but doesn’t do well once scrutinized
- Key details shift with every check
Every decision slows down because nobody trusts the information in front of them. Sarah knows that if the systems underneath aren’t reliable, nothing else she builds could possibly scale.
“We have all these tools, but I still don’t know what’s true.”
Sarah believes there should be a way to verify data as it moves, not after the damage is done. Something that gives her team clean, contextual signals without requiring them to rebuild their workflow from scratch. With all the innovation happening in tech today, Sarah is convinced the technology does exist. She has seen prototypes and fast growing startups promising the world. What she hasn’t found yet is something she can trust at scale.
The Turning Point
As Sarah started to compare notes with her peers, she noticed a shift. More teams are looking beyond traditional enrichment and toward newer intelligence layers that validate and contextualize data directly inside the systems companies already rely on.
Not another dashboard. Not another place to log into.
Just more accurate, trustworthy information feeding the workflows her revenue engine already runs on.
She doesn’t have full clarity yet. She just knows that better solutions are emerging. Ones built for the complexity of today’s data requirements, not yesterday’s static lists and one-time enrichments.
I don’t need another tool, I just need a simple solution
It’s not about adding more tools. It’s about creating a foundation she can trust. A system that verifies contacts, enriches context, and flags inconsistencies automatically. A system that keeps pace as new regions open, compliance rules change, and teams expand.
Sarah starts to see that the solution isn’t in more manual cleanup. It’s in rethinking the layer where data quality is established in the first place.
And the encouraging thing is, the technology to do this is starting to mature. Companies like Salmon are building toward it, but the bigger story is that this future is becoming real.
For the first time, probably ever, executives like Sarah are seeing a path forward that doesn’t require burning everything down.
What does tomorrow look like
Sales and marketing executives like Sarah imagine a future where their teams aren’t constantly second-guessing the basics.
Where the CRM behaves predictably instead of like a patchwork. Where entering new markets doesn’t mean bracing for a new wave of data inconsistencies. Where compliance has reliable identity signals without halting operations. Where manual review becomes an occasional check, not a weekly ritual.
These leaders hope for a workflow that finally feels stable.
A rhythm their teams can trust.
A system that supports the work they’ve already built instead of undermining it.
Sarah was realistic. She didn’t expect perfection. But what she wanted wasn’t unreasonable–to be in a place where the information her company relies on is strong enough to let her focus on strategy, leadership, and growth instead of cleanup cycles.
The technology for that future exists. With the right mix of people, process, and partners, it’s achievable.
This story
Sarah is a fictitious name, based on a real-life situation one of our clients lived through over the past two years.
If this sounds like you, we’d love to hear from you. https://www.salmonrun.ai/contact-us
