Missing Cardinals & Signal Drift
The signals we shape & the cardinals we miss
Birds, nerds, and insight infrastructure
What started as backyard birdwatching reminded me of something I encounter at work all of the time: The focus and structure you choose early defines the signals — and the outcomes — that follow.
My partner gave me a bird feeder with a built-in camera — a little break from work, a gentle nudge to spend more time outside and less time staring at my monitor. At first, it worked.
There was always something to see: chickadees, sparrows, the occasional tufted titmouse. Even a Baltimore oriole showed up once — a rare treat!
After a few weeks, something started to bother me: Where were the cardinals?
When I was gifted the feeder, I was most excited to see them. But they never came. And once I noticed, I couldn't stop thinking about it. Maybe cardinals were rarer than I realized. Maybe they were fussier. Except… I was still seeing them around the neighborhood — just not at my feeder.
At that point, it felt personal — and I needed to understand why.
It wasn’t that the feeder was quiet. There were constant visitors — chickadees flitting in, sparrows about, squirrels staging seed heists.
But the longer I watched, the clearer it became: It wasn’t about how much activity there was. It was about who wasn’t showing up — and how easily that absence could be missed.
Turning curiosity into questions
At first, the bird feeder did its job: it pulled me outside, away from dashboards and deliverables. But once I noticed the cardinals missing, the break quietly unraveled.
Eventually, I started digging into the visitation logs — tracking which species showed up, how often, and when — thinking I'd find a simple answer.
Instead, the patterns pointed somewhere I hadn’t expected. The feeder stayed busy. But the longer I watched, the more the real gap came into focus.
It wasn’t about how many visitors there were. It was about which ones never arrived.
The feeder was rewarding activity — any activity — but not the activity I actually cared about. And for a while, the misalignment was easy to miss.
When narrowing focus hides the real patterns
At first, I thought it was just the cardinals. But looking back, my fixation on that one missing bird made me miss something bigger: It wasn’t just cardinals that were absent — it was other larger-bodied species too. Grosbeaks. Woodpeckers.
In narrowing my focus too quickly, I overlooked early patterns that could have led me to the real issue sooner.
What you measure early informs what you build later
The more I analyzed, the more it mirrored something I see every day in my work: Signals aren’t neutral. They’re shaped — by what you choose to measure, and how you structure the system around it.
Every early decision — what you collect, how you define it, how you compare it — stacks downstream.
Get it right, and small patterns lead to real insight, better systems, smarter action.
Get it wrong, and the distortion compounds, quietly reshaping outcomes before you even realize you’ve drifted off course.
That’s what had started happening here.
I was busy tracking activity — who showed up, how full the feeder seemed — without asking deeper questions:
What conditions had I set? Who was being supported — or filtered out — without me noticing?
The quiet structural choices shaping my backyard feeder mirrored the same dynamics I see in product and business systems every day: What you design for early doesn’t just shape what you see — it shapes what’s possible.
Meet the dataset: Backyard birds + small decisions with big downstream impact
When I first started digging into the visitation logs, I kept the framing simple:
How many birds + squirrels visited each day
Which species showed up
When they tended to land
But here’s the problem: I had defined success too narrowly — focusing on who showed up, not who thrived.
I hadn’t aligned the system’s inputs — the seed types, the feeder design — with the outcomes I actually cared about. I was optimizing for surface activity, not meaningful success. I was measuring the wrong signals — and quietly locking in the wrong future.
Without that alignment, the gaps stayed hidden. The counts told me how many; they didn’t reveal who was missing or why. And because the system’s design unintentionally favored small visitors, it kept attracting them — not the birds I was most interested in.
It all felt harmless, just casual observation. But that’s exactly how small distortions slip in: quietly, gradually, until they reshape what you think you’re building.
How inputs shape organizational outcomes
Systems rarely drift off course all at once. They slip, one missing input, one unexamined assumption, one flattened signal at a time.
And that was the real lesson buried under the bird counts: The structure you set early, what you measure and what you enable, shapes not just the insights you find, but the future you make possible.
At my birdfeeder, the consequences were small. Misreading the signals just meant a quieter feeder and a cardinal that never showed up. But in larger systems—product ecosystems, user experiences, operational feedback loops—small early misses don’t just compound. They cascade.
Misinterpreting signals there can mean:
In bigger systems, early signal misalignment doesn’t just distort understanding.
It reshapes the system itself, sometimes locking in blind spots you won’t detect until the damage is irreversible.
System drift starts with signal drift. If you can't catch it early, you can't steer it later.
What happened when I aligned my bird feeders to my work philosophy, measure what matters
Once I reframed the problem, not as “Why aren’t cardinals visiting?” but as “What conditions have I created, and who are they actually serving?”, the path forward became clearer.
I started by examining the inputs:
That’s when a new pattern emerged. The missing cardinals weren’t the anomaly. They were the clue.
By segmenting by size, feeding behavior, and habitat preference, I realized cardinals weren’t the only birds excluded. Grosbeaks, woodpeckers, even red-winged blackbirds—all larger-bodied species—were being quietly filtered out. Not because they didn’t exist in the area, but because the system I’d designed wasn’t built to support their participation.
This wasn’t just about a single species. It was about a structural misfit—and the cascade of exclusions that followed.
Once I identified those shared traits, I could cluster by need, not just by name. I wasn’t designing for cardinals. I was designing for a segment with shared requirements:
So I made the changes. I swapped in a platform feeder, adjusted the blend, and redesigned the system not around surface-level success, but around supporting the kinds of birds I truly wanted to include.
And then one morning, they showed up.
What better signals make possible
The first slip was small. A default seed mix. A feeder built for the average bird. But the outcome drifted quickly. What I got was motion. What I missed was meaning.
Once I redefined success, and rebuilt the system to support it, I didn’t just attract cardinals.
I surfaced the entire segment. Birds with bigger bodies and different needs.
The power of better signals aligned to customer value & outcomes.
If this sounds familiar…
You’ve probably seen versions of this play out far beyond the backyard:
These aren’t bad systems — they’re misaligned ones. And that misalignment often starts not with intent, but with what gets considered.
Want to avoid missing your own cardinals? Start here:
Better signals don’t just tell you what’s happening. They help you build the future you actually want.
Want to go deeper?
I had originally planned to write a separate piece on this: construct validity, segmentation strategy, and explainability not as lofty ideals, but as operational guardrails. The kind of thinking that keeps systems honest and proactive.
Bahareh Jozranjbar recently published this post, and she captured it so clearly and precisely, that it made more sense to amplify her work than to try and say it another way.
She explores how to define and measure complex constructs in ways that hold across methods and contexts. Her writing is a powerful reminder to ask not just “What are we measuring?” but “What are we actually trying to understand?”
We’ve been thinking through these problems in parallel—how systems distort, how metrics drift, and what it takes to design signals that reveal rather than obscure. Whether it’s DAGs, psychometric models, or more accountable UX measurement frameworks, the goal is the same:
Build systems that don’t just describe what is. Build systems that shape what could be.
The lesson and how to apply it to your day-to-day
Cardinals were never the problem. The problem was a structure that made their absence invisible.
Once I redefined success, and rebuilt the system to support it, I didn’t just attract cardinals. I uncovered a whole segment of birds I hadn’t been serving. Whether it’s birds, users, or stakeholders, the lesson holds: If you only measure for what’s easy, you’ll miss what matters most.
‘Til next time, I’m Bianca
