We talk about “generating insights” as if they can be harvested on demand, like a crisp pilsner on tap. The reality is far messier. Most analytic work doesn’t fail because the data’s wrong - it fails because we mistake information for insight.
Somewhere between the data pull and great insights, we fall short. We collect, clean, and graph, but we don’t connect. The final leap, from signal and sense to story, is a stalling point. Not for lack of data, but because we celebrate (but are lost in) a sea of information.
Why we stop at signal
More is not always more. Somewhere along the line, analysis became a sport of data collection. We race to mass to prove rigour and mistake over-reporting for progress wins. We became obsessed with datasets, polishing, slicing, and over-producing them in the hope that more output meant more certainty. Risk aversion crept in: instead of making sense of the data we had, we snuggled into the Oodie of volume.
Insights don’t live in spreadsheets, they live in the meaning we draw from them. Great analysts know data is never perfect, but it gives us the signal. What matters is building upon and moving beyond signal to make sense of what it means, and telling a story that people can use.
If you had to draw it (and I like to, so please see picture below), insight would sit where three potatoes overlap: Signal, Sense, and Story.
Most organisations are pretty good at detecting Signal. Some manage Sense. Very few can communicate it into a Story. You can use this as a quick test: are we still chasing signal, trying to make sense, or ready to tell the story?
What good insight actually looks like
A real insight has three properties:
It reveals something genuinely new (or locks in / out a prevailing assumption).
Perhaps turnover was thought to be seasonal. Then a spikes after a specific training milestone is discovered.
It changes the question.
Now question is not “how do we retain people?” but “why are they leaving right after we invest in them?”.
It provokes forward action.
People are inspired and provoked into effective action.
You can usually spot a goodie when the conversation moves from defending numbers to exploring meaning. It’s not enough to be an interesting data point — a real insight makes people a little uncomfortable, because they can see the truth in it and know action is needed.
Why most insight work doesn’t land
The failure modes are painfully familiar.
Speed kills sense-making. Briefs are often “urgent”, so analysis gets delivered before anyone’s had time to sit with what it means. Like a good pilsner, insights need fermentation, not flash freezing (I hope I do not live to see the day of dehy beers).
Optimisation for completeness over clarity. Overreporting can become incentivised if it helps RAG status. My clever colleague notes “Trying to create too many metrics for too many audiences means none of them get owned. Momentum gets lost and the initiative fizzles out.” That’s what happens when teams stay stuck in Signal, busy collecting and categorising, without moving through Sense to Story.
Data and people live in separate worlds. Analysts speak in DAX code. Executives speak in metaphors. And while it does take a village, by the time translation happens, everyone’s a little lost.
Vanity metrics take over. Dashboards become glossy but meaningless “data theatre” that look rigorous but tell no story.
Precision masquerades as truth. A perfectly tuned model built on questionable assumptions is just time consuming way to be wrong with confidence.
Getting from Signal to Story
The craft of insight isn’t mysterious. It’s adjustments that respect both the data and the humans who have to live with it.
Clarifying the signal
What’s worth paying attention to
The first job is to find out why. What uncertainty are people actually trying to resolve? What do they not have currently?
What’s the pattern or issue worth paying attention to? Framing defines which signals matter and which are noise.Building the sense
What’s the meaning or implication
Sketch the narrative arc. What tension are you exploring? What patterns might connect? Doing this on a whiteboard saves weeks of spreadsheet archaeology later.
Sketching the narrative arc forces you to interpret what the signal might mean before the analysis snowballs.
Testing the story
Sense-make with and for others
Bring early findings into conversation. Ask, “Does this resonate?”, “What decisions does this support?” or “What’s missing?”
Insight rarely emerges from a solo epiphany. It’s a social sport.
4. Refining the craft
Reflect afterwards
After the project, ask: What surprised us? What didn’t land? What will we do differently next time?
Reflection loops you back through all three: did we chase the right signal, draw the right sense, and tell the story well?
If you drew the process, it would look like a curly fry loop, not a pipeline: signal, sense, story, reflect.
Storytime
Most organisations invest heavily in Signal — systems, metrics, dashboards. Fewer invest in Sense — interpretation and context. Almost none invest in Story — the time and permission to communicate meaning.
We need to close the loop and start celebrating getting all the way to great insights. That means a happy meal of:
Rewarding finishing the story, not just delivering the data.
Making space for synthesis, translation, and engagement.
Encouraging challenge and reflection.
It also means letting analysts be more than technicians. This means authorship and the freedom to notice, interpret, and care about the mahi.
Producing something that helps people see their world differently gives that lick of quiet dignity which may not get us up in the morning but certainly helps us sleep well at night.
Cheers
Great insights can be found in the holy potato trinity: finding the right Signal, making Sense of it, and telling a Story people can share over a cold one.
At Nimbl our job is to stitch Signal, Sense, and Story back together, so that insight becomes a shared empowerment rather than a data request. Because when we get that right, we don’t just produce reports; we produce understanding. And that’s what turns dials.
Lou Rooney is a consultant with Nimbl Consulting. She helps organisations turn information into insight, and insight into action — preferably without adding another dashboard to the pile.