Category: ApertureCI

Someone on the strategy team asks for a competitive landscape in a new therapeutic area. "Just the key players, where they are in development, and how they compare."

Just.

What "just" actually looks like

You start in ClinicalTrials.gov. Pull every trial for the condition. Cross-reference with vendor databases — Citeline, Evaluate Pharma, Cortellis. Figure out who owns each asset, what phase they're actually in, and whether they're relevant to the indication you care about.

The data cleaning part is straightforward. Tedious, but straightforward. You can get a decent Excel sheet together in a few days.

Then it gets painful.

The slide

The landscape needs to be a PowerPoint slide. Arranged by development phase. Each drug is a textbox. You're placing them on a grid, color-coding by MOA, adjusting because twenty drugs don't fit the way ten did.

You realize you missed one. Add it. The layout breaks. Reformat. Someone mentions a drug you hadn't included. Add it. Reformat again.

This is where the time actually goes. Not in the data — in the visualization. Getting fifty drugs onto a single slide in a way that's readable and tells a story. Every change to the underlying data means moving textboxes around on a PowerPoint.

The "so what"

Leadership doesn't care about the grid. They care about what it means. Where are the white spaces? What does the competitive picture mean for our strategy?

That narrative — the actual intelligence — takes maybe a day to write. But you can't write it until the data is clean and the visualization makes sense. So the strategic thinking, which is the whole point, gets whatever time is left after two weeks of data work and slide formatting.

The shelf life

A landscape starts going stale the day you finish it. A trial readout or an FDA action can change the picture overnight. Three months later, the landscape is a historical artifact.

So you either rebuild from scratch or you try to maintain it. Maintaining means going back through the same sources, checking what changed, updating the Excel, and — this is the part that kills you — moving the textboxes again.

The gap

The vendor platforms are excellent databases. I've used all of them. What they don't do is build the landscape for you. You still export to Excel. You still build the PowerPoint. The data is better organized, but the workflow is the same.

The gap isn't data availability. Public sources contain almost everything you need. The gap is everything between raw data and a finished landscape — verification, building the slide, keeping it updated. All manual work, and it's where most of the time goes.

The hardest part isn't building the first landscape. It's keeping it alive. A landscape that can't update itself is just a more expensive version of the slide it replaced.

CI analysts spend 80% of their time on data work and 20% on the strategic thinking that actually influences decisions. The ratio is wrong.

The strategic work is what CI is supposed to be. Anticipating competitive moves, synthesizing across programs, surfacing insights that change how leadership thinks about a market. That's the part that matters. And it gets whatever time the noise leaves behind.

The noise

Google Alerts, ClinicalTrials.gov updates, SEC filing notifications, RSS feeds, PubMed digests, industry newsletters, stakeholder asks. Hundreds of items a week across a dozen sources. Most of it is noise. Re-syndicated press releases, routine filings, publications that mention a competitor in passing.

Buried in that noise, occasionally, is something that actually matters. A data point that changes the competitive picture.

The problem is you can't tell which is which without processing all of it.

Signal has a half-life

Intelligence that surfaces Monday morning changes a strategy conversation. The same intelligence buried in Thursday's alert batch is already stale.

Every source delivers at its own pace. Google Alerts batch overnight. ClinicalTrials.gov updates whenever records change. Newsletters arrive weekly. SEC filings post on EDGAR's schedule. None of them know what you're watching for or how urgent any given update is. They just dump everything into the same stream.

When CI works, it's genuinely valuable. You catch something early, connect it to what you already know, surface it before a decision gets made. But that only happens if the signal arrives in time. Right now nothing in the workflow respects that.

Why better filters won't fix it

"Build better filters" is the obvious fix. But relevance in CI is contextual. The same event is critical or meaningless depending on what else is happening.

An 8-K filing could be a material event or a routine auditor change. A new publication could be novel data or a rehash. You can't filter by keyword or filing type. You need to know what's happening with that specific competitor, that specific program, at that specific moment to decide whether it matters.

That requires combining every alert with everything you already know about the competitive landscape. Humans do that kind of synthesis well. They can't sustain it at volume, week after week.

So you start skimming. And the thing you skim past might be the signal.

The patchwork

There's no single system that holds the full competitive picture. Vendor platforms for pipeline data. Spreadsheets for what the vendor doesn't cover. Slide decks for the landscapes leadership reads. A dozen browser tabs for the sources you check manually.

Every CI analyst I know has some version of this patchwork. The tools vary. The fragmentation doesn't. Nothing connects.

The tools are good at storing facts. They're bad at surfacing what those facts mean in context.

The ratio

80% data work. 20% strategic thinking. The thinking is the part that influences decisions, and it gets squeezed into whatever's left after triage, tracker updates, landscape rebuilds, and source switching.

I want to flip that ratio. That's what I'm building toward.