Why I'm Writing This

In my experience, the biggest issue facing the analytics industry isn't a tooling gap in the usual sense. It's communication — specifically, how quickly and how well an analyst can get an actual insight in front of the person who's about to make a decision on it.

I want to be clear about what I'm not talking about. I'm not talking about a lack of good dashboards or data apps — those are genuinely great, and anything repetitive keeps getting better, with software increasingly surfacing its own insights to non-technical users. That side of the industry is fine. What I'm talking about is the rest of the pipeline. Some of my favourite work has been diving headfirst into something the business has never looked at before — and once you're there, how do you actually communicate it? What if the finding is one single metric, one callout, nothing that fits a dashboard tile? What if you need to attach business context to a report before the number means anything? The industry keeps talking about moving away from dashboards, agentic this, AI that — but what are you actually handing an executive who doesn't have time to care and just needs a recommendation with a justification attached? How many analysts are doing the real work in a notebook, then rebuilding the story by hand in PowerPoint, then again in an Outlook email? Where's the tooling that actually helps analysts tell that story well?

What's actually pulling me toward this: the level of depth an analyst can produce and the level a room is ever shown are drifting further apart, right as the tools on both sides get more capable. Closing that gap is the whole motivation for this blog, and for Infigured.

I spend a lot of time tracking how AI is moving through three adjacent fields, and none of them are meeting in the middle where I need them to. Development is getting faster and more open — AI-assisted coding, open component libraries like shadcn, boilerplate you can actually own instead of rent. Presentation tools are getting AI layered on top too, but mostly in the generic direction: make me a deck about X, in a template, from a prompt. And analytics is growing its own agentic layer — agents that can query, summarise, even recommend — usually sitting on top of a platform that keeps the actual output locked inside it, whether that's Tableau or Hex or whatever comes next.

What I haven't found is the workflow that connects all three: agents that can help build real, detailed analytical output using open components rather than a vendor's black box, that still lands in something with the polish and immediacy of a deck. I don't even dislike PowerPoint as much as people expect me to. It does most of what I need — it's fast, it's familiar, everyone in the room already knows how to read it. It's just not built to carry analytical depth without breaking under the weight of it.

That gap is what has me looking seriously at what better analytics tooling could actually look like — and it's what I'm building toward with Infigured.

I don't think this is a small, personal complaint. Every analyst I've worked alongside has some version of the same story: good work, quietly flattened on its way to the room where it actually matters. The tools we use to explore and query have gotten genuinely good. The tools we use to hand that work to someone else largely haven't kept pace — we're still exporting, screenshotting, and rebuilding things by hand that we already built once, properly, somewhere else.

This blog is where I'm going to work through that problem in public. Some posts will be practical — notes from actually building this, decisions made and occasionally reversed. Some will be more opinionated — where I think analytics tooling is heading, and where I think it's stuck. I'll use real datasets and real examples rather than abstractions wherever I can, because I'd rather show something than describe it.

I'm writing this as an analyst first. The frustration is genuine and it's mine. The rest is what I'm doing about it.