Insights
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Practical thinking on data, AI, project controls and design — the things we've learned turning noise into signal for teams where delivery is hard.
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Latest thinking.
Agentic AI, minus the hype: what actually ships
The distance between a slick agent demo and a digital co-worker your operations team trusts is not model quality. It's guardrails, escalation, auditability and integration. Here's what we actually build.
7 min read Project controlsDCMA 14 in plain English
Fourteen checks decide whether a project schedule can be trusted. Here's what each one is really testing — without the acronym soup.
6 min read Data storytellingReport design principles we steal from newsrooms
Editors have spent a century making complex information scannable under deadline. Analysts building dashboards should borrow far more of their playbook.
5 min read Data platformsMicrosoft Fabric vs the modern data stack
One governed platform, or a dozen best-of-breed tools stitched together? The honest trade-offs behind the biggest data-architecture decision you'll make.
8 min read AutomationThe £-per-hour case for automation
You don't need an AI strategy to start automating. You need a simple sum — and the discipline to point it at the right work first.
4 min read Data platformsTableau → Power BI: what actually changes
Migrating BI platforms is rarely about the charts. It's about the model, the governance and the habits underneath them. What to expect when you move.
6 min read Project controlsProject controls in the age of AI
The PMO's job has always been to turn schedule and cost data into decisions. AI doesn't replace that judgement — it removes the compiling that gets in its way.
6 min read Data platformsThe modern data stack for mid-market
You don't need a FTSE-100 data team to get FTSE-100 insight. The trick is matching the architecture to the organisation you actually are.
5 min readMore landing every week. Want the next drop in your inbox? Tell us →
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