Articles, videos, and practical guidance to help pharma teams build data foundations that work.
Every SaaS company you work with has shipped an AI feature this year. Some have shipped six. They demoed beautifully. The pilots looked promising. Then you put them in front of real users with real questions, and the wheels came off.
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A senior pharma operations leader recently shared that her organisation has eleven active AI projects involving eight vendors and five departments. At first, she saw this as a success, as it showed the organisation's focus on innovation and digital transformation.
Read Full StoryEvery business has one person who knows where everything is. They have been there for fifteen years. They know exactly which spreadsheet is the real forecast and which one is last year’s numbers left open in a tab. When they leave for good, something always breaks that no handover document could ever quite capture.
Read Full StorySomewhere in your organisation right now, someone is asking an AI tool a question about your business, and the tool is confidently giving them an answer that may well be wrong, incomplete, or six months out of date. This answer sounds plausible, so they might not notice. That, in a nutshell, is the problem that this paper sets out to solve.
Read Full StoryIn 1983, physicist Lorne Whitehead published a paper in the American Journal of Physics that described something deceptively simple: a domino can topple another domino about one and a half times larger than itself. It sounds like a party trick, but the implications are profound.
Read Full StoryWhat is a marketing taxonomy, and why does it matter? A short explainer showing how structured content classification builds the data foundations needed for accurate reporting, confident decision-making, and effective personalisation.
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