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2 mins read

Wrong Numbers, Thin Sources: NGOs Need to Raise the Bar

Too many NGO reports fail on basic facts. A statistic from a 2011 study presented as current. A figure cited to a report that never contained it. Correlation read as causation. Impact claims that crumble under one follow-up question from a funder.

Too many NGO reports fail on basic facts. A statistic from a 2011 study presented as current. A figure cited to a report that never contained it. Correlation read as causation. Impact claims that crumble under one follow-up question from a funder.

This is not a communications problem. It is a data governance problem — and funders, regulators, and journalists have noticed.

Why it happens. Facts enter reports through copy-paste. A colleague cites a number, the next report cites the colleague, and nobody has seen the original source in years. Data lives in personal folders, old laptops, and memory. There is no single place where verified, current, traceable facts live. When everything is scattered, nothing is checked.

Data governance does not begin with a department or a policy document. It begins with a trusted reference layer: a core set of verified facts, properly sourced, kept current, accessible to everyone writing reports. One place where “what do we actually know, and where did it come from” has a straight answer.

That is what BIRI is for. Subscribe and you get a curated, checked reference base — figures with real sources, updated as things change, built for people who write reports under deadline. It is the first brick: start there, build the habit of citing from a verified base, and the governance culture grows around it.

The consequences. Every wrong number in a funding proposal costs credibility. Every inflated impact claim that gets challenged makes the next proposal harder. NGOs operate on trust — from communities, donors, and governments. In a world where AI makes confident fabrication cheap, verified facts become the differentiator.

Solid results come from solid data. BIRI™ is one way to assess source reliability.

AI can also make greenwashing faster. A developer asks for a persuasive paragraph about a ‘carbon-neutral’ product; the model produces a confident claim without a lifecycle assessment or supporting inventory. Before publishing, ask for the boundary, baseline, calculation and source. If those are missing, the claim is not ready.

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