<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Primers in Insights, Forecasting and Market Research]]></title><description><![CDATA[Insights, Books, and Beyond]]></description><link>https://www.insightprimer.com/blog</link><generator>RSS for Node</generator><lastBuildDate>Wed, 03 Jun 2026 06:21:22 GMT</lastBuildDate><atom:link href="https://www.insightprimer.com/blog-feed.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Are we living in a world of insight inflation?]]></title><description><![CDATA[Just finished an invigorating strategy workshop but one thing I noticed was the amount of time the word ‘insight’ was mentioned and it got me thinking… are we living in a world of ‘insight inflation’. The word is used a lot but, honestly, most  “insights” aren’t insights at all. We use the word constantly — in brand plans, advisory boards, research decks, strategy meetings. But when you boil it down, what’s labelled an insight is usually something far more ordinary: a data point, a quote, a...]]></description><link>https://www.insightprimer.com/post/are-we-living-in-a-world-of-insight-inflation</link><guid isPermaLink="false">69e10e1716b0ab534cf32d2b</guid><pubDate>Thu, 16 Apr 2026 16:32:51 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/b5b020_878fc2a0117b4dfb8dc384ee4e143f89~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Brian Kilfeather-Larkin</dc:creator></item><item><title><![CDATA[Build an Insight Engine]]></title><description><![CDATA[This week I’m attending a strategic tactic workshop — the kind where cross‑functional teams wrestle with evidence, pressure‑test assumptions, and try to turn inputs into something that actually informs action. And quite often we’ll be looking for the nuggets or “insights” among lots and lots of data points. We don’t have an insight problem. We have an insight engine problem. Even in rare disease I find that teams are drowning in data but starved of clarity. We generate observations,...]]></description><link>https://www.insightprimer.com/post/build-an-insight-engine</link><guid isPermaLink="false">69da6cf89c4f89104660e4e9</guid><pubDate>Sat, 11 Apr 2026 15:50:45 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/b5b020_8a654ac286d34d8c913ab7f098b5d313~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Brian Kilfeather-Larkin</dc:creator></item><item><title><![CDATA[Managing complexity and different needs in forecasts]]></title><description><![CDATA[This article was originally published on LinkedIn in 2025 Just finished a forecasting workshop with J+D Forecasting and Ipsen... one thing that's still ruminating as we head to the weekend is that there’s this  tendency when building forecasting tools to keep adding — more logic, more detail, more exceptions. I guess it starts with good intentions: trying to meet what seems like endless stakeholder needs and the need cover every possible scenario. But the result is usually the same: a complex...]]></description><link>https://www.insightprimer.com/post/managing-complexity-and-different-needs-in-forecasts</link><guid isPermaLink="false">69da6b8d9c4f89104660e372</guid><pubDate>Sat, 11 Apr 2026 15:43:32 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/b5b020_333d110f2d894b8ca7948efbc3805586~mv2.png/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Brian Kilfeather-Larkin</dc:creator></item><item><title><![CDATA[Analysis in Rare Disease - Working with Contradictions]]></title><description><![CDATA[This post was originally published to coincide with Rare Disease Day, which takes place on 29th (or 28th) February February 28th is Rare Disease Day ,which has got me thinking what it really means to work in rare disease analytics — and why it requires a fundamentally different mindset. In rare diseases, data isn’t just smaller. It’s more precious, more fragile, and more human. And it's built on what feels like a paradox. Rare disease analytics is both more precise and more uncertain than in...]]></description><link>https://www.insightprimer.com/post/analysis-in-rare-disease-working-with-contradictions</link><guid isPermaLink="false">69d94c8946e8409f60b18a23</guid><pubDate>Fri, 10 Apr 2026 19:18:12 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/b5b020_0683ad6decde417aa9949b5915860e19~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Brian Kilfeather-Larkin</dc:creator></item><item><title><![CDATA[Why Clarity Is Now a Competitive Advantage]]></title><description><![CDATA[Recently, I received feedback that my communication with senior teams — especially around insights and forecasting — could be even sharper and more influential. It was honest, constructive, and exactly the kind of feedback that forces you to level up. So I went looking for resources. Books, frameworks, courses… but nothing addressed the real challenge: how to translate complex analytical thinking into senior‑ready clarity that drives decisions. When I couldn’t find what I needed, I did what...]]></description><link>https://www.insightprimer.com/post/why-clarity-is-now-a-competitive-advantage</link><guid isPermaLink="false">69d900844750526d40bca34e</guid><pubDate>Fri, 10 Apr 2026 13:52:16 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/b5b020_f52fd29910bc43e6b86ae515a6b97028~mv2.png/v1/fit/w_415,h_312,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>Brian Kilfeather-Larkin</dc:creator></item></channel></rss>