Drinks companies are full of polished sales dashboards and dead production ones. This 3-part series is about that gap — process intelligence: analytics built around the production process itself, in the units, time and KPIs the trade actually uses. It covers what the four classic types of analytics mean in distillery language, why skilled Power BI developers still build dashboards the floor abandons, and what changes when process knowledge and BI engineering live in the same head.
No hype, as always. Where the tools genuinely help, I’ll show you. Where the failure is human and organisational, I’ll show you that too.
The series
- Descriptive, Diagnostic, Predictive, Prescriptive: The Four Analytics in a Distillery — the analytics ladder in wash, spirit and warehouse language, and where Microsoft Fabric’s lakehouse, real-time intelligence and Direct Lake actually fit.
- Why Power BI Dashboards Die in Distilleries and Breweries: The Domain Gap — units that bite, missing batch genealogy, KPIs that don’t match the trade, and why one wrong number kills trust for good.
- The Translator: When the Brewer Is Also the Power BI Developer — what changes when one person has stood at the mash tun, the spirit safe and the crush pad and also writes the DAX, and the honest limits of being one.
Read them in order — each builds on the last. Every post in the series is tagged #process-intelligence.
For the foundations underneath this series — what AI, machine learning and generative AI actually are for a distillery — start with AI Foundations for Distillers. For the full spirits catalogue, see the Distilling & Maturation track.