How to Optimize a Gelato Production Line? KPI Analysis, Waste Reduction, and New Tools for Better Performance
This article reveals the behind-the-scenes of gelato production optimization at GROM—from applying World Class Manufacturing and OEE analysis to implementing Power BI for performance monitoring. The author shows how to reduce production losses, better plan processes, and improve supply reliability, while also pointing to the future: full automation of data collection. It's a great inspiration for any gelato maker who wants their production to be based on data, not intuition.
This is precisely the type of article that shows that gelato production is not just about flavors and decorations, but above all, about precise process management. The author, working on a project at the GROM factory, introduces us to the world of World Class Manufacturing (WCM)—a methodology aimed at eliminating waste, improving quality, and continuous process improvement.
What does the analysis focus on? Primarily on key indicators: Overall Equipment Effectiveness (OEE) and Output Reliability (OR). The author explains how these KPIs help understand the real efficiency of the production line and quickly identify problems—from overly long changeovers to machine breakdowns. It is noteworthy that the biggest impact on performance drops was identified in so-called process losses—an important tip for anyone wanting to operate faster and cheaper.
One of the most interesting elements is the description of gelato production in a Make to Order system—everything is planned based on actual demand and orders from different countries. The author guides us step-by-step through the process: from preparing the gelato mix, through adding inclusions, quality control (including metal detection and weight measurements), to packaging and palletizing.
The article also shows how to improve data visibility in a simple yet effective way—by moving its analysis from a complex Excel spreadsheet to interactive Power BI dashboards. This allows managers to track KPIs in real-time, group losses (e.g., transfer losses, filling waste, final rejects), and make decisions faster. It is this fragment that best demonstrates a practical approach to continuous improvement.
Finally, the author looks to the future, describing plans to implement a SCADA system—an automated, networked system for collecting data from machines. This is a game-changer because it will allow for real-time performance monitoring and instant response to problems.
For gelato makers who want to work smarter, not harder, this article is a great inspiration. Importantly, a similar approach can be introduced even in smaller artisan workshops using modern tools. This is exactly what our application for gelato shops is for: it helps design flavors, adjust recipes, eliminate the problem of sandiness or crumbliness, and also generate ingredient lists and calculate calories. This allows you to bring the same mindset that large factories use on an industrial scale into your own workshop—managing production based on data.